The Implications of JK-1(FAM134B) Gene in Human Cancer · School of Medicine The Implications of...

School of Medicine

The Implications of JK-1(FAM134B)

Gene in Human Cancer

Kais Kasem

M.B.Ch.B. Pg.Dip.

Submitted in fulfilment of the requirements of the degree of

Doctor of Philosophy

June 2013

CONTENTS Page Number

Chapter 1: Literature Review 01-64

1.1 Cancer

1.1.1 Introduction 2

1.1.2 Incidence 5

1.1.3 Aetiology 5

1.1.4 Inherited defects 6

1.1.5 Acquired mutations 6

1.1.6 Oncogenes 7

1.1.7 Tumour suppressor genes 8

1.1.8 Apoptosis regulating genes 9

1.1.9 DNA regulating genes 10

1.1.10 Metastasis suppressor genes 11

1.1.11 Environmental carcinogens 15

1.1.12 Chemical carcinogens 16

1.1.13 Immunosuppressive and chemotherapy drugs 17

1.1.14 Radiation carcinogens 17

1.1.15 Bacterial and viral carcinogens 18

1.2 Colorectal cancer

1.2.1 The colorectum – anatomy and histology 19

1.2.2 Epidemiology and incidence 21

1.2.3 Aetiology 22

1.2.4 Screening 24

1.2.5 Symptoms 26

1.2.6 Diagnosis 27

1.2.7 Familial factors 28

1.2.7.1 Familial Adenomatous Polyposis Syndromes 29

1.2.7.2 Hereditary Non-Polyposis Colorectal Cancer Syndromes 32

1.2.7.3 Hamartomatous Polyposis Syndromes 35

1.2.7.4 Non-Syndrome Familial Colorectal Cancer 38

1.2.8 Tumour Markers and Prognostic Factors 39

1.2.9 Tumour Classification: Stage and Grade 44

1.2.10 Current Treatments 49

1.2.11 Molecular and Genetic Alterations Found in Colorectal Cancer 52

1.3 JK-1(FAM134B) gene 57

1.3.1 Introduction 57

1.3.2 Genomic location for JK-1(FAM134B) gene 57

1.3.3 JK-1(FAM134B) gene description 59

1.3.4 Previous Studies on JK-1 (FAM134B) Gene: 59

1.4 Aims and significance of the study 62

Chapter 2: DNA study 65-112

2.1 Introduction 66

2.2 Aims of the study 68

2.3 Materials and Methodology

2.3.1 Population and Tissue samples 69

2.3.2 Clinicopathological data 74

2.3.3 DNA extraction 76

2.3.4 Assessing DNA Purity 79

2.3.5 Primer Design 79

2.3.6 Polymerase chain reaction (PCR) 81

2.3.7 Real Time Polymerase Chain Reaction (qPCR) 82

2.3.8 PCR Efficiency: 84

2.3.9 High-Resolution Melt (HRM) 86

2.3.10 Mutation detection using sequencing 88

2.3.11 Statistical Analysis 91

2.4 Results

2.4.1 JK-1(FAM134B) identification 93

2.4.2 JK-1(FAM134B) copy number changes 94

2.4.3 HRM Study and sequencing results 99

2.4.4 Survival Analysis 103

2.5 Discussion 106

Chapter 3: RNA study 113-146

3.1 Introduction 114


3.3 Materials and methods

3.3.1 Data collection and Tissue Recruitment 116


3.3.3 RNA Extraction 120

3.3.4 Assessing RNA Purity and Integrity 124

3.3.5 cDNA Preparation 125

3.3.6 Real-time Quantification PCR 125

3.3.7 Primer Design 126

3.3.8 PCR Efficiency 128


3.4 RESULTS

3.4.1 mRNA expression of JK-1 (FAM134B) gene in colon tissue 132

3.4.2 mRNA expression of JK-1 (FAM134B) gene in CRC 133


3.5 Discussion 142

Chapter 4: Protein study 147-188


4.2 Aims of FAM134B protein study 150

4.3 Materials and Methods

4.3.1 Data collection and Tissue Recruitment 151


4.3.3 FAM134B Antibody 155

4.3.4 Immunohistochemistry 155


4.3.6 Western Blot for Antibody Specificity 160

4.3.7 Western Blot Analysis 161

4.4 Results

4.4.1 Specificity of JK-1(FAM134B) antibody 163

4.4.2 Subcellular localization of JK-1(FAM134B) protein 164

4.4.3 Protein expression of JK-1(FAM134B) gene 164


4.4.5 Correlation between JK-1(FAM134B) mRNA and

protein expression 180

4.5 Discussion 181

Chapter 5: Functional study 189-233




5.3.1 The cell lines 193

5.3.2 SW480 cell lines 193

5.3.2.1 Handling of frozen cells 194

5.3.2.2 Sub-culturing procedures 194

5.3.3 JK-1(FAM134B) knock down 195

5.3.3.1 Puromycin selection 196

5.3.3.2 The control group 197

5.3.4 mRNA extraction and cDNA conversion 197

5.3.5 Protein extraction from cell lines 198

5.3.6 Quantitative real time PCR 199

5.3.7 Primers 200

5.3.8 Immunocytochemistry study 202

5.3.9 Western blot analysis 203

5.3.10 Cell proliferation study 204

5.3.11 Cell migration study 205

5.3.11.1Migration assay protocol 206

5.3.12 Analysis of results 209

5.4 Results

5.4.1 JK-1(FAM134B) expression in colorectal cell lines 210

5.4.2 Confirming JK-1(FAM134B) knockdown and 212

transduction efficiency in SW-480 cell lines

5.4.2.1 Morphological changes on JK-1(FAM134B) 212

knockdown in SW-480 cell lines

5.4.2.2 mRNA expression of JK-1(FAM134B) gene 213

in knocked down SW-480 cell lines

5.4.2.3 Western blot findings in JK-1(FAM134B) 215

knockdown in SW-480 cell lines

5.4.3 JK-1(FAM134B) knock-down effect on cell proliferation 216

5.4.4 JK-1(FAM134B) knock-down effect on cell migration 218

5.5 Discussion

5.5.1 JK-1(FAM134B) mRNA expression in colorectal cell lines 227

5.5.2 Confirming JK-1(FAM134B) knockdown and 227

transduction efficieny in SW-480 cell lines

5.5.3 Effect of JK-1(FAM134B) knockdown on cell 228

proliferation in colorectal cancer cells

5.5.4 Cell migration assay 229

Chapter 6: Summary and conclusions 234-238

References 239-277

Abstract

Cancer is now the most common cause of death in Australia and in many other countries.

Cancer is a disease where abnormal cells grow rapidly and spread throughout the body in an

uncontrolled manner. Cancer occurs due to several damaging events occur in an individual cell

or from a combination of many processes. DNA damage is a common feature to all cancers,

though not all DNA damage will result in cancer. It has been proven that research on molecular

pathways of cancers directly contributes in advanced care for cancer patients by more accurately

refining prognosis and selecting the most appropriate adjuvant therapy for these patients.

Previous studies on oesophageal squamous cell carcinoma have led to the discovery of a

new gene (JK-1(FAM134B)) that plays a role in cancer pathogenesis. JK-1(FAM134B), a novel

gene located at 5p15.2 , was found to be over-expressed in oesophageal squamous cell carcinoma

cell lines and patient cases. Overexpression of JK-1 in NIH-3T3 mouse fibroblasts and HEK293

cells caused an increase in growth rate, colony formation in soft agar and foci formation in

confluent cultures. Also, high-grade sarcomas were formed in athymic nude mice following

subcutaneous injection of JK-1-overexpressing NIH-3T3 cells.

In addition to the role of the gene in oesophageal cancer, a recent study of a hereditary

form of sensory and autonomic neuropathy revealed that a JK-1(FAM134B) gene defect is an

important cause of this disease. Apart from these two studies, the molecular features, function

and potential role in human cancer of this gene were largely unknown.

This is the first systematic study to address JK-1(FAM134B) expression, copy number

and mutations on a model of colorectal cancer. A large cohort of cases (236 colorectal cancers,

32 colon adenomas and 20 colonic non tumour tissue samples) were recruited for the study. JK-

1(FAM134B) was quantified at DNA, mRNA and protein levels, using paraffin embedded tissue

and colorectal cell lines to understand its role in tumour development. Moreover, a successful

knock down of JK-1(FAM134B) protein was performed using shRNA lentiviral particles and its

downstream effects were studied in human colon cancer cell lines.

Changes in JK-1(FAM134B) DNA copy number were associated with tumour

recurrence, histological subtypes, and cancer stage. Lower copy numbers were associated with

higher T(p=0.013), N(p=0.05) and overall stage of cancer (p=0.042). Conversely, higher DNA

copy numbers were detected more often in the mucinous type of colorectal adenocarcinoma

(p=0.001).

JK-1(FAM134B) expression profile at mRNA and protein level was investigated in

colorectal cancer and adenoma patients using real-time quantification PCR and

immunohistochemistry. In all colorectal tissues, JK-1(FAM134B) mRNA was expressed, though

with noticeable variation. Adenomas showed a much higher rate of mRNA expression, whilst

cancer’s levels of expression were significantly lower (p=0.005). Within the colorectal cancer

population, significantly lower mRNA expression was noted in higher T, N, M and overall stages

(p=0.039).

In concert with the changes seen on the mRNA level, JK-1(FAM134B) protein

expression was lower in colorectal cancers of larger size (p=0.004) and higher stage (p=0.005).

The functional role of JK-1(FAM134B) in human cancer was studied in vitro, using

shRNA-lentiviral based knock down methods in SW480 cell line. JK-1(FAM134B) suppression

in a colon cancer cell line resulted in increased cell invasiveness and migration capacity on

multiple extracellular matrix substrates (p=0.04). It had no effect, however, on cancer cellular

proliferation, as shown in a MTT calorimetric assay.

The current study noted multiple new findings, including relationships with clinical and

pathological parameters with JK-1(FAM134B) copy number, mRNA and protein expressions in

colorectal cancer. The findings suggest that JK-1(FAM134B) gene and its products can be a

potential new tumour suppressor gene. This study also noted functional roles of JK-

1(FAM134B) in cell invasion and migration capacity in colorectal cancer. Results of this study

indicate that JK-1(FAM134B) has a significant role in human cancer pathogenesis and is likely

to be involved in the development and progression of colorectal cancer and is linked to cancer

initiation, invasiveness, aggressiveness and metastasis.

Statement of Originality

This work has not previously been submitted for a degree or diploma in any university. To the

best of my knowledge and belief, the thesis contains no material previously published or written

by another person except where due reference is made in the thesis itself.

Kais Kasem

Abbreviations

µl Microliter

µm Micron

µMol Micro Molar

5-FU 5-flurouracil

AFAP Attenuated FAP

AJCC American Joint Committee on Cancer

ANOVA Analysis of Variance

APC Adenomatous polyposis coli

ATCC American Type Culture Collection

bp Base pair

BRCA-1 Breast cancer susceptibility gene 1

BRCA-2 Breast cancer susceptibility gene 2

cDNA Complementary DNA

CEA Carcinoembryonic antigen

CHRPE Congenital hypertrophy of the retinal pigment epithelium

COX Cyclo-oxygenases

CRC Colorectal carcinoma

DAB 3, 3’-diaminobenzidine

DC Distal colorectum

DEPC Diethylpyrocarbonate

DMSO Dimethyl sulfoxide

DNA Deoxyribonucleic acid

EBV Epstein- Barr virus

ECM Extracellular matrix

EGFR Epidermal growth factor receptor

FAM134B Family with sequence similarity 134B

FAP Familial adenomatous polyposis

FFPE Formalin-fixed, paraffin-embedded

FGF Fibroblast growth factor

FJP Familial Juvenile Polyposis

FOBT Faecal occult blood test

g Gram

GAPDH Glyceraldehyde 3-phosphate dehydrogenase

GI Gastrointestinal tract

GICA Gastrointestinal cancer-associated antigen

GMO Genetically modified organism

HNPCC Hereditary non-polyposis colorectal cancer

HRM High resolution melt

HSAN2B Hereditary sensory and autonomic neuropathy type 2B

IHC Immunohistochemistry

LOH Loss of heterozygosity

MAP MYH-associated polyposis

miRNA Micro RNA

MMR Mismatch repair genes

mRNA Messenger RNA

MSI Microsatellite instability

MSI-H MSI High

ng Nanogram

C ͦ Degree Celsius

PC Proximal colorectum

PCR Polymerase chain reaction

q-PCR Real time quantitative PCR

RNA Ribonucleic acid

RT-PCR Reverse transcription PCR

shRNA Small hairpin RNA

siRNA Small interfering RNAs

SSAs Sessile serrated adenomas

STK11 Serine-threonine kinase 11

TBS Tris-buffer saline

TNF Tumour necrosis factor

TNM Tumour, Node, Metastasis

tRNA Transfer RNA

TSAs Traditional serrated adenomas

TSG Tumour suppressor gene

UHRR Universal human reference RNA

WHO World Health Organization

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CChhaapptteerr 11

Literature Review

2

LITERATURE REVIEW

1.1 Cancer

1.1.1 Introduction

In Western society, Cancer is a leading cause of mortality, coming second only to heart

disease and accidents in adults and children, respectively (Greenlee et al., 2001; Jemal et al.,

2002; Jemal et al., 2003; Jemal et al., 2004; Jemal et al.,2008, Jemal et al., 2011). Cancer is the

leading cause of death in economically developed countries and the second leading cause of

death in developing countries (World Health Organization 2004).

Epithelial carcinomas such as colon, lung, breast, prostate and bladder cancer are the

most common forms of disease in the adult population, with the majority occurring in the over

55 age group (Greenlee et al., 2001; Jemal et al., 2003; Jemal et al., 2004; American Cancer

Society, 2008; Jemal et al., 2008, Jemal et al., 2011). In infants and children, however,

mesenchymal (muscle, cartilage and bone), haematopoietic (including acute leukaemia) and

central nervous system neoplasms are the more common types. These childhood neoplasms

frequently occur before the age of 15 (Tripathy, 1995; Jemal et al., 2008, Cotran et al., 2010,

Jemal et al.,2011).

3

Although different neoplasms arising at various locations differ in such characteristics as

rate of growth and aggressiveness, all human tumours share certain commonalities. All tumours

arise from cells that lose normal cellular regulation to become proliferating neoplastic cells,

whose rogue growth is supported by a stroma of connective tissue and blood vessels (Cotran et

al., 2010). Following the discovery that the majority of cells within a tumour mass are comprised

of similar cells (Nowell, 1976), the genetic or clonal theory was formulated, which states that

tumours arise from single cells that lose control of normal function and proliferate, with further

alterations in these clonal neoplastic cells leading to the heterogeneity of cells observed within

neoplasms (Nowell, 1976; Axelrod et al, 2006). Cancers evolve by a reiterative process of clonal

expansion, genetic diversification and clonal selection within the tissue ecosystems with highly

complex dynamics and variable patterns of genetic diversity. (Greaves and Maley, 2012)

Epithelial cells are constantly renewed within the basal layer during normal cell

turnover. The mature cells remain in this cell layer and do not invade through the basal layer into

the basement membrane. Once cells become neoplastic their rate of proliferation increases and

an increase in the fraction of cells in the S phase of the cell cycle can be observed (Lundberg et

al., 1999; Malumbres et al., 2001; Cotran et al., 2010). Alterations in the expression of cell cycle

and signalling proteins, together with changes in hormonal stimuli caused by neoplastic cells,

affect the expression of growth factors and carcinogenic progression (Malumbres et al., 2001).

Tumour invasion through the extracellular matrix (ECM), which allows cells to

metastasise to secondary sites, is aided by proteolytic enzymes produced either by the tumour

4

cells themselves or by nearby stromal cells that have been stimulated by the tumour cells (Jiang

et al., 1994; Taipale et al., 1997; Egeblad et al,2002).

Tumours, whether benign or malignant, are problematic as they lead to compression or

invasion of vital structures in the body, which in turn results in

dysfunction of the affected organ(s) and can ultimately lead to death. Although the location of a

benign tumour can result in organ dysfunction, cancerous masses pose a greater threat due to

their capacity to spread throughout the body and the requirement for more aggressive treatment

(Liotta et al., 2002; Mareel et al., 2003; Steeg, 2003; Cotran et al., 2010).

Both primary and metastatic tumours can invade blood and lymphatic vessels, nerves, the

brain, bone and the airways, as well as the gastrointestinal and urinary tracts, disrupting the

normal functioning of these systems and leading to such phenomena as altered hormone levels,

bleeding ulceration and perforation, and even infarction, all of which can cause death (Liotta et

al., 2002; Friedl et al., 2003; Pantel et al., 2004). Cachexia, or body-wasting, associated with

cancer is caused by the gradual loss of body fat and lean body mass. This cancer-associated

condition is not believed to be due to the nutritional demands of the proliferating tumour, but

rather to an imbalance of soluble factors like cytokines within the body (Johnen et al., 2007;

Bennani-Baiti et al., 2008; Bing et al., 2008). Together with the associated weakness, anorexia

and anaemia, cachexia can also cause death in cancer patients (Martignoni et al., 2003; Cotran et

al., 2010).

5

The variability that exists between different cancers, as well as between cancers of the

same organ origin, makes the development of effective treatments extremely difficult. It is

therefore necessary to continue learning more about the mechanisms of tumour pathogenicity, in

order to better understand their mysteries.

1.1.2 Cancer Incidence

In recent years, the absolute global incidence of cancer per year has increased, with a

corresponding rise in mortality (Parkin, et al., 1999; Descriptive Epidemiology Group, 2000;

Mathers et al., 2001; Descriptive Epidemiology Group, 2002; Parkin et al., 2005). About 12.7

million cancer cases and 7.6 million cancer deaths are estimated to have occurred in 2008

worldwide (Ferlay J. 2010). This increase in cancer incidence and mortality is mainly due to an

aging population. Other contributing factors include better screening and diagnostic methods, as

well as an increase in the number of cancer registries collecting patient data. Overall, males have

a higher incidence and mortality rate worldwide than do females. (Jemal A., 2011)

1.1.3 Cancer Aetiology

The exact cause of carcinogenesis has been much debated in the past and remains a

controversial topic. There are three areas that are known to contribute to the initiation and/or

progression of cancer, either individually or in concert: (1) inherited defects; (2) acquired

6

mutations resulting from mistakes during normal cell division; and (3) environmental exposure

(Tripathy, 1995; Simpson et al., 1998; Hahn et al., 2002;; Oliveira et al., 2007; Pavlovic-Calic et

al., 2007; Lynch et al., 2008). The type(s) of genetic alterations and environmental factors differ

between the different cancer types. Hence, the aetiology for different types of cancers may vary

substantially, which has wide implications in terms of screening, treatment and prevention (Wei

et al., 2010).

1.1.4 Inherited Defects

Inherited or familial defects that are known to be associated with a specific condition are

the easiest to detect, especially if a thorough family history is available. These defects are a

useful predictive marker that can be used for screening prior to presentation of symptoms,

resulting in early detection and intervention, and ultimately better outcome (Lynch et al., 2008;

Maradiegue et al., 2008).

1.1.5 Acquired Mutations

Acquired or somatic mutations are usually not detected until a lesion has been removed

and examined. These alterations can vary from patient to patient and are not definitively

predictive. Causative alterations are therefore more difficult to identify. Molecular changes,

either familial or somatic, can alter cell functions including proliferation, invasion and metastatic

7

ability. Changes in specific genes at the DNA, mRNA and protein levels have been observed and

tend to be more common in certain types of cancers. Some genes, for example p53, are mutated

in a wide variety of cancers (Kuribayashi et al., 2008; Meulmeester et al., 2008; Ohnishi et al.,

2008; Tomkova et al., 2008), whereas others, such as the adenomatous polyposis coli (APC) and

mismatch repair (MMR) genes implicated in familial adenomatous polyposis (FAP) and

hereditary non-polyposis colorectal cancer (HNPCC) syndromes, tend to be associated with a

specific malignancy (Hegde et al., 2006; Bonis et al., 2007; Pavlovic- Calic et al., 2007;

Giráldez et al., 2008; Wilkins et al., 2008). Genes important to cell regulation or dysregulation

can be classified into several groups based on function.

1.1.6 Oncogenes

Protooncogenes are genes coding for factors responsible for promoting cell growth,

including growth factors, growth factor receptors, signal transduction proteins, nuclear

transcription proteins, cyclins and cyclin dependant kinases (Tripathy, 1995; Grønbaek et al.,

2007). A mutation in only one allele, whether via a point mutation, a chromosomal

rearrangement or gene amplification, is sufficient to attain a gain-of function in these genes,

which are then termed oncogenes (Studzinski, 1989; Tripathy, 1995; Cordon-Cardo et al., 1997;

Kopnin, 2000; Cotran et al., 2010).

Examples of known oncogenes are myc and fos (transcription factors, involved in

multiple tumour types; myc translocations are seen in Burkitt’s lymphoma; Popescu et al., 2002;

8

Milde- Langosch, 2005; Janz, 2006; De Falco et al., 2007), the fibroblast growth factor (FGF)

int-2 (growth factor, amplified in bladder and breast cancers as well as in melanoma; Klagsbrun,

1989; Benharroch et al., 1990; Yayon et al., 1990), ras (GTP-binding, point mutations detected

in a variety of cancers including lung, colon and pancreas, and in leukaemias; Wark et al., 2006;

Ahmed et al., 2008; Braun, et al., 2008; Emanuel, 2008), cyclin D (cyclin, amplification in

breast, liver and oesophageal cancers; Pignataro et al., 2005; Van Dross et al., 2006), HER-2

/neu (cell surface growth factor receptor, in breast, gastric and ovarian cancer; Moasser, 2007;

Whenham et al., 2008), and Fes (a tyrosine kinase, in leukaemia; Tripathy, 1995; Scheijen et al.,

2002; Kanda et al., 2007).

1.1.7 Tumour Suppressor Genes

Dysregulation of tumour suppressor genes results in a loss of functional control. These

genes inhibit growth by regulating nuclear transcription, the cell cycle, and signal transduction

by down-regulating growth-promoting signals and cell surface receptors (Weinberg, 1991;

Tripathy, 1995; Grønbaek et al., 2007). Potential tumour suppressor genes are often detected by

consistent chromosomal deletions, that is, loss of heterozygosity (LOH; Oliveira et al., 2005).

For tumour suppressor function to be abrogated, both alleles require deactivation (Tripathy,

1995).

Known tumour suppressor genes include p53, a cell cycle regulator mutated in many

tumour types (Oliveira et al., 2005; Lynch et al., 2008; Riley et al., 2008; Scoumanne et al.,

2008), retinoblastoma (Rb), a nuclear cell cycle regulator in retinoblastoma, small cell lung

9

cancer, osteosarcoma, breast and colon cancer (Paggi et al., 1996; Leiderman et al., 2007; Sun et

al., 2007), BRCA-1 and BRCA-2 which are involved in nuclear DNA repair in familial breast

and ovarian cancer (Dillon et al., 1998; Nicoletto et al., 2001; Lynch et al., 2008), nm23, a

nuclear kinase affecting colon, breast and other cancers (Lombardi et al., 2000; Oliveira et al.,

2005), and E-cadherin, a cell surface adhesion molecule found in stomach, breast and familial

gastric cancer (Tripathy, 1995; Tamura, 2006; Masterson et al., 2007; Cheng et al., 2008). Cells

from some tumours use an altered metabolic pattern compared with that of normal differentiated

adult cells in the body (Levine, 2010)

Of all these genes, p53 has been the most widely studied. Up to 50% of all human

tumours display mutations in p53, and the homozygous loss of this gene is seen in many tumours

types (Oliveira et al., 2005; Ohnishi et al., 2008). Normally, this gene detects DNA damage,

arrests the cell in the G1 phase of the cell cycle and initiates DNA repair. If this is successful, the

repaired cell continues on through the cell cycle, but if damage is still present then p53 induces

apoptosis. p53 mutations cause damaged cells to progress through the cell cycle and proliferate

in an uncontrolled fashion (Braithwaite et al., 2005; Cotran et al., 2010).

1.1.8 Apoptosis-Regulating Genes

Often these genes need mutation of just a single allele, however some apoptosis genes do

require deactivation of both alleles for functional dysregulation to occur (Renehan et al., 2001).

10

Bcl-2 and bcl-xL both inhibit apoptosis, whereas bax, bak, bad, and bcl-xS promote cell suicide

(Saikumar et al., 1999; Renehan et al., 2001; Sjöström et al., 2001; Deming et al., 2006; Adams

et al., 2007; Fletcher et al., 2008; Gul et al., 2008; Mohammad et al., 2008; Wong et al., 2008).

The presence of specific enzymes within a cell can also affect apoptosis. The enzyme telomerase

prevents telomere shortening, which in turn prevents senescence and subsequent cell death after

a defined number of cell divisions (Cong et al., 2008). Telomerase, which is not usually present

in normal somatic cells, and other telomere lengthening mechanisms have been detected in

tumour cells (Harley, 2008; Cotran et al., 2010).

1.1.9 DNA Repair Genes

Mutations of DNA repair genes affect a cell’s ability to repair damage to protooncogenes,

tumour suppressor genes and apoptosis-regulating genes, allowing damaged cells to survive and

proliferate (Jascur et al., 2006; Hällström et al., 2008; Lieberman, 2008; Paz-Elizur et al., 2008).

Inactivation of both alleles is necessary to cause dysregulation of this gene type. For example, a

common familial mutation in the mismatch repair genes associated with HNPCC increases

susceptibility to colon cancer (Felton et al., 2007; Ou et al., 2007; Pavlovic-Calic et al., 2007).

DNA repair system may be inactivated or decreased in effectiveness by epigenetic gene

inactivation mechanisms affecting DNA repair genes (Lahtz et al., 2011).

11

1.1.10 Metastasis Suppressor Genes

These genes are able to suppress metastasis but usually have no such effect on

tumourigenesis (Berger et al., 2005; Hedley et al., 2006; Stafford et al., 2008). Examples of

these are nm23, which functions as a metastasis suppressor in breast cancer but not in other

cancers (Fournier et al., 2003; Okabe-Kado et al., 2003; Palmieri et al., 2006), and KAI-1, which

is down-regulated in prostate, bladder and other cancers (Dong et al., 1996; Akita et al., 2000;

Steeg, 2003; Hurst and Welch, 2011).

Tumourigenesis occurs when there is a gain of oncogene function and/or a loss of tumour

suppressor function, leading to alterations in growth, differentiation, or cell

cycle regulation, apoptosis, adhesion protein expression, cell-cell interactions and alterations in

signal transduction (Gonos et al., 1993; Lanfrancone et al., 1994; Coates

et al., 2005). These changes can correlate with clinical features and act as predictors, thereby

allowing their effects on progression, invasion and metastasis to be determined and a likely time

frame for these events to be estimated (Macleod et al., 1999; Velculescu, 2008).

Tumour progression is not a simple event and usually involves the accumulation of

multiple mutations over time (Michor et al., 2004). Activation of several oncogenes, together

12

with loss of two or more tumour suppressor genes and impairment of DNA repair mechanisms, is

likely to occur as a tumour proliferates, invades surrounding tissue and metastasises

(Lanfrancone et al., 1994; Coates et al., 2005; Cheng et al., 2008).

An important question to consider is whether the order of occurrence of these mutations

is important: must there be an initiator mutation to begin the cascade, or can any random

mutation begin the process? In colon cancer there is one model of tumour progression that

describes the preferred sequence in which mutations occur to transform normal epithelium to

neoplastic tissue and neoplastic tissue to a tumour. This model is discussed in details later in this

chapter (Section 1.2.11, page 52).

Although such a clear sequence of events may not be known for many other cancers, it is

thought that an order of progression does exist, and further examination of the role of different

genes in a variety of cancers will help to confirm this (Ilyas et al., 1996; Cotran et al., 2010).

Such research is clinically important in terms of screening, determining appropriate therapies and

predicting disease outcome (Duffy et al., 2008).

Though cancer is a common disease in our society and a significant cause of mortality,

the human body is not totally defenceless against carcinogenesis. In order to metastasise, tumour

cells must detach from the primary tumour, invade through the basement membrane which

comprises collagens, glycoproteins (cadherin family of adhesion molecules) and proteoglycans,

move through the ECM, intravasation into a blood vessel, interact with lymphocytes, adhere to

the basement membrane at a foreign site, extravasate out of the blood vessels and form new

13

tumour masses at a secondary site (Jiang et al., 1994; Tang et al., 1995; Liotta et al., 2002;

Cheng et al., 2008; Clines et al., 2008; Stafford et al., 2008).

Throughout this process, these cells will face the defences of the body and the immune

response (Renehan et al., 2001). Those that survive are ‘strong’ cells that have adapted to their

environment and so once a patient develops metastatic disease he/she is usually no longer

curable (Tang et al., 1995; Hedley et al., 2006; Melvold et al., 2007; Ostrand-Rosenberg, 2008;

Cotran et al., 2010).

Some genetic alterations that cause cancer induce the expression of cell surface antigens

that the body sees as foreign (Bustin et al., 2001). The immune system responds to tumour-

specific antigens and tumour-associated antigens by evoking a cytotoxic T-cell response

(Bhardwaj, 2007; Kim et al., 2007). Generating cytotoxic T-cells against tumour cells with

specific gene mutations makes them very cell-specific (Mantovani et al., 2008). For example,

sensitising T-cells to mutations such as p53, K-ras, CDK4 or bcr-c-abl, enables a faster immune

response towards tumour cells displaying those specific alterations. T-cells can also target

tumour cells that overexpress a particular antigen, such as those that occur in breast and ovarian

cancer where c-erbB2 is overexpressed. The immune system is also able to recognise viral and

embryonic antigens like the carcinoembryonic antigen (CEA), whose expression arises from cell

de-differentiation (Cotran et al., 2010).

14

Natural killer cells, which can be activated by IL-2, also attack tumour cells. However,

they differ from cytotoxic T-cells in that they do not require sensitisation prior to destroying

tumour cells (Papazahariadou et al., 2007; Caligiuri, 2008). Both T-cells and natural killer cells

can release interferon (IFN)-gamma, which activates macrophages that can assist tumour cell

killing by releasing lytic cytokines such as tumour necrosis factor (TNF)-alpha or reactive

oxygen metabolites, leading to yet another effective way in which the immune response kills

these cells (Papazahariadou et al., 2007). So, with all these defences in place, how do cancer

cells evade the immune response? There are several mechanisms that can be adopted: (i) tumour

subclones with reduced antigen expression are favoured; (ii) reduced expression of

histocompatibility antigens; (iii) lack of T-cell sensitisation; (iv) external and/or internal induced

immunosuppression; or (v) tumour-induced apoptosis of cytotoxic T-cells (Cotran et al., 2010).

Even so, to enhance the immune system’s natural killing ability there exists

immunotherapy. This therapy encompasses several options including the harvesting of

tumour-infiltrating lymphocytes and reinfusion following population expansion or transfection

with cytokines to enhance their anti-tumour effects (Burgess, 1998;

Bhardwaj, 2007; Stagg et al., 2007).

15

1.1.11 Environmental Carcinogens

In terms of causative tumourigenic factors, environmental exposure to carcinogens is the

most difficult to confirm. It can take decades to examine the effect of a particular substance on

cellular function and prove its causative tumourigenic effect (Arasaradnam et al., 2008).

Nevertheless, past studies have detected many factors that contribute to an increased cancer risk

(Irigaray et al., 2007).

The role of environmental factors becomes apparent when the incidence of different

cancers in different geographic locations, and the alteration in cancer incidence amongst

immigrants, is examined. In Australia and New Zealand, where the sun emits harmful UV

radiation throughout the year, skin cancer is prevalent. Japan, with its high salt/soy diet, has a

high rate of stomach cancer, but Japanese immigrants in Western society exhibit a higher

incidence of colorectal cancer, which is associated with a low fibre diet (Adlercreutz, 1990).

Similarly, the descendents of immigrants acquire the cancer incidence of their new localities, and

not of the country from which their parents migrated (Cotran et al., 2010). Factors known to

increase the risk of tumourigenesis include:

16

1.1.12 Chemical Carcinogens

There are a range of known chemical carcinogens, these include chemicals like asbestos

which is known to cause mesothelioma and lung and gastrointestinal tract cancers; i) asbestos is

found in old construction and is still present in floor tiles and in brake linings; ii) vinyl chloride

which causes angiosarcoma of the liver; used as a refrigerant, plastic adhesive and aerosol

propellant); iii) 2-naphthylamide and alcohol abuse which causes cancer of the oropharynx,

larynx, oesophagus, and liver; iv) polycyclic aromatic hydrocarbons present in tobacco and

cigarette smoke which causes cancer of the mouth, pharynx, larynx, oesophagus, pancreas,

bladder, and lung; (Belpomme et al., 2007) and produced from animal fat in smoked meat and

fish which cause lung and bladder cancer; v) arsenic and arsenic compounds that cause lung and

skin cancer as well as angiosarcomas present in herbicides, fungicides and in medications

(Oliveira et al., 2007); vi) benzene which causes leukaemia and Hodgkin’s lymphoma; found in

paints and rubber, used in dry cleaning as a solvent; (Belpomme et al., 2007); vii) ethylene oxide

that causes leukaemia; used as a ripening agent for fruit and nuts, and for sterilisation of hospital

equipment); and viii) nitrates which causes gastric cancer, present in food preservatives (Cotran

et al., 2010).

17

1.1.13 Immunosuppressive and Chemotherapy Drugs

Drugs like cyclophosphamide and chlorambucil, which act by damaging DNA, can lead

to an increased risk of developing lymphoid neoplasms and leukaemia (Ember et al., 1995;

Sessink et al., 1999; Belpomme et al., 2007; Rekhadevi et al., 2007).

1.1.14 Radiation Carcinogens

These include UV rays which causes skin cancer; ionising electromagnetic rays including

X-rays and gamma rays; and particulate radiation (alpha particles, beta particles, protons, and

neutrons; Belpomme et al., 2007; Grewal et al., 2008). Individuals exposed to particulate

radiation, from, for example, an atomic bomb explosion, experience a latency period of several

years before presenting with an increased incidence of, in particular, myelocytic leukaemias, as

well as breast, colon, thyroid and lung cancers (Cotran et al., 2010).

18

1.1.15 Bacterial and Viral Carcinogens

DNA viruses implicated in the causation of cancer include the human papillomavirus

(HPV; squamous cell carcinoma of the cervix, oral, and laryngeal cancers); Epstein- Barr virus

(EBV; African Burkitt’s lymphoma, B-cell lymphoma in

immunocompromised individuals, Hodgkin’s disease and nasopharyngeal carcinoma); hepatitis

B virus (liver cancer), and Kaposi sarcoma associated human herpes virus 8 (Belpomme et al.,

2007; Boccardo et al., 2007). The human T-cell leukaemia virus, type 1, is an RNA oncogenic

retrovirus implicated in T-cell leukaemia/lymphoma. A bacterial carcinogen, Helicobacter pylori,

is a known cause of gastric cancers and lymphomas (Ferreira et al., 2008; Cotran et al., 2010).

There are many other environmental carcinogens that have not yet been linked to

tumourigenesis. These will be difficult to identify as their effects can take decades to produce

tumours, and a large population exposed to the same carcinogen, resulting in development of the

same tumours, is required to confirm the substance as an environmental risk factor.

Environmental factors can lead to the generation of genetic alterations. These changes,

once detected, are quicker and easier to screen for and hence form the basis for better screening

and diagnostic tools, and more effective treatment modalities.

19

1.2 Colorectal Cancer

1.2.1. The Colorectum – Anatomy and histology

The colon and rectum are a part of the human gastrointestinal tract, which consists of the

oesophagus, stomach, small intestine, appendix, colon, rectum and the anal canal. In an adult, the

colon is 1-2 metres in length. The colorectum is separated into various segments, which are the

caecum, ascending, transverse and descending colon, hepatic and splenic flexures, the sigmoid

colon and the rectum. The entire colon together with half of the rectum resides within the

peritoneal cavity; the remaining portion of the rectum passes between the perineal muscles and is

positioned extraperitoneally.

The gastrointestinal tract is responsible for the breakdown and absorption of food

materials to supply the body’s cells with a ready source of energy, and for the elimination of the

remaining solid waste products. The colon is responsible for the resorption of about 90% of

water and electrolytes secreted by the small intestine to assist in the breakdown of food and

uptake of nutrients. The colonic epithelium is specialised to also secrete digestive enzymes and

mucus proteins, and is rich with microbial flora, to assist in the formation and propulsion of

unabsorbed material (Lingappa, 1995; Pough, 1996; Davis, 2001). It maintains a tight luminal

barrier and intracellular charge differences, and is able to exclude toxins from cellular absorption

(Lingappa, 1995). Undigested waste products are finally stored in the rectum prior to

elimination.

20

The colonic mucosa is flat and made up of several layers: the mucosa, submucosa,

muscular coat and serosa. The surface epithelium is made up of columnar absorptive cells, or

crypts, with short microvilli and goblet mucous cells. Endocrine cells and undifferentiated crypt

cells are also present. The mucosa lining the caecum and ascending colon has additional Paneth

cells, which secrete lysozymes, at the base of their crypts (Lingappa, 1995; Crawford, 1999).

Beneath the columnar absorptive cells and the membranous cells lie lymphoid tissue nodules.

The membranous cells trancytose antigenic macromolecules to the lymphocytes and thereby act

as the colon’s own immune system. Colonic epithelium is very regenerative and is replaced

every 3-8 days, constantly repairing the surface. This quick turnover means, however, that the

colonic epithelium is very sensitive to radiation and chemotherapies that target cell replication.

Arterial blood supply to the proximal transverse colon is from the superior mesenteric

artery. The remainder of the colon to the rectum is fed by the inferior mesenteric artery, while

the superior haemorrhoidal branch supplies the upper rectum. The lower portion receives its

supply from the haemorrhoidal branch of the internal iliac or internal pudendal artery. Venous

drainage is via similar distribution and is connected to the superior and inferior haemorrhoidal

veins by an anastomotic capillary bed. The colon not only has a rich blood supply but also good

lymphatic drainage (Crawford, 1999). Peristalsis, used to prolong the contact of the luminal

contents with the mucosa in order to increase absorption potential, is mediated by an intrinsic

myenteric plexus including the Meissner and Auerbach plexus, and by extrinsic, autonomic

neural control (Crawford, 1999).

1.2.2 Epidemiology and Incidence

21

Colorectal cancer (CRC) equally affects men and women and is a worldwide concern

(Parkin et al., 1999). In Western countries, CRC is the third most common cancer diagnosed in

adults (Jemal et al., 2008), with most cases diagnosed at over 50 years of age (Cotran et al.,

2010). The median age at which colorectal cancer is diagnosed nowadays is 69 years (Lemmens

V. 2013).

There are over 1.2 million new cancer cases and 608,700 deaths estimated to have

occurred in 2008. The highest incidence rates are found in Australia and New Zealand, Europe,

and North America, whereas the lowest rates are found in Africa and South-Central Asia. Rates

are substantially higher in males than in females. (Jemal et al., 2011)

Although CRC is a global disease, the highest incidence rates are found in Australia and

New Zealand, Europe, and North America, whereas the lowest rates are found in Africa and

South-Central Asia. Rates are substantially higher in males than in females. (Parkin et al., 1999;

Jemal et al, 2011). Patient survival is dependant on a number of factors, in particular, the stage at

diagnosis. Only 39% patients are diagnosed with localised disease when the 5-year survival rate

is 90% (Jemal et al., 2008). A further 36% present with localised invasion and another 19% with

distant metastasis; once this occurs, their 5-year survival drops to 60% and 10% respectively

(Jemal et al., 2008; Jemal et al., 2011).

22

1.2.3 Aetiology

Although definitive causes of colorectal carcinoma are unknown there are a number of

factors associated with an increased risk of this disease. Many environmental factors have been

attributed as causal factors for CRC; they include diet (e.g. high red meat consumption

containing saturated fats that are possibly linked to higher bile production), carcinogenic by-

products of food metabolism, obesity, low physical activity, consumption of alcoholic beverages,

smoking, colonic bacteria substances and inflammatory bowel diseases (Tripathy, 1995;

Crawford, 1999; Boyle et al., 2000; de Leon et al., 2000; Jänne et al., 2000; Heavey et al., 2004;

Arasaradnam et al., 2008; Early et al., 2008; Cotran et al., 2010; Winkels et al, 2012). In

contrast, a diet high in fibre, fruits, vegetables and an intake of vitamins with antioxidant

properties, calcium and folate, combined with regular physical activity shows a protective effect.

This is also seen with hormone-replacement therapy and where non-steroidal anti-inflammatory

drugs are used to treat inflammatory bowel diseases (Batty et al., 2000; Boyle et al., 2000; de

Leon et al., 2000; Jänne et al., 2000; Heavey et al., 2004; Early et al., 2008).

As CRC develops from adenomatous polyps, the presence of these in the bowel leads to

an increased risk of this disease (de Leon et al., 2000). Cancer risk is also increased by genetic

alterations including oncogene mutations, inactivation of tumour suppressor genes and

commonly microsatellite instability. The likelihood of a CRC diagnosis increases when there is

an extensive family history of CRC, or of cancer syndromes such as Familial Adenomatous

23

Polyposis (FAP) resulting from a germline mutation of the APC gene, Hereditary Non- Polyposis

Colorectal Cancer (HNPCC); a mutation of mismatch repair loci detected in 3% of cases, Peutz-

Jeghers syndrome resulting from LKB1 gene mutation and Cowden’s syndrome resulting from

PTEN gene mutation (Tripathy, 1995;; de Leon et al., 2000; Scholefield, 2000; Heavey et al.,

2004).

Other conditions known to increase the likelihood of CRC include inflammatory diseases

such as ulcerative colitis (UC); which has 5% higher risk and Crohn’s disease (Crawford, 1999;

Scholefield, 2000). A family history of ovarian, endometrial, or breast cancer may also increase

the risk of CRC (Scholefield, 2000).

24

1.2.4 Screening

The ultimate goal of cancer screening is to detect tumours in the asymptomatic phase

whilst the disease is confined to earlier, more curable stages, thereby improving recurrence-free

survival. As years can elapse between the formation of colonic polyps to the development of

malignant tumours, it is strongly believed that early detection and removal of colonic polyps can

prevent CRC. Effective screening could therefore result in decreased incidence and mortality

from this disease (Scholefield, 2000; Buckhaults et al., 2001; Atkin, 2003). This theory is

supported by a number of randomised trials which demonstrated that mortality from CRC was

reduced by up to 20% when screening was offered biennially (Atkin, 2003).

Since CRC is prevalent in the over 50 year age group, wide spread population screening

should begin at this age. Thorough investigation of a family history is critical to the process; a

family history of this disease necessitates more frequent screening due to the much increased

likelihood of developing cancer in these individuals (Pavlovic-Calic et al., 2007).

Large scale population screening is possible with the use of available faecal occult blood

test (FOBT) kits, which can detect small amounts of blood in the faeces; their annual use is likely

to detect CRC in the early stages (Atkin, 2003). Such tests are the most extensively used

screening tools for CRC and although highly specific, their overall sensitivity is lower, detecting

only 50-60% of carcinomas (Scholefield, 2000). If positive results are obtained using the FOBT

25

further examination of the individual by barium enema, colonoscopy or flexible sigmoidoscopy

(able to detect 80% CRCs) is warranted (Scholefield, 2000; Buckhaults et al., 2001).

New screening protocols are being developed to detect genetic mutations in DNA

extracted from stool samples, e.g. for k-ras, APC, p53 and BAT26 (Atkin, 2003). Potentially

useful markers for CRC screening would be genes that were differentially expressed in normal,

adenoma and tumour specimens, and which encode for either secreted or cell surface proteins.

Several such genes, TGFB1, LYS, RDP, MIC-1, and REGA, display elevated expression in

adenomas and tumour specimens making them suitable candidates for development of screening

tests able to detect pre-symptomatic neoplasia (Buckhaults et al., 2001).

Population-based colorectal screening programs are feasible only in economically

developed countries, although future attention should also be focused in those areas of the world

with an aging population and increasingly westernized lifestyle (eg, Brazil) (Lambert et al.,

2009). According to a recent randomized trial in the United Kingdom, a one-time flexible

sigmoidoscopy screening between 55 and 64 years of age reduced colorectal cancer incidence by

33% and mortality by 43%. (Atkin et al., 2010)

26

1.2.5 Symptoms

Colorectal cancer at its early stages is likely to be asymptomatic. Once patients present

with symptoms, the disease has already progressed to a later stage. Primary symptoms of CRC

include rectal bleeding or mucus discharge, changes in bowel habits including a feeling of

incomplete emptying of the bowel, constipation or diarrhoea or other changes in the size or shape

of the stool, blood in the stool, tenesmus, fatigue linked with severe iron deficiency anaemia,

abdominal pain, bloating, fever, weight loss and in later stages an inability to expel faeces

(Lingappa, 1995; Crawford, 1999; Hobbs, 2000; Davis, 2001; Cotran et al., 2010).

Patients may also develop obstruction, perforation of the bowel, hypercalcaemia and in

late stages, ascites and liver disease. These symptoms are not specific for CRC; many other

gastrointestinal disorders display these symptoms (Hobbs, 2000).

27

1.2.6 Diagnosis

Abdominal palpation and laboratory tests including FOBT or analysis of known cancer

markers are often performed to determine the likelihood of CRC. In some patients, a digital

rectal examination, or a barium x-ray is also performed (following introduction of barium

sulphate into the colon via an enema; Hobbs, 2000; Davis, 2001). A more definitive early

diagnosis can be obtained using colonoscopy or flexible sigmoidoscopy, ruling out diverticular

disease which displays similar symptoms to CRC; these procedures enable immediate surgical

removal of any potentially malignant colonic polyps detected in the colon or rectum (Crawford,

1999; Hobbs, 2000; Davis, 2001).

Performing biopsies of colorectal lesions results in the ability to differentiate between

benign and malignant growths; histological and pathological staging and grading of these

samples are routinely performed to determine this. Obtaining a personal and family history is

also very important in diagnosing syndromes that can lead to early onset CRC.

28

1.2.7 Familial Factors

Sporadic colorectal tumours form the majority of CRC cases. Of the remaining cases,

which can be as much as 25%, some type of family CRC history is evident (Eng et al., 1993;

Hisamuddin et al., 2004; Jo et al., 2005).

Within this hereditary cancer subset, 5-6% cases are attributed to a genetic predisposition

to one of the familial CRC syndromes outlined below (Jo et al., 2005; Pavlovic-Calic et al.,

2007). These syndromes can be classified into 4 separate groups, based on the presence, absence

and/or type of polyps that form in the colon: (1) Familial Adenomatous Polyposis Syndromes;

(2) Hereditary Non-Polyposis CRC Syndromes (HNPCC); (3) Hamartomatous Polyposis

Syndromes; and (4) Non-Syndrome Familial CRC (Eng et al., 1993; Strate et al., 2005).

A low risk (5-6%) of developing CRC through inheritance occurs when only one first

degree relative was diagnosed with CRC after 55 years of age (Scholefield, 2000). This risk

increases to 20% when the one first-degree relative was diagnosed with CRC before the age of

45, or two or more first- or second-degree relatives suffered from CRC. The risk of developing

CRC increases further (to 80-100%), when FAP and HNPCC is diagnosed (Scholefield, 2000).

In the absence of family details, a cancer history is suspected when an individual is diagnosed

with multifocal tumours within a single organ or at multiple sites with an early age of onset (Eng

et al., 1993); in the case of CRC this is before 45-50 years of age.

29

1.2.7.1 Familial Adenomatous Polyposis (FAP) Syndromes

This disease is inherited in an autosomal dominant manner and displays a high

penetrance (Eng et al., 1993; Hisamuddin et al., 2004; Jo et al., 2005; Davidson, 2007). It

constitute 1% of CRC cases, results in the formation of countless adenomatous polyps in the

colon at around 20 years of age and almost 100% cases will progress to CRC before the patient

turns 50 years old (Eng et al., 1993; Tripathy, 1995; de la Chapelle et al., 1998; Crawford, 1999;

Midgley et al., 1999; Jänne et al., 2000; Jo et al., 2005; Strate et al., 2005; Davidson, 2007;

Early et al., 2008). In order to prevent the almost inevitable development of CRC in these

individuals, a prophylactic colectomy is usually performed (Crawford, 1999; Hisamuddin et al.,

2004; Jo et al., 2005; Strate et al., 2005; Pavlovic-Calic et al., 2007).

Other clinical manifestations associated with this condition include congenital

hypertrophy of the retinal pigment epithelium (CHRPE), supernumerary teeth, and the formation

of polyps in the stomach and small intestine (especially the duodenum; Eng et al., 1993;

Hisamuddin et al., 2004; Jo et al., 2005). A range of benign and malignant tumours such as

cutaneous lipomas or cysts, osteomas, hepatoblastomas, adrenal cortical adenomas, desmoid

tumours, ampullary adenocarcinomas, as well as cancer of the thyroid, stomach and duodenum

may also develop (Hisamuddin et al., 2004; Jo et al., 2005; Strate et al., 2005; Rustgi, 2007).

Eighty percent of FAP cases are caused by dysregulation of APC (Hisamuddin et al.,

2004; Strate et al., 2005; Davidson, 2007; Pavlovic-Calic et al., 2007; Cotran et al., 2010). This

30

is a tumour suppressor gene located on chromosome 5q21 (Tripathy, 1995; Cunningham et al.,

1996; Crawford, 1999; Hisamuddin et al., 2004; Jo et al., 2005; Strate et al., 2005). APC

regulates cell adhesion and migration via β-catenin; Dysregulation of APC results in stabilisation

of β-catenin leading to the uncontrolled transcription of its target genes (e.g. c-myc, cyclin D1,

MMP-7, Axin2/conductin and EphB/Ephrin B (Cunningham et al., 1996; Crawford, 1999;

Midgley et al., 1999; Jo et al., 2005; Cotran et al., 2010).

The most common type of alterations found in APC are nonsense mutations resulting in

protein truncation (Cunningham et al., 1996; de la Chapelle et al., 1998; Hisamuddin et al.,

2004; Jo et al., 2005; Strate et al., 2005). Generally, for colonic polyps to progress to CRC there

are additional genetic alterations such as LOH of 5q, and chromosomes 14, 17, 18 and 22, or

mutations of p53, DCC and K-ras as is observed in sporadic tumours (Eng et al., 1993).

Attenuated FAP (AFAP): AFAP is a modified version of FAP where mutations of APC occur in

either extreme 5’ or 3’ ends of the gene’s exons (Midgley et al., 1999; Hisamuddin et al., 2004;

Jo et al., 2005; Davidson, 2007). These mutations likely affect protein stability and may result in

only partial normal function, thereby leading to the reduction and delayed onset of symptoms

observed for this disease (Eng et al., 1993; Cunningham et al., 1996; Hisamuddin et al., 2004; Jo

et al., 2005).

AFAP is also an autosomal dominant inherited disease, however, compared with FAP

this disease is associated with the formation of fewer colonic polyps (dozens to hundreds) at

around 50-60 years of age and subsequently to a later onset of CRC (Eng et al., 1993; Jo et al.,

2005; Strate et al., 2005; Davidson, 2007). Colorectal polyps tend to form in the proximal colon

31

as flat adenomas increasing the risk of CRC; AFAP also carries an increased risk of developing

extracolonic malignancy (Eng et al., 1993; Strate et al., 2005).

MYH-associated polyposis (MAP): MAP is inherited in an autosomal recessive manner

and only patients with biallelic gene inactivation display an increased risk of CRC (Jo et al.,

2005; Strate et al., 2005; Davidson, 2007). Patients present with multiple adenomatous polyps

but do not display APC gene mutations as usually seen in FAP and AFAP (Jo et al., 2005; Strate

et al., 2005). Further, they display a family history similar to that seen in HNPCC, but without

the associated mutations in MMR genes. Germline mutations of MYH, a base excision repair

gene located on chromosome 1p33-34, were identified as being responsible for the onset of this

condition. There is limited evidence to suggest that missense or nonsense mutation of MYH may

result in the production of truncated, less functional proteins (Hisamuddin et al., 2004; Jo et al.,

2005; Strate et al., 2005).

Gardner syndrome: This syndrome is autosomal dominant and displays mutations of the

APC gene (Eng et al., 1993; Crawford, 1999). A feature of this disease is the formation of polyps

in the small bowel and colon which eventually leads to colorectal tumours (Eng et al., 1993). A

number of soft tissue tumours may also arise including lipomas, osteomas, hepatoblastomas and

fibromas (Eng et al., 1993; Hisamuddin et al., 2004; Strate et al., 2005). Further, CHRPE, dental

abnormalities and skin lesions such as sebaceous cysts may also eventuate (Eng et al., 1993;

Strate et al., 2005).

32

Turcot syndrome: As with the previous FAP syndromes this condition results in the

formation of polyps and adenocarcinomas in the small bowel and the colon (Eng et al., 1993).

The presence of skin lesions such as cafe-au-lait spots or the development of central nervous

system tumours (e.g. gliomas, astrocytomas, ependymomas and medulloblastomas) may also be

detected (Eng et al., 1993; Jo et al., 2005; Strate et al., 2005; Rustgi, 2007). In 67% cases a

germline APC mutation is responsible for disease and in the remaining 33% there is a mutation

in the MMR genes (Strate et al., 2005).

1.2.7.2 Hereditary Non-Polyposis Colorectal Cancer Syndromes

Hereditary Non-Polyposis Colorectal Cancer (HNPCC): Also known as Lynch

syndrome (Davidson, 2007; Giráldez et al., 2008). This autosomal dominant disease is

responsible for 3-6% CRC cases (Eng et al., 1993; Midgley et al., 1999; Hisamuddin et al.,

2004; Strate et al., 2005; Davidson, 2007; Pavlovic-Calic et al., 2007; Rustgi, 2007; Early et al.,

2008). These cases display an 80% risk of developing CRC and occur at an early age with the

mean age of diagnosis for HNPCC-associated CRC being 44 years of age (Eng et al., 1993;

Cunningham et al., 1996; Hisamuddin et al., 2004; Jo et al., 2005; Strate et al., 2005; Davidson,

2007; Giráldez et al., 2008).

Patients may present with colonic polyps but this is not a dominant feature of this disease

(Eng et al., 1993). There is, however, an 18% chance of synchronous tumours arising in the

33

colon and a 40% risk of developing metachronous tumours; the majority of these lesions (72%)

are detected in the proximal colon (Eng et al., 1993; Guillem et al., 1999; Hisamuddin et al.,

2004; Strate et al., 2005).

HNPCC is further divided into two disease subsets. Lynch syndrome I is a milder form of

the disease and displays the formation of colorectal tumours only. Lynch syndrome II is

characterised by the presence of additional extracolonic malignancies which may include cancer

of the skin, brain, breasts, stomach, bile duct, pancreas, small bowel, kidneys, bladder, ureters,

endometrium and ovaries (Eng et al., 1993; Cunningham et al., 1996; Guillem et al., 1999;

Midgley et al., 1999; Hisamuddin et al., 2004; Jo et al., 2005; Strate et al., 2005; Bonis et al.,

2007; Davidson, 2007; Giráldez et al., 2008).

To more accurately identify individuals with HNPCC a classification system known as

the Amsterdam criteria was devised. According to the updated criteria a diagnosis of HNPCC

should be made if: (i) three relatives display HNPCC-related tumours and that 2 of these are

first-degree relatives; (ii) two consecutive generations are affected; (iii) at least one case of

cancer occurred before 50 years of age; (iv) FAP had been excluded as the causative condition;

and (v) the diagnosis was verified via histopathological analysis of the tumour (Eng et al., 1993;

Guillem et al., 1999; Midgley et al., 1999; Hisamuddin et al., 2004; Jo et al., 2005; Strate et al.,

2005; Davidson, 2007).

34

Additionally, according to the Bethesda guidelines a diagnosis of HNPCC is warranted if:

(i) an individual is diagnosed with CRC before the age of 50; (ii) regardless of age, an individual

presents with synchronous tumours (either CRC alone or together with extracolonic tumours) or

develops metachronous CRC; (iii) colorectal tumours that develop before 60 years of age display

high MSI, mucinous/signet-ring differentiation, a medullary growth pattern, a Crohn’s-like

lymphocytic reaction or tumour infiltrating lymphocytes); (iv) CRC was diagnosed in 1 or more

first-degree relatives before the age of 50; or (v) CRC was diagnosed in 2 or more first- or

second-degree relatives regardless of their age (Hisamuddin et al., 2004; Jo et al., 2005; Strate et

al., 2005; Bonis et al., 2007; Davidson, 2007).

It has been determined that HNPCC is caused mainly by inherited mutations of the MMR

genes (Guillem et al., 1999; Strate et al., 2005; Pavlovic-Calic et al., 2007; Giráldez et al.,

2008). These genes are responsible for proofreading and repair of bases during DNA replication

(Tripathy, 1995; Crawford, 1999). The majority of these germline mutations (60-80%) occur in

three MMR genes, MLH1 (chromosome 3p21), MSH2 (chromosome 2p22) and MSH6

(chromosome 2p16); however, PMS1

(chromosome 2q31-33) and PMS2 (chromosome 7p22) have also shown involvement

(Cunningham et al., 1996; de la Chapelle et al., 1998; Crawford, 1999; Hisamuddin et al., 2004;

Strate et al., 2005; Bonis et al., 2007; Davidson, 2007). Dysregulation of these genes results in

DNA replication errors of repeat sequences known as microsatellites (Midgley et al., 1999; Jo et

al., 2005; Strate et al., 2005; Davidson, 2007; Bonadona et al., 2011).

35

Microsatellite instability (MSI) is a well-recognized phenomenon that is classically a

feature of tumours in HNPCC. Ten to 15% of sporadic colorectal cancers, however, will have

MSI. Microsatellite unstable tumours can be divided into two distinct MSI phenotypes: MSI-

high (MSI-H) and MSI-low (MSI-L). MSI sporadic colorectal cancers with a high level of MSI

(MSI-H) form a well-defined group with distinct clinicopathologic features characterized by an

overall better long-term prognosis. (Pawlik, Raut CP et al., 2004)

1.2.7.3 Hamartomatous Polyposis Syndromes

All of the known hamartomatous syndromes are inherited in an autosomal dominant

manner. Even though this subset of diseases only account for less than 1% of CRC cases there is

an increased risk of colorectal- and extracolonic-malignancies

(Strate et al., 2005).

Peutz-Jeghers (PJ) Syndrome: This is a rare syndrome displaying variable penetrance

(Crawford, 1999; Davidson, 2007). It is characterised by the formation of multiple

hamartomatous polyps throughout the entire gastrointestinal (GI) tract; even so, they most

commonly develop in the small bowel but are also often found in the colon and stomach (Eng et

al., 1993;; Jo et al., 2005; Strate et al., 2005; Davidson, 2007). Polyps tend to be moderate to

large in size, firm, pedunculated and lobulated, containing branching bundles of smooth muscles

within that help to identify these growths during histopathological analysis (Crawford, 1999; Jo

et al., 2005; Strate et al., 2005). Due to the large size these polyps may attain there is a likelihood

36

that obstructions, haemorrhage and anaemia may develop (Jo et al., 2005; Strate et al., 2005).

Polyposis generally begins in early childhood to the teen years but in exceptional cases may be

present at birth (Strate et al., 2005; Davidson, 2007). This condition carries with it an increased

risk of CRC and, to a lesser extent, small bowel cancer (Hisamuddin et al., 2004; Strate et al.,

2005).

A number of extracolonic conditions have a higher incidence in PJ syndrome. These include the

formation of sinus, bronchial, lung, uteral and bladder polyps, ovarian cysts, as well as a number

of different malignancies (Eng et al., 1993; Crawford, 1999). Oesophageal, lung, thyroid, gastric,

pancreatic, breast, ovarian, uterine, cervical and endometrial cancer, sex cord tumours and

Sertoli cell tumours (leading to gynecomastia) may all develop in association with this disease

(de la Chapelle et al., 1998; Hisamuddin et al., 2004; Jo et al., 2005; Strate et al., 2005;

Davidson, 2007).

A causative gene of PJ syndrome was identified as being a tumour suppressor gene.

LKB1, also called serine-threonine kinase 11 (STK11), is located on chromosome 19p13 (de la

Chapelle et al., 1998; Hisamuddin et al., 2004; Jo et al., 2005; Strate et al., 2005; Davidson,

2007). It is involved in regulating cell growth, proliferation and apoptosis via the mTOR

pathway by controlling cell metabolism and cellular polarity. Gene dysregulation is usually

caused by either mutation or LOH, thereby leading to the increased risk of cancer observed for

this syndrome (Jo et al., 2005).

37

Familial Juvenile Polyposis (FJP): Another rare disease, FJP results in the formation of

hamartomatous polyps mainly in the colon, rectum and small bowel (Eng et al., 1993; Crawford,

1999; Jo et al., 2005; Strate et al., 2005). To qualify as FJP there must be at least 10 juvenile

polyps present within the GI tract (Hisamuddin et al., 2004). Juvenile polyps are large (1-3 cm in

diameter), smooth, round, shiny, somewhat translucent, slightly lobulated with stalks up to 2 cm

long (Crawford, 1999; Hisamuddin et al., 2004; Strate et al., 2005). Polyposis usually affects

children under the age of 5 but they may develop anytime from childhood to adolescence

(Crawford, 1999; Jo et al., 2005).

This condition has a high risk of colorectal adenoma and carcinoma and potentially also

gastric, small bowel and pancreatic cancer (Crawford, 1999; Hisamuddin et al., 2004; Strate et

al., 2005). Other complications that can arise from this polyposis include haemorrhage and

obstruction. There may also be the presence of microcysts in the epithelia, pulmonary

arteriovenous malformations, jaw abnormalities and digital clubbing (Jo et al., 2005)

Mutations in SMAD4 (chromosome 18q21), bone morphogenic protein receptor 1A

(BMPR1A; chromosome 10q22), PTEN and Endoglin (ENG) have all been detected in FJP

(Hisamuddin et al., 2004; Jo et al., 2005; Strate et al., 2005; Davidson, 2007).

1.2.7.4 Non-Syndrome Familial Colorectal Cancer

Hyperplastic Polyposis: Colorectal polyps can be either benign or malignant. The most

common types of benign polyps are microvesicular, goblet-rich and mucin-poor growths (Rustgi,

38

2007). Sessile serrated adenomas (SSAs), traditional serrated adenomas (TSAs) and mixed

polyps (TSAs and tubular adenomas) carry malignant potential (Rustgi, 2007). There is no clear

pattern of inheritance for these types of polyps but their presence does predispose the patient to

CRC that is more frequently a flat type of tumour and located in the proximal colon, with a

higher probability that synchronous colorectal tumours will develop (Jo et al., 2005; Rustgi,

2007). It has been suggested that hyperplastic polyps progress first to serrated adenomas and

then to carcinomas and that this effect is confined to the colon (Jo et al., 2005; Davidson, 2007).

It has also been suggested that SSAs may actually be the precursors for a subset of sporadic CRC

that display a high level of MSI (Rustgi, 2007). Apart from MSI, other genetic alterations that

were detected in hyperplastic polyps included mutations of BRAF and hypermethylation of

MLH1 (Jo et al., 2005; Davidson, 2007; Rustgi, 2007).

The identification of a number of key genes such as APC, PTEN and the MMR genes in

the development of several familial CRC syndromes has greatly advanced our understanding of

colorectal tumourigenesis in general. Dysregulation of these same genes is also often observed in

cases of sporadic CRC (Eng et al., 1993; Hisamuddin et al., 2004; Strate et al., 2005).

1.2.8 Tumour Markers and Prognostic Factors

A number of cellular surface alterations accompany the transformation of normal to

malignant cells (Hackford, 1993). These changes form the basis to differentiate cell types and

assist in identifying abnormal cells. Tumour markers not only help detect primary tumours in the

39

early stages of disease when cure rates are much improved but they are also useful in

determining the necessity of adjuvant therapies, in the assessment of treatment efficacy and

likelihood of residual disease, and in detection of recurrent or metastatic tumours (Haier et al.,

2000; Janakiram et al., 2008; Cotran et al., 2010). The most commonly utilised tumour marker

for CRC is carcinoembryonic antigen (CEA).

CEA is a glycoprotein that is normally only expressed in foetal colonic mucosa but is

also detectable in the serum of individuals with colorectal adenomas and in up to 90% with CRC

(Hackford, 1993; Hundt et al., 2007). Unfortunately, CEA lacks the specificity and sensitivity to

detect early colorectal tumours as levels are often also elevated in benign colorectal conditions as

well as other cancer types, thereby eliminating CEA as a useful marker for CRC screening

(Tripathy, 1995; Hackford, 1993; Hundt et al., 2007; Kim et al., 2008; Cotran et al., 2010).

However, post-operative levels of CEA that fail to decrease indicate the presence of

residual disease whereas continually increasing levels identify recurrent tumours in 80-95%

cases (Hackford, 1993; Haier et al., 2000). Gastrointestinal cancer-associated antigen (GICA),

the sialyated Lewis antigens SLEX and CO 29.11, and the mucins TAG 72 and MAM-6 are

other tumour markers used to detect CRC but like CEA, no individual marker displays both high

specificity and sensitivity (Hackford, 1993; Kim et al., 2008).

In addition to CEA, a much larger family of 12 carcinoembryonic antigen-related cell

adhesion molecules (CEACAMs) were identified. These molecules carry diverse functions in

40

cell adhesion, in intracellular and intercellular signaling, and during complex biological

processes such as cancer progression, inflammation, angiogenesis, and metastasis. Indeed,

CEACAM1, CEACAM5, and CEACAM6 are now considered valid clinical biomarkers and

promising therapeutic targets in melanoma, lung, colorectal, and pancreatic cancers. These

fascinating proteins illustrate how a better understanding of the CEACAM family of cell

adhesion molecules reveals their functional link to the underlying disease and lead to new

monitoring and targeting opportunities (Beauchemin and Arabzadeh, 2013).

A number of specific oncogenes have been implicated in the development of colorectal

cancer. These include: c-myc, src, kras, wnt, egfr, egf, raf, vegf, mek and many others. In the

study of molecular markers, the roles of p53, p16, telomerase, survivin and aurora kinase in

Australian patients with colorectal cancer have been documented [Lam et al., 2008].

Nevertheless, none of these molecular alterations can give a complete picture of the processes of

carcinogenesis or clear cut indication of prognosis in colorectal cancers.

Recent studies have continued to examine cellular alterations for their potential as early

stage CRC markers. A number of promising markers have been identified and further analysis

will clarify their role in CRC progression and usefulness as tumour markers. Increased detection

of colon cancer secreted protein-2 (CCSP-2), COX-2, nitric oxide synthase (iNOS), HMG-CoA,

ER, β-catenin, 5-lipoxygenase (5-LOX), signal transduction and translation-3 (Stat-3), CA19-9,

cancer procoagulant (CP), GCC, TIMP-1 and decreased detection of RXR were observed as

tumours progressed to higher stage disease (Haier et al., 2000; Xin et al., 2004; Hundt et al.,

2007; Janakiram et al., 2008; Kim et al., 2008). Further, CA195, u-PA, TPA-M and plasma

41

VEGF displayed both high specificity and sensitivity for CRCs with highest specificity (over

90%) and sensitivity (over 75%) observed for soluble cluster of differentiation 26 (sCD26), BSP,

prolactin, fibrin degradation, L6 mRNA and detection of circulating tumour cells using

membrane arrays (~94% specificity and sensitivity), making them exciting targets for continued

evaluation (Haier et al., 2000; Hundt et al., 2007; Kim et al., 2008). Additionally, improved

sensitivity for CRC detection has been achieved through the use of a panel of multiple markers

(Kim et al., 2008).

Anatomic extent of disease at first diagnosis, determined using the staging system for

CRC, is the single most important prognostic factor for CRC with the rate of survival

progressively worsening as the tumour stage increases to penetration of the tumour through the

bowel wall, involvement of regional lymph nodes and finally to the formation of distant

metastases (Mainprize et al., 1998; Crawford, 1999; Haier et al., 2000; Sobin et al., 2002;

Compton, 2003; Compton, 2007; Sayar et al., 2007; Turner et al., 2007; Washington, 2008;

Cotran et al., 2010). Perforation of the bowel wall, serosal involvement, adherence of tumours to

adjacent organs and involvement of a large number of LNs all confer a poor outcome (Compton,

2003; Compton, 2007; Quirke et al., 2007; Turner et al., 2007). Conversely, an improved

outcome occurs as more LNs are identified (Compton, 2007; Washington, 2008) and is likely

due to more accurate staging.

Other factors with prognostic significance include the type of tumour (signet-ring cell and

small cell carcinoma confer a worse outcome; medullary and mucinous carcinoma with

associated MSI confers a better outcome); cell grade (least differentiated cells are associated

42

with a poor prognosis); tumour location (colon tumours have a better prognosis than rectal

tumours); infiltrative tumour border, tumour budding, venous invasion and perineural invasion

all associated with aggressive tumours and poor outcome; MSI-H, a host lymphoid response,

older age, good overall health and longer disease-free interval post-operatively are all favourable

prognostic factors associated with increased survival (Mainprize et al., 1998; Compton, 2003;

Compton, 2007; Quirke et al., 2007; Turner et al., 2007; Washington, 2008). It has also been

suggested that the expertise and surgical technique of the surgeon are important factors in the

postoperative morbidity and mortality of patients, with incomplete resection or inadequate

resection margins (especially the circumferential resection margin in the rectum) associated with

disease recurrence and poor rate of survival (Midgley et al., 1999; Haier et al., 2000; Compton,

2003; Compton, 2007; Quirke et al., 2007; Washington, 2008).

Genetic alterations and expression or loss of expression of proteins also provide

prognostic information. MSI in colorectal tumours confers a favourable disease outcome which

may be due to an enhanced immunogenicity of these tumours (Bustin et al., 2001; Compton,

2003; Turner et al., 2007; Worthley et al., 2007; Kim et al., 2008).

On the other hand, an increased risk of recurrence, formation of metastases and reduced

survival are associated with chromosomal aneuploidy; allelic loss of 18q, 17p and DCC

(Compton, 2003; Turner et al., 2007); increased number of allelic losses per tumour (>5; Fearon

et al., 1990); p53 mutations (Fearon et al., 1990; Houbiers et al., 1995; Hibi et al., 1998;

Midgley et al., 1999; Crowe et al., 2001; Sayar et al., 2007; Worthley et al., 2007); post-

operative K-ras in stool (Fearon et al., 1990; Midgley et al., 1999; Cotran et al., 2010); bcl-2

43

overexpression; overexpression of matrix metalloproteinases (MMP-1, -3, -10, -2, -7, -9; Kim et

al., 2008); reduced E-cadherin, β-catenin expression (Midgley et al., 1999; Bodey et al., 2000;

Haier et al., 2000); microsatellite stability; CpG island methylation (Worthley et al., 2007);

expression of oncofoetal fibronectin, E-selectin and 2-integrin (Haier et al., 2000); and reduced

expression of 6-laminin and CD44-v6 (Haier et al., 2000).

Good progress has been made in the identification of helpful tumour markers and

prognostic factors for CRC, however, there is still a need for specific, sensitive and reliable

factors that will aid in early stage tumour detection and prognosis, assisting in selection of the

most appropriate treatment modalities for individual patients and ultimately improving disease-

free survival.

44

1.2.9 Tumour Classification: Stage and Grade

Accurate staging of colorectal tumours is important in determining the extent of tumour

invasion and consequently prognosis. This has implications for assessing appropriate treatment

strategies for each patient and is useful in evaluating treatment efficacy (Mainprize et al., 1998;

Midgley et al., 1999; Sobin et al., 2002; Compton, 2007; Quirke et al., 2007; Washington, 2008).

Two classification systems commonly used to assess CRC are the TNM and Dukes staging

systems (B; Sobin et al., 2002; Sayar et al., 2007). Fig 1.1, Tables 1.1, 1.2 and 1.3 summarize the

two classification systems and differences between them. Both systems describe the anatomical

extent of disease which has been determined to be the best overall predictor of disease outcome,

with localised, early stage disease associated with a higher rate of survival than late stage disease

(Sobin et al., 2002; Washington, 2008).

Fig 1.1: TNM Classification of colorectal cancer stages. (See table 1.1 for details) – Adapted

from John Hopkins Colon Cancer Centre website (http://www.hopkinscoloncancercenter.org/)

45

Stage Explanation

T Stage

TX Primary tumour cannot be assessed

T0 No evidence of primary tumour

Tis Carcinoma in situ: intraepithelial or invasion of lamina

propria

T1 Tumour invades submucosa

T2 Tumour invades muscularis propria

T3 Tumour invades through muscularis propria into subserosa or

into nonperitonealized pericolic or perirectal tissues

T4 Tumour directly invades other organs or structures and/or

perforates visceral peritoneum

N Stage

NX Regional lymph nodes cannot be assessed

N0 No regional lymph node metastasis

N1 Metastasis in one to three regional lymph nodes

N2 Metastasis in four or more regional lymph nodes

M Stage

MX Distant metastasis cannot be assessed

M0 No distant metastasis

M1 Distant metastasis

46

Table 1.1: TNM staging system for colorectal cancer.

Table 1.2: Duke’s classification of colorectal cancer.

Table 1.3: A comparison of TNM and Duke’s classification systems for colorectal

cancer.

47

Although the TNM classification system was devised more recently and contains greater

anatomical detail in terms of tumour progression, the Dukes system is still the most widely used

tool for clinical assessment of colorectal tumour stage in Australia (referred to as the Australian

ClinicoPathological Staging System).

Clinical staging (cTNM) involves physical examination, imaging, endoscopy, biopsy

and/or surgical exploration and is used initially to determine an appropriate course of treatment,

and later on, to examine treatment efficacy (Sobin et al., 2002). Pathological stage (pTNM),

obtained via post-surgical histopathological analysis of tumour specimens, is the most accurate

measurement of disease progression and is used to determine prognosis. Primary lesions

removed via biopsy or surgical resection are always examined in this manner. Draining regional

LNs are also dissected to determine whether the cancer has spread locally; their site will vary

depending on the segment of colon involved (Sobin et al., 2002; Compton, 2007). Where

possible, metastatic lesions (including distant LNs) will be removed and analysed. Further,

tumour grade is assessed to determine the level of cell differentiation (C; Compton, 2007; Turner

et al., 2007). As cells progress more to an undifferentiated state they display a greater propensity

to invade and metastasise (Sobin et al., 2002).

Morphological features also assist in the assessment of tumour type, invasive potential

and disease outcome. Macroscopically, early lesions may appear as pedunculated, sessile or

48

polypoid (Mainprize et al., 1998; Crawford, 1999). The malignant potential of these

adenomatous polyps depends on their size, histologic type and the extent of epithelial dysplasia

(Crawford, 1999; Midgley et al., 1999). Sessile and flat lesions display a higher rate of

tumourigenicity than do pedunculated or polypoid adenomas (Mainprize et al., 1998).

Pedunculated polyps are less likely to invade into the deep submucosal layer, whereas, lesions

displaying a central depression are more dysplastic (Mainprize et al., 1998). Sessile, villous

adenomas that are larger than 4 cm pose the highest risk of invasion (40%; Crawford, 1999;

Midgley et al., 1999). Similarly, carcinomas with a greater invasive potential may display

irregularities of the mucosal surface such as a depression, fading or loss of normal mucosal

colour, haemorrhagic spots or granularity and nodularity (Mainprize et al., 1998).

Microscopically, the majority of colorectal tumours are adenocarcinomas (up to 98%)

and may include mucinous or colloid variants (higher malignant potential; Crawford, 1999;

Sayar et al., 2007). The mucinous adenocarcinoma subtype is encountered in approximately 14%

of colorectal cancers (Lam et al., 2006). Signet ring cell adenocarcinoma is a type of mucinous

adenocarcinoma which can be defined as tumour cells with prominent intra cytoplasmic mucin

which has their nuclei displaced towards the cell periphery (Lam et al., 2005).

Other cancer types that exist include squamous cell carcinoma, adenosquamous

carcinoma, signet-ring cell carcinoma, neuroendocrine carcinoma, small cell carcinoma and

undifferentiated carcinoma (Crawford, 1999; Compton, 2007). Carcinoid tumours (often detected

49

as metastatic disease), lymphomas and sarcomas are other cancers found to originate in the colon

and rectum (Crawford, 1999).

1.2.10 Current Treatments

Primary treatment for early stage ‘curable’ CRC continues to be surgical excision of the

tumour including the regional lymph nodes (Patwardhan et al., 2006). Advances in surgical

techniques have resulted in improved patient survival rates at each stage of disease. Total

mesorectal excision for rectal tumours, and resection of hepatic or pulmonary metastases have

vastly improved disease prognosis and are now performed not only as palliative therapy but with

curative intent (Patwardhan et al., 2006; van der Voort van Zijp et al., 2008).

Although surgery is the mainstay of CRC treatment, adjuvant chemotherapy is also an

important aspect of increasing patients’ survival rates. The role of adjuvant chemotherapy is to

eradicate micrometastatic tumour deposits, which can increase the chance of cancer recurrence.

Recommendations regarding the role and type of adjuvant chemotherapy for patients with CRC

have evolved greatly in the past 20 years because of the growing number of clinical trials

searching for more effective treatment. AC has shown to improve the risk of recurrence and

mortality of CRC (Brezden-Masley et al., 2013).

As tumours progress to locally advanced disease additional adjuvant therapies including

chemotherapy and radiotherapy are employed, these differ between colon and rectal cancer:

50

Colon cancer: For late-stage colon cancer, systemic postoperative chemotherapy (for example,

using 5-flurouracil (5-FU) and leucovorin) is indicated and reduces cancer related mortality

(Patwardhan et al., 2006; Kosmider et al., 2007).

Rectal cancer: Preoperative radiotherapy is standard clinical practice for advanced rectal cancer

and in combination with surgical resection these therapies reduce tumour recurrence by up to

60% (van der Voort van Zijp et al., 2008). Following progression to locally advanced disease,

systemic chemotherapy (for example, 5-FU, leucovorin or capecitabine) may be used in addition

to radiotherapy; these combined modalities are also referred to as radiochemotherapy

(Patwardhan et al., 2006; Willett et al., 2007; Lindsetmo et al., 2008; Nagy, 2008; van der Voort

van Zijp et al., 2008).

The liver is the most common site for metastatic CRC lesions to form with the second

most common site being the lungs (Biasco et al., 2001; Timmerman et al., 2009). As described

above, the first line of treatment for advanced disease involves surgical metastectomy which is

the only potentially curative treatment for metastases (Biasco et al., 2001; Lindsetmo et al.,

2008; van der Voort van Zijp et al., 2008; Timmerman et al., 2009). Other therapies employed at

the later stages of disease and in cases where the metastatic lesion is located, for example, in an

unresectable portion of the liver include: chemotherapy (for example, using irinotecan or

oxaliplatin) delivered systemically or directly via the hepatic artery; radiofrequency thermal

ablation which causes coagulative necrosis and tissue desiccation; or stereotactic body

51

radiotherapy which is still being examined for efficacy in CRC (Biasco et al., 2001; Small et al.,

2007; Lindsetmo et al., 2008; van der Voort van Zijp et al., 2008; Timmerman et al., 2009).

Additionally, palliative chemo- or radio-therapy with no curative intent may be employed

for metastatic disease (Patwardhan et al., 2006).A number of promising alternative therapies are

currently being examined for use as CRC treatments, these include:

(i) Immunotherapy: This may involve immunisation with tumour-specific

antigens to augment anti-tumour immunity, introduction of

immunostimulatory monoclonal antibodies, or amplification techniques (for

example, using cytokines). For this therapy to be effective initial tumour-

debulking is required and even then genetic and/or epigenetic unstable

tumours may evolve mechanisms allowing them to evade these induced

immune responses (Mazzolini et al., 2007);

(ii) (ii) targeted immuno-gene therapy, which is undergoing clinical trials in

combination with chemotherapy for advanced CRC using bevacizumab

(monoclonal antibody targeting VEGF), cetuximab and pantumumab

(monoclonal antibodies targeting EGFR; Kosmider et al., 2007; Nagy, 2008);

and

(iii) (iii) gene therapy such as suicide gene therapy (enzyme/prodrug system), or

tumour suppressor replacement therapy and oncogene inactivation (Durai et

al., 2008).

52

There are reviews available detailing current and putative treatment regimes and their

associated disease outcomes (Chung-Faye et al., 2000; Midgley et al., 2000; Young et al., 2000;

Patwardhan et al., 2006; Benson III, 2007; Kosmider et al., 2007; Mazzolini et al., 2007; Durai

et al., 2008; Timmerman et al., 2009) and these are outside the scope of this study.

1.2.11 Molecular and Genetic Alterations Found in Colorectal Cancer

The importance of genetic mutations in cancer has been recognised for decades with

obvious genetic involvement observed in inherited cancer syndromes. With advances in

molecular biology numerous studies began to examine the role of genetic alterations in the onset

of tumourigenesis and in disease progression, to invasion and metastasis, and found that they

also play a large role in sporadic tumourigenesis which constitutes the majority of CRC cases

(75%-80%; Sayar et al., 2007).

The goal of molecular studies is to identify key genes involved in these processes that

may act as tumour markers to assist in disease prognosis and identification of putative

therapeutic targets. CRC provides a good model for examination of genetic alterations as early

detection of disease allows access to normal bowel, pre-cancerous lesions (polyps) and tumour

tissues for study. In this way, a number of genes altered in CRC were identified and found not

only in hereditary forms of this disease but also in sporadic CRC cases (for example, APC) and

53

led to the development of the first adenoma-carcinoma sequence (Fearon et al., 1990). Figure 1.2

illustrates progression from normal to adenoma to carcinoma in the colorectum and some major

molecular players in this process.

Fig 1.2: A simplified model of colorectal normal-adenoma-carcinoma progression and the key

molecular players involved in the process of tumourigenesis.

The adenoma-carcinoma sequence describes a model of stepwise genetic alterations that

lead to the development of CRC through different stages of tumourigenesis, progression and

metastasis (Fearon et al., 1990; Tripathy, 1995). An accumulation of several genetic defects (at

least 4-5) occurs with disease progression to malignancy and although alterations may occur at

any disease stage a trend has been observed with some mutations (for example, in APC)

commonly occurring early in the sequence and others (for example, in p53) occurring later

(Fearon et al., 1990; Cho et al., 1992; Tripathy, 1995; Cotran et al., 2010). In the initial model

(Fearon et al., 1990), homozygous loss or mutation of APC (located on chromosome 5q;

54

involved in cellular adhesion and migration) occurs as an early event resulting in

hyperproliferation of the colonic epithelium in around 80% of sporadic CRC cases. Additionally,

Dysregulation of DNA methylation results in abnormal loss (due to methylation) or gain (due to

loss of methylation) of oncogene and/or tumour suppressor gene expression, leading to formation

of early adenomas.

Point mutations of K-ras occur (located on chromosome 12p; resulting in enhanced

cytoplasmic signalling and rapid cell division) and are most commonly detected in advanced

adenomas and carcinomas, as are allelic losses of chromosome 18q (LOH in 50% advanced

adenomas and 70% carcinomas) which was suspected to involve dysregulation of DCC (located

on 18q; encodes an adhesion molecule and may result in loss of cellular cohesion. See Fig 1.2.

Finally, allelic loss of chromosome 17p was detected in the progression step from

advanced adenoma to carcinoma in 75% CRC cases and was associated with mutations in p53, a

common tumour suppressor gene involved in cell cycle regulation and apoptosis (Tripathy, 1995;

Fearon et al., 1990; Crawford, 1999; Midgley et al., 1999; Cho et al., 1992; Cotran et al., 2010).

This traditional model describes the most common form of tumour progression with 70-80%

CRCs developing chromosomal loss, oncogene activation and/or loss of suppressor function;

hence this pathway is also referred to as the chromosomal instability or suppressor pathway

(Worthley et al., 2007).

55

Research data in more recent years have suggested an alternative pathway of CRC

tumour progression (see Figure 1.5; Bodmer, 2006; Worthley et al., 2007). This second pathway

progresses from normal colonic epithelium to carcinoma via a serrated polyp intermediate

(including hyperplastic polyps, mixed polyps and serrated or sessile serrated adenomas; Jass et

al., 2000; Harvey et al., 2007). Although genetic mutations detected in these lesions (for

example, in K-ras) are the same as seen in the suppressor pathway, other mutations (for example,

BRAF mutations detected in 78% serrated adenomas) are only observed in this pathway

(Worthley et al., 2007). Even so, the most common alterations that occur in these lesions are in

the mismatch repair (MMR) genes that are responsible for detection and repair of base

mismatches in daughter DNA strands following DNA replication resulting in MSI (Worthley et

al., 2007).

Dysregulation of MMR genes is responsible for tumourigenesis in up to 80% of HNPCC

cases but has also been consistently detected in 15-20% of sporadic colorectal tumours

(Crawford, 1999; Clark et al., 2004; Sayar et al., 2007). In sporadic cases the most common

alteration observed is epigenetic silencing of hMLH1 (Xiong et al., 2001; Bodmer, 2006;

Worthley et al., 2007). Microsatellites are short tandem repeat sequences (usually 1-6

nucleotides in length) which are the same in every tissue within an individual and remain fixed

throughout life (Cotran et al., 2010).

Instability occurs when MMR genes fail to recognise and repair DNA replication errors

resulting in expansion or contraction of these repeat sequences allowing detection of an altered

nucleotide number in tumour DNA when compared to germline DNA from the same individual

56

(Midgley et al., 1999; Worthley et al., 2007). Tumours with MSI display a certain pattern of

clinical behaviour including a propensity for the proximal colon, rapid rate of progression from

pre-malignant adenoma to invasive disease but an improved overall prognosis (Clark et al.,

2004; Worthley et al., 2007).

57

1.3 JK-1(FAM134B) gene

1.3.1 Introduction

JK-1 gene (also known as FAM134B) is a new gene discovered in 2006, which

appeared to play a role in molecular pathogenesis of oesophageal squamous cell carcinoma. It

has been speculated that the gene has oncogenic properties in the development of that kind of

neoplasm (Tang et al., 2007). A later separate study of a hereditary form of sensory and

autonomic neuropathy revealed that JK-1(FAM134B) gene defect is an important cause of this

disease (Kurth et al., 2009). The actual function of this gene remains unknown, no further studies

were done on this gene and its role in other types of human cancer needs further study and

investigation.

1.3.2 Genomic Location for JK-1 (FAM134B) Gene

The JK-1(FAM134B) gene is located on the short (p) arm of chromosome 5 at position

15.1, from base pair 16,473,146 to base pair 16,617,117 on chromosome 5. It is located 3’

downstream to delta-catenin gene (CTNND2; 604275). The gene location is illustrated in Figure

1.3. Other given names for the gene, in addition to JK-1 and FAM134B are FLJ20152,

58

Fig

1.3

Th

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FLJ22155, FLJ22179 and HSAN2B. (Tang et al 2007; www.genecards.org;

www.ncbi.nlm.nih.gov; http://atlasgeneticsoncology.org)

1.3.

3

JK-

1

(FA

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34B

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Gen

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Des

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J

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(FA

http://www.genecards.org/

http://www.ncbi.nlm.nih.gov/

http://atlasgeneticsoncology.org/

59

M134B) gene belongs to a family of 3 genes, namely FAM (family with sequence similarity)

134A, FAM 134B and FAM 134C. All the 3 are protein coding. The gene has 2 isoforms

produced by alternative splicing. All previous studies on JK-1(FAM134B) refer to isoform 1,

which represents the longer transcript (3234 base pairs compared to length of 3083 from isoform

2) and encodes the longer isoform. (Kurth et al., 2009; www.ncbi.nlm.nih.gov;

http://genome.ucsc.edu)

The gene consists of 9 exons, has a start and end codon and encodes a 497-amino acid,

54681 Da. protein with 2 hydrophobic long segments, in addition to a C-terminal coiled-coil

domain. JK-1(FAM134B) protein isoform 2 differs in the 5’ UTR coding sequence compared to

variant 1 (Genetics Home Reference http://ghr.nlm.nih.gov). The resulting isoform 2 has a

shorter (356 amino acids) and distinct N-terminus compared to isoform 1. There are 1-141

amino-acid missing and substitution of 142-152: RGAQLWRSLSE → MPEGEDFGPGK).

(Kurth et al., 2009; www.ncbi.nlm.nih.gov)

1.3.4 Previous Studies on JK-1 (FAM134B) Gene:

By searching a region of chromosome 5p amplified in Oesophageal squamous cell

carcinoma (OSCC) in a Chinese population, Tang et al. (2007) identified JK-1(FAM134B),

which they called JK1. The deduced 39.3-kD protein has an EGF-like domain, 3 N-glycosylation

sites, 3 N-myristoylation sites, and numerous possible phosphorylation sites. Using multiplex

RT-PCR, they found that JK-1(FAM134B) was overexpressed in a significant number of OSCC


http://genome.ucsc.edu/

http://ghr.nlm.nih.gov/

http://www.uniprot.org/blast/?about=Q9H6L5%5b1-141%5d

http://www.uniprot.org/blast/?about=Q9H6L5%5b142-152%5d


60

cell lines and tumours compared with normal oesophageal cells and tissues. Overexpression of

JK-1(FAM134B) in NIH-3T3 mouse fibroblasts and HEK293 cells caused an increase in growth

rate, colony formation in soft agar, and foci formation in confluent cultures. High-grade

sarcomas were formed in athymic nude mice following subcutaneous injection of JK1-

1(FAM134B) overexpressing NIH-3T3 cells (Tang et al., 2007).

Kurth and colleagues in 2009 stated that the human JK-1(FAM134B) protein contains

497 amino acids. Structure analysis showed that the N-terminal half of JK-1(FAM134B) has 2

unusually long hydrophobic segments of about 35 amino acids each that are separated by a

hydrophilic loop of about 60 amino acids. This structure is similar to that of reticulon proteins

that shape the curvature of endoplasmic reticulum membranes. The C terminus of JK-

1(FAM134B) contains a coiled-coil domain. Northern blot analysis of adult mouse tissues

detected at least 4 Fam134b transcripts. High expression of an approximately 1.5-kb transcript

was detected in testis only. Transcripts of about 3.5 kb were more weakly expressed in dorsal

root ganglia, oesophagus, skeletal muscle, and kidney, and many other tissues showed much

weaker Fam134b expression. In situ hybridization of day-14.5 mouse embryos showed

prominent staining of sensory and autonomic ganglia. In cultured mouse dorsal root ganglia,

Fam134b colocalized with a cis-Golgi marker and partly colocalized with a trans-Golgi marker

(Kurth et al, 2009).

61

Defects in JK-1(FAM134B) are the cause of hereditary sensory and autonomic

neuropathy type 2B (HSAN2B), form of hereditary sensory and autonomic neuropathy, a

genetically and clinically heterogeneous group of disorders characterized by degeneration of

dorsal root and autonomic ganglion cells, and by sensory and/or autonomic abnormalities.

HSAN2B is an autosomal recessive disorder characterized by impairment of pain, temperature

and touch sensation. Onset occurs in the first or second decade, with impaired nociception and

progressive mutilating ulceration of the hands and feet with osteomyelitis and acroosteolysis.

Amputations of the hands and feet are common. Autonomic dysfunction includes hyperhidrosis,

urinary incontinence, and slow pupillary light response. (Kurth et al, 2009; Genetics Home

Reference http://ghr.nlm.nih.gov)

http://ghr.nlm.nih.gov/

62

1.4 Aims and Significance of the Study

This study addresses the profile of the recently discovered JK-1(FAM134B) gene in human

cancer. The study will investigate JK-1(FAM134B) gene at the DNA, mRNA, protein and

functional levels in human cancer on a colorectal cancer model.

The gene has been studied in oesophageal squamous cell carcinoma and has been shown to

play a significant role in the pathogenesis of this malignant neoplasm.

The study will focus mainly on benign and malignant tumours of colorectum, due to the

anatomical relationship between the colon and the oesophagus (the first kind of tissue where this

gene was noted), being part of the embryological and anatomical unit, the gastrointestinal tract.

Although the genetics of the 2 organs (colon and oesophagus) and the pathways of

carcinogenesis are not similar, they do share many genetic characteristics. In addition, many

studies have found common genes that play a role in cancer formation in both organs. (Hibi et

al., 1996; Ito et al., 2007).

Another reason to adopt a colorectal cancer model to study JK-1(FAM134B) gene is a

study by Xu et al in which they observed a high LOH frequency and patterns of allelic losses of

chromosome 5p15.2 in colorectal cancer (Xu, Li et al. 2008) . They suggested that the region is

preferentially deleted and likely to harbour important tumour suppressor genes in colorectal

development and progression.

63

Another study suggested that polymorphism affecting genes at 5p15.2 is a risk factor for

colorectal carcinoma is Japanese population (Matsuo et al., 2002). JS-2 is another recently

discovered gene located at 5p15.2. A recent study has described changes in the copy number and

expression of JS-2 in progression of colorectal neoplasm. In addition, genetic alteration and

differential regulation of JS-2 was found to be related to location, pathological subtypes and

staging of colorectal cancer (Lam et al., 2011).

The JK-1(FAM134B) gene will be investigated using a variety of molecular methods that

will reveal the gene mutations, alterations and polymorphisms, its activities and roles in human

cancer. The main methods that will be utilised are PCR-based procedures used to identify

polymorphisms and mutations using copy number changes, high resolution curve (HRM)

technology and sequencing. Real-time PCR will be used to demonstrate RNA gene expression

changes in both benign and malignant tumours. Immunohistochemistry will be also used to

evaluate outcomes and products of these varieties of changes in progression mechanisms and the

carcinogenesis.

The role of JK-1(FAM134B) gene in clinical and pathological characteristics of human

cancer will be studied. Different clinical features of the tumours, pathological changes such as

tumour grade, stage, size, type and metastasis as well as survival data will be analysed to

establish the relationship between them from the one hand and JK-1(FAM134B) gene mutations,

RNA and protein expression changes on the other hand.

64

In addition, the study will examine the role of genetic alteration of this gene on the

development and progression of different tumours from benign to malignant state, pathways of

carcinogenesis, tumour aggressiveness and likelihood of local spread and distant metastasis.

The study will finally investigate the functional role of JK-1(FAM134B) gene through a

series of in vitro experiments, including gene expression assays in cell lines, gene knock down,

cell proliferation studies and invasion and migration assays.

65

CChhaapptteerr 22

JK-1(FAM134B) DNA Study

66

The DNA study

2.1 Introduction

Understanding the molecular features of specific tumours can increase our knowledge

about the mechanisms underlying disease development and progression. This is particularly

significant for colorectal cancer, which is a heterogeneous complex of diseases developed in a

sequential manner through a multistep carcinogenic process. As such, it is likely that tumours

with similar characteristics might originate in the same manner and have a similar molecular

behaviour (Jass, 2007; Ogino and Goel, 2008). Therefore, studying the molecular features can be

potentially useful for tumour classification and the development of appropriate therapeutic

regimens.

One well-established genetic mechanism by which cancer cells alter the activity of

oncogenes and tumour suppressors is through changes in gene dosage. Detailed characterization

of DNA copy number aberrations have helped identify important oncogenes including ERBB2

and EGFR, as well as tumour suppressors such as TP53(Speleman et al., 2008). The genomic

instability and structural dynamism that characterize cancer cells make this form of genetic

variation particularly intriguing to study in cancer biology.

Discoveries from cancer genome sequencing have the potential to translate into advances

in cancer prevention, diagnostics, prognostics, treatment and basic biology (Mwenifumbo and

67

Marra, 2013). A well-known characteristic of cancer genomes is that they are frequently altered

in their gross chromosomal structure by amplification, deletion, translocation and/or inversion of

chromosomal segments. Such alterations often, of course, concomitantly alter genes in a number

of ways that may be critical to cancer onset or progression. Therefore, characterization of

structural variation in tumour genomes is an important part of any cancer study (Beroukhim et

al., 2007)

.

High resolution melting (HRM) is an emerging technique for detection of nucleic acid

sequence variation (Wittwer et al., 2003). A particularly desirable HRM application is the

detection of cancer specific mutations, especially since the technique does not require

foreknowledge of the sequence variation, as with probe and restriction enzyme approaches. It is

thus able to detect de novo mutations in cancer cell lines and tissues, and is both cheap and

simple, though the technique requires some optimisation and verification by sequencing. HRM

has been used to identify somatic mutations in the c-KIT, BRAF, HER2 and EGFRgenes, to

mention a few (Willmore-Payne et al., 2005; Willmore-Payne, et al., 2006).

This part of the study focuses on using the abovementioned techniques to characterize

changes in JK-1(FAM134B) at the DNA level in cancer and exploring any possible correlations

with clinical and pathological features of the tumours.

68

2.2 Aims of the study

Establish if JK-1(FAM134B) DNA is amplified in colorectal tissue using PCR.

Determine the degree of copy number changes in JK-1(FAM134B) DNA using a semi-

quantitative method (real time PCR).

Correlate clinical and pathological features of colon cancer cases with JK-1(FAM134B)

copy number changes in cancer specimens.

Predict any possible mutation in JK-1(FAM134B) gene using the HRM method.

Correlate clinical and pathological features of colon cancer cases with JK-1(FAM134B)-

predicted mutations by HRM.

Investigate the nature of any found mutations using sequencing.

Investigate the relationship (if any) between FAM134B protein expressed and patients’

survival.

69

2.3 Materials and Methodology

2.3.1 Population and Tissue samples

After full ethical approval was obtained from the Griffith University Human Research

Ethics Committee (GU Ref No: MED/05/06/HREC), 211 colorectal cancer, 32 colorectal

adenoma and 20 colorectal non-neoplastic tissue samples for the study were obtained from

patients in hospitals from Queensland, Australia. Patients who were chosen for this study had

resection for primary colorectal carcinomas between May 2004 and September 2010. Colorectal

adenoma and non-neoplastic tissue samples were collected between October 2002 and April

2009. The patients were chosen consecutively, in an attempt to eliminate any selection bias.

Patient management was by a pre-agreed standardized multidisciplinary protocol

supervised by a senior specialist colorectal surgeon. None of the rectal cancer patients had

undergone neoadjuvant radiotherapy or chemotherapy prior to surgery.

For each sample; the age, gender of the patients as well as the size of cancer in

millimetres site (colon or rectum), sub-sites (caecum, ascending colon, transverse colon

including splenic and hepatic flexures, descending colon, sigmoid and rectum) were

prospectively collected in a computerized database. Sub-sites were also divided into two major

groups, proximal (caecum, ascending colon, transverse colon including splenic and hepatic

flexures) and distal (descending colon, sigmoid and rectum) colon. This classification is

illustrated in Fig 2.1. Lympho-vascular invasion, lymph node involvement and the presence of

70

distant metastasis were also recorded. Follow up, recurrence of cancer and survival data were

also entered to the database to be used in the survival analysis. Furthermore, the presence of

associated benign tumours (adenoma), polyposis, family history of colorectal carcinoma,

presence of metachronous (two or more cancers appearing at different points in time) or

synchronous (two or more histologically distinct simultaneously detected malignancies) tumours

and mismatch repair gene status were all noted.

Fig 2.1 Diagram illustrating colon sites and sub-sites (adapted from www.dwp.gov.uk)

The samples were fixed in 10% formalin, and embedded in paraffin wax according to

standard hospital procedures. The formalin-fixed paraffin-embedded blocks were then cut into

sections, stained by haematoxylin and eosin and mounted on slides following standard clinical

practice. The histological slides were reviewed by an expert hospital pathologist and reviewed

again by the research supervisor and thesis author. The benign and malignant tumours were

71

described and graded according to the World Health Organization (WHO) criteria (Bosman et

al.,2010)

When choosing the tissue samples for the non-neoplastic category, which was mainly

used in the study as a control group, care was taken in choosing samples that were neither

premalignant conditions, nor adjacent to any malignant or premalignant conditions.

Inflammatory bowel diseases were therefore excluded and the samples included were totally

benign with no premalignant potential as diverticular disease, prolapse, angiodysplasia, enteric

fistulae, etc.

The adenoma samples were viewed microscopically and graded histologically into high-

grade and low-grade tumours based on nuclear and architectural features.

All colorectal cancer samples were of the adenocarcinoma type, which constitute the vast

majority of malignant colorectal tumours. Most of the adenocarcinoma tumours were classical,

with a few mucinous and signet-ring variants of adenocarcinoma. Endocrine colon neoplasm like

carcinoid, non-epithelial tumours such as lipoma and malignant lymphoma, or secondary

colorectal tumours were not included in the study, mainly because these tumours are fairly rare

and insufficient numbers would likely be available for proper statistical analysis.

The defining feature of colorectal adenocarcinoma is invasion through the muscularis

mucosa layer into the submucosa and the deeper layers. On pathological examination of

colorectal carcinoma samples, the changes in the glandular architecture and cellular

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differentiation were graded into three major groups (well, moderate and poorly differentiated

cancer). The more the glandular structures resemble normal colonic glands in appearance, the

better the grade.

The histological slides of these samples were reviewed by a senior academic pathologist

(Prof. Alfred Lam), alongside the thesis author. The staging of the malignant colorectal tumours

was performed according to TNM (Tumour, Node, Metastasis) classification adopted in the

American Joint Committee on Cancer. In TNM, “T” denotes tumour invasion, “N” for lymph

node metastasis and “M” for distant metastasis. According to the changes in T, N and M, each

cancer was staged in to 4 groups (Stages 1, 2, 3 and 4).

A thorough explanation of this classification system and the method of colorectal tumour

staging are described below:

TNM classification:

T – Tumour invasion

T1 Tumour invades submucosa

T2 Tumour invades muscularis propria

T3 Tumour invades through muscularis propria into subserosa or into non-peritonealized

pericolic or perirectal tissues

T4 Tumour directly invades other organs or structures and/or perforates visceral peritoneum

73

N – Regional Lymph Nodes

N0 No regional lymph node metastasis

N1 Metastasis in 1 to 3 regional lymph nodes

N2 Metastasis in 4 or more regional lymph nodes

M – Distant Metastasis

M0 No distant metastasis

M1 Distant metastasis

Stage Grouping:

Stage I T1 N0 M0

T2 N0 M0

Stage II T3 N0 M0

T4 N0 M0

Stage III Any T N1 M0

Any T N2 M0

Stage IV Any T Any N M1

The adenocarcinoma was considered mucinous if more than 50% of the lesion is composed of

mucin. Lymph node involvement and the presence of distant metastasis were recorded from the

original pathologist report.

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2.3.2 Clinicopathological data

The median age of the 20 patients (13 males; 7 females) with non-neoplastic colorectal

tissue was 58 years (range, 41-87). Of the 32 patients with colorectal adenomas, 59% (n=19)

were males. The median age of the patients with adenomas was 65 years (range, 33-86). Twelve

of the adenomas (37.5%) were classified as tubular adenomas and 20 samples (62.5%) as

tubulovillous adenomas. More than two-thirds of the adenomas were of low grade (n=22) and

the rest were considered as high grade (n=10). The adenomas were located in the caecum in

28.1% (n=9), ascending colon in 9.4% (n=3), transverse colon in 12.5% (n=4), sigmoid in 9.4%

(n=3) and rectum in 40.6% (n=13).

The median age of the 211 patients with colorectal cancer was 72 years (range, 30-92),

whilst the mean age was 69.4 years. Fifty seven per cent (n=121) of all the 211 patients were

males. The mean size of the cancers was 43.6 mm, ranging between 11-120 mm. The cancers

were located in the caecum, ascending colon, transverse colon, descending colon, sigmoid colon

and rectum in 17.5% (n=37), 9% (n=19), 12.8% (n=27), 2.8% (n=6), 27.5% (n=58) and 30.3%

(n=64) respectively.

Just over ninety per cent (n=191) of the colorectal cancers were conventional non-

mucinous adenocarcinomas and 9.5% (n=20) were mucinous adenocarcinoma. Overall, the

adenocarcinomas were well differentiated in 15.6% (N=33) of the cases, moderately

differentiated in 68.7% (n=145) and poorly differentiated in 15.6% (n=33). The cancers were

classified according to TNM staging system fell into the following categories: stage I in 20.9%

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(n=44), stage II in 33.2% (n=70), stage III in 33.6% (n=71) and stage IV (distant metastasis) in

12.3% (n=26).

Forty-three per cent of colorectal cancer cases had lymph node involvement by the

tumour (n=91). Polyposis associated with a colorectal carcinoma was noted in 8.1% (n=17) of

cases, whilst an associated adenoma was present in 42.2 % of cases (n=89). Histologically, just

above one quarter of cancer cases (n=54) showed lympho-vascular invasion. Out of 211

colorectal cancer cases studies, only 4 (1.9%) had a reported family history of colorectal cancer.

Metachronous cancers were present in 5.7% (n=12) of cases and synchronous tumours were

present in less than 3 % of cases (n=6). In metachchronous tumours, the first encountered

tumour was chosen for the study. In the synchronous tumour category, the more advances

tumour (higher T stage) was selected for the study.

76

2.3.3 DNA extraction

Formalin-fixed, paraffin-embedded (FFPE) tissue is one of the most widely practiced

methods for clinical sample preservation and archiving. Although remains inferior to the DNA

extracted from fresh tissue, multiple studies in the last 2 decades have demonstrated that DNA

extracted from FFPE tissue can be used for copy number analysis as well as mutation analysis,

with reproducible and reliable results. The purified nucleic acids, although fragmented, are

suitable for a variety of downstream genomic and gene expression analyses, such as polymerase

chain reaction (PCR), real-time PCR (q-PCR) and sequencing. (Schweiger et al., 2009; Gilbert,

et al.,2009; Tang et al., 2009; Sato et al., 2004)

Four micrometre sections from each selected formalin-fixed paraffin embedded (FFPE)

tissue block were cut and stained with haematoxylin and eosin to identify the area of interest for

DNA extraction. The histology of the slides was used to distinguish tumour from the

histologically normal surrounding tissue. For DNA extraction, eight 10μm sections were cut and

put on slides. The previously identified tumour tissue was scraped away with a scalpel blade

from adjacent non-tumour tissues and collected in tubes. The surrounding non-tumour tissue was

discarded in order to prevent the dilution effect of non-tumour colon tissue.

The sections were suspended in 1200μl xylene in order to remove paraffin. The tubes

were then centrifuged to move cellular contents to the bottom of the tube and allow removal of

the xylene and dissolved paraffin. This was followed by 2 washes of 1200μl absolute ethanol.

77

Then, they were incubated with proteinase K for 24 hours at 56oC for digestion of proteins.

Further DNA extraction was performed according to the manufacturer’s protocol for Qiagen

DNA extraction kits (Qiagen, Hilden, NRW, Germany). Using Nanodrop Spectrophotometer

(BioLab, Scoresby, VIC, Australia), DNA content was quantified by spectrophotometric

absorption at 260 nm and the DNA concentration was noted in ng/μl, in addition to evaluation of

purity by measuring the A260/A 280 ratio. A ratio of 1.8–2.0 indicates high purity DNA. The

extracts were then diluted to a concentration of 50ng/μl and stored at 4o C until assayed. The

standardized sample concentration provides more reliable results in further quantitative DNA

study using real-time PCR.

The full protocol of the DNA extraction procedure as provided by Qiagen DNA extraction kit

consists of the following steps:

1. Placing paraffin-embedded tissue in a 2 ml microcentrifuge tube.

2. Adding 1200 μl xylene followed by vigorous vortexing.

3. Micro-centrifuging at full speed for 5 min at room temperature

4. Removing supernatant by pipetting

5. Adding 1200 μl ethanol (96–100%) and mixing gently by vortexing.

6. Micro-centrifuging at full speed for 5 min at room temperature.

7. Carefully removing the ethanol by pipetting.

8. Repeating steps 5–7 once.

9. Incubating the open microcentrifuge tube at 37°C for 10–15 min. to evaporate the residual

ethanol.

78

10. Resuspending the tissue pellet in 180 μl Buffer ATL, and adding 20 μl proteinase K, mixing

thoroughly by vortexing, and incubating at 56°C until the tissue is completely lysed.

11. Placing the tubes in a shaking water bath. Samples are lysed overnight.

12. Vortexing for 15 s. then adding 200 μl Buffer AL to the sample, and mixing thoroughly by

vortexing.

13. Adding 200 μl ethanol (96–100%), and mix again thoroughly by vortexing.

14. Pipetting the mixture (including any precipitate) into the DNeasy Mini spin column placed in

a 2 ml collection tube.

15. Micro-centrifuging at 8000 rpm for 1 min

16. Placing the DNeasy Mini spin column in a new 2 ml collection tube, adding 500 μl Buffer

AW1, and centrifuge for 1 min at 8000 rpm, then discarding the flow-through and collection

tube.

17. Placing the DNeasy Mini spin column in a new 2 ml collection tube, adding

500 μl Buffer AW2, and micro-centrifuging for 3 min at 20,000 x g (14,000 rpm) to dry the

DNeasy membrane. Discard flow-through and collection tube.

18. Placing the DNeasy Mini spin column in a clean 1.5 ml or 2 ml microcentrifuge tube and

pipetting 200 μl Buffer AE directly onto the DNeasy membrane.

19. Incubating at room temperature for 1 min, and then microcentrifuging for 1 min at 8000 rpm

to elute.

79

2.3.4 Assessing DNA Purity:

To assess DNA purity, Nanodrop Spectrophotometer (BioLab, Scoresby, VIC, Australia)

was used. DNA content was quantified by spectrophotometric absorption at 260 nm and the \

concentration was noted in ng/μl, in addition to evaluation of purity by measuring the A260/A

280 ratio. A ratio of 1.8–2.0 indicates good purity DNA , with DNA falling outside this range not

being used for analysis.

2.3.5 Primer Design

Primers were designed for DNA analysis of JK-1 (FAM134B) - (GenBank accession

number for variant 1 NM_001034850 and for variant 2 NM_019000) and GAPDH (GenBank

accession number NM_002046) using Primer3 version 0.4.0 (http://frodo.wi.mit.edu/primer3/).

The specificity of the primers was checked using Primer Blast

(http://www.ncbi.nlm.nih.gov/tools/primer-blast) and Primer Premier program version 5

(Premier Biosoft, Palo Alto, Califrnia) to check for primer parameters like GC content, Tm and

∆G, in addition to forecast any possible mismatching, primer dimmer or hairpin formation.

The primers for JK-1(FAM134B) gene were designed to amplify both isoforms of the

gene. The product lengths were 106bp for JK-1(FAM134B) and 88bp for GAPDH. The primer

http://frodo.wi.mit.edu/primer3/

http://www.ncbi.nlm.nih.gov/tools/primer-blast

80

pairs were ordered from Sigma-Aldrich (NSW, Australia). The list of chosen primer sets are

summarized in Table 2.1

The product of the primers for JK-1(FAM134B) gene is located in Exon 7 of the gene at

reference sequence of 1092-1180 of variant 1. Kurth et al. has previously described a

homozygous mutation in the splice donor consensus site of intron 7 of the gene (Kurth et al.,

2009).

\Primer Name Sequence (5’-3’) Primer Size

JK1 Forward

TGACCGACCCAGTGAGGA 18

JK1 Reverse GGGCAAACCAAGGCTTAA 18

GAPDH Forward TGCACCACCAACTGCTTAGC

20

GAPDH Reverse GGCATGGACTGTGGTCATGAG

21

Table 2.1: Primers for JK-1(FAM134B) and GAPDH used in the study

81

2.3.6 Polymerase chain reaction (PCR)

Polymerase chain reaction (PCR) is a technique used for amplification of short DNA

sequence with the help of an enzyme known as DNA polymerase. Polymerase chain reaction

doubles the number of DNA molecules present in each PCR cycle by a process known as DNA

amplification. When the content of the reaction is tracked using fluorescent DNA conjugating

dyes at each cycle, this is considered the best semi-quantitative method for detecting the

presence or absence of particular DNA.

Routine PCR for DNA amplifications were carried out using 50ng of extracted genomic

DNA (1 μl) as a template in a 10 μl PCR reaction mixture containing 2 μl of 5x Mango Taq

reaction buffer, 0.5 μl of each primer, 0.8 μl of 50mM MgCl2 , 0.2 μl of 100mM dNTP mix, 0.2

μl of Mango Taq DNA polymerase and 4.8 μl of 0.1 % DEPC treated water. All of the

components were provided by Bioline USA Inc. Taunton, USA. The mixture was prepared in 0.2

mL PCR tubes.

Thermal cycling was performed using Corbett Research thermocycler (Corbette

Research, NSW, Australia). Initial denaturation at 95o

C for 4 minutes was followed by 40 cycles

comprising 30 seconds at 95o

C, 30 seconds at 60o

C, 30 seconds at 72oC, and a final 10 minutes

extension at 72oC. A PCR reaction without DNA template was used as negative control in each

run.

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DNA gel electrophoresis was performed on the produced amplicons. Two grams of high-

resolution agarose gel (Applichem, Darmstadt, Germany) were added to 100 mL of TAE buffer

and 4 μl of SybrSafe DNA gel stain (Invitrogen, California, USA). The mixture was heated in a

microwave oven on high power for 3 minutes then stirred. The hot mixture was poured in a gel

bath and left to cool down for 20 minutes.

DNA ladder 100 bp (BioLabs, MA, USA) was used as a molecular weight marker for

determination of DNA size. Five μl of DNA loading buffer blue (Bioline USA Inc. Taunton,

USA) was mixed with equal volume of DNA amplicon and loaded in the gel wells. The

electrophoresis was run using PowerPac Basic (BioRad, PA, USA) to generate electric field in

the gel bath at 90V for 20 minutes.

The gel was then transferred to a high-resolution fluorescence digital imaging system

VersaDoc (Biorad, Ca, USA) to obtain digital images of the results.

2.3.7 Real Time Polymerase Chain Reaction (qPCR)

Real time quantitative PCR (qPCR) is a quantitative method that allows quantitation of

genomic DNA or messenger RNA (mRNA) expression. In qPCR, amplified product can be

measured in real time at each PCR cycle through the use of a fluorescent dye. This dye binds to

double stranded DNA only and will give off fluorescence proportional to the amount of DNA in

the PCR reaction. Quantitation of original amounts of DNA/RNA can only be accurately

determined if the amount of DNA in the PCR is tracked using the fluorescence available while

83

the PCR is in the exponential phase. The area typically used for this is the point at which the

amount of DNA first enters this area, and is termed the CT, or cycle threshold

To achieve optimal relative DNA amplification results in quantitative real time PCR,

appropriate normalization strategies are required to control the experimental error and also for

ensuring identical cycling performance. These variations are introduced by various processes

required to extract and process the DNA, during PCR set-up and by the cycling process. For

normalising the real time PCR results choice of housekeeping or control genes are rather critical.

A control gene is a gene which is amplified at a constant level and it can be used for normalizing

the gene amplification results for variable template amount or template quality. In addition,

normalization can be done using different total DNA amounts in the reaction.

To study JK-1 gene copy number changes of the genomic DNA, real-time quantitative

polymerase chain reaction (qPCR) was performed using IQ5 Multicolour Real-Time PCR

Detection system (Bio-Rad, Hercules, CA, USA).

The qPCR was performed in a total volume of 20 μl reaction mixture containing 10μl of

DyNAmo Flash SYBR green master mix (Finnzymes, Espoo, Finland), 1.5 μl of each 5 μmol/L

primer, 3 μl of DNA at 50ng/μl, and 4 μl of 0.1% diethylpyrocarbonate (DEPC) treated water.

For comparing the JK-1 copy number changes, housekeeping gene glyceraldehyde 3-

phosphate dehydrogenase (GAPDH) was used for DNA study. GAPDH has been used

extensively as a ubiquitous control for gene copy number in multiple cancer studies as its copy

84

number remains almost unchanged. All the samples (JK1(FAM134B) and GAPDH) were run in

duplicate and accompanied by a non-template control.

Thermal cycling conditions included initial denaturation of 7 minutes at 95°C which is

needed to denature template DNA and activate the hot start DNA polymerase. This was followed

by 40 cycles of 10 seconds at 95°C (denaturation) and 30 seconds at 60°C (annealing/extension).

Analysis of the melting curve was conducted using eighty cycles of 30 seconds

increasing from 55°C. The melting curves of all final real-time PCR products were analysed for

determination of genuine products and contamination by non-specific products and primer

dimers. To ensure that the correct product was amplified in the reaction, all samples were also

separated on 2% agarose gel electrophoresis. For each tissue sample, the PCR reaction was

performed in duplicate to increase the reliability of the results.

2.3.8 PCR Efficiency:

The real-time PCR efficiency was calculated from the standard curve. A standard curve

was constructed from a set of known concentrations of cDNA generated from universal human

reference RNA (UHRR) (Stratagene, Cedar Creek, TX, USA) for the determination of PCR

efficiency. Comparison of PCR efficiency for both target gene (JK-1) and house-keeping genes

(GAPDH) was done by using DNA from UHRR. The dilution series consisted of concentrations

of 210, 160, 110, 60 and 10ng/μl. ∆Ct for JK-1(FAM134B) and GAPDH was determined for

85

each concentration and the slope of the line of best fit was calculated from a plot with delta Ct on

the y axis and the log of total cDNA on the x axis. The differences in PCR efficiency are

determined by calculating the absolute slope of the line. If the slope of the resulting straight line

is <0.1, amplification efficiencies are comparable. Efficiencies for the JK-1 and GAPDH genes

were found to be sufficiently comparable. (Figure 2.2)

Figure 2.2: Normal probability plot for JK-1 (FAM134B) and GAPDH. The slope of the plot

was less than 0.1 and R2 equals 0.964 (close to 1) which illustrates the comparative efficiency of

the two real time PCRs at multiple concentrations of DNA.

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2.3.9 High-Resolution Melt (HRM)

HRM characterizes double-stranded PCR products based on their melting behaviour as

they transition from double-stranded DNA to single-stranded DNA with increasing temperature.

PCR products can be easily discriminated according to sequence, length, GC content, or strand

complementarity, down to single base pair changes. Understanding the genetic differences

associated with human disease or cancer as well as linking them to biomarkers, such as SNPs or

deletions, is crucial for the prognosis and future treatment of genetic disorders.

Amplification of target sequences (PCR cycling) and HRM analysis were done on the

Rotor-Gene Q (Qiagen, Germantown, MD, USA). For the Rotor-Gene Q, the intercalating dye

used was SsoFast EvaGreen Supermix (Biorad, Hercules, CA, USA). EvaGreen dye is a

fluorescent nucleic acid dye with spectral properties similar to SYBR® Green I and fluorescein.

Unlike SYBR® Green I, EvaGreen dye exhibits very low PCR inhibition, which makes it an

ideal choice for fast qPCR protocols. Thus, it can be used at high concentrations to generate

reater fluorescent signals and provide increased sensitivity, making it ideal for several

applications, including qPCR and high-resolution melting HRM technology.

The reaction mixtures consisted of 5 μl of SsoFast EvaGreen Supermix , 2 μl of

50ng/μl genomic DNA, DEPC treated water 1.5 μl and 0.75 μl of each JK-1 primer in a total

volume of 10 μl. The cycling protocol started with one cycle of 98°C for 2 min. Full activation of

the Sso7d-fusion polymerase occurs within 30 seconds at 95°C. Longer initial denaturation times

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and higher temperatures (98°C) are required for complete denaturation of genomic DNA. This

was followed by 40 cycles of 98°C for 5 s and 60°C for 15 s. Optical measurements in the green

channel were recorded during the extension step to generate a primary melting curve, which was

used to ensure that no contamination, primer dimers or non-specific products were generated that

can affect the accuracy of the HRM that followed.

The melt curve data were generated by increasing the temperature from 65°C to 85°C

for all assays, with temperature increase rate of 0.05°C/s. and recording fluorescence. All

reactions were done in duplicate.

HRM curve analysis was performed using the software Rotor-Gene ScreenClust HRM

Software. It uses an innovative mathematical approach and advanced statistical methods to

differentiate between different alleles in an HRM experiment. By grouping samples into clusters,

Rotor-Gene ScreenClust HRM Software enables efficient mutation scanning.

Rotor-Gene

ScreenClust HRM Software analyses HRM data in 4 steps: normalization, generation of a

residual plot, principal component analysis and clustering. In the first step in analysis, raw data

are normalized by applying curve scaling to a line of best fit so that the highest fluorescence

value is equal to 100 and the lowest is equal to zero. Next, the curves are differentiated and a

composite median curve is constructed using the median fluorescence of all samples. The melt

traces for each sample are subtracted from this composite median curve to draw a residual plot.

The individual sample characteristics are extracted by principal component analysis from

the residual plot. Principal component analysis highlights similarities and differences in the data

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and is used to create a cluster plot in supervised or unsupervised mode. Figure 2.3 illustrates an

example of the way the curves are interpreted in HRM.

Figure 2.3: An example of high resolution melt curve results interpretation. The shape of the

curve differentiate between a non-mutant sample (wild type) and a mutation by the degree of

change from a known standard for a wild type melting curve.

2.3.10 Mutation detection using sequencing

To screen for possible JK-1(FAM134B) gene mutations, gene amplification was

performed using the primer pairs designed as follows: Forward Primer: 5'-

TGACCGACCCAGTGAGGA -3', Reverse Primer: 5'- GGGCAAACCAAGGCTTAA -3'.

Amplifications were carried out using 60ng of extracted genomic DNA in a 10 μl PCR reaction

mixture containing 5.5 μl MasterAmp 2X PCR premix A (MasterAmp™ PCR Optimization

Kits, Epicentre, Wisconsin, USA), 0.4 µM of each primer, and with 4 units of Taq DNA

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polymerase. Initial denaturation at 95o

C for 4 minutes was followed by 45 cycles comprising 30

seconds at 95o

C, 45 seconds at 58 oC, 45 seconds at 72

o C, and a final 7 minutes extension at

72oC. Products were submitted to electrophoresis on 2% agarose gel in TAE buffer and stained

with Cyber safe gel stain (Invitrogen, USA).

After being checked by agarose gel electrophoresis, the appropriate band with strong

visible band was removed by X-tracta, Gel extraction tool (Genewoks, Australia), over the UV

light of the Bio-Rad transilluminator (Bio-Rad, Australia). Weight of agarose gels bands were

obtained and 3 volumes of Buffer QG were added to 1 volume agarose gel. The samples were

then incubated at 50oC until gel was completely dissolved. 1 gel volume of isopropanol was

added and the samples were placed in spin column and centrifuged at high speed for 1 minute.

Flow-through were discarded and 500 μl of Buffer QG were added and centrifuged for another 1

minute. Spin columns were washed with 750 μl Buffer PE, and after 5 minutes were centrifuged

at high speed for 1 minute. Flow-through were discarded again and columns were centrifuged for

an additional minute. Eventually, the product was collected by adding 30 μl Buffer EB to the

centre of the spin columns’ membrane and then centrifuging at high speed for 1 minute.

Fluorescent labeling of products by BigDye® terminator v3.1 cycle Sequencing kit

(Applied Biosystems, Australia) was performed. 3 to 10 nanograms of the extracted amplicon

was mixed well with 3.2 pmol of primer forward and reverse and 2ul of big dye terminator

version 3.1 and 3 ul of 5X sequencing buffer provided by the manufacturer (Applied Biosystems,

Australia). Cycle sequencing reaction like PCR consists of three major steps. First 96°C for 1

90

minute and then repeated cycles of 96°C for 10 seconds, 50°C for 5 seconds and 60°C for 4

minutes for 30 times. Finally the samples were held at 4°C until purification step.

Dye-terminator removal with DyeEx Kit (Qiagen, Australia) was performed in order to

remove unincorporated terminators from sequencing reactions to stop it from interfering with

analysis of sequencing results. In two steps the storage buffer was removed from the columns

and labelled DNA fragments were passed through the gel-filtration material. Samples were then

dried with the thermoconcentrator (Savant Thermoconcentrator,) and sent to our sequencing

facility for loading onto the capillary sequencer (Applied Biosystems 3130, Australia).

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2.3.11 Statistical Analysis:

For the purpose of data analysis, relative quantification is used to determine the ratio

between the quantity of a target molecule in a sample (JK-1 gene) and in the calibrator (the

reference housekeeping gene GAPDH). Since the amplification efficiency of a reference gene is

almost the same as that of the target gene, the comparative ΔΔCt method can be used for relative

quantification.

Both the sample and the calibrator data are first normalized against variation in sample

quality and quantity. Normalized (ΔCt) values are calculated by the following equations: ∆Ct =

Ct JK-1 [sample] – Ct GAPDH [sample]

The samples were analysed in duplicates, therefore, normalised values for each duplicate

sample were averaged to give the final data used. The fold change in the target gene for the

results of quantitative amplification was also calculated for each sample using 2-∆∆Ct

method:

∆∆Ct = (Ct JK-1 – Ct GAPDH) SAMPLE CANCER - (Ct JK-1 - Ct GAPDH) AVG. NORMAL.

Ratios (=Mean Ct JK-1 [sample] / Ct GAPDH [sample]) were also used for display of results. These

were expressed as inverse rations (1/Ratio) in order to reorient changes in ratio to reflect actual

behaviour of JK-1 (i.e. increased ratio = increase in JK-1(FAM134B) amplification). The ratios

were used to compare between different groups.

Moreover, to determine DNA deletion and amplification, fold change was calculated. The

fold-change in gene amplification is equal to 2-ΔΔCt

. A fold change of less than 0.5 was

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considered as deletion in DNA real-time PCR study. On the other hand, a fold change of more

than 2 was noted as amplification of DNA.

For continuous variables (such as inverse ratios), these were analysed using student T-test

and one-way Analysis of Variance (ANOVA) to determine if there was a significant difference

of gene expression between tissue groups. For t-test analysis or ANOVA performed between

different populations, a test of homogeneity was first performed and homogeneity is established.

The Bonferroni adjustment was used to correct for multiple comparisons made. Comparison

between categorical variables was performed using Chi-square test. Fisher’s exact test was used

instead with smaller sample sizes. These 2 statistical analyses were used to calculate DNA copy

number change in different colorectal cancer stages. Survival analysis was conducted using

Kaplan-Meier and Cox regression methods.

All the data was entered into a Microsoft Excel spread sheet first, and then statistical

analysis was performed using the Statistical Package for Social Sciences for Windows (version

21.0, SPSS Inc., Chicago, IL, USA). Significance level was taken at P<0.05.

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2.4 Results

2.4.1 JK-1(FAM134B) identification

JK-1(FAM134B) gene was detectable in all the samples used in the DNA study. Figure 2.4

illustrate that the gene is amplified in varying degrees in all colorectal tissue used (cancer,

adenoma and non-tumour), when GAPDH was used as a control. After performing PCR, a 106-

bp fragment was observed for JK-1(FAM134B) gene and 87-bp fragment for GAPDH gene.

Fig 2.4 : JK-1(FAM134B) gene amplification in colorectal cancer. JK-1 (FAM134B) gene

was detectable in all colorectal tissue samples. The control that was used is GAPDH gene.

Samples 1 and 2: colorectal adenocarcinoma, sample 3 and 4: colorectal adenoma, sample 5:

non-tumour tissue.

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2.4.2 JK-1(FAM134B) copy number changes

In colorectal cancer, 57% (n=120) of cases showed a decrease in JK-1(FAM134B) copy number

(deletion), relative to control tissue. Twenty nine per cent (n=61), on the other hand showed

amplification of DNA copy numbers, and the rest (n=30) showed no significant change in

number of copies of JK-1(FAM134B) gene. Figure 2.5 illustrate this data

Fig 2.5: JK-1(FAM134B) copy number change in colorectal cancer tissue. The most

common change was deletion, followed by amplification of DNA copy number, and a relatively

smaller number of cases with no change in the DNA copy number.

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Colorectal adenomas, on the other hand, were more likely to be amplified than delete with

regards to JK-1(FAM134B) DNA copy number change. 18/32 (56%) of the benign tumours were

amplified, 7 were deleted and another 7 showed no change in number of DNA copies. Figure 2.6

illustrates these differences.

Fig 2.6: JK-1(FAM134B) copy number change in colorectal adenomas. The most common

change was amplification (56%), followed by 23% for both deletion and no change in DNA copy

number for JK-1(FAM134B).

The copy number level of JK-1(FAM134B) DNA in adenocarcinomas was significantly lower in

comparison to control tissue (p < 0.001) and colorectal adenomas (p < 0.001).

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0.7

0.8

0.9

1

1.1

1.2

1.3

Non-tumour Adenoma Cancer

JK-1(FAM134B) DNA amplification levels was slightly higher in adenoma compared to non-

tumour tissue (Inverse ratio is 1.07±0.098), whilst cancer showed a significantly lower levels of

DNA amplification (0.83±0.04). ANOVA showed a statistically significant difference (p=0.001)

(Figure 2.7). After testing for homogeneity and applying Bonferroni correction, the difference

was still statistically significant (p=0.029).

n=20 n=32 n=211

Fig 2.7 : JK-1(FAM134B) amplification levels in different colorectal tissues. Lower level of

amplification ratio (shown as inverse ratio) was obtained for cancer samples compared to the

adenoma and non-tumour samples (p=0.029).

Inverse

Ratio

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Mucinous adenocarcinoma of the colorectum seemed to have more JK-1(FAM134B) DNA

amplifications/no change than deletions (16 vs 4), whilst just over 60% of classical

adenocarcinoma showed deletion. The statistically significant difference (p=0.001) is shown in

table 2.2

Type of cancer Total

Classical Mucinous

JK1 Copy No Change Amplification/No change 75 16 91

Deletion 116 4 120

Total 191 20 211

Table 2.2 : JK-1(FAM134B) DNA copy number change in mucinous colorectal

adenocarcinoma. This variant of adenocarcinoma had much less deletions in DNA copy number

than the classical type. (p=0.001)

JK-1(FAM134B) DNA copy numbers were more likely to undergo deletions with more

advanced T,N or M stages and for overall stage. Similarly, amplifications seemed to be a less

common event in more advanced stages of cancer. Using Chi-square test and Fisher’s exact test,

this difference was statistically significant in T stage (p=0.013), N stage (p=0.05) and overall

cancer stage (p=0.042). Metastasis (M stage) however, although it showed the same overall

trend of DNA copy number change, fell short of being statistically significant (p=0.077). Table

2.3 demonstrate how different stages of colorectal cancer showed different patterns of JK-

1(FAM134B) copy number.

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No other clinicopathologic parameter showed associations with JK-1(FAM134B) DNA copy

number changes.

JK-1(FAM134B) DNA copy number change -----------------------------------------------------------------------------------------

Stage Number Amplification Deletion No change p value ------------------------------------------------------------------------------------------------------------

T Stage T1 8 3 5 0 0.013*

T2 44 19 16 9

T3 121 31 71 19

T4 38 8 28 2

N Stage N0 120 41 61 18 0.05*

N1 91 20 59 12

M Stage M0 185 58 102 25 0.077

M1 26 3 18 5

Overall stage Stage 1 44 19 17 8 0.042*

Stage 2 70 21 42 7

Stage 3 71 18 43 10

Stage 4 26 3 18 5

Table 2.3 : Correlations between JK-1(FAM134B) DNA copy number change and staging

of colorectal cancer.

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2.4.3 HRM Study and sequencing results

High Resolution Melt method was used to screen for possible mutations in JK-

1(FAM134B) gene and explore any possible correlations with clinicopathologic characteristics

of colorectal cancer. An example of the results seen on HRM analysis in this study is illustrated

in figure 2.8

Figure 2.8 HRM study to detect mutations in JK-1(FAM134B) gene. The wild type

and the mutants show a different curve on analysis

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Of the 211 cases in this study, 17 (8.1%) cases showed a mutation on HRM. Two-thirds

of these (11) were heterozygous mutations and 6 were homozygous. The rest of the 194 cases in

the study (91.9%) showed no mutation in that region of the gene and were thus called wildtype.

The presence of mutations in colorectal cancer cases on HRM was associated with distant

metastasis of the tumours. More than one quarter of cases with metastasis (7/26) had a mutation

detected on HRM, yet only about 5 % of cases with no metastasis (10/185) had mutations. The

difference was statistically significant (p=0.002) and the population results are shown in table 2.4

M Stage Total

No metastasis(0) Metastasis (1)

Mutation on HRM Absent 175 19 194

Present 10 7 17

Total 185 26 211

Table 2.4: Correlation between JK-1(FAM134B) mutations detected on HRM and tumour

metastasis. Tumours with detected mutations have much higher chance of metastasis (p=0.002)

In addition to distant metastasis, lymphovascular invasion on histological examination of

the tumours was also more common in tumours with JK-1(FM134B) mutations on HRM.

Around 15% of tumours with lymphovascular invasion had mutations of the gene (8/54),

compared to only about 5 % (9/157) in tumours with no cancer in lymphovascular spaces on

histology. Table 2.5 show this significant difference (p=0.039)

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Lymphovascular invasion Total

Absent Present

Mutation on HRM Absent 148 46 194

Present 9 8 17

Total 157 54 211

Table 2.5: Correlation between JK-1(FAM134B) mutation detected on HRM and tumour

lymphovascular invasion. Tumours with detected mutations have much higher rates of

lymphovascular invasion (p=0.039)

After HRM analysis of possible mutations, two representative samples of colorectal

cancer cases in each group (wildtype, heterozygous mutations and homozygous mutation) were

selected for sequencing. The results reveal an A to C transition at base 1098 on the JK-1 mRNA

variant 1. This mutation is not a known SNP point in the gene, but results in no change in the

amino acid produced (Arg337Arg). The mutation was detected in both representative samples of

the heterozygous group selected for sequencing, but in none of the other groups. The detected

heterozygous mutation is illustrated in figure 2.9

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Normal (JK-1 wildtype)

Mutant (JK-1 heterozygous mutation)

Fig 2.9 Detection of JK-1(FAM134B) mutation in colorectal cancer. There was an A to C

transition at base 1098 on the JK-1 mRNA variant 1, with the amino acid being (Arg337Arg) –

(arrow).

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2.4.5 Survival Analysis

The survival rate of the patients was calculated from the date of surgical resection of the

colorectal carcinomas to the date of death or last follow-up. The median survival for the patients

with colorectal cancer was 56 months and disease free survival had a medium of 48 months.

Thirty-two per cent (n=68) of patients had recurrence of the malignant tumour. During the

follow-up period, 118 (55.9%) patients survived, 82 (38.9%) died and 11(5.2%) were lost to

follow-up.

Using Kaplan-Meier method analysis of all patients with colorectal cancer, patients with

JK-1(FAM134B) DNA copy number deletion survived disease-free for 76 months, compared to

82 months for patients with DNA copy number amplification or no change. The difference,

though not statistically significant (p=0.18), is illustrated in figure 2.10

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Fig 2.10: Survival disease-free distribution by JK-1 (FAM134B) DNA copy number change

in number of months for patients with colorectal carcinoma. Patients with copy number

deletion had a somewhat worse survival compared to patients with amplification or no change in

DNA copy numbers (p=0.18)

Kaplan-Meier analysis of the effect of mutations detected on HRM showed that patients

with JK-1(FAM134B) mutations had significantly shorter survival times compared to the

patients with no mutations (62 months versus 80 months). This was statistically significant

(p=0.048). See figure 2.11

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Fig 2.11: Survival distribution by JK-1 (FAM134B) mutation detected on HRM in number

of months for patients with colorectal carcinoma. Patients with mutations had a worse

survival outcome compared to patients with no detectable mutations (p=0.048)

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2.5 Discussion

To date, this is the first systematic study of JK-1(FAM134B) gene in cancer, at the DNA

molecular level. Previous studies on JK-1(FAM134B) gene have addressed its role in

degenerative neurological diseases (Kurth, 1993; Kurth et al., 2009; Kong et al., 2011;

Davidson et al., 2012) and the only study that investigated the role of this gene in cancer (Tang

et al., 2007) was indeed an RNA expression and functional study.

Chromosomal copy number alterations can lead to activation of oncogenes and

inactivation of tumour suppressor genes (TSGs) in human cancers. These genes play key roles in

multiple genetic pathways to positively and negatively regulate cell growth, proliferation,

apoptosis, and metastasis (Hanahan, 2000).

This research has indicated that change to JK-1(FAM134B) copy number is a common

event in colorectal cancers. The research also shows that low JK-1(FAM134B) copy number

correlates strongly with several clinical and pathological parameters, and may be a useful marker

of survival in colorectal cancer patients. In this study, it has been demonstrated for the first time

that colorectal adenocarcinomas have lower JK-1(FAM134B) copy number than non-neoplastic

tissues and adenoma, implying that the expression of the gene is probably also lower in

colorectal adenocarcinoma.

Adenomas, on the other hand, demonstrated more DNA copy number amplification of

JK-1(FAM134B) gene, compared to non-tumour tissues and cancers. The ability to distinguish

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adenomas that do progress to cancer from those that will not progress is highly relevant for

colorectal cancer screening. Because colorectal tumour progression is driven by an accumulation

of genetic abnormalities, genetic testing focused specifically at these genetic alterations may

show a higher specificity for discriminating adenomas with a high risk of progression from

adenomas that will not progress. In a study by Hermsen and colleagues using chromosomal

CGH, the number of chromosomal alterations was predictive of which adenomas had progressed

to cancer and which had not (Hermsen et al., 2002)

The lower copy number of JK-1(FAM134B) in cancers compared to those of control

tissue and adenomas was highly significant in this study. The high prevalence of JK-

1(FAM134B) deletions in colorectal adenocarcinomas indicates that it may be an important part

of the pathogenesis of many colorectal adenocarcinomas, perhaps in concert with other

mutations. It is possible, however, that as the cancer develops, deletion of JK-1(FAM134B) may

occur simply as a side effect of other mutations associated with the progression, perhaps

associated with the loss of other nearby genes. Further studies, including a DNA micro-array, of

the associated molecular events accompanying JK-1(FAM134B) copy number changes is

warranted.

It is possible that the higher JK-1(FAM134B) DNA copy number in premalignant

tumours may offer some protection from transforming into more aggressive stage. The findings

may imply that JK-1(FAM134B) loss was required in the early stages of carcinogenesis at the

adenoma level and the initial amplification is able to prevent complete cancer transformation, or

be a side effect of other tumour suppressors, but as the tumour progresses to a more advanced

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stage, lower DNA copy numbers of JK-1(FAM134B) dominate, again, potentially as a direct

driver of the change or as a bystander mutation. Further comprehensive analysis of JK-

1(FAM134B) mRNA and protein products, in addition to a functional study of the gene is

performed in this study and results are demonstrated and discussed in the following chapters.

Xu et al previously observed a high LOH frequency and patterns of allelic losses of

chromosome 5p15.2 in colorectal cancer (Xu et al., 2008) . They suggested that the region is


development and progression. The JK-1(FAM134B) gene deletion in colorectal cancer as an

event that happen in more than half of the cases in this study, suggests that JK-1(FAM134B)

may be at least one of these tumour suppressor genes.

Using comparative genomic hybridization (CGH) in 52 cases of oesophageal squamous

cell carcinoma, 52% of the cancers showed gain in 5p in a previous study. (Kwong, Lam et al.

2004) . This study was however conducted on a different type of cancer with different molecular

pathways of carcinogenesis (Maehara et al., 2010) and it showed a trend of gain in a region of

chromosome 5, rather than a specific gene. JK-1(FAM134B) is located in 5p15 and the precise

area of amplification in oesophageal cancers may simply not contain the gene. Thus more

specific studies will be required in other cancers to obtain a better idea of JK-1's role in cancer

development in other tissues.

In this experiment, JK-1(FAM134B) gene copy number changes were highly correlated

with TNM staging of colorectal carcinomas. The higher the pathological TNM stages of the

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cancer, the lower the copy number. More deletions in JK-1(FAM134B) gene are noted in higher

T and N stage. However, M stage (metastasis) although exhibiting the same trend, failed to

achieve statistical significance. This may indicate that FAM134B gene may have an important

role in preventing tumour growth and local spread to lymph nodes, which may be mediated by

integration into other regulatory systems. The gene's influence on the process of actual

metastasis may be weak, perhaps simply associated with the ability to enter the lymph nodes,

rather than a direct contribution to the survival of cancer cells in another tissue niche. Also, it is

likely that chromosomal instability is an early event in colorectal carcinogenesis, and that the

overall DNA copy number altered is not significantly different between metastatic and non-

metastatic tumours once invasive cancer develops, at least with respect to the primary tumours.

Hermsen and colleagues compared genomewide chromosomal aberrations in non-

progressed adenomas to adenomas proven capable of progression toward malignancy. The data

revealed that an accumulation of certain gains and losses were strongly associated with advanced

lesions, including both adenomas that contained foci of carcinoma and simple carcinomas. These

former lesions implicitly demonstrated their capability of progression. The presence of these

“cancer-associated events” in colorectal adenoma thus could be an indicator of high risk of

progression. In addition, the study yielded evidence for the association of multiple independent

patterns of chromosomal aberrations associated with progressed adenomas and colorectal

carcinomas, suggesting the presence of multiple chromosomal instability pathways toward

colorectal cancer (Hermsen, 2002). Therefore, the results of this chapter should only be

interpreted as a part of a more complex tumourigenesis pathway in colorectal tumours.

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On the basis of the data produced, however, JK-1(FAM134B) gene copy number changes

seem to play a role in controlling some steps in development of the invasive phenotype,

potentially affecting pathways such as cell growth, cell attachment, local proteolysis and cell

migration, amongst others.

Amplification of JK-1(FAM134B) gene copy number was more often noted in colorectal

adenocarcinoma of the mucinous type. Mucinous adenocarcinoma is known for being more

aggressive, carrying higher recurrence rates and worse survival (Umpleby et al., 1985;

Yamamoto et al., 1993; Secco et al., 1994; Lam et al., 2006). Other studies have shown that

mucinous adenocarcinoma in addition to behaving differently, may have different genetic

pathways (Park et al., 2006; Leopoldo al., 2008). It is possible that JK-1(FAM134B) has a role

in one of the alternative pathways for mucinous adenocarcinoma development or that the copy

number change noticed is a reflection of other molecular events peculiar to this type of colorectal

carcinoma. Exactly how JK-1 plays into the development of the mucinous subtype of colorectal

cancer will need to be addressed by other research.

This is the first study to investigate possible mutations in JK-1(FAM134B) gene in

cancer. Previous studies by Kurth et al. (2009) stated that the human FAM134B protein contains

497 amino acids. Structure analysis showed that the N-terminal half of FAM134B has 2

unusually long hydrophobic segments of about 35 amino acids each that are separated by a

hydrophilic loop of about 60 amino acids. This structure is similar to that of reticulon proteins

that shape the curvature of endoplasmic reticulum membranes. FAM134B mutations are found

over the entire coding sequence and are prone to loss-of-function mutations. Of the five

http://omim.org/entry/613114#reference1

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homozygous mutations reported to date, three are nonsense mutations, one is a frameshift

mutation, and one is a splice-site mutation. . (Kurth et al., 2009; Davidson et al., 2012; Murphy

et al., 2012).

In this study, colorectal cancers with mutations detected on HRM are more likely to

metastasize and invade tissue lymphovascular spaces. This implies that the particular JK-

1(FAM134B) gene mutation is associated with more aggressive phenotype of colorectal

carcinoma.

Although the mutation detected on sequencing is not an amino acid changing mutation, it

is possible for a non-amino acid changing variation to affect gene expression by changing from a

codon which has more tRNAs available to one where there are fewer tRNAs, which could slow

down the process of gene expression, thereby affecting tumour behaviour. Another possibility is

that this mutation alters an miRNA binding site, which would influence tumour behaviour by

altering transcriptional and post-transcriptional regulation of gene expression.

It is also possible that the presence of the HRM variations actually equates to the

presence of another variant close by or it might be a sign of higher mutation rates in the gene.

Such mutations may well be loss-of-function mutations and be the causative agents behind the

associations seen with clinicopathological features and patient survival. It is worth noting that

due to the small sample size and the limited region of the gene sequenced, a more comprehensive

scan of the gene for mutations is called for and more studies are needed to confirm these results.

http://www.ncbi.nlm.nih.gov/books/n/gene/glossary/def-item/frameshift-mutation/

http://www.ncbi.nlm.nih.gov/books/n/gene/glossary/def-item/frameshift-mutation/

http://www.ncbi.nlm.nih.gov/books/n/gene/glossary/def-item/splice-site-mutation/

112

This study is also the first to investigate the role of JK-1(FAM134B) in the prognosis of

patients with colorectal cancer. A decrease in JK-1(FAM134B) copy number was correlated

with a shorter disease-free survival time. Although the trend was not statistically significant, it

may mean patients with low copy number of JK-1(FAM134B) have more aggressive cancer,

which is supported the finding that low copy number was associated with higher cancer stage

parameters.

Mutations detected by HRM had a strong predictive value in terms of patient survival.

JK-1(FAM134B) mutations were associated with significantly lower survival, which can also be

explained by the previously described association between JK-1(FAM134B) gene mutation and

ability of the tumour to metastasize. Though these results are promising regarding the potential

of JK-1(FAM134B) as a prognostic indicator, the findings need to be confirmed in a larger

cohort of patients with longer follow-up and more extensive mutational analysis.

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CChhaapptteerr 33

JK-1(FAM134B) RNA Study

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Chapter 3: RNA Study

3.1 Introduction

Molecular characterization of any gene usually includes a thorough analysis of RNA

expression. A number of widely used procedures exist for detecting and determining the

abundance of a particular mRNA of a certain gene in a total RNA sample. RT-PCR is the most

sensitive method for detecting and quantitating gene expression. Relative quantitative RT-PCR

involves amplifying an internal control simultaneously with the gene of interest. The internal

control is used to normalize the samples. Once normalized, direct comparisons of relative

abundance of a specific mRNA can be made across the samples (Heid et al., 1996; Avison,

2007).

This part of the study addresses the expression profile of the JK-1(FAM143B) gene in the

pathogenesis of colorectal cancers. Potential associations of total RNA expression of the JK-1

(FAM143B) gene with clinical and pathological features in colorectal cancer and the precursor

lesions was studied. Analysis of the survival data was also performed and correlated with levels

of mRNA expression of the gene.

This is the first study that has analysed the roles of JK-1(FAM143B) mRNA expression

profile in colorectal cancer.

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Establish if JK-1(FAM134B) mRNA is expressed in colorectal tissue using PCR.

Determine the JK-1(FAM134B) mRNA expression levels in colorectal tissue using a

semi-quantitative method (real time PCR).

Correlate clinical and pathological features of colorectal tumour cases with JK-

1(FAM134B) mRNA expression.

Investigate the relationship (if any) between JK-1(FAM134B) mRNA expressed by the

tumours and patients’ survival.

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3.3 Materials and methods

3.3.1 Data collection and Tissue Collection

Two hundred and nine colorectal cancer, 32 colorectal adenoma and 20 colorectal non-

neoplastic tissue samples for the RNA study were collected from patients who underwent

surgery at hospitals in Queensland, Australia. Australian patients who were chosen for this study

had resection for primary colorectal carcinomas, colorectal adenomas and non-neoplastic

colorectal tissue between May 2004 and October 2010. Ethical approval for this study was

obtained from the Griffith University Human Research Ethics Committee (GU Ref No:

MED/05/06/HREC). The patients were consecutively chosen, therefore eliminating any selection

bias.

For each sample; the age and gender of the patients as well as the location and size of

cancer in millimetres were prospectively collected in a computerized database. Lympho-

vascular invasion, lymph node involvement and the presence of distant metastasis were also

recorded. Follow up, recurrence of cancer and survival data were also entered to the database to

be used in the survival analysis. The presence of associated benign tumours (adenoma),

polyposis, family history of colorectal carcinoma, presence of metachronous (two or more

cancers appearing at different points in time) or synchronous (two or more histologically distinct

simultaneously detected malignancies) tumours and mismatch repair gene status were all noted.

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Patient management was by a pre-agreed standardized multidisciplinary protocol

supervised by a senior specialist colorectal surgeon. None of the rectal cancer patients had

undergone neoadjuvant radiotherapy or chemotherapy prior to surgery.

The histological slides of these samples were reviewed by a senior academic pathologist

(Prof. Alfred Lam), alongside the thesis author. The benign and malignant tumours were

described and graded according to the World Health Organization (WHO) criteria (Bosman et

al., 2010). The adenoma samples were also classified into tubular, villous and tubulovillous

according to their structural appearance. In this study, only colorectal adenocarcinoma was

included for the malignant tissues. The adenocarcinoma was considered mucinous if more than

50% of the lesion is composed of mucin. The carcinomas were staged according to the TNM

classification adopted in the American Joint Committee on Cancer (Greene, 2002). The changes

in the glandular architecture and cellular pleomorphism both mucinous and classical

adenocarcinomas were graded in to three major groups (well, moderate and poorly differentiated

cancer). In TNM, “T” denotes tumour invasion, “N” for lymph node metastasis and “M” for

distant metastasis. According to the changes in T, N and M, each cancer was staged in to 4

groups (Stages 1, 2, 3 and 4).

Carcinoma in proximal colorectum (PC) was categorised as carcinoma arising either

from caecum, ascending colon, transverse colon (including hepatic and splenic flexures).

Carcinoma in distal colorectum (DC) was defined as carcinoma arising either from descending

colon, sigmoid colon and rectum.

118

In choosing the tissue samples for non-neoplastic category, which was mainly used in

the study as a control group, care was taken in choosing samples that were neither premalignant

conditions, nor adjacent to any malignant or premalignant conditions. Inflammatory bowel

diseases were also excluded, as they can increase the risk of colorectal carcinoma in the long run.

Examples of the surgically resected benign samples included diverticular disease, prolapse, and

fistulae, amongst others.

For each chosen sample, the formalin-fixed paraffin-embedded block was then cut,

stained by haematoxylin and eosin and mounted for light microscopic examination to confirm

the identity of the lesion for RNA extraction and immunochemical study. For cancer tissue, the

cancer was micro-dissected away from the non-cancer tissue on the formalin-fixed paraffin-

embedded tissue block.

Throughout the last 2 decades, many laboratories have shown that mRNA levels in

formalin-fixed and paraffin-embedded (FFPE) tissue specimens can be quantified by reverse

transcriptase-polymerase chain reaction (RT-PCR) techniques. Multiple studies demonstrated

that extracting mRNA from formalin-fixed and paraffin-embedded (FFPE) tissue samples is

reliable and reproducible method for gene expression studies. (Penland et al., 2007; Specht et

al., 2001; Cronin et al., 2004).

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The median age of the 20 patients (13 males; 7 females) with non-neoplastic colorectal

tissue was 58 years (range, 41-87). Of the 32 patients with colorectal adenomas, 59% (n=19)

were males. The median age of the patients with adenomas was 65 years (range, 33-86). Twelve

of the adenomas (37.5%) were classified as tubular adenomas and 20 samples (62.5%) as

tubulovillous adenomas. More than two-thirds of the adenomas were of low grade (n=22) and

the rest were considered as high grade (n=10). The adenomas were located in the caecum in

28.1% (n=9), ascending colon in 9.4% (n=3), transverse colon in 12.5% (n=4), sigmoid in 9.4%

(n=3) and rectum in 40.6% (n=13).

The median age of the 209 patients with colorectal cancer was 71 years (range, 30-92),

whilst the mean age was 69 years. Fifty five per cent (n=115) of all the 209 patients were males.

The mean size of the cancers was 43.9 mm, ranging between 11-120 mm. The cancers were

located in the caecum, ascending colon, transverse colon, descending colon, sigmoid colon and

rectum in 18.2% (n=38), 9.1% (n=19), 15.3% (n=32), 3.6% (n=8), 25.8% (n=54) and 27.8%

(n=58) respectively.

Eighty nine per cent (n=186) of the colorectal cancers were conventional non-mucinous

adenocarcinomas and 11% (n=23) were mucinous adenocarcinoma. Overall, the

adenocarcinomas were well differentiated in 16.7% (N=35) of the cases, moderately

differentiated in 68.4% (n=143) and poorly differentiated in 14.8% (n=31). The cancers were

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classified according to TNM staging system fell into the following categories: stage I in 22%

(n=46), stage II in 34% (n=71), stage III in 32.5% (n=68) and stage IV (distant metastasis) in

11.5% (n=24).

Forty-two per cent of colorectal cancer cases had lymph node involvement by the tumour

(n=87). Polyposis associated with a colorectal carcinoma was noted in 6.3% (n=13) of cases,

whilst an associated adenoma was present in just above 40% of cases (n=85). Histologically,

approximately one quarter of cancer cases (n=54) showed lympho-vascular invasion. Out of 209

colorectal cancer cases studies, only 5 (2.4%) had a reported family history of colorectal cancer.

A total of 11 patients (5.3%) had metachronous tumours and a only 5 patients in the cohort

(2.4%) had synchronous tumours.

3.3.3 RNA Extraction:

Eight 7 micron slices were sectioned from the selected tissue blocks for RNA extraction.

For each selected block, additional sections were taken for haematoxylin & eosin staining, for

later reference to immediately surrounding histology. H&E stained slides were used to

distinguish tumour from surrounding morphologically normal tissue. Paraffin was then removed

with xylene, followed by centrifugation to move cellular contents to the bottom of the tube and

allow removal of the xylene and dissolved paraffin.

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Total RNA was extracted and purified using Qiagen RNeasy FFPE Kits (Qiagen Pty.

Ltd., Hilden, NRW, Germany), which were specially designed for purifying total RNA from

formalin-fixed, paraffin-embedded tissue sections.

Procedure: The following procedure was followed:-

1. Using a scalpel, trim excess paraffin off the sample block.

2. Cut sections 5–20 μm thick.

3. Immediately place the sections in a 2 ml microcentrifuge tube and close the lid.

4. Add 320 μl Deparaffinization Solution, vortex vigorously for 10 seconds, and centrifuge

briefly to bring the sample to the bottom of the tube.

5. Incubate at 56°C for 3 min, and then allow to cool at room temperature.

6. Add 240 μl Buffer PKD, and mix by vortexing.

7. Centrifuge for 1 min at 11,000 x g (10,000 rpm).

8. Add 10 μl proteinase K to the lower, clear phase. Mix gently by pipetting up and down.

9. Incubate at 56°C for 15 min, then at 80°C for 15 min.

10. Transfer the lower, uncolored phase into a new 2 ml microcentrifuge tube.

11. Incubate on ice for 3 min. Then, centrifuge for 15 min at 20,000 x g (13,500 rpm).

12. Transfer the supernatant to a new microcentrifuge tube taking care not to disturb the pellet.

13. Add DNase Booster Buffer equivalent to a tenth of the total sample volume (approximately

25 μl) and 10 μl DNase I stock solution. Mix by inverting the tube. Centrifuge briefly to collect

residual liquid from the sides of the tube.

14. Incubate at room temperature for 15 min.

15. Add 500 μl Buffer RBC to adjust binding conditions, and mix the lysate thoroughly.

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16. Add 1200 ml ethanol (100%) to the sample, and mix well by pipetting.

17. Transfer 700 μl of the sample, including any precipitate that may have formed, to an RNeasy

MinElute spin column placed in a 2 mlcollection tube. Close the lid gently, and centrifuge for 15

seconds at ≥8000 x g (≥10,000 rpm). Discard the flow-through.

18. Repeat step 17 until the entire sample has passed through the RNeasy MinElute spin column.

19. Add 500 μl Buffer RPE to the RNeasy MinElute spin column. Close the lid gently, and

centrifuge for 15 s at ≥8000 x g (≥10,000 rpm). Discard the flow-through.

20. Add 500 μl Buffer RPE to the RNeasy MinElute spin column. Close the lid gently, and

centrifuge for 2 min at ≥8000 x g (≥10,000 rpm) to wash the spin column membrane. Discard the

collection tube with the flow-through.

21. Place the RNeasy MinElute spin column in a new 2 ml collection tube (supplied). Open the

lid of the spin column, and centrifuge at full speed for 5 min. Discard the collection tube with the

flowthrough.

22. Place the RNeasy MinElute spin column in a new 1.5 ml collection tube. Add 14–30 μl

RNase-free water directly to the spin column membrane. Close the lid gently, and centrifuge for

1 min at full speed to elute the RNA.

A diagram illustrating the protocol followed is shown in figure 3.1

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Figure 3.1: Qiagen RNeasy Formalin-fixed paraffin-embedded RNA extraction protocol.

124

3.3.4 Assessing RNA Purity and Integrity:

To assess RNA purity and integrity, Nanodrop Spectrophotometer (BioLab, Scoresby,

VIC, Australia) and Bio-Rad Experion electrophoretogram instrument (Bio-Rad, Hercules, CA)

were used. RNA content was quantified by spectrophotometric absorption at 260 nm and the

DNA concentration was noted in ng/μl, in addition to evaluation of purity by measuring the

A260/A 280 ratio.

A ratio of 1.8–2.0 indicates good purity DNA. Integrity of RNA was assessed by Bio-Rad

Experion device and Experion™ RNA StdSens Analysis Kit. The integrity was evaluated using

special Bio-Rad Experion software by observing total size of RNA transcripts along with 18S

and 28S peaks. (Figure 3.2)

Figure 3.2: RNA quality determined by Bio-Rad Experion. RNA is shown in size bands of

descending size on the left and graphed as fluorescence (total RNA) on the Y axis and

125

approximate size on the X-axis. The presence of RNA from 18S and 28S ribosome subunits (as

evident here) in distinct peaks denotes good quality of the RNA extracted.

3.3.5 cDNA Preparation :

Reverse transcription reactions were performed using 1 µg (5 μl) of total RNA in a final

reaction volume of 20 μl. For this purpose, DyNAmo™ cDNA Synthesis Kit (Finnzymes, Espoo,

Finland) was used. The cDNA synthesis premix was prepared first, that consisted of 10 μl of 2x

reverse transcription (RT) buffer, 0.75 μl of random hexamers and another 0.75 μl of oligo dT as

primers, 1.5 μl of RNAse-free water and 2 μl of M-MuLV RNase H+reverse transcriptase.

The tubes were then placed into a thermal cycler (Corbette Research, NSW, Australia)

and were run through pre-denaturation, primer extension, cDNA synthesis and reaction

termination steps, according to manufacturer instructions. Each cDNA sample was diluted to 30

ng/ μl for providing uniformly concentrated samples for real-time PCR. Samples were stored in a

-20ºC freezer till used.

3.3.6 Real-time Quantification PCR

To study JK-1(FAM134B) gene RNA expression changes, an IQ5 Multicolour Real-

Time PCR Detection system (Bio-Rad, Hercules, CA, USA) was used to perform real-time

quantitative polymerase chain reaction (q-PCR).

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q-PCR was performed in a total volume of 20 μl reaction mixture containing 10μl of

DyNAmo Flash SYBR green master mix (Finnzymes, Espoo, Finland), 1.5 μl of each of 5

μmol/L primers, 3 μl of cDNA at 50ng/μl, and 4 μl of 0.1% diethylpyrocarbonate (DEPC) treated

water. For comparing the JK-1 gene expression changes, housekeeping gene glyceraldehyde 3-

phosphate dehydrogenase (GAPDH) was used. GAPDH has been used as a ubiquitous control

for gene expression in many cancer studies as its expression remains almost unchanged. All the

samples (JK-1(FAM134B) and GAPDH) were run in duplicate and accompanied by a non-

template control (distilled water).

Thermal cycling consisted of initial step of 7 minutes at 95°C which is needed to

denature template cDNA and activate the hot start DNA polymerase in the DyNAmo master mix.

This was followed by 40 cycles of 10 seconds at 95°C (denaturation) and 30 seconds at 60°C

(annealing/extension). Melting curve analysis was conducted using eighty cycles of 30 seconds

increasing 1°C/cycle from 55°C. The melting curves of all final real-time PCR products were

observed for determination of genuine products. Contamination by non-specific products and

primer dimers resulted in samples being excluded. To ensure that the correct product was

amplified in the reaction, all samples were also separated on 2% agarose gel electrophoresis.

3.3.7 Primer Design:

Primers were designed for the amplification and expression analysis of JK-1 (FAM134B)

- (GenBank accession number for variant 1 NM_001034850 and for variant 2 NM_019000) and

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GAPDH (GenBank accession number NM_002046) using Primer3 version 0.4.0

(http://frodo.wi.mit.edu/primer3/).

Primers were also checked for specificity using Primer Blast


(Premier Biosoft, Palo Alto, CA, USA) to check for primer parameters like GC content, melting

temperature of the primers and ∆G to prevent any possible mismatching, primer dimer or hairpin

formation.

The primers for JK-1(FAM134B) gene were designed to amplify both isoforms of the

gene. The product lengths were 106bp for JK-1 and 88bp for GAPDH. The primer pairs were

ordered from Sigma-Aldrich (Sydney, NSW, Australia). The list of chosen primer sets are

summarized in Table 3.1.

Primer Name Sequence (5’-3’) Primer Size (base pairs)

===============================================================

JK-1 forward TGACCGACCCAGTGAGGA 18

JK-1 reverse GGGCAAACCAAGGCTTAA 18

GAPDH forward TGCACCACCAACTGCTTAGC 20

GAPDH reverse GGCATGGACTGTGGTCATGAG 21

Table 3.1: Primes for JK-1(FAM134B) and GAPDH genes.


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3.3.8 PCR Efficiency:

The efficiency of real-time PCR assay was calculated from the standard curve. (Livak et

al., 2001). A standard curve was constructed from a set of known concentrations of cDNA

generated from universal human reference RNA (UHRR) (Stratagene, Cedar Creek, TX, USA)

for the determination of PCR efficiency. Comparison of PCR efficiency for both target gene

(JK-1) and house-keeping genes (GAPDH) was performed by using the same cDNA dilution

from UHRR. The dilution series consisted of concentrations of 210, 160, 110, 60 and 10ng/μl.

∆Ct for JK-1 and GAPDH was determined for each concentration and the slope of the line of

best fit for the data obtained was calculated from a plot with delta Ct on the y axis and the log of

total cDNA on the x axis. The differences in PCR efficiency were determined by calculating the

absolute slope of the line. If the difference in the slopes of the resulting straight lines were <0.1,

amplification efficiencies between the PCRs were considered comparable (Dorak, 2006).

Efficiencies for the JK-1 and GAPDH genes were found to be sufficiently comparable. (Figure

3.3)

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Figure 3.3 : Normal probability plot for JK-1 (FAM134B) and GAPDH. The slope of the

plot was less than 0.1 and R2 equals 0.964 (close to 1) which illustrates the comparative

efficiency of the two real time PCRs at multiple concentrations of cDNA.

3.3.9 Statistical Analysis:

For the purpose of data analysis, relative quantification is used to determine the ratio

between the quantity of a target molecule in a sample (JK-1 gene) and in the calibrator (the

reference housekeeping gene GAPDH). (Livak et al., 2001). Since the amplification efficiency

of a reference gene is almost the same as that of the target gene, the comparative ΔΔCt method

can be used for relative quantification.

130

Both the sample and the calibrator data are first normalized against variation in sample

quality and quantity. Normalized (ΔCt) values are calculated by the following equations: ∆Ct =

Ct JK-1 [sample] – Ct GAPDH [sample]

The samples were analysed in duplicates, therefore, normalised values for each duplicate

sample were averaged to give the final data used. The fold change in the target gene for the

results of quantitative amplification was also calculated for each sample using 2-∆∆Ct

method:

∆∆Ct = (Ct JK-1 – Ct GAPDH) CANCER (sample) - (Ct JK-1 - Ct GAPDH) NORMAL (average).

Ratios (=Mean Ct JK-1 [sample] / Ct GAPDH [sample]) were also used for display of results to

allow direct comparison of cancer and normal tissue populations. These were expressed as

inverse rations (1/Ratio) in order to reorient changes in ratio to reflect actual behaviour of JK-1

(i.e. increased ratio = increase in JK-1 expression). The ratios were used to compare between

different groups.

Moreover, to determine RNA over and under-expression, fold change was calculated.

The fold-change in gene expression is equal to 2-ΔΔCt

. A fold change of less than 0.5 was

considered as under-expression in RNA real-time PCR study. On the other hand, a fold change

of more than 2 was noted as over-expression in RNA. Inverse ratios and fold changes were

analysed using student T-test and one-way Analysis of Variance (ANOVA) to determine if there

was a significant difference of gene expression between tissue groups.

131

For t-test analysis or ANOVA performed between different populations, a test of

homogeneity was first performed and homogeneity is established. Comparison between

categorical variables was done using Chi-square test,. Fisher’s exact test was used instead with

smaller sample sizes. Survival analysis was conducted using Kaplan-Meier and Cox regression

methods.

All the data was entered into a computer database and the statistical analysis was

performed using the Statistical Package for Social Sciences for Windows (version 21.0, SPSS

Inc., Chicago, IL, USA). Significance level was taken at P<0.05.

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3.4 RESULTS

3.4.1 mRNA expression of JK-1 (FAM134B) gene in different colorectal tissues

Using PCR, RT-PCR and gel electrophoresis, JK-1 gene mRNA was expressed in all

tissue samples. See Fig 3.4

Fig 3.4: mRNA expression of JK-1(FAM134B) gene in colorectal cancer. All colorectal

tissue expressed JK-1 (FAM134B) gene. The control that was used was GAPDH gene.

The mean inverse ratio for JK1(FAM134B) gene (a measure of mRNA expression level)

in adenoma samples was 0.929 ± 0.005 which was significantly higher than in non-cancer

samples (0.901 ± 0.009) (p=0.005). On the other hand, cancer samples had a mean inverse ratio

of 0.875 ± 0.006 which was significantly lower than in non-cancer tissues (p<0.001). The

differences are demonstrated in Fig. 3.5

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Fig 3.5 : JK-1(FAM134B) gene mRNA expression pattern (shown as mean of inverse ratio) in 3

different types of colorectal tissue.

3.4.2 mRNA expression of JK-1 (FAM134B) gene in colorectal cancer

In colorectal cancer samples, almost half of the population (47.5%) had low levels of JK-

1(FAM13B) mRNA expression (n=99). On the other hand, only 17.2% (n=36) overexpressed the

gene. The remaining 35.3% (n=74) had no change in their gene expression levels. Fig 3.6

demonstrates these figures

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Fig 3.6 : mRNA expression of JK-1 (FAM134B) gene in colorectal cancer cases. The percentage

of cases with over-expression, under-expression or no changes in gene expression.

JK-1(FAM13B) mRNA expression (measured as inverse ratio) fell progressively with

the advancing of cancer stage (Fig. 3.7). The mean inverse ratio of stage I cancer samples was

0.887 ± 0.009, which decreased to 0.869 ± 0.074 and 0.872 ± 0.012 for stage II and stage III

respectively. In colorectal cancer metastases (i.e. stage IV), the mean inverse ratio dropped

significantly to 0.819 ± 0.029 (p=0.02). In addition, the mean inverse ratio for JK-1(FAM134B)

in non-metastatic cancers (0.875 ± 0.006) was significantly higher than in metastatic cancers

(0.820 ± 0.029) (p=0.039).

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Fig 3.7 : JK-1(FAM134B) mRNA expression profile (shown as mean of inverse ratio) across the

4 pathological stages of colorectal cancer.

From the 24 cases with distant metastasis, three-quarters (n=18) under-expressed JK-1

(FAM134B) gene mRNA. The remaining cases had no change in mRNA expression and only

one case over-expressed the gene. ANOVA showed a statistically significant difference

(p=0.009). Bonferroni correction between groups showed statistical significance (p=0.045).

The relationship between colorectal cancer metastasis and JK-1 (FAM134B) gene mRNA

expression is illustrated in fig 3.8

136

Fig 3.8 The relationship between colorectal cancer metastasis (0: no metastasis, 1: distant

metastasis present) and JK-1 (FAM134B) gene mRNA expression (shown as inverse ratio)

(p<0.001)

Lymph node involvement by the tumour (N stage) was also significantly associated

(p=0.016) to JK-1 (FAM134B) gene mRNA expression. In tumours with nodal involvement, the

mean inverse ratio was 0.849±0.010, which was significantly lower that cases with clear lymph

nodes, with a mean inverse ratio of 0.879±0.006. See figure 3.9

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Figure 3.9 The relationship between lymph node involvement with colorectal cancer (0: not

involved, 1: tumour present in lymph nodes present) and JK-1 (FAM134B) gene mRNA

expression (shown as inverse ratio) (p=0.016)

Lympho-vascular invasion of the tumour on histopathology correlated independently

with JK-1 (FAM134B) gene expression. Half of the cases (33/66) with low gene expression had

also lympho-vascular invasion, as compared to lympho-vascular invasion in less than one quarter

of cases (21/89) when the expression level was normal or high (p=0.014). See table 3.2

LVI Total

Absent Present

JK1 Expression

Low 66 33 99

Normal

/High 89 21 110

Total 155 54 209

Table 3.2 Demonstrating the relationship between lympho-vascular invasion (LVI) on

histopathology of colorectal cancer and the levels of JK-1 (FAM134B) gene mRNA expression

(p=0.014)

138

The mean inverse ratio of JK-1 gene expression in cancers from the proximal part of the

large intestine (caecum, ascending and transverse colon) (0.857 ± 0.009) was generally lower

than cancers in its distal parts (descending colon, sigmoid and rectum) (0.872 ± 0.005). The

difference however was not statistically significant. (p=0.10). See figure 3.10

Fig 3.10 The relationship JK-1 (FAM134B) gene mRNA expression (shown as inverse ratio)

and tumour site (p=0.10)

Other than this, the level of JK-1 gene mRNA expression showed no significant

relationship with the age, gender of the patient, size, grade or histological type of cancers.

139

Similarly, for colorectal adenomas, no relationship was found between JK1 mRNA

expression and any of the clinical and pathologic features. The data and anlyses for these values

are outlined in Table 3.3

------------------------------------------------------------------------------------------------------------ Adenoma Cancer ---------------------------------------------- -------------------------------------------

Features Number Mean Inverse P-value Number Mean Inverse P-value

Ratio Ratio

------------------------------------------------------------------------------------------------------------

Age <50 4 (12.5%) 0.917±0.013 0.39 21(10%) 0.874±0.014 0.79

>50 28 (87.5%) 0.931±0.005 188(90%) 0.871±0.005

Gender Male 19 (59.4%) 0.927±0.005 0.67 115(55%) 0.862±0.006 0.99

Female 13 (40.6%) 0.937±0.009 94 (45%) 0.882±0.007

Site PC 16(50%) 0.930±0.007 0.90 88(42%) 0.855±0.009 0.1

DC 16(50%) 0.928±0.006 121(58%) 0.882±0.005

Pathological Grade Well/ 22(68.8%) 0.930±0.007 0.51 178(85%) 0.873±0.005 0.21

Moderate

Poor 10(31.2%) 0.927±0.007 31 (15%) 0.860±0.016

-----------------------------------------------------------------------------------------------------------

PC: Proximal colon, DC: Distal colon and rectum

Table 3.3: Relationships between clinicopathological features and JK-1 mRNA expression level

in patients with colorectal adenoma and cancer.

140


The actuarial survival rate of the patients was calculated from the date of surgical

resection of the colorectal carcinomas to the date of death or last follow-up. The median follow-

up period for the patients with colorectal cancer was 49 months. Sixty-seven patients (37%) had

recurrence of the malignant tumour. During the follow-up period, 149 (71%) patients survived,

49 (24%) died and 11(5%) were lost to follow-up.

Kaplan-Meier analysis of the data collected indicated that the mean survival of patients

with colorectal carcinoma was strongly dependant on the pathological stage of the cancer (p<

0.0001). For stage 3 and 4 colorectal carcinoma, Kaplan-Meier analysis also showed that

patients with high JK-1(FAM134B) mRNA expression had longer survival times compared to

the patients with low or normal JK-1(FAM134B) mRNA expression (60 months versus 52

months). However, this trend was not statistically significant (p=0.23). See figure 3.11

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Fig 3.11 Survival distribution by JK-1 (FAM134B) mRNA expression in number of months

for patients with stages 3 and 4 colorectal carcinoma

Additional analysis using Kaplan-Meier method of all patients with colorectal cancer showed

that patients with low JK-1(FAM134B) mRNA expression survived disease-free for 76 months,

compared to 85 months for patients with high mRNA expression of the gene by the colorectal

cancer tissue. Nevertheless, statistical significance was not achieved (p=0.17). Figure 3.12

illustrated the survival analysis results

142

Fig 3.12 Survival disease-free distribution by JK-1 (FAM134B) mRNA expression level in

number of months for patients with colorectal carcinoma

3.5 Discussion

This is the first systematic survey of JK-1(FAM134B) mRNA expression in colorectal

tumours, indicating that alterations to its expression is associated with several markers of tumour

aggression. In this study, adenoma demonstrated a higher JK-1(FAM134B) mRNA expression,

in comparison to non-cancer tissues. This may indicate that the gene has a function in benign

tumours associated with tumour growth and development. Another possible explanation of

143

increased expression in adenoma is that the mRNA plays a protective role in normal tissues and

its increased expression in adenomas is part of a feedback system for tumour suppression. The

increase in JK-1(FAM134B) mRNA may prevent the progression of the adenoma to more

invasive carcinomas, by limiting cancer proliferation, changing growth rate, contact inhibition or

influencing other genes. This hypothesis is supported by the demonstrated sharp fall in JK-

1(FAM134B) mRNA expression in colorectal carcinomas in our study population.

The drop in mRNA expression in carcinomas is so great that it results in a level of

expression below that found in both adenomas and non-neoplastic tissues. The overall picture of

JK-1(FAM134B) activity is an impression of a gene expression change that leads to increasing

gene activity in premalignant stages, perhaps due to a feedback mechanism. During the next

stage of progression to cancer, there is a subsequent drop in JK-1(FAM134B) gene expression

which eventually leads to carcinogenesis, perhaps due to the decreased tumour suppression

action of the gene or as a result of more complex molecular mechanism.

The general trend of JK-1(FAM134B) gene expression thus shows some tumour

suppressor gene properties. This also indicates that there may be up and down-regulation of

JK1(FAM134B) due to signalling by other genes or mechanisms that change with cancer

progression. This makes some interesting connections with studies examining DNA in the region

of JK-1(FAM134B).

In a previous study using comparative genomic hybridization (CGH) in 52 cases of

oesophageal squamous cell carcinoma, 52% of the cancers showed gain in 5p . (Kwong et al.,

144

2004). JK-1(FAM134B) is itself located in 5p15 and may be the target of these changes. In the

same region, there are, however, other genes that may be related to cancer progression, including

cadherins 6 and 14 that may also be involved in changed in 5p15 copy number. Xu et al,

however, observed a high loss of heterozygosity (LOH) frequency and patterns of allelic losses

of chromosome 5p15.2 in colorectal cancer. (Xu et al., 2008). They suggested that the region is


development and progression. Given the expression patterns detected in this study, it is likely

that JK-1(FAM134B) is one of the candidate gene(s) involved in the pathogenesis of colorectal

cancer in this region.

In this experiment, JK-1(FAM134B) gene mRNA expression was highly inversely

correlated with TNM staging of colorectal carcinomas. The higher the pathological TNM stages

of the cancer, the lower the expression. Higher N (lymph node spread) staging correlated with

lower JK-1(FAM134B) mRNA expression. Furthermore, positive M (metastasis) staging was

also associated with lower JK-1(FAM134B) mRNA expression.

This may indicate that JK-1(FAM134B) mRNA, if not protein may have an important

role in preventing tumour metastasis by regulating other genes or pathways. This may be

mediated by integration into other regulatory systems, such as competition for miRNA binding

sites with other mRNAs. It is also possible that other relationships exist with JK-1(FAM134B)

and mRNA levels, but experimental or tissue noise in our data made detecting these relationships

difficult. On the basis of the data produced, however, JK-1(FAM134B) mRNA expression seems

145

to play a role in controlling some steps in development of the invasive phenotype, potentially

affecting pathways such as cell attachment, local proteolysis, cell migration and angiogenesis.

Previous work on JK-1(FAM134B), however, indicated that when overexpressed, the

gene induces an increase in cellular growth, acting like an oncogene. This does not appear to

support the contention of JK-1(FAM134B) as a tumour suppressor that we make here. It is

possible that JK-1(FAM134B) has both oncogenic and tumour suppressive qualities, but that its

specific effects are modulated by either tissue specific factors or the presence of particular

protein cofactors. It is also possible that mutant forms of JK-1(FAM134B) exist that induce

cancer formation or progression, which would be supported by the high LOH rates in the region

containing JK-1(FAM134B) that have been previously observed. Further studied are needed to

identify JK-1(FAM134B)'s mechanism of action to determine whether these possibilities are

true, though data concerning tumour location in this research may offer some further clues.

Researchers have demonstrated that right-sided (proximal) and left-sided (distal)

colorectal cancers can be distinguished by clinical as well as molecular criteria. Accumulating

evidence suggests that the risk of colorectal cancer conferred by various environmental and

genetic factors is different for proximal and distal colorectal cancers. This may be due to

different carcinogenic and molecular pathways in these two regions of the colorectum, which

may behave as distinct tissue populations, with altered biology and thus susceptibility to these

factors. (Iacopetta, 2002; Berkenkamp-Demtroder et al., 2005)

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More than a hundred genes were found to be differentially expressed between normal and

proximal or distal cancers of the colon, showing even more pronounced differences in colorectal

cancer tissue. In our laboratory's previous study in colorectal cancers, we have documented that

aurora kinase, p16 and telomerase activity showed difference in roles between proximal and

distal colorectum (Lam et al., 2008; Saleh et al., 2008). Other studies showed that proximal

colorectal cancers carry worse prognosis and 5-year survival. Proximal tumours tend also to be

larger, more common in more advanced age and in women, compared to distal ones (Elsaleh et

al., 2000; Christodoulidis et al., 2010) .

In this study, JK-1(FAM134B) mRNA expression also changed between proximal and

distal colorectum. The expression was lower in proximal colon. This may be related to site-

specific effects or environment, or an independent effect caused by other pathological factors

associated with JK-1(FAM134B) expression. JK-1(FAM134B) thus appears to be one of many

other genes that show different expression levels in proximal and distal colorectal tumours. This

may have important implications with specifically targeted therapeutic regimens in the future.

Overall, we have determined that the pattern of JK-1(FAM134B) expression is one of decreasing

mRNA levels as the cancer advances towards more malignant and particularly towards

metastatic forms of the disease. Whether the gene is a mediator of, or mediated by these factors

is unclear, but our data indicates that it may be a useful molecular marker for tumour aggression,

and if it is functionally involved in metastatic processes, it may be a useful target for the

development of adjuvant therapies.

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CChhaapptteerr 44

JK-1(FAM134B) Protein Study

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4.1 Introduction

Protein study is another essential part of JK-1(FAM134B) gene research. Proteins are the

functional units in the cell and genomic analyses may not be able to predict protein expression

and the resultant biological changes. Post-transcriptional control events sometimes mean that

protein expression does not run parallel with mRNA expression, although they tend to correlate

well in most cases (Avison, 2007). Thus, the main measure of gene expression is a measure of

protein production.

The JK-1(FAM134B) gene has at least 2 reported splicing isoforms. In addition, protein

diversity can result from post-translational modifications, like cleaving, cross linking and

addition of small molecules. (Gulmann and Cummins, 2012)

There are currently multiple ways to study protein expression. Antibody-based methods

of determining protein expression are generally considered one of the most robust and reliable.

However, as antigen-antibody binding can be quite non-specific due to generic protein binding in

fixed cells, Western Blotting is necessary to establish the antibody specificity for the protein.

(Avison, 2007)

As JK-1(FAM134B) has not been studied before in colorectal tissue, it was important to

characterise its subcellular localization there. This can give important clues to the functional role

of the protein. Thus we would undertake both Western Blotting and immunohistochemistry for

this part of the study.

149

Similarly to the previous parts of the study, protein expression needs to be correlated with

clinicopathological features of colorectal tumours and survival data analysis needs to be

performed.

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4.2 Aims of FAM134B protein study

Test the specificity of the commercially available antibody against JK-1(FAM134B)

antigen to be used in all protein study experiments using the Western Blot method.

Determine subcellular localization of the JK-1(FAM134B) protein in colonic cells

(cytoplasmic, nuclear, membranous, etc)

Determine the amount of JK-1(FAM134B) protein expressed by the cells using semi-

quantitative Immunohistochemistry.

Assess the relationship between JK-1(FAM134B) mRNA and protein expression in colon

cancer cases.

Correlate clinical and pathological features of colon cancer cases with JK-1(FAM134B)

protein expression cancer specimens.

Investigate the relationship (if any) between JK-1(FAM134B) protein expressed and

patients’ survival rate.

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4.3.1 Data collection and Tissue Recruitment

Two hundred and thirty-six colorectal cancer, 32 colorectal adenoma and 20 colorectal

non-neoplastic tissue samples were collected from patients who underwent surgery at hospitals in

Queensland, Australia. Patients who were chosen for this study had resection for primary

colorectal carcinomas, colorectal adenomas and non-neoplastic colorectal tissue between June

2004 and August 2010. Ethical approval of this study has been obtained from the Griffith

University Human Research Ethics Committee (GU Ref No: MED/05/06/HREC). The patients

were consecutively chosen to eliminate any selection bias.

The following clinicopathological data were collected prospectively for each patient; age,

gender of the patients, location and size of cancer in millimeters. Lympho-vascular invasion,

lymph node involvement and the presence of distant metastasis were also recorded. Follow up,

recurrence of cancer and survival data were also entered to the database to be used in the survival

analysis. In addition, the presence of associated benign tumours (adenoma), polyposis, family

history of colorectal carcinoma, presence of metachronous (two or more cancers appearing at

different points in time) or synchronous (two or more histologically distinct simultaneously

detected malignancies) tumours were all noted. Mismatch repair gene status was also noted.

None of the rectal cancer patients had undergone neoadjuvant radiotherapy or

chemotherapy prior to surgery. Management was by a pre-agreed standardized multidisciplinary

protocol supervised by a senior specialist colorectal surgeon.

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First of all, the histological slides of these samples were reviewed by a senior academic

pathologist (Supervisor, Professor Alfred Lam). The benign and malignant tumours were

described and graded according to the World Health Organization (WHO) criteria. (Bosman et

al., 2010). The adenoma samples were also classified into tubular, villous and tubulovillous

according to their structural appearance. In this study, only colorectal adenocarcinoma was

included. The adenocarcinoma was considered mucinous if more than 50% of the lesion is

composed of mucin. The carcinomas were staged according to the TNM classification adopted

in the American Joint Committee on Cancer (Greene, 2002). The changes in the glandular

architecture and cellular pleomorphism both mucinous and classical adenocarcinomas were

graded in to three major groups (well, moderate and poorly differentiated cancer). In TNM, “T”

denotes tumour invasion, “N” for lymph node metastasis and “M” for distant metastasis.

According to the changes in T, N and M, each cancer was staged in to 4 groups (Stages 1 to 4).

Carcinoma in proximal colorectum (PC) was categorised as carcinoma arising either

from caecum, ascending colon, transverse colon (including hepatic and splenic flexures).

Carcinoma in distal colorectum (DC) was defined as carcinoma arising either from descending

colon, sigmoid colon and rectum.

In choosing the tissue samples for non-neoplastic (control) group, care was taken in

choosing samples that were neither premalignant conditions, nor adjacent to any malignant or

premalignant conditions. Inflammatory bowel diseases were also excluded, as they can increase

the risk of colorectal carcinoma in the long run. Examples of the surgically resected benign

samples included diverticular disease, prolapse, and fistulae, amongst others.

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The non-tumour and the adenoma samples used for the protein study are identical to the

ones used in DNA and mRNA parts of the study. The median age of the 20 patients (13 males; 7

females) with non-cancer colorectal tissue was 58 years (range, 41-87). Of the 32 patients with

colorectal adenomas, 59% (n=19) were males. The median age of the patients with adenomas

was 65 years (range, 33-86). Twelve of the adenomas (37.5%) were classified as tubular

adenomas and 20 samples (62.5%) as tubulovillous adenomas. More than two-thirds of the

adenomas were of low grade (n=22) and the rest were considered as high grade (n=10). The

adenomas were located in the caecum in 28.1% (n=9), ascending colon in 9.4% (n=3), transverse

colon in 12.5% (n=4), sigmoid in 9.4% (n=3) and rectum in 40.6% (n=13).

The median age of the 236 patients with colorectal cancer was 70 years (range, 25-92).

Fifty six percent (n=134) of all the 227 patients were males. The mean size of the cancers was 44

mm, ranging between 11-120 mm. The cancers were located in the caecum, ascending colon,

transverse colon, descending colon, sigmoid colon and rectum in 17.4% (n=41), 9.3% (n=22),

15.7% (n=37), 3.4% (n=8), 26.7% (n=63) and 27.5% (n=65) of the cases respectively.

Eighty-seven per cent (n=206) of the colorectal cancers were conventional non-mucinous

adenocarcinomas and the rest were mucinous adenocarcinoma (n=30). The cancers were

classified according to TNM staging system fell into the following categories: stage I in 20.8%

(n=49), stage II in 34.3% (n=81), stage III in 33.5% (n=79) and stage IV in 11.4% (n=27).

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Fifty-seven per cent of colorectal cancer cases had their lymph nodes involved by the

tumour (n=135). Polyposis associated with a colorectal carcinoma was noted in 5.9% (n=14) of

cases, whilst an associated adenoma was present in just above 39.4% of cases (n=93).

Histologically, 27.5% of cancer cases (n=65) showed lympho-vascular invasion. Out of 236

colorectal cancer cases studies, only 7 (3%) had a reported family history of colorectal cancer.

Of the 236 colorectal cancer patients, only 3% (n=7) had synchronous tumours and 5%

(n=12) had metachronous tumours.

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4.3.3 JK-1 (FAM134B) Antibody

The antibody-based method to study JK-1(FAM134B) gene protein expression was

performed using a commercially available antibody from Santa Cruz Biotechnology (Santa Crus,

CA, USA). JK-1 (FAM134B) is a purified rabbit polyclonal antibody raised against JK-1 of

human origin.

The JK-1 antibody (designated Y-20 clone) is recommended for detection of JK-1 of mouse, rat,

human and dog origin by Western Blotting and immunohistochemistry including paraffin-

embedded sections. (http://www.scbt.com/datasheet-101986-jk-1-y-20-antibody.html)

4.3.4 Immunohistochemistry

Immunohistochemistry (IHC) was one of the main methods to determine the expression

of JK1 (FAM134B) genes in tissues. This technique was used to determine how much of the JK-

1(FAM134B) RNA expression detected by PCR has actually been translated into the final

product.

Formalin-fixed paraffin embedded blocks for the study were cut 5-6 μm thickness using

Leica microtome (Leica RM2235, Wetzlar, Germany) and placed on tissue-adhesive coated

Superfrost plus microscope slides (Lomb scientific, NSW, Australia). Following this, they were

allowed to dry overnight at 37° C in an incubator.

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The sections then were deparaffinised in xylene for 2 min, followed by another xylene

bath for 90 seconds to remove residual wax. The sections were immediately rehydrated using

graded ethanol, starting at 100% for 1 min, 45 seconds of another 100% ethanol bath and lastly

45 seconds in 70% ethanol. The slides were washed afterwards briefly in running tap water.

Retrieval of antigen was performed using chemical, heat and pressure methods. Then

slides were heated in a pressure vessel at 120oC for 7 minutes in citrate buffer (pH 6) solution.

The optimal temperature and time were determined on the basis of multiple trials. Slides were

allowed to cool down for 30 minutes and rinsed with PBS ready for immunostaining.

The immunostaining was performed using an automated staining machine Autostainer

360 (Lab vision, Suffolk, UK) to provide more standardized results than manual staining

techniques. The immunohistochemistry staining was performed using a polymer detection

system, according to the manufacturer’s instructions for the immunohistochemistry staining kit

Novolink polymer detection system RE7280K (Novocastra Laboratories, Newcastle, UK). The

protocol of immunohistochemistry staining included the following steps, all of which were

conducted at room temperature :

1. After antigen retrieval was completed, the slides were washed with de-ionized water.

2. Slides were treated with peroxidase block for 5 minutes to neutralize tissue endogenous

peroxidase.

3. Slides were washed in Tris-buffer saline (TBS) solution for 2 times, each for 5 minutes.

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4. Slides were incubated with protein block for 5 minutes. The protein block provided was

made of 0.4% Casein in phosphate-buffer saline with stabilizer and surfactant.

5. Slides were washed again in Tris-buffer saline (TBS) solution for 2 times, each for 5

minutes.

6. Slides were incubated with 1:150 diluted primary antibody for JK-1 (FAM134B) for 60

minutes. The antibody used is a purified rabbit polyclonal antibody raised against JK-

1(FAM134B) of human origin (Santa-Cruz Biotechnology, CA, USA). The optimal 1:150

dilution was determined after conducting multiple trials with graded dilutions.


minutes.

8. For 30 minutes, the slides were incubated with Post-primary block which is a polymer

penetration enhancer.

9. Once more, slides were washed in Tris-buffer saline (TBS) solution for 2 times, each for 5

minutes

10. Slides were incubated with NovoLink polymer for 30 minutes. The polymer is Anti-

mouse/rabbit IgG-poly-HRP containing 10% animal serum in TBS.


minutes.

12. Peroxidase activity was developed with 3, 3’-diaminobenzidine (DAB) working solution.

13. The slides were rinsed briefly in water.

14. The slides were put in a haematoxylin 0.02% bath for 15 minutes for counter staining.

15. The slides were rinsed for 5 minutes in water.

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16. The slides were finally dehydrated using graded concentrations of alcohol and xylene in

reverse of the initial steps then mounted.

These slides were then examined by the expert pathologist for the quality of staining,

with each experiment controlled by suggested positive and negative control. A section of the

colorectal carcinoma known to be strongly positive for JK-1 protein was used as the positive

control in each run of the experiment. Negative controls were sections treated using the same

techniques as above, but with omission of the primary antibody.

A semi-quantitative database based on the strength of staining was produced from the

collected information and the protein expression of JK-1(FAM134B) was evaluated against the

studied gene’s expression.

The strength of staining assessment was performed based on the comparison of the

intensity of immunohistochemichal stain with negative and positive controls. The strength

(intensity) of staining was accordingly classified into 4 categories. A score of 0 was given to

negative staining (all tumour cells lack staining) and a score of 3+ to a very strong positive

staining. The shades between these two ends of spectrum were given a score of 1+ and 2+ for

weak and moderate intensity of staining respectively. When positive, the assessment represents

the average staining strength score of the positively stained tissue rather than the highest score

possible from all tissue examined.

The second method of assessing the degree of JK-1(FAM134B) protein expression on

immunohistochemistry was done using an approximate estimation of the percentage of the

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positively stained tissue in a slide. Slides with no positively stained tissue were given 0%. Others

were graded according to the nearest 10%.

Both of the abovementioned methods are widely described in literature and regarded as

highly reliable. All samples in the study were analysed using both methods. However, for

colorectal cancer samples, only the strength of staining / degree of positivity method (the first

method described) was included in the final results and discussion, as it showed more correlation

and statistical significance than the percentage of the tissue positively stained. On the contrary,

some clinicopathological correlations were noted on studying the percentage of positive staining

in adenoma tissue samples, whilst the strength of staining/degree of positivity showed no

statistically significant correlations in these samples.

Manual scoring by an expert pathologist was thus used in this study to assess protein

expression. Multiple studies have showed no advantage of using automated approaches over the

manual visualization in determining protein expression by this method (Avison, 2007;

Choudhury et al., 2010; Rizzardi et al., 2012).

Many factors may introduce variations in immunohistochemistry: differences in tissue

fixative and fixation time, day-to-day variations due to temperature, variations due to conditions

of reagents applied on a particular day (Seidal et al., 2001). To compare immunohistochemistry

results of different runs, care was taken to ascertain that intensity of staining is comparable. This

was done using internal tissue positive and negative controls for all samples studied.

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4.3.5 Statistical Analysis

For the immunohistochemistry study, comparisons between groups were performed using

the chi-square test, likelihood ratio, Fisher’s exact test and Student’s t test. Fisher’s exact test,

chi-square test or the likelihood ratio was used for categorical variables when suitable. Fisher’s

exact test was used with smaller populations. Survival analysis was conducted using Kaplan-

Meier and Cox regression methods.

All the data was entered into a computer database and the statistical analysis was

performed using the Statistical Package for Social Sciences for Windows (version 21.0, SPSS

Inc., Chicago, IL, USA). Significance level was taken at P<0.05.

4.3.6 Western Blot for Antibody Specificity

The characterization of antibody specificity requires demonstration that the antibody

binds only to the protein that contained the immunogenic peptide. Each antibody is produced by

methods that determine its specificity. Today, many antibodies, both monoclonal and polyclonal,

are generated to synthetic peptides. Many of these antibodies are purified with the immunizing

peptide on an affinity column, greatly reducing the possibility that the antibodies will bind to

epitopes not found on the original peptide. Immunoblotting with an antibody should show that

the antibody recognizes a single protein of the appropriate molecular weight. (Schuh et al., 1992;

Kurien et al., 2011)

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4.3.7 Western Blot Analysis

This was used to confirm the specificity of the antibody used in the study to JK-

1(FAM134B) protein. Although the antibody used is a commercially available product which has

been subjected to multiple specificity testings, confirming the specificity of the antibody in our

study would provide more confidence in the results of the semi-quantitative Western Blot tests,

the immunohitochemical assays and the immunocytochemistry used in the functional cell culture

part of the study.

Releasing proteins from formalin fixed paraffin embedded tissues for Western Blot

analysis can be difficult due to extensive molecular crosslinking that occurs upon formalin

fixation which reduces protein extraction efficiency and may interfere with immunoreactivity.

(Crockett et al., 2005). Although some studies have described more efficient protein extraction

methods from formalin fixed paraffin embedded tissues (Addis et al., 2009), we used high-

quality protein extraction method from fresh cultured cell lysate.

Total protein was extracted from cultured cells with lysis buffer (Bio-Rad) and

quantitated by absorbance spectrometry. Then, the total protein (30mg) was loaded in Laemmli

buffer onto a 15% polyacrylamide stacking gel, run at 40 V, then at 100 V through a 15%

separating gel by using a Mini Cell (Bio-Rad). The proteins were then transferred to

nitrocellulose membranes (Bio-Rad no. 162-0146) for 1 hr by using a Mini Trans-Blot

Electrophoretic Transfer Cell (Bio-Rad). Next, the membrane was blocked with 5% non-fat milk

powder for 2 hours at room temperature. After two washes in PBS with 0.005% Tween 20, the

162

JK-1(FAM134B) monoclonal antibody (at 1:150) and GAPDH antibody was added and

incubated overnight at 4˚Celsius. Then, membranes were washed three times and incubated with

secondary antibody (NovoLink polymer) at room temperature for 2 hours. The secondary

antibody is an anti-rabbit Poly-HRP-IgG (<25μg/mL) containing 10% (v/v) animal serum in tris-

buffered saline/0.09%. Protein bands were detected by developing the peroxidise activity with

freshly prepared 3, 3’-diaminobenzidine (DAB) and substrate chromogen solution (Novocastra

Laboratories). Total protein content loaded was then normalized by the GAPDH signal.

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4.4 Results

4.4.1 Specificity of JK-1(FAM134B) antibody

Western blot results using the JK-1(FAM134B) antibody from Santa-Cruz Biotechnology

showed that the antibody recognizes a single protein of a molecular weight of 52 kDa, the

estimated molecular weight for JK-1. This is shown in figure 4.1. Upon confirmation, this

antibody was used for all subsequent IHC studies.

Figure 4.1 SW480 Western Blot: Western Blot analysis of JK-1(FAM134B) protein expression

in colorectal cancer cell lysate using SW480 colorectal cancer cell line (methods are described in

chapter 5). The antibody recognizes a single protein of a molecular weight of approximately 52

kDa.

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4.4.2 Subcellular localization of JK-1(FAM134B) protein

Immunohistochemical studies performed on colorectal tissue, both non-tumour and tumour

types, have demonstrated a nuclear subcellular localization of the JK-1(FAM134B) protein. The

different tissue samples had a staining strength ranging from null to a very strong intensity; the

only subcellular localization noted however was nuclear. This observation was mirrored in cell

culture studies using colorectal cancer cell lines (SW480), where the staining was again localized

to the nucleus, sparing the cytoplasm. This can be seen in figures 4.2, 4.4 and 4.5

4.4.3 Protein expression of JK-1(FAM134B) gene

JK-1(FAM134B) protein was detected in 65.3% (154 of 236) of patients with colorectal

carcinoma, 90.5% (29 of 32) of adenoma patients and 100% (20 of 20) of patients with non-

neoplastic colorectal mucosa.

The colorectal cancers were positive for JK-1(FAM134B) protein by

immunohistochemistry at (1+) grade in 34.7% (n=82/236), (2+) in 21.2% (n=50/236) and (3+) in

9.3% (n=22/236), with regards to the strength of staining. Colorectal adenomas, on the other

hand, were (1+) in 25% (n=8/32), (2+) in 37.5% (n=12/32) and (3+) in 28 % (n=9/32) of the

cases.

Overall, adenoma had a much higher grade of positive staining for JK-1 than cancer,

being strongly positive (+++) in 32% of positive cases. In comparison, colorectal cancer

showed strong positive staining in less than one-tenth of the cases (22/236), showing a

significant difference in expression distribution to the adenomas (p<0.001). (Fig 4.2)

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Fig 4.2 JK-1 protein staining in tubular adenoma: Shown is the result of immunohistochemical

staining of JK-1 protein staining in a tubular adenoma sample. Note the strong intensity of

nuclear stating in the dysplastic cells (Inset: high magnification). Magnification: 40X . Inset

magnification 200X.

Other than staining being significantly different in cancers and adenomas, JK-1 protein

expression was associated with several clinicopathological factors in the cancers themselves.

Positive staining for JK-1 was associated with a later age of presentation of colorectal

cancer (mean age =71, n=154) in comparison with the negatively-stained samples which

belonged to patients of a younger age at presentation (mean age =67, N=82). The difference is

statistically significant (p=0.032).

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Low levels of JK-1 (FAM134B) protein expression (0 or 1+) were associated with higher

recurrence rate (41% versus 29 % in colorectal cancers with higher levels (2+ or 3+) of protein

expression of the gene). This difference was statistically significant (p=0.04), with population

data summarized in Table 4.1

Recurrence Total

Absent Present

JK1 protein

Expression

Low 51(59%) 36(41%) 87(100%)

High 105(71%) 44(29%) 149(100%)

Total 156 80 236

Table 4.1: Relationship between immunohistochemichal expression of JK-1(FAM13B) protein

and colorectal cancer recurrence. Lower protein expression is associated with higher recurrence

(p=0.04)

In terms of tumour localization in the colorectum, tumours with low JK-1 (FAM134B)

protein expression were more likely to be located in proximal colon (78% were in proximal

colon), while the cancers with higher expression of the protein tend to be more distal (located in

proximal colon in less than 69% of cases). The difference was however not statistically

significant (p=0.08)

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The size of the tumour on macroscopic examination also correlated with levels of JK-

1(FAM134B) protein expression. Tumours that have lost the expression of the protein had a

mean size of 49.2 ± 2.6 mm. The mean size of cancers that were positive for JK-1(FAM134B)

protein was 41.1 ± 1.47 mm. This difference was statistically significant (p=0.004) and the data

for the population is illustrated in figure 4.3

Figure 4.3: Relationship between colorectal cancer size in millimeters and its expression of a

protein for JK-1(FAM134B) gene. (0: not expressed, 1:expressed), error bars represent the

95%CI of the sizes of the populations . (p=0.004)

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Tumour grade was high in one fifth of the cases (18/87) when the colorectal cancer lost

JK-1(FAM134B) protein expression, as compared to only 12% (18/149) where tumours

expressed the protein. Table 4.2 demonstrates the population data for this relationship.

Although the statistical significance was borderline (p=0.058), the trend was obvious on

histological examination. This is illustrated in figure 4.4

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Fig 4.4: JK-1 protein staining on immunohistochemistry across different grades of colorectal

cancer: A. Strong staining was noted in well-differentiated adenocarcinoma. B. Moderately-

differentiated adenocarcinoma with lower level of staining. C. Negative staining in a poorly

differentiated adenocarcinoma. (Magnification 100X)

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Cancer Grade Total

Low High

JK-1 on IHC Neg - 69(79%) 18(21%) 87

Pos + 131(88%) 18(12%) 149

Total 199 36 235

Table 4.2: Colorectal cancer grade association with expression of JK-1(FAM134B) protein.

(p=0.058)

T stage of colorectal cancers in the study showed a strong correlation with JK-

1(FAM134B) protein expression, measured using the strength of staining in

immunohistochemical assay. Protein expression levels fell with the progression to higher stages.

Cancers of stage 4 were mostly negative or low expressers of JK-1(FAM134B) protein (39/45

were negative or weakly positive), whilst most stage 1 cancers had a stronger protein expression

signal (5/7 cases). Using Fisher’s exact test, the difference was highly statistically significant

(p=0.005). See table 4.3

T Stage

1 2 3 4

JK1Degree of Positivity Low 2 30 93 39

High 5 18 43 6

Total 7 48 136 45

Table 4.3: JK-1(FAM134B) protein expression levels (low 0/1+ versus high 2+/3+) distribution

between the four T stages of colorectal cancer. (p=0.005)

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The N stage demonstrated a correlation with JK-1(FAM134B) protein expression as well.

Tumours with a higher expression profile of the protein were less likely to be lymph node

positive. Less than one quarter of cases (5/22) with high JK-1(FAM134B) protein expression had

nodal spread of the cancer. On the other hand, almost half of the tumours (39/82) with no or low

protein expression of the gene had cancer involving the lymph nodes. Using Chi-square analysis,

the difference between the populations was statistically significant (p=0.028). See table 4.4

N Stage Total

0 (Node-) 1 (Node+)

JK1 Degree of

positivity on IHC

Negative 43(52%) 39(48%) 82(100%)

1+ 43(52%) 39(48%) 82(100%)

2+ 32(64%) 18(36%) 50(100%)

3+ 17(77%) 5(23%) 22(100%)

Total 135 101 236

Table 4.4: JK-1(FAM134B) colorectal cancer protein expression levels (ranging from negative

to 3+ on immunohistochemistry) and its relationship with presence or absence of lymph node

spread of tumour. (p=0.028)

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Independently, the presence or absence of metastasis (M stage) had a very strong

correlation with JK-1(FAM134B) protein expression. Cancers that had lost the protein

expression have much higher metastasis rate (18.4% versus 7.3%). The difference was

statistically significant (p=0.01). See table 4.5

M Stage Total

0 (Met.-) 1 (Met.+)

JK1 on IHC Positive 71(81.7%) 16(18.3%) 87(100%)

Negative 138(92.7%) 11(7.3%) 149(100%)

Total 209 27 236

Table 4.5 : Colorectal cancer M stage (presence or absence of distant metastasis) in relationship

to JK-1(FAM134B) protein expression on immunohistochemistry. Loss of protein expression is

associated with higher rates of metastasis (p=0.01)

The overall stage of the tumour is determined by the 3 above-mentioned staging

components (T, N and M stage). The overall stage had a strong correlation as well with the

protein expression levels of JK-1(FAM134B) gene. As demonstrated in Table 4.6, the higher the

stage, the lower the protein expression of JK-1(FAM134B) gene. Eighty-one percent of the stage

4 tumours had a low expression profile for the gene (22/27). Stage one tumours on the other hand

had low protein expression in 53% of the cases (26/49). Strong statistical significance was

demonstrated using the Chi-square analysis. (p=0.016)

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Stage

1 2 3 4

JK1 Degree of Pos Low 26(53%) 55(68%) 61(77%) 22(81%)

High 23(47%) 26(32%) 18(23%) 5(19%)

Total 49(100%) 81(100%) 79(100%) 27(100%)

Table 4.6: The overall stage of colorectal cancers in relationship to their levels of JK-

1(FAM134B) protein expression. (p=0.016)

Analyzing other clinicopathological parameters, including age, gender, type of cancer

(classical or mucinous), family history of colorectal cancer, presence of synchronous or

metachronous tumours showed no statistically significant differences in JK-1(FAM134B) protein

expression. Mismatch repair gene status showed no correlation with JK-1 protein expression

either. It is worth noting that due to the small sample size in some of the categories,

interpretation of the results should be done with caution.

Histologically, lymphovascular invasion by cancer appeared to be more likely to be

present in cancers with low expression of JK-1(FAM134B) protein, however the difference was

not statistically significant (p=0.084). Table 4.7 summarizes the aforementioned results, using

Chi-square and Fisher’s exact test analysis.

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Features Low expression High expression Total p-value

-----------------------------------------------------------------------------------------------------

Gender

Male 86(64%) 48(36%) 134 0.29

Female 78(76%) 24(24%) 102

Type

Classical 146(70%) 18(30%) 206 0.16

Mucinous 18(60%) 12(40%) 30

Family history of colorectal cancer

No FHx 159(69%) 70(31%) 229 0.63

Positive FHx 5(71%) 2(29%) 7

Lympho-vascular invasion

Absent 114(66%) 57(34%) 171 0.084

Present 50(77%) 15(33%) 65

Presence of associated polyposis

Absent 155(70%) 67(30%) 222 0.43

Present 9 (64%) 5 (36%) 14

Presence of a synchronous tumours

Absent 159(69%) 70(31%) 229 0.63

Present 5(71%) 2(29%) 7

Presence of a metachronous tumours

Absent 155(69%) 69(31%) 224 0.47

Present 9 (75%) 3 (25%) 12

-------------------------------------------------------------------------------------------------

Table 4.7: JK-1(FAM134B) protein expression in relation to various other clinicopathological

parameters in colorectal cancer.

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For adenomas, villous and tubulovillous types had significantly lower levels of JK-1

protein expression than the tubular type. (p=0.016). This was noted on measuring the percentage

of the positively stained tissue, rather than the strength of staining/degree of positivity. The latter

showed no statistical significance with any of the clinicopathological features in patients with

adenoma.

Other than this, the level of JK-1 protein expression showed no significant relationship

with the age, gender of the patients or tumour site or grade (Table 4.8). It is worth noting that due

to the small sample size in some of the categories, interpretation of the results should be done

with caution.

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Features 0-49% 50-100% Total p-value

--------------------------------------------------------------------------------------------

Age

<50 1(25%) 3(75%) 4 0.07

>50 21(75%) 7(25%) 28

Gender

Male 11(57%) 9(43%) 19 0.11

Female 11(85%) 2 (15%) 13

Site

PC 10(62%) 6(38%) 16 0.35

DC 12(75%) 4(25%) 16

Pathological Grade

Low Grade 16(72%) 6(18%) 22 0.48

High Grade 6 (60%) 4 (40%) 10

Morphological Type

Tubular 5 (41%) 7 (59%) 12 0.016*

Tubulovillous/Villous 17 (85%) 3 (15%) 20

-----------------------------------------------------------------------------------------------------------

PC: Proximal colon, DC: Distal colon and rectum.

Table 4.8: Levels of JK-1 protein expression (percentages of positively stained cells) in

correlations with clinicopathological parameters in colorectal adenomas.

correlations with clinicopathological parameters in colorectal adenomas.

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The overall impression of JK-1(FAM134B) protein expression on histological

examination is best illustrated in figure 4.5. This can be generally described as positive staining

for the protein in the adjacent non-dysplastic epithelium, which maintains its positivity when

glands become dysplastic, but not yet invasive. This is finally observed as partial or complete

loss of protein staining in the malignant infiltrating glands. This transformation in the level of

expression was often observed in the same slide, and sometimes in the same field of vision, as

seen in the picture.

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Fig 4.5: JK-1 protein expression in colorectal cancer.: A: area of non-neoplastic glands showing

positive nuclear staining. B: area of dysplastic mucosa appears to be strongly positive for JK-

1(FAM134B). C: infiltrating malignant glands with negative or weak staining for JK-

1(FAM134B). – Magnification 40x

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Similarly to the survival analysis performed for the DNA and mRNA study, the actuarial

survival rate of the patients was calculated from the date of surgical resection of the colorectal

carcinomas to the date of death or last follow-up. Two hundred and twenty three patients had

available follow up data to analyze. The median follow-up period for the patients with colorectal

cancer was 41 months. During the follow-up period, 133 (56.4%) patients survived, 94 (39.8%)

died and 9 (3.8%) were lost to follow-up.

Kaplan-Meier analysis of the data collected indicated that the mean survival of

patients with colorectal carcinoma was strongly dependent on the pathological stage of the

cancer (p< 0.01). Apart from that, Kaplan-Meier analysis showed no significant predictive value

of JK-1(FAM134B) protein expression on patients’ survival.

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4.4.5 Correlation between JK-1(FAM134B) mRNA and protein expression

Analysis of the 209 colorectal cancer cases that had both mRNA and protein expression

data for JK-1(FAM134B) gene reveals a significant correlation between the two. To quantify

mRNA expression, inverse ratio was used as a measure of expression (as described in Chapter 3

methodology). Although not rigidly, mRNA expression (measured in inverse ratio) positively

correlated with protein expression (measured by degree of positivity) of JK-1(FAM134B) gene

(p=0.048). Figure 4.6 illustrate this correlation

Figure 4.6: Correlation between JK-1(FAM134B) mRNA and protein expression. The more

the mRNA expression, the higher the signal of staining for JK-1(FAM134B) protein (p=0.048)

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4.5 Discussion

This is the first systematic description of JK-1(FAM134B) protein expression in

colorectal tumours. This study described the sub-cellular localization of the protein, quantified

the protein expression and demonstrated the relationship of the expression level with its

clinicopathologic and survival parameters.

To confirm the specificity of the antibody used in the study to JK-1(FAM134B) protein,

immunoblotting was performed. The Western Blotting analysis using the commercially available

antibody showed that the antibody recognizes a single protein of the appropriate molecular

weight for JK-1(FAM134B) protein. Confirming the specificity of the antibody in the study

provided more confidence in the results of the semi-quantitative Western Blot tests, the

immunohistochemical assays and the immunocytochemistry used in the functional cell culture

part of the study as well as in this work.

Kurth et al, while studying a severe form of sensory and autonomic neuropathy showed

that nerve tissue expresses JK-1(FAM134B) as a Golgi protein (Kurth et al., 2009). In our study,

immunohistochemistry demonstrated clearly that the protein expression was in the nuclei of the

colorectal cancer, adenoma and non-cancer epithelial cells. The difference in location being

detected in our study may be related to the different tissue type being studied or different

methods of detecting the protein. Nevertheless, the protein was studied in mouse cells in Kuth’s

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study whereas the location of the protein was demonstrated in large number of human colorectal

tissues (236 cancers, 32 adenomas and 20 non-cancer mucosa). This may also indicate that the

distribution of the protein is also dependent upon species as well as tissue factors.

Lee et al described a dual sub-cellular localization of a tumour suppressor gene

responsible for the von Hippel-Lindau cancer syndrome as well as sporadic renal clear cell

carcinoma. The nuclear or cytoplasmic subcellular localization of von Hippel-Lindau gene

protein seem to play an important role in its function. The redistribution of protein is dependent

on a transcription-dependent nuclear cytoplasmic trafficking (Lee et al., 1999). This could

possibly provide an explanation of the different sub-cellular localization of JK-1(FAM134B)

protein in various tissues and may represent an area of potential growth in our understanding of

its function.

The nuclear location of the JK-1(FAM134B) protein in our study would indicate that the

gene is in some way involved in transcriptional control. JK-1(FAM134B), however, lacks any

known zinc-finger or other DNA interaction motifs, so it is likely that it is part of a larger

signaling complex if it does affect gene expression. This may offer a clue to its potential dual

tumour suppressor or oncogenic effects, as it may depend on which partner proteins are present

as to which genes are altered by its presence.

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Benign adenomas appear to have higher JK-1(FAM134B) protein expression, in

comparison to cancer tissues. The high expression of the protein in adenoma suggests that is

plays a protective role, which may prevent the progression of the adenoma to more invasive

carcinomas, by limiting cancer proliferation, changing growth rate, contact inhibition or

influencing other genes. The high level JK-1(FAM134B) protein in non-neoplastic and benign

tumours gives an impression that the gene is related to colorectal cancer carcinogenesis and that

its loss influences or is influenced by this process.

Colorectal cancers with lower protein expression profiles for JK-1(FAM134B) gene

tended to affect a relatively younger age group. Age is an important risk factor for colorectal

carcinoma, with risk increasing with age (Wu et al., 1987). Early age of onset of colorectal

cancer is a feature of hereditary non-polyposis colorectal cancer (HNPCC). This disease is

caused by heterozygous mutations in mismatch repair (MMR) genes. Approximately 85 % of

genetically defined HNPCC patients have germline mutations in MLH1 and MSH2. These

patients are at increased risk of developing extra-colonic cancers (Chai et al., 2004; Perez-

Cabornero et al., 2013). In this study however, there was no association between the mismatch

repair gene status and JK-1(FAM134B) gene protein expression. This may be due to JK-

1(FAM134B) expression alteration independently increasing the risk of earlier cancer

development via a different pathway.

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Age-associated differences in gene expression are common in hormone-dependent

cancers, like breast and prostate cancers (Pirone et al., 2012; Powell et al., 2013). Colorectal

cancers are not known to be hormone-dependent, however one of the studies suggested that

possibility (Lamberts, 1994). It is possible that the difference in the age of presentation of

colorectal cancer patients with variable JK-1(FAM134B) protein expression is due to some

“hormone-like” growth factors that affect a certain subgroup of “receptor-positive” tumours.

In this experiment, JK-1(FAM134B) gene protein expression was highly correlated with

TNM staging of colorectal carcinomas. The correlation is noticed independently in each of the

components of the staging system (T, N and M), in addition to the overall stage correlation. In

JK-1 (FAM134B) protein expression, the higher the pathological TNM stages of the cancer, the

lower the expression. Higher T (depth of invasion), N (lymph node spread) and M (distant

metastasis) staging correlated with lower JK-1protein expression. This also mirrors the

clinicopathological correlations observed in mRNA expression of the gene, described in Chapter

3.

The findings may indicate that JK-1 (FAM134B) protein has a role in stopping cancer

progression and local spread. Moreover, the protein may have an important role in preventing

tumour distant metastasis. As loss of JK-1(FAM134B) protein expression is shown to be

associated with more advanced cancer stages, it is hypothesized that JK-1(FAM134B) protein

expression seem to play a role in controlling some steps in development of the invasive

phenotype, potentially affecting pathways such as cell attachment, local proteolysis, cell

migration and angiogenesis.

185

In addition to the strong correlation with cancer stage, JK-1(FAM134B) protein

expression also showed some correlation with tumour grade. In the mRNA study (Chapter 3), it

is under-expressed more commonly in higher grade colorectal cancers. Loss of the JK-

1(FAM134) protein can be a marker for the general aggressiveness of colorectal cancer, in

addition to the more specific factors within the TNM staging. These findings concur with the

results showing that loss of the protein occurs in cancers of advanced pathological staging.

Due to the strong relationship between low JK-1(FAM134B) protein expression and

tumours of higher stage and grade, it is clear that the low expression of the protein would also

mean a higher recurrence rate, as these results suggest. Recurrence rates are generally associated

with tumour stage and are often affected by tumour grade (Fenoglio-Preiser, 2008).

Cancer size, although independent of T-stage, shows a strong correlation with JK-

1(FAM134B) protein expression. Researchers demonstrated that tumour size can be a

reproducible predictor of cancer T stage, but also act as a complimentary clinical staging factor

(Zlobec et al., 2010). Larger tumours had generally a lower expression profile of JK-

1(FAM134B) protein, which can be explained by the same association noted between the protein

expression and cancer T stage.

In this study, JK-1(FAM134B) protein expression tends to varied between proximal and

distal colorectum. The protein expression was lower in proximal colon, although the difference

did not achieve statistical significance. Also, lower protein expression was noted in earlier age

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of presentation. This may be related to site-specific effects or environment, or an independent

effect caused by cell senescence. JK-1(FAM134B) appears to be one of many other genes that

show some difference in gene expression levels in proximal and distal colorectal tumours,

perhaps reflecting fundamental differences in biology in these cell populations.

Previous studies have shown that cancers located in the right (proximal) and left (distal)

colorectum can be distinguished by clinical criteria (Kapiteijn et al., 2001; Iacopetta, 2002;

Birkenkamp-Demtroder et al., 2005). Proximal colorectal tumours, when compared with distal

tumours, are more often found in older age and females. In recent years, it has become clear that

colorectal cancer evolves through multiple pathways on the basis of 2 molecular features: (i)

DNA microsatellite instability (MSI) status stratified as MSI-high, MSI-low, and MS-stable; and

(ii) CpG island methylator phenotype (CIMP) stratified as CIMP-high, CIMP-low, and CIMP-

negative (Jass, 2007). It is worth noting that MSI-high or MS stable with CIMP-high colorectal

cancers are more often noted in the proximal colorectum and in female patients of advanced age.

Thus, the clinical difference between proximal and distal colorectal cancers may partly be

explained by different involvement of these 2 molecular pathways.

Apart from the 2 molecular pathways, right-sided tumours show significantly less nuclear

β-catenin and p53 overexpression than left-sided tumours (Kapiteijn et al., 2001; Iacopetta,

2002). Other study has demonstrated that p16 protein expression was more often noted in

mucinous adenocarcinoma of the distal colorectum and that telomerase activity was higher in the

distal colorectum (Lam et al., 2006; Saleh et al., 2008). Thus, differences in gene expression in

187

different locations in the colorectum exist, and may have important implications for specifically

targeted therapeutic regimens based in JK-1 in the future. Co-localization of JK-1(FAM134B)

with some other molecular or protein changes for future studies may be warranted.

Tubular adenoma is less likely to progress to carcinoma than tubulovillous adenoma or

villous adenoma. In this study, we noted that higher expression of JK-1(FAM134B) protein was

noted in tubular adenoma than in tubulovillous or villous adenomas. This supports the

hypothesis that JK-1 (FAM134B) protein under-expression may be influencing the progression

of tumours during carcinogenesis and onward as they become more aggressive. This finding was

echoed by our mRNA results mentioned above, showing under expression of the protein and

mRNA in advanced staged and higher grade cancers.

Overall, the protein study has indicated that JK-1(FAM134B) is involved in the

development and progression of colorectal cancer, confirming the data obtained during the

mRNA portion of the research (Chapter 3). The loss of expression of its protein in colorectal

tumours appears to be linked to cancer initiation, increased invasiveness and metastasis. The

relationships uncovered in this research hint at complex regulatory effects, as well as potential

utility for the gene as a cancer biomarker and on into targeted treatment.

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The pattern of JK-1(FAM134B) gene expression seems to suggest some tumour suppressor gene

properties. There may be up and down-regulation of JK-1(FAM134B) by other genes or by

other feed-back mechanisms that change with cancer progression. Hence, we have shown the

need for further functional studies, to demonstrate whether these properties of the gene are

merely a reflection of other changes ongoing during carcinogenesis or whether the gene and its

products play a more substantial direct role in colorectal carcinogenesis.

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CChhaapptteerr 55

JK-1(FAM134B) Functional Study

190

JK-1 (FAM134B) functional study

5.1 Introduction

This is the first study of the role of JK-1(FAM134B) gene in human cancer, conducted on

a colorectal cancer model. Previous chapters have illustrated that the JK-1(FAM134B) gene

shows unique characteristics on the DNA, mRNA and protein levels. Moreover, the gene and its

products appear to be associated with a variety of clinicopathological parameters, ranging from

patient age to tumour stage and grade, to name a few. The common denominator in most of these

characteristic changes suggests that mutations, deletions, loss of mRNA and protein expression

all tend to be associated with more aggressive clinicopathologic cancer phenotypes. These

features can often be seen in tumour suppressor genes.

Like most other genes in human cancer, it is safe to assume that the JK-1(FAM134B)

gene is part of a pathway, in which many possible molecular mechanisms come into play.

Although the gene shows very peculiar relationships with multiple clinicopathological features,

this does not necessarily imply that it is the driver of these changes. Furthermore, the gene may

be merely a bystander, that is influenced by other molecular events and exhibiting these changes

as a reflection of other molecular driving forces, while having no effect in any of the events it

shows association with. If this is the case, the gene can still serve as a new prognostic and

predictive marker of colorectal cancer behaviour and aggressiveness, yet will have no molecular

therapeutic implications.

191

Therefore, the need to establish if JK-1(FAM134B) is more of a driver or a bystander

becomes essential. Thus, a functional study of role of JK-1(FAM134B) was performed using a

cell culture model. A colorectal cancer cell line was used to simulate the changes occurring in

vivo. A knock-down experiment was designed to suppress JK-1(FAM134B) protein expression

in these cells and observe its downstream effects on functional characteristics like cellular

proliferation and ability to spread, invade and metastasize.

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Establish if there is a difference in JK-1(FAM134B) expression between colorectal

cancer and non-cancer cell lines.

Successfully obtain a stable JK-1(FAM134B) knockdown in human colorectal cancer cell

line.

Gain insight into the kinds of phenotypic changes resulting from JK-1(FAM134B)

alteration.

Carry out a cell proliferation assay on the colorectal cancer cell line with the knocked-

down gene and compare it to a control. This will establish if the gene performs a

functional role in cell proliferation in cancer.

Perform a cell invasion and migration assay on the cell lines to understand the functional

role of JK-1(FAM134B) gene in these essential cellular characteristic changes in

cancers.

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5.3.1 The cell lines

The human colon cancer cell line SW480 was obtained from American Type Culture

Collection (ATCC) and cultured in RPMI 1640 medium (containing 10% fetal bovine serum and

1% penicillin/streptomycin). A normal colon epithelial cell line FHC (obtained from ATCC) was

used as a control and these cells were cultured in 1:1 mixture of Ham F-12 medium and DMEM

medium supplemented with 25 mmol/L HEPES (N-(2-hydroxyethyl) piperazine-N′(2-

ethanesulfonic acid)) 10 ng/mL cholera toxin, 0.005 mg/mL insulin, 0.005 mg/mL transferrin,

100 ng/mL hydrocortisone and 10% fetal bovine serum. SW480 and FHC cell lines were

cultured at 37oC in a humidified atmosphere containing 50 mL/L CO2.

5.3.2 SW 480 Cell Lines

SW480 was established from a primary adenocarcinoma of the colon, from a 50 year old

Caucasian male. The manufacturer provides the following information regarding the genes

expressed by these cell lines: carcinoembryonic antigen (CEA) 0.7 ng/106 cells/10 days; keratin;

transforming growth factor beta, myc +; myb + ; ras +; fos +; sis +; p53 +; abl -; ros -; src -,HLA

A2, B8, B17; blood type A; Rh+. The cells are positive for keratin by immunoperoxidase

staining. The line is positive for expression of c-myc, K-ras, H-ras, N-ras, myb, sis and fos

oncogenes.

194

5.3.2.1 Handling of frozen cells

The vial was thawed by gentle agitation in a 37°C water bath for 2 minutes, removed

from the water bath as soon as the contents were thawed, and decontaminated by spraying with

70% ethanol. The vial contents were then transferred to a centrifuge tube containing 9.0 ml

complete culture medium and spun at approximately 125x g for 5 to7 minutes. Next, the cell

pellet was re-suspended with the recommended complete medium (RPMI 1640) and dispensed

into a new culture flask.

5.3.2.2 Sub-culturing procedures

The following steps were followed in subculturing:

1. Remove and discard culture medium.

2. Briefly rinse the cell layer with 0.25% (w/v) Trypsin 0.53 mM EDTA solution to remove all

traces of serum which contains trypsin inhibitors.

3. Add 2.0 to 3.0 mL of Trypsin EDTA solution to flask and observe cells under an inverted

microscope until cell layer is dispersed (usually within 5 to 15 minutes).

4. Add 6.0 to 8.0 mL of complete growth medium and aspirate cells by gently pipetting.

5. Add appropriate aliquots of the cell suspension to new culture vessels.

6. Incubate cultures at 37°C without CO2.

Subcultivation ratio: A subcultivation ratio of 1:2 to 1:4 was used

Medium Renewal: 2-3 times per week

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5.3.3 JK-1(FAM134B) knockdown

Gene knock-down was performed using transduction-ready viral particles “Lentiviral

particles (JK-1 shRNA) - sc-92031-V” obtained from Santa Cruz Biotechnology, Dallas, USA.

Lentiviral Particles generally contain three to five expression constructs each encoding target-

specific 19-25nt (plus hairpin) small hairpin RNAs (shRNA) designed to knockdown gene

expression. The shRNA sequences correspond to JK-1(FAM134B) small interfering RNA

(siRNA) Gene Silencer sequences.

A GMO project approval was obtained from Griffith University Institutional Biosafety

Committee (GU-IBC). IBC reference number: NLRD/105/11. The experiments were conducted

in a PC2 certified laboratory. A copy of the approval letter was included in the appendix.

shRNA Lentiviral Particle transduction was performed using the following protocol:

Target cells were plated in a 12-well plate 24 hours prior to viral infection, with 1 ml of complete

optimal medium (with serum and antibiotics) and incubated overnight. The cells were

approximately 60% confluent on the day of infection. A mixture of complete medium with

Polybrene® (sc-134220) - Santa Cruz Biotechnology, Dallas, USA, at a final concentration of 8

µg/ml was prepared followed by removing media from plate wells and replacing with 1 ml of the

Polybrene/media mixture per well. Polybrene is a polycation that neutralizes charge interactions

to increase binding between the pseudoviral capsid and the cellular membrane. The

concentration of Polybrene was optimized and 8µg/ml was used in this experiment, as opposed

to the 5µg/ml suggested in the manufacturer’s instructions.

196

The lentiviral particles were then thawed at room temperature and mixed gently before

use. Cells were infected by adding the shRNA Lentiviral Particles to the culture then incubating

overnight. Four concentrations of lentiviral particles were tested (50 000 to 100 000 infectious

units of virus (IFU) per 1 ml medium). The highest concentration of lentiviral particles was

eventually used. Following overnight incubation, the culture medium was removed and replaced

with 1 ml of complete medium and the cells were again incubated overnight.

5.3.3.1 Puromycin selection

After that, selection of stable clones expressing the shRNA was performed via Puromycin

dihydrochloride (sc-108071) selection. For puromycin selection, an amount sufficient to kill

100% of the non-transduced cells was used. To determine this, a “kill curve” experiment was

designed to determine the Puromycin titration. The following protocol was used: 2 x 105 cells

were plated in each well of a 6-well plate containing 3 ml of the appropriate complete medium

plus increasing concentrations of puromycin (i.e., 0, 1.0, 2.5, 5.0, 7.5, and 10.0 µg/ml). A fresh

selective medium was used every 2 days to remove dead cells. Wells were examined for viable

cells every two days and the percentage of surviving cells was noted. Optimum effectiveness

should be reached in 1-4 days. The minimum antibiotic concentration used was the lowest

concentration that killed 100% of the cells in 3-5 days from the start of puromycin selection. The

optimum concentration in this study was determined at 2.5µg/ml.

197

The medium for cells undergoing selection was replaced with fresh puromycin-

containing medium every 3-4 days, until resistant colonies could be identified. Colonies were

then picked, expanded and assayed for stable expression.

5.3.3.2 The control group:

The abovementioned protocols were used with the control group of colorectal cancer cell

lines (SW480), using Control shRNA Lentiviral Particles (sc-108080) - Santa Cruz

Biotechnology, Dallas, USA instead of the JK-1 siRNA containing particles. The product is a

negative control for experiments using targeted shRNA Lentiviral Particle transduction which

encodes a scrambled shRNA sequence that will not lead to the specific degradation of any

known cellular RNA. After transduction, cells stably expressing the control shRNA were isolated

via puromycin selection using the same protocol and puromycin concentration as test cells.

5.3.4 mRNA Extraction and cDNA conversion

The mRNA was extracted from the harvested cells of both the knock-down and the

control groups using and miRNeasy Mini kit (Qiagen Pty. Ltd.). RNA quality was assessed by

using Bio-Rad electrophoretogram Experion instrument (Bio-Rad, Hercules, CA, USA). In

addition, purity of RNA was determined by checking the optical density (OD) 260/280 ratio by

using a nanodrop spectrophotometer. Concentration of mRNA was also noted in ng/µL.

198

Reverse transcription reactions were performed using 1 µg (5 µl) of total RNA in a final

reaction volume of 20 µl. For this purpose, DyNAmo™ cDNA Synthesis Kit (Finnzymes,

Espoo, Finland) was used. The cDNA synthesis premix was prepared first, that consisted of 10

µl of 2x reverse transcription (RT) buffer, 0.75 µl of random hexamers and another 0.75 µl of

oligo dT as primers, 1.5 µl of RNAse-free water and 2 µl of M-MuLV RNase H+reverse

transcriptase.

The tubes were then placed into a thermal cycler (Corbette Research, NSW, Australia)

and were run through pre-denaturation, primer extension, cDNA synthesis and reaction

termination steps according to manufacturer instructions. Each cDNA sample was diluted to 30

ng/µl for providing uniformly concentrated samples for real-time PCR. Samples were stored in a

-20ºC freezer till used.

5.3.5 Protein Extraction from cell lines

First, the harvested cells were collected in ice cold PBS by detaching manually using a

cell scraper. Cell pellets were obtained after centrifugation and incubated with protein extraction

buffer (Invitrogen), 20X proteinease inhibitor and 1mM PMSF (phenylmethylsulfonyl fluoride)

for 30 minutes on ice. Tubes were then centrifuged again and total protein was collected from the

supernatant. This was then stored in -80 ºC for Western Blot experiments.

199

Concentration of the protein extracted was detected by optical density methods using a

nanodrop spectrophotometer (Nanodrop, Willmington, USA). A standard curve was generated

each time for accurate protein quantification.

5.3.6 Quantitative real-time polymerase chain reaction

To study JK-1(FAM134B) gene RNA expression changes in different cell lines, an IQ5

Multicolour Real-Time PCR Detection system (Bio-Rad, Hercules, CA, USA) was used to

perform real-time quantitative polymerase chain reaction (qPCR).

Real time PCR was performed in a total volume of 20 μl reaction mixture containing

10µL of DyNAmo Flash SYBR green master mix (Finnzymes, Espoo, Finland), 1.5 µL of each

of 5 μmol/L primers, 3 μl of cDNA at 50ng/μl, and 4 µL of 0.1% diethylpyrocarbonate (DEPC)

treated water. For comparing the JK-1 gene expression changes, the housekeeping gene

glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was used. GAPDH has been used as a

ubiquitous control for gene expression in many cancer studies as its expression remains almost

unchanged in multiple cellular conditions.

All the samples (for both JK-1 and GAPDH) were run in triplicates and accompanied by

a non-template control (distilled water). Thermal cycling consisted of initial step of 7 minutes at

95°C which is needed to denature template cDNA and activate the hot start DNA polymerase.

This was followed by 40 cycles of 10 seconds at 95°C (denaturation) and 30 seconds at 60°C

(annealing/extension). Melting curve analysis was conducted using eighty cycles of 30 second

200

holds increasing 0.5°C/cycle from 55°C. The melting curves of all final real-time PCR products

were observed for determination of genuine products. Samples found to have contamination by

non-specific products and primer dimers were excluded. To ensure that the correct product was

amplified in the reaction, all samples were also separated on 2% agarose gel electrophoresis.

5.3.7 Primers

Primers were designed for the amplification and expression analysis of JK-1 (FAM134B)

- (GenBank accession number for variant 1 NM_001034850 and for variant 2 NM_019000) and

GAPDH (GenBank accession number NM_002046) using Primer3 version 0.4.0

(http://frodo.wi.mit.edu/primer3/).

Primers were also checked for specificity using Primer Blast


(Premier Biosoft, Palo Alto, CA, USA) to check for primer parameters like GC content, melting

temperature of the primers and ∆G to prevent any possible mismatching, primer dimer or hairpin

formation. The list of chosen primer sets are summarized in Table 5.1


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Primer Name Sequence (5’-3’) Primer Size (base pairs)

===============================================================

JK-1 forward TGACCGACCCAGTGAGGA 18

JK-1 reverse GGGCAAACCAAGGCTTAA 18

GAPDH forward TGCACCACCAACTGCTTAGC 20

GAPDH reverse GGCATGGACTGTGGTCATGAG 21

Table 5.1: Primers for JK-1(FAM134B) and GAPDH genes.

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5.3.8 Immunocytochemistry study

The immunocytochemistry study was conducted to localise JK-1(FAM134B) protein in

cells and to note any visible changes in protein expression, cyto-morphology or cyto-architecture

in cell lines with JK-1(FAM134B) gene knock-down compared to the control group.

The following protocol was used: Cells were first seeded on 48-well plates. Once they

had reached the desired confluency, cells were fixed with 70% ice cold ethanol for 10 minutes

and permeabilised with 0.1% Triton X-100 for 5 minutes. Cells were then treated with 5% BSA

(bovine serum antigen) for 30 minutes for blocking the protein.

Then cells were incubated with 1:200 diluted primary antibody for JK-1(FAM134B)

overnight at 4˚C. The antibody used is a purified rabbit polyclonal antibody raised against JK-

1(FAM134B) of human origin (Santa-Cruz Biotechnology, CA, USA). The optimal 1:200

dilution was decided after conducting multiple trials with graded dilutions.

After washing with PBS 3 times, the secondary antibody (NovaLink polymer) was added

at 37˚C for 1 hour. After washing three times with PBS and 3, 3’-diaminobenzidine (DAB)

solution with substrate chromogen solution (Novocastra Laboratories) was added to develop

peroxidase activity and stain protein. Cells were kept in DAB solution for 3 minutes. The slides

were rinsed briefly in water and haematoxylin 0.02% was added for one minute for counter

staining. The cells were finally visualized under light microscopy and photographed.

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5.3.9 Western Blot analysis

The semi-quantitative Western Blot method was used to confirm a successful JK-

1(FAM134B) knockdown in colorectal cancer cell lines (SW480). The reduction in the protein

signal of the lentiviral particle-transducted cell lines compared to a control (non-transducted cell

line) and a scramble control (control shRNA lentiviral particles), would serve as a proof of

successful transduction and JK-1(FAM134B) knockdown.

Total protein extracted (30mg) was loaded in Laemmli buffer and onto a 15%

polyacrylamide stacking gel, run at 40 volts, then at 100 volts through a 15% separating gel by

using a Mini Cell (Bio-Rad). The proteins were transferred to nitrocellulose membranes (Bio-

Rad) for 1 hour by using a Mini Trans-Blot Electrophoretic Transfer Cell (Bio-Rad). This was

followed by membrane blocking with 5% non-fat milk for 2 hours at room temperature.

After two washes in PBS 0.005% Tween 20, JK-1(FAM134B) and GAPDH monoclonal

antibody was added (1:150 each) and incubated overnight at 4˚Celsius. Then, membranes were

washed three times and incubated with a secondary antibody (NovoLink polymer) at room

temperature for 2 hours. Detection of protein bands was performed by developing the peroxidise

activity with freshly prepared 3, 3’-diaminobenzidine (DAB) and substrate chromogen solution

(Novocastra Laboratories). Total protein content loaded was then normalized by the signal from

GAPDH protein.

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5.3.10 Cell proliferation Study

To study cell proliferation changes related to JK-1(FAM134B) gene knock-down, MTT

calorimetric assays were performed. The MTT system is a simple, accurate, reproducible means

of measuring the activity of living cells via mitochondrial dehydrogenase activity. The key

component is 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyl tetrazolium bromide or MTT. Solutions

of MTT solubilized in tissue culture media or balanced salt solutions, without phenol red, are

yellowish in color. Mitochondrial dehydrogenases of viable cells cleave the tetrazolium ring,

yielding purple MTT formazan crystals which are insoluble in aqueous solutions. The crystals

can be dissolved in acidified isopropanol. The resulting purple solution is spectrophotometrically

measured. An increase in cell number results in an increase in the amount of MTT formazan

formed and an increase in absorbance.

The following protocol was applied to the SW480 cell lines, for both the JK-

1(FAM134B) knock-down and the control group. The cells were first seeded in flat-bottom 96-

well plates at 1 × 104 cells/well. After transduction with lentiviral particles (for both knock-down

and control groups), 0.5 mg/ml 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide

(MTT) (Sigma-Aldrich, St. Louis, MO) was added to each well at 12, 24, 36, 48 and 72 hours.

The cells were then incubated at 37 °C for another 4 h, the medium was removed and 150 μl

dimethyl sulfoxide (DMSO, Sigma–Aldrich Co.) was added. The cells were agitated for 10 min

with protection from light. Absorbance was measured by spectrophotometry (Infinite M200,

Grodig, Austria) using a wavelength of 570 nm, while a wavelength of 630 nm was used as a

reference.

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5.3.11 Cell migration study

Cell migration is a highly integrated, multistep process that orchestrates morphogenesis,

tissue repair and regeneration. It plays a pivotal role in the disease progression of cancer. The

initial response of a cell to a migration-promoting agent is to polarize and extend protrusions in

the direction of the attractant; these protrusions can consist of large, broad lamellipodia or spike-

like filopodia. In either case, these protrusions are driven by actin polymerization and can be

stabilized by extracellular matrix (ECM) adhesion or cell-cell interactions (Ridley et al., 2003).

Invasion of cancer cells into surrounding tissue and the vasculature is an initial step in

tumour metastasis. This process requires chemotactic migration of cancer cells, steered by

protrusive activity of the cell membrane and its attachment to the extracellular matrix. In vitro

invasion assays provide new insights into how cancer cell migration is regulated by elements of

the local microenvironment, including the extracellular matrix architecture and other cell types

found in primary tumours. These results can lead to new insights into the molecular mechanisms

of cell protrusive activity and chemotactic migration during invasion and metastasis. (Yamaguchi

et al., 2005)

The Radius™ Cell Migration Assay Kit utilizes a proprietary 24-well plate, which has

been pre-coated with various extracellular matrix (ECM) proteins, to monitor the migratory

properties of cells (as seen in Figure 5.1). Each plate well contains a 0.68 mm non-toxic,

biocompatible hydrogel spot where cells cannot attach. When adherent cells are seeded in the

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Radius™ Cell Migration well, they attach outside of the gel coated area. Once firm cell

attachment is achieved, the hydrogel is quickly removed to expose a cell-free region to study cell

migration/closure. This format provides a robust in vitro system to measure 2-D cell migration.

Fig 5.1 : The following layout indicates the location of ECM protein-coated wells and uncoated

wells. Row A: Collagen I; Row B: Fibronectin; Row C: Laminin I; Row D: uncoated. All wells

contain one gel spot.

5.3.11.1 Migration Assay Protocol

I. Pretreatment of Radius™ Migration Plate

Under sterile conditions, 500 μL of Radius™ gel pretreatment solution was added to each well of

the Radius™ 24-well cell migration plate by carefully pipetting down the wall of the well. The

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plate was then covered and incubated at room temperature for 20 minutes before the pretreatment

solution was aspirated from the wells. 500 μL of Radius™ wash solution was added to each well.

II. Cell Seeding

Cells were harvested and re-suspended in culture medium at 0.25 x 106

cells/ml. Radius™ wash

solution was aspirated from the wells, then 500 μL of the cell suspension was added to each well

by carefully pipetting down the wall of the well. The plate is then transferred to a cell culture

incubator for 2-6 hours at standard conditions for culture of the target cells to allow firm

attachment and spreading

III. Radius™ Gel Removal

The Radius™ Migration Plate was carefully removed from cell culture incubator. The media was

aspirated from each well and washed 3 times with 0.5 mL of fresh media. The media was then

replaced by 0.5 mL of 1X Radius™ Gel Removal Solution. The plate was then transferred to a

cell culture incubator for 30 minutes to allow complete gel removal, and the solution was then

aspirated and washed with 0.5 mL of fresh media again. After the final washing was complete, 1

mL of complete medium was added to each well and pre-migration images captured with an

inverted microscope.

Next, the plate was transferred back to the cell culture incubator for the migration process.

Migration was monitored in real time and serial pictures were taken every 2 hours.

A simplified diagram demonstrating the protocol is illustrated in figure 5.2

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Fig 5.2: A diagram illustrating the cell migration study protocol. Cells are added to the culture

wells, containing the gel layer in the centre to prevent cellular growth. Once the cells have been

209

allowed to attach to the well in the non-gel coated area, the gel is removed and the cells are

allowed to migrate into the centre of the cell free region.

5.3.12 Analysis of Results

The results were analyzed visually by comparing cell migration pattern and speed in colorectal

cancer cell lines with JK-1(FAM134B) gene knockdown to a scramble of the same cell lines. In

addition to the visual comparison, CellProfiler™ Cell Image Analysis Software

(www.cellprofiler.org) was used to quantify the number of migrated cells in the center of the gel

spot. The numerical results were then compared statistically using paired t-test to establish if the

differences were statistically significant. Significance level was taken at P<0.05.

http://www.cellprofiler.org/

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5.4 Results

5.4.1 JK-1(FAM134B) mRNA expression in colorectal cell lines

Real time PCR results for mRNA expression of JK-1(FAM134B) in cell lines showed

that colon cancer cell lines (SW480) had reduced expression of the mRNA compared to a normal

colonic epithelial cell line (FHC). Using inverse ratio as a measure of mRNA expression, colon

cancer cell lines had a mean inverse ratio of 0.74±0.040 (n=3), compared to normal colonic

epithelium cell line which had a mean inverse ratio of 0.97±0.076 (n=3). Statistical significance

was achieved when using a t-test tom compare these values (p=0.014). Figure 5.3 illustrates the

difference in mRNA expression of JK-1(FAM134B) in these 2 cell lines.

Fig 5.3 : JK-1(FAM134B) mRNA expression (measured in inverse ratio) of colorectal cancer

(SW480) cell lines and normal colorectal (FHC) cell lines. Cancer cell lines showed lower

mRNA expression of the gene. (p=0.014)

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Immunocytochemistry of both colorectal cancer and normal colonic epithelium cell lines

(SW480 and FHC) revealed a strong nuclear staining for JK-1(FAM134B) protein. This is

illustrated in Fig 5.4

Figure 5.4: JK-1(FAM134B) protein in colon cell lines: Immunocytochemistry of colon cell

lines, showing strong nuclear staining for JK-1(FAM134B) protein in both colorectal cancer cell

line (SW480) and normal colonic epithelium cell line (FHC). Magnification 200X.

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5.4.2 Confirming JK-1(FAM134B) knockdown and transduction efficiency in SW-480 cell

lines

5.4.2.1 Morphological changes on JK-1(FAM134B) knockdown in SW-480 cell lines

There were no apparent morphological or architectural changes in SW480 cells after

transduction with lentiviral particles carrying with JK-1(FAM134B) shRNA, compared with

control SW480 cells transducted with scrambled shRNA. However, a lower strength of staining

of the nuclear JK-1(FAM134B) protein was evident on immunocytochemistry in the knocked

down cells compared to control (scramble). Figures 5.5 and 5.6 illustrate that difference.

SW 480 with scramble SW with JK-1 knockdown

Fig 5.5: JK-1(FAM134B) knockdown in SW480 cell lines (low power). Although there was no

significant alteration of cellular morphology, the staining intensity of the nucleus for JK-

1(FAM134B) protein appears to be less in the knocked down cell lines. Magnification 200X.

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SW 480 with scramble SW with JK-1 knockdown

Fig 5.6: JK-1(FAM134B) knockdown in SW480 cell lines (high power). Although there was no

significant alteration of cellular morphology, the staining intensity of the nucleus for JK-

1(FAM134B) protein appears to be less in the knocked down cell lines. Magnification 400X.

5.4.2.2 mRNA expression of JK-1(FAM134B) gene in knocked down SW-480 cell lines

After knocking down JK-1(FAM134B) in SW480 colon cancer cell lines, mRNA

expression of the gene was measured in the knocked down cell lines, and was compared to the

mRNA expression levels in the SW480 cell lined transducted with a scrambled siRNA and the

unmodified control in SW480 cell lines.

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JK-1(FAM134B) mRNA levels (expressed in terms of fold change mean) of the

knocked down SW480 cell lines were 5 fold less compared to the unmodified control SW480

(0.23±0.021 compared to 1.15±0.19), and more than four fold less compared to the scrambled

SW480 which was 1.02±0.11 (n=3 for each). The differences between the knockdown on the one

hand and both the scrambled and the unmodified control on the other, were significant (p=0.004

and 0.007 respectively). The scrambled and the unmodified control groups showed no

statistically significant difference in the levels of JK-1(FAM134B) mRNA. Figure 5.7 illustrates

these differences.

0

0.5

1

1.5

mRNA Expression (fold change)

SW480 - control

SW480-Scramble

SW480-JK-1knockdown

Fig 5.7: JK-1(FAM134B) mRNA expression (measured in fold change) of colorectal cancer

(SW480) cell lines in its unmodified control form, scrambled shRNA control and JK-

1(FAM134B) knock down group. mRNA expression of the gene plummeted in the knock-down

group, compared to the 2 controls.

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5.4.2.3 Western blot findings in JK-1(FAM134B) knockdown in SW-480 cell lines

To confirm and detect transduction efficiency in the knock down experiment, JK-

1(FAM134B) protein levels were determined using a semi-quantitative Western blot method in

cells treated with lentiviral particles containing siRNAs targeting JK-1(FAM134B), one

scrambled siRNA and one unmodified control group.

Cells treated with lentiviral particles containing siRNAs targeting JK-1(FAM134B)

showed reduction in JK-1(FAM134B) protein levels compared to the unmodified control and

cells treated with scrambled siRNA groups. Figure 5.8 illustrates the changes in the antibody

signal detected. This indicates the efficiency of JK-1(FAM134B) knock down at the protein

level, in addition to the abovementioned histological and mRNA evidences.

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Figure 5.8 JK-1(FAM134B) knock down confirmation by Western blotting. The lentiviral

siRNA treated cells showed marked reduction in JK-1(FAM134B) protein signal detected

compared to the unmodified control and scrambled siRNA groups.

5.4.3 JK-1(FAM134B) knock-down effect on cell proliferation

To assess the effect of JK-1(FAM134B) on cell proliferation, an MTT assay was used to

compare between SW480 unmodified control colorectal cancer, scrambled shRNA control and

JK-1(FAM134B) knock down cells. Absorbance was measured for 50 and 70 percent confluency

in all cell lines, in 5 plates for each confluency and the mean of absorbance was taken as a

measure of cell proliferation.

In both confluencies, there was no statistically significant difference in absorbance,

which is a measure of cell proliferation. Cell proliferation levels were slightly higher in the

colorectal cell lines with JK-1(FAM134B) knock down, yet this difference was insignificant.

Table 5.2 and figure 5.9 illustrate the results obtained.

70% confluence 50% confluence

SW480 - control 1.38±0.09 0.69±0.03

SW480-Scramble 1.43±0.07 0.73±0.04

SW480-JK-1 knockdown 1.5±0.09 0.72±0.07

Table 5.2: Relative absorbance (measure of cell proliferation) on MTT assay in 70% and 50%-

confluence cell lines (unmodified control colorectal cancer (SW480), scrambled shRNA control

and JK-1(FAM134B) knock down). The differences in absorbance between different cell lines

in each group were not significant.

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Figure 5.9 : MTT assay to determine the effects of JK-1(FAM134B) on cell proliferation.

70% and 50%-confluence cell lines (unmodified control colorectal cancer (SW480), scrambled

shRNA control, JK-1(FAM134B) knock down and FHC) absorbance was measured. No significant

change in absorbance (cell proliferation rates) was observed between different colorectal cancer

cell lines in each group. Normal colonic epithelium cell lines on the other hand, showed 5 fold less

absorbance (cell proliferation)

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5.4.4 JK-1(FAM134B) knock-down effect on cell migration:

The results of the migration study was determined by visual assessment of cell migration

from the periphery of the artificial spot on the plate to the centre, in addition to using the cell

count software to determine the number of viable cells in the centre of the spot over time.

The first set of cell migration data were obtained from analysing colorectal cancer cell

migration capacity on a plate covered by Collagen Type I, one of the major extracellular matrix

proteins in the body.

Colorectal cancer cells with a knock down of JK-1(FAM134B) showed much higher rate

of cell migration over time. The significant difference (p=0.040) in cell migration between the

JK-1(FAM134B) knock down of SW480 cells and a scrambled shRNA treated SW480 cell lines

is demonstrated in figures 5.10 and 5.11

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Figure 5.10: JK-1(FAM134B) knockdown effect on cell migration capacity in a collagen

type I coated plate. The knock down cells had a much higher rate of migration, shown by the

rate of increase in viable cell counts within the empty region.(p=0.040)

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Fig 5.11: JK-1(FAM134B) knockdown effect on SW480 migration capacity in collagen type

I coated plates. Cells with the knockdown migrate at higher rate compared to the control, shown

by the rate of increase in viable cell counts within the empty region. Magnification 20X.

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Fibronectin is another abundant extracellular matrix protein. Plates coated with

fibronectin were used to assess colorectal cancer cell migration properties in SW480 cell lines

with JK-1(FAM134B) knockdown, compared to a control (scrambled shRNA transducted cell

lines)

Cells with JK-1(FAM134B) knockdown had higher migration rates compared to the

control on a fibronectin coated plate. The difference was statistically significant (p=0.043). Fig

5.12 and 5.13 illustrate that difference.

Figure 5.12: JK-1(FAM134B) knockdown effect on cell migration capacity in a fibronectin

coated plate. The knock down cells had a much higher rate of migration , shown by the rate of

increase in viable cell counts within the empty region.(p=0.043)

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Fig 5.13: JK-1(FAM134B) knockdown effect on SW480 migration capacity in fibronectin

coated plates. Cells with the knockdown had higher migration rate compared to the control.

Magnification 20X.

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Laminin I was also used to simulate a naturally occurring extracellular matrix protein

using plates coated with this protein assess colorectal cancer cell migration properties in SW480

cell lines with JK-1(FAM134B) knockdown, in comparison with a control (scrambled shRNA

transducted cell lines).

JK-1(FAM134B) knockdown colorectal cell lines showed migration rates that are slightly

higher compared to the control on a laminin type I coated plate. The difference was nonetheless

not statistically significant (p=0.071). Morphologically, the pattern of invasion was also

different. Invading cancer cells with JK-1(FAM134B) knockdown were more cohesive, while

the control group had scattered and single cell morphology. This is illustrated in figures 5.14 and

5.15

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Figure 5.14: JK-1(FAM134B) knockdown effect on cell migration capacity in a laminin

type I coated plate. The knock down cells had generally a higher rate of migration, but the

difference was not statistically significant (p=0.071)

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Fig 5.15: JK-1(FAM134B) knockdown effect on SW480 migration capacity in laminin I

coated plates. Knockdown cells showed higher migration rate compared to the control, though

this difference was not statistically significant. Magnification 20X.

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In contrast to the results obtained using extracellular matrix protein coated plates, cell migration

assay of JK-1(FAM134B) gene knockdown effect using uncoated plates showed no difference in

cell migration capacity. Figure 5.16 shows the migrating viable cell count trends over time,

which had no statistically significant difference (p=0.282). There was no apparent difference in

the pattern of invasion morphologically either.

Figure 5.16: JK-1(FAM134B) knockdown effect on cell migration capacity in non- coated

plate. No difference in cell migration between the knock down and the control groups was noted.

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5.5 Discussion

5.5.1 JK-1(FAM134B) mRNA expression in colorectal cell lines

This is the first study to demonstrate JK-1(FAM134B) mRNA expression in colorectal

cell lines, both cancer (SW480) and non-cancer (FHC) cell lines.

Colorectal cancer cell lines show significantly lower levels of mRNA expression of JK-

1(FAM134B) gene, compared to a normal colonic epithelium cell line. This finding, although by

itself is not important due to the limited number of cell lines, mirrors our previous finding in a

large cohort of colorectal cancer cases, where mRNA expression of JK-1(FAM134B) was

significantly lower in colorectal cancer cases than in normal and benign tumour groups.

5.5.2 Confirming JK-1(FAM134B) knockdown and transduction efficieny in SW-480 cell

lines

Cytological evidence of lower strength of JK-1(FAM134B) protein staining on

immunocytochemistry, coupled with a more than four-fold decrease in JK-1(FAM134B) mRNA

expression and Western blot evidence of the same, served as a confirmation of successful JK-

1(FAM134B) knockdown in colorectal cancer cell lines. The robustness of the subsequent

functional assays in this chapter is vastly dependent on the confirmation of the gene knock down

success, so this confirmation is an excellent result for the significance of this research.

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5.5.3 Effect of JK-1(FAM134B) knockdown on cell proliferation in colorectal cancer cells

Study of JK-1(FAM134B) effect on cellular proliferation was performed by comparing

unmodified control colorectal cancer (SW480), scrambled shRNA control and JK-1(FAM134B)

knock down cells with one another and with a normal colonic epithelium cell line (FHC), on the

other.

JK-1(FAM134B) knock down appears to have no effect on the proliferation potentials of

colorectal cancer cell lines. Previous results showing the effect of suppressed JK-1(FAM134B)

expression on tumour size and T stage, along with the general change in gene expression in

cancer would have implied that the gene products have an effect on cell proliferation. However,

both tumour size and T stage are determined by multiple factors in addition to the rate of tumour

cell proliferation, and both parameters are results of a long term effect in vivo, rather than a short

term measurement of cellular proliferation in a cell culture environment.

Fundamentally, cancer is a disease of accumulation of clonal cells. Abnormal cell

proliferation is necessary, although often insufficient, for tumourigenesis. In this study, the non-

cancer cell lines (FHC) demonstrated a much lower cell proliferation rate compared to colorectal

cancer, as would be expected. It is the increase in tumour cell number, and thus tumour burden,

that ultimately accounts for the adverse effects on the host. The rate of cell proliferation within

any population of cells depends on three parameters: The rate of cell division, the fraction of

cells within the population undergoing cell division and the rate of cell loss from the population

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due to terminal differentiation or cell death (Pardee, 1989). We can assume that JK-

1(FAM134B) has no effect on cell proliferation in colorectal cancer cell lines, or that the effect is

so minimal that it could not be detected in this study. Our results from the cell migration assays

suggest another potential mechanism by which the change in JK-1 expression is associated with

tumour size, however.

5.5.4 Cell migration assay

Cell migration, governed by polarity and reorganization of the cellular cytoskeleton, is an

integral aspect of tumour cell invasion (Ridley et al., 2003). Tumour cell invasion is a complex

process involving genetic and cellular alterations which lead to proteolysis and dispersion

through three-dimensional biological barriers in the host tissue (Stetler-Stevenson et al., 1993).

Collagen I can self-assemble into a 3-D super-molecular gel in vitro, making it an ideal

biological scaffold to promote more in vivo-like cellular morphology and function (Bornstein and

Sage 1980). The effect on invasion and metastatic capacity of the JK-1(FAM134B) gene in

colorectal cancer was studied using a set of extracellular matrix protein coated plates, to simulate

in vivo conditions. JK-1 knock-down cells showed significantly higher rates of invasion and

migration in all substrates, with the exception of laminin I

Type I collagen coasted plates used to study JK-1(FAM134B) knock down in colorectal

cancer cell lines showed that the knock down caused a marked increase in cell invasion rates.

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Type I collagen is the most abundant component of the extracellular matrix (ECM), and

is therefore a significant obstacle for tumour cell dissemination into the lymphatics, vasculature,

and surrounding areas (Seiki, 2003). Thus, in most cases, collagen must be degraded in order for

tumour cells to spread into surrounding anatomic structures and metastasize. This could be one

of the steps where JK-1(FAM134B) plays an important role in cancer development and why it

shows association with tumour size and aggression, since whatever its proliferation rate, it

cannot grow large if it cannot access new regions for growth.

Tissue invasion during metastasis requires cancer cells to negotiate a stromal

environment dominated by cross-linked networks of type I collagen. Although cancer cells are

known to use proteinases to sever collagen networks and thus ease their passage through these

barriers, migration across extracellular matrices has also been reported to occur by protease

independent mechanisms, whereby cells squeeze through collagen-lined pores by adopting an

amoeboid phenotype (Sabeh et al., 2009)

Tumour cells traverse epithelial and endothelial basement membranes during the

successive stages of the metastatic process. At the transition from in situ to invasive carcinoma,

local dissolution of the basement membrane is observed microscopically, and coincides with

tumour cell invasion of the underlying stroma. Tumour cells further traverse the endothelial

basement membrane during entry into and egress from blood vessels. Electron microscopic

studies have shown local dissolution of basement membrane at its area of contact with invading

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tumour cells, suggesting an enzymatic mechanism (Liotta et al., 1980). This could be another

pathway by which is exerting its effect.

One of the most well characterized adhesion factors in cell migration and metastasis is

the glycoprotein fibronectin (Humphries et al., 1989). Fibronectin is also involved in wound

healing and embryonic development as well as oncogenic transformation (Ritzenthaler et al.,

2008). JK-1(FAM134B) knock down in colorectal cancer cell lines promoted cellular invasion

in plates coated with fibronectin as cells with JK-1(FAM134B) knockdown had higher migration

rates compared to the control on a fibronectin coated plate. (p=0.043). This difference is

illustrated in Fig 5.12 and 5.13.

The adhesive glycoprotein fibronectin and integrin receptors appear to play important

roles in the progression of metastatic disease. Fibronectin is a multifunctional extracellular

glycoprotein that has at least two independent cell adhesion regions with different receptor

specificities (Akiyama et al,. 1995). It is possible that JK-1(FAM134B) gene exerts at least some

of its effects through regulating proteins binding to one or both of these regions.

Laminin, another basement membrane glycoprotein, has been implicated in a number of

stages in tumour invasion and metastasis. In addition to its roles in cell adhesion and migration,

laminin may be important in mediating interactions of tumour cells with the immune system and

have more subtle roles in controlling metastatic behaviour (Hunt, 1989).

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JK-1(FAM134B) knock down has also caused increased cancer cell invasiveness in

laminin I coated plates (Fig 5.15 and 5.16). Although this difference was only close to

significant on statistical analysis, cellular morphological changes were noted in the knocked

down phenotype, where cancer cells appeared more cohesive in structure, moving as a more

solid mass than cells subject to scrambled siRNA.

Forester et al. describes that in normal tissue, laminin presence is largely restricted to

basement membranes, including that underlying the epithelial cells. In rectal carcinomas,

basement membrane-like staining for laminin associated with tumour cells was found in 54% of

cases studied. The study showed that the presence of laminin-containing basement membranes

was correlated with low histological grade and with a reduced incidence of distant metastases

and increased patient survival (Forster et al., 1984). Another study also describes anti-metastatic

properties of laminin in cancer cells (Jiang et al., 1998). It is possible that JK-1(FAM134B)

knock down has a role in counteracting the anti-invasion and anti-metastatic properties of

laminin in cancer tissue, but that its effects are not generally sufficient to overcome the

restrictive effect of the protein.

Viewed as a whole, the cell migration assays support the association of reduced JK-

1(FAM134B) expression in colorectal cancers with increased cancer stage and aggression, and

indicate that the mechanism behind this association is at least partly mediated through an

increase in motility within the local tissue and potentially metastatic capacity. The ability of cells

lowly expressing JK-1 (FAM134B) to significantly increase their invasion rates on collagen and

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fibronectin coated plates, but not in laminin coated plates may indicate that this altered capacity

is a result of an increased tendency to bind to the ECM and to migrate through pores, rather than

using enzymatic breakdown as a primary method of mobility. These results further imply that

JK-1(FAM134B) serves to repress the capacity of cells to move within their tissue, and that it

may have utility as a means to prevent cancer cells from forming new metastases.

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Chapter 6

Summary and conclusions

235

Summary and conclusions

This is the first study showing significant correlations of the JK-1(FAM134B) gene and

its products, both on molecular and functional levels, with clinical and pathologic features in

human cancers. JK-1(FAM134B) expression, copy number and mutations were studied on a

model of colorectal cancer and their implications for human health examined. A large cohort of

cases of colorectal cancers, benign tumours and non-tumour conditions were recruited for the

study. JK-1(FAM134B) was quantified at DNA, mRNA and protein levels, using paraffin

embedded tissue and colorectal cell lines to understand its role in tumour development. Also, a

successful suppression of JK-1(FAM134B) protein was performed using shRNA lentiviral

particles and its downstream effects were studied in human colon cancer cell lines.

JK-1(FAM134B) DNA copy numbers, mRNA and protein expression levels were

significantly altered in all selected cancer tissue. Moreover, a mutation detected by HRM and

sequencing was found to be associated with cancer metastasis. An in vitro knockdown of JK-

1(FAM134B) in colon cancer cell lines led to a change in cell behaviour and aggressive

phenotypes.

Changes in JK-1(FAM134B) DNA copy number were associated with tumour

recurrence, histological subtypes, and cancer stage. Lower copy numbers were associated with

higher T, N and overall stage of cancer, and also with a higher rate of cancer recurrence.

Conversely, higher DNA copy numbers were detected more often in the mucinous type of

colorectal adenocarcinoma.

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In all colorectal tissues, JK-1(FAM134B) mRNA was expressed, though with noticeable

variation. Adenomas showed a much higher rate of mRNA expression, whilst cancer’s levels of

expression were significantly lower. Within the colorectal cancer population, significantly lower

mRNA expression was noted in higher T, N, M and overall stages and in tumours that are

located in the proximal part of the colorectum.

In concert with the changes seen on the mRNA level, JK-1(FAM134B) protein

expression was lower in colorectal cancers of larger size, higher stage and grade, higher

recurrence rates and cancers of proximal colorectal location.

Lower mRNA and protein expression, in addition to DNA copy number deletion of JK-

1(FAM134B) gene in colon cancer patients were generally associated with shorter survival

periods, indicating that JK-1(FAM134B) could play a role in influencing and predicting patient

prognosis.

The abovementioned features of JK-1(FAM134B) gene and its products described in this

study suggest a tumour suppressor gene profile. One previous study has also predicted that the

part of the chromosome containing JK-1(FAM134B) gene harbours some tumour suppressor

genes for colorectal carcinoma. On the other hand, another previous study on the role of JK-

1(FAM134B) in oesophageal squamous cell carcinoma suggested some oncogenic properties of

the gene. It is possible that the gene has a complex mode of action, giving it both tumour

237

suppression and oncogenic capacity, depending on tissue of origin or the presence of modifying

gene products.

The changes shown on DNA, mRNA and protein levels and their strong association with

certain clinicopathologic features in colorectal cancer patients are very promising, but remain of

limited significance in terms of gene function and potential future use in cancer molecular

therapeutics unless a functional study is performed, and such a study was performed as an

additional arm of this research. The aim of that segment of the study was to investigate if the

gene was merely a bystander in colorectal carcinogenesis or a potential driver of some of the

observed associations in cancer tissues.

The functional role of JK-1(FAM134B) in human cancer was studied for the first time,

using shRNA-lentiviral based knock down methods. JK-1(FAM134B) suppression in a colon

cancer cell line resulted in increased cell invasiveness and migration capacity on multiple

extracellular matrix substrates. It had no effect, however, on cancer cellular proliferation. The

findings suggest that alterations in the state of JK-1(FAM134B) activity and their correlation

with clinical and pathological features of colorectal cancers were not merely a side effect of the

region containing the JK-1(FAM134B) gene being influenced by other molecular changes, rather

that it is one of the drivers of these changes. Thus, the present study opens the door for a range

of clinical implications for this newly discovered gene with tumour suppressor features. These

may include tumour diagnosis and prognosis profiling as well as molecularly based therapies in

human cancers, once its complete mechanism of action is better understood.

238

Further research in unveiling JK-1(FAM134B) protein structure, its functional interaction

sites and post translational modifications will help in understanding of the complete role of this

gene in cell and cancer biology. In addition, future studies of this gene can be directed at

studying its interaction with other known genes in colorectal cancer pathways, and its potential

role in these pathways. Moreover, whole gene sequencing is needed to reveal other possible

mutations in the gene and their roles in carcinogenesis in colorectal cancer and other tissues, if

any. This will further improve our current understanding of cancer pathways and gene targeted

therapies.

239

References

240

References:

Aaltonen LA and Hamilton SR (2000) Pathology and genetics of tumours of the digestive

system. World Health Organization., International Agency for Research on Cancer: IARC Press

;Oxford University Press 314 p. p.

Adams, J.M. and Cory, S. (2007) The Bcl-2 apoptotic switch in cancer development and therapy.

Oncogene, 26(9): 1324-1337.

Addis MF, Tanca A, Pagnozzi D, et al (2009) Generation of high-quality protein extracts from

formalin-fixed, paraffin-embedded tissues. Proteomics 9(15):3815-3823.

Adlercreutz, H. (1990) Western diet and Western diseases: some hormonal and biochemical

mechanisms and associations. Scand J Clin Lab Invest Suppl., 201: 3-23.

Ahmed, M.M., Sheldon, D., Fruitwala, et al. (2008) Downregulation of PAR-4, a pro-apoptotic

gene, in pancreatic tumors harboring K-ras mutation. Int J Cancer.,122(1): 63-70.

Akita, H., Iizuka, A., Hashimoto, et al. (2000) Induction of KAI-1 expression in metastatic

cancer cells by phorbol esters. Cancer Lett., 153(1-2): 79-83.

Akiyama, S. K., Olden K., et al. (1995). Fibronectin and integrins in invasion and metastasis.

Cancer Metastasis Rev 14(3): 173-189.

American Cancer Society. Cancer facts & figures 2008: 1-69. Atlanta: American Cancer

Society, 2008.

Anker, P., Mulcahy, H., Chen, X.Q. et al. (1999) Detection of circulating tumour DNA in the

blood (plasma/serum) of cancer patients. Cancer & Metastasis Reviews, 18(1): 65-73.

241

Arasaradnam, R.P., Commane, D.M., Bradburn, D., et al. (2008) A review of dietary factors and

its influence on DNA methylation in colorectal carcinogenesis. Epigenetics, 3(4): 193-198.

Atkin, W. (2003) Options for screening for colorectal cancer. Scand J Gastroenterol Suppl., 237:

13-16.

Atkin, W. S., Edwards, R., Kralj-Hans, I., Wooldrage, K., Hart, A. R., Northover, J., et al (2010).

Once-only flexible sigmoidoscopy screening in prevention of colorectal cancer: a multicentre

randomised controlled trial. The Lancet, 375(9726), 1624-1633.

Australian Institute of Health and Welfare and the Australasian Association of Cancer

Regestries. Cancer in Australia 2001, Cancer series no. 28: 1-141, AIHW cat. no. CAN23.

Canberra: AIHW, 2004.

Avison MB. Measuring gene expression. New York ; Abingdon [England]: Taylor & Francis;

2007. x, 324 p. p.

Axelrod, R., Axelrod, D.E. , Pienta, K.J. (2006) Evolution of cooperation among tumor cells.

PNAS, 103(36): 13474-13479.

Batty, D. and Thune, I. (2000) Does physical activity prevent cancer? BMJ, 321: 1424-1425.

Beauchemin, N., & Arabzadeh, A. (2013). Carcinoembryonic antigen-related cell adhesion

molecules (CEACAMs) in cancer progression and metastasis. Cancer and Metastasis Reviews,

32(3-4), 643-671.

Belpomme, D., Irigaray, P., Hardell, L., et al.. (2007) The multitude and diversity of

environmental carcinogens. EnvironRes., 105(3): 414-429.

Bender, C.M., Pao, M.M. and Jones, P.A. (1998) Inhibition of DNA methylation by 5-aza-2’-

deoxycytidine suppresses the growth of human tumor cell lines. Cancer Res., 58(1): 95-101.

242

Benharroch, D. and Birnbaum, D. (1990) Biology of the fibroblast growth factor gene family. Isr

J Med Sci., 26(4): 212-219.

Bennani-Baiti, N. and Davis, M.P. (2008) Cytokines and cancer anorexia cachexia syndrome.

Am J Hosp Palliat Care., Epub ahead of print.

Benson III, A.B. (2007) New approaches to assessing and treating early-stage colon andrectal

cancers: Cooperative group strategies for assessing optimal approaches in early stage disease.

Clin Cancer Res., 13(22 Suppl): 6913s-6920s.

Berger, J.C., Vander Griend, D.J., Robinson, V.L et al. (2005) Metastasis suppressor genes: from

gene identification to protein function and regulation. Cancer Biol Ther., 4(8): 805-812.

Beroukhim, R., G. Getz, et al. (2007). Assessing the significance of chromosomal aberrations in

cancer: methodology and application to glioma. Proc Natl Acad Sci U S A 104(50): 20007-

20012.

Bhardwaj, N. (2007) Harnessing the immune system to treat cancer. J Clin Invest., 117(5): 1130-

1136.

Biasco, G. and Gallerani, E. (2001) Treatment of liver metastasis from colorectal cancer: what is

the best approach today? Dig Liver Dis., 33(5): 438-444.

Bing, C. and Trayhurn, P. (2008) Regulation of adipose tissue metabolism in cancer cachexia.

Curr Opin Clin Nutr Metab Care., 11(3): 201-207.

Birkenkamp-Demtroder K, Olesen SH, et al. (2005) Differential gene expression in colon cancer

of the caecum versus the sigmoid and rectosigmoid. Gut.;54(3):374-84.

243

Boccardo, E. and Villa, L.L. (2007) Viral origins of human cancer. Curr Med Chem., 14(24):

2526-2539.

Bodey, B., Bodey, B. Jr., Siegel, S.E. and Kaiser, H.E. (2000) Prognostic significance of matrix

metalloproteinase expression in colorectal carcinomas. In Vivo, 14(5): 659- 666.

Bodmer, W.F. (2006) Cancer genetics: colorectal cancer as a model. J Hum Genet., 51(5): 391-

396.

Bompard, G., Sharp, S.J., Freiss, G. and Machesky, L.M. (2005) Involvement of Rac in actin

cytoskeleton rearrangements induced by MIM-B. Journal of Cell Science, 118: 5393-5403.

Bonadona, V., Bonaïti, B., Olschwang, S., Grandjouan, S., Huiart, L., Longy, M. et al. (2011).

Cancer risks associated with germline mutations in MLH1, MSH2, and MSH6 genes in Lynch

syndrome. JAMA: The Journal of the American Medical Association, 305(22), 2304.

Bonis, P.A., Trikalinos, T.A., Chung, M., et al. (2007) Hereditary nonpolyposis colorectal

cancer: diagnostic strategies and their implications. Evid Rep Technol Assess., (150): 1-180.

Booth, R.A. (2007) Minimally invasive biomarkers for detection and staging of colorectal

cancer. Cancer Lett., 249(1): 87-96.

Bornstein, P. and H. Sage (1980). Structurally distinct collagen types. Annu Rev Biochem 49:

57-1003.

Bosman, F., Carneiro, F., Hruban, R. and Theise, N. (Eds.) (2010) WHO classification of

tumours of the digestive system. World Health Organization. 4th

ed., International Agency for

Research on Cancer: IARC Press

Boyle, P. and Langman, J.S. (2000) ABC of colorectal cancer: Epidemiology. BMJ, 321: 805-

808.

244

Braithwaite, A.W., Royds, J.A. and Jackson, P. (2005) The p53 story: layers of complexity.

Carcinogenesis, 26(7): 1161-1169.

Braun, B.S. and Shannon, K. (2008) Targeting Ras in myeloid leukemias. Clin CancerRes.,

14(8): 2249-2252.

Brezden-Masley, C., & Polenz, C. (2013). Current Practices and Challenges of Adjuvant

Chemotherapy in Patients with Colorectal Cancer. Surgical oncology clinics of North America,

23(1), 49-58.

Buckhaults, P., Rago, C., St. Croix, B., et al. (2001) Secreted and cell surface genes expressed in

benign and malignant colorectal tumors. Cancer Research, 61: 6996-7001.

Burgess, A.W. (1998) Growth control mechanisms in normal and transformed intestinal cells.

Philos Trans R Soc Lond B Biol Sci., 353(1370): 903-909.

Bustin, S.A., Li, S.R., Phillips, S. and Dorudi, S. (2001) Expression of HLA class II in

colorectal cancers: evidence for enhanced immunogenicity of microsatellite-instability positive

tumours. Tumour Biol., 22(5): 294-298.

Caligiuri, M.A. (2008) Human natural killer cells. Blood, 112(3): 461-469.

Callahan, C.A., Ofstad, T., Horng, L., et al. (2004) IM/BEG4, a Sonic hedgehog-responsive

gene that potentiates Gli-dependent transcription. Genes & developmemt, 18: 2724-2729.

Cerni, C., Bousset, K., Seelos, C., et al. (1995) Differential effects by Mad and Max on

transformation by cellular and viral oncoproteins. Oncogene, 11(3): 587-596.

Chai, S. M., Zeps N., et al. (2004). Screening for defective DNA mismatch repair in stage II and

III colorectal cancer patients. Clin Gastroenterol Hepatol 2(11): 1017-1025.

245

Cheng, G.Z., Zhang, W. and Wang, L-H. (2008) Regulation of cancer cell survival, migration,

and invasion by Twist: AKT2 comes to interplay. Cancer Research, 68: 957-960.

Cho, K.R. and Vogelstein, B. (1992) Genetic alterations in the adenoma-carcinoma sequence.

Cancer, 70(6 Suppl): 1727-1731.

Choudhury, K. R., Yagle K. J., et al. (2010). A robust automated measure of average antibody

staining in immunohistochemistry images. J Histochem Cytochem 58(2): 95-107.

Chung-Faye, G.A. and Kerr, D.J. (2000) Innovative treatment for colon cancer. BMJ., 321: 1397-

1399. Clark, A.J., Barnetson, R., Farrington, S.M. and Dunlop, M.G. (2004) Prognosis in DNA

mismatch repair deficient colorectal cancer: are all MSI tumours equivalent? Fam Cancer., 3(2):

85-91.

Christodoulidis G, Spyridakis M, Symeonidis D, et al. Clinicopathological differences between

right- and left-sided colonic tumors and impact upon survival. Techniques in coloproctology.

2010;14 Suppl 1:S45-7. Epub 2010/08/12.

Clines, G.A. and Guise, T.A. (2008) Molecular mechanisms and treatment of bone metastasis.

Expert Rev Mol Med., 10: e7.

Coates, P.J., Lorimore, S.A. and Wright, E.G. (2005) Cell and tissue responses to genotoxic

stress. J Pathol., 205(2): 221-235.

Compton, C.C. (2003) Colorectal carcinoma: Diagnostic, prognostic, and molecular features.

Mod Pathol., 16(4): 376-388.

Compton, C.C. (2007) Optimal pathological staging: Defining stage II disease. Clin Cancer Res.,

13(22 Suppl.): 6862s-6870s.

246

Cong, Y. and Shay, J.W. (2008) Actions of human telomerase beyond telomeres. Cell Res.,

18(7): 725-732.Cordon-Cardo, C. (1995) Mutation of cell cycle regulators: Biological and

clinical implications for human neoplasia. American Journal of Pathology, 147(3): 545-560.

Cotran, R.S., Kumar, V., Abbas, A., et al. Neoplasia: (In) Robbins: Pathologic basis of disease,

eighth edition. Cotran, R.S., Kumar, V. and Collins, T. (Eds.). W.B. Saunders Elsevier

Company, Pennsylvania, 2010.

Cotran, R.S., Kumar, V., Abbas, A., et al. The gastrointestinal tract: (In) Robbins: Pathologic

basis of disease, eighth edition. Cotran, R.S., Kumar, V. and Collins, T. (Eds.). W.B. Saunders

Elsevier Company, Pennsylvania, 2010.

Crockett DK, Lin Z, Vaughn CP, et al (2005) Identification of proteins from formalin-fixed

paraffin-embedded cells by LC-MS/MS. Lab Invest 85(11):1405-1415.

Cronin M, Pho M, Dutta D, et al. (2004). Measurement of gene expression in archival paraffin-

embedded tissues: development and performance of a 92-gene reverse transcriptase-polymerase

chain reaction assay. Am J Pathol. ;164(1):35-42.

Crowe, P.J., Yang, J.L., Berney, C.R., et al. (2001) Genetic markers of survival and liver

recurrence after resection of liver metastases from colorectal cancer. World J Surg., 25(8): 996-

1001.

Cunningham, C. and Dunlop, M.G. (1996) Molecular genetic basis of colorectal cancer

susceptibility. British Journal of Surgery, 83: 321-329.

Davidson, N.O. (2007) Genetic testing in colorectal cancer: who, when, how and why.

Keio J Med., 56(1): 14-20.

Davidson, G., S. Murphy, et al. (2012). Frequency of mutations in the genes associated with

hereditary sensory and autonomic neuropathy in a UK cohort. J Neurol 259(8): 1673-1685.

247

Davis, F.A. Taber’s cyclopedic medical dictionary, 19th edition. Venes, D. (Ed.). F.A. Davis

Company, Philadelphia, 2001.

De Falco, G., Leucci, E., Lenze, D., et al. (2007) Gene-expression analysis identifies novel

RBL2/p130 target genes in endemic Burkitt lymphoma cell lines and primary tumours. Blood,

110(4): 1301-1307.

De la Chapelle, A. and Peltomäki, P. (1998) The genetics of hereditary common cancers.

Current Opinion in Genetics & Development, 8: 298-303.

De Leon, M.P. and Roncucci, L. (2000) The cause of colorectal cancer. Digestive and Liver

Disease, 32(5): 426-439.

Deming, P.B. and Rathmell, J.C. (2006) Mitochondria, cell death, and B cell tolerance. Curr Dir

Autoimmun., 9: 95-119.

Descriptive Epidemiology Group, Biostatistics and Epidemiology Cluster. Globocan 2000

Database: Cancer Mondial, International Agency for Research on Cancer (15th

February, 2003).

http://www.dep.iarc.fr.

Descriptive Epidemiology Group, Biostatistics and Epidemiology Cluster. Globocan 2002

Database: Cancer Mondial, International Agency for Research on Cancer (21st June, 2005).

http://www.dep.iarc.fr.

Dillon, D.A., Howe, C.L., Bosari, S. and Costa, J. (1998) The molecular biology of breast

cancer: accelerating clinical applications. Crit Rev Oncog., 9(2): 125-140.

Dorak MT. Real-time PCR. New York: Taylor & Francis; 2006. xxvi, 333 p., 2 p.

http://www.dep.iarc.fr/

248

Duffy, M.J., McGowan, P.M. and Gallagher, W.M. (2008) Cancer invasion and metastasis:

changing views. J Pathol., 214(3): 283-293.

Durai, R., Yang, S.Y., Seifalian, A.M. and Winslet, M.C. (2008) Principles and applications of

gene therapy in colon cancer. J Gastrointestin Liver Dis., 1: 59-67.

Early, D.S., Fontana, L. and Davidson, N.O. (2008) Translational approaches to addressing

complex genetic pathways in colorectal cancer. Trans Res., 151(1): 10-16.

Egeblad, M. and Werb, Z. (2002) New functions for the matrix metalloproteinases in cancer

progression. Nature Reviews, 2: 161-174.

Elsaleh H, Joseph D, Grieu F, et al.. Association of tumour site and sex with survival benefit

from adjuvant chemotherapy in colorectal cancer. Lancet. 000;355(9217):1745-50..

Emanuel, P.D. (2008) RAS pathway mutations in juvenile myelomonocytic leukemia. Acta

Haematol., 119(4): 207-211

Ember, I., Raposa, T., Varga, et al. (1995) Carcinogenic effects of cytostatic protocols in

CBA/Ca mice. In Vivo, 9(1): 65-69.

Eng, C. and Ponder, B.A.J. (1993) The role of gene mutations in the genesis of familial cancers.

FASEBJ, 7: 910-919.

Fawole, A.S., Simpson, D.J., Rajagopal, R et al. (2002) Loss of heterozygosity on chromosome

10q is associated with earlier onset sporadic colorectal adenocarcinoma. Int J Cancer., 99:30-36

Fearon, E.R. and Vogelstein, B. (1990) A genetic model for colorectal tumorigenesis. Cell, 61:

759-767.

249

Felmlee, T.A., Liu, Q., Whelen, A.C., et al. (1995) Genotypic detection of Mycobacterium

tuberculosis rifampin resistance: Comparison of single-strand conformation polymorphism and

dideoxy fingerprinting. Journal of Clinical Microbiology, 33(6): 1617-1623.

Felton, K.E., Gilchrist, D.M. and Andrew, S.E. (2007) Constitutive deficiency in DNA mismatch

repair. Clin Genet., 71(6): 483-498.

Fenoglio-Preiser, C. M. (2008). Gastrointestinal pathology : an atlas and text. Philadelphia,

Wolters Kluwer/Lippincott Williams & Wilkins., 76-160

Ferlay J, Shin HR, Bray F, Forman D, Mathers C, Parkin DM. (2010) Estimates of worldwide

burden of cancer in 2008: Int J Cancer: 21-34

Ferreira, A.C., Isomoto, H., Moriyama, M., et al. (2008) Helicobacter, 13 Suppl 1: 28-34.

Fletcher, J.I. and Huang, D.C. (2008) Controlling the cell death mediators Bax and Bak: puzzles

and conundrums. Cell Cycle, 7(1): 39-44.

Fogh, J., Fogh, J.M. and Orfeo, T. (1977) One hundred and twenty-seven cultured human tumor

cell lines producing tumors in nude mice. J Natl Cancer Inst., 59(1): 221- 226.

Forster, S. J., Talbot, I. C. et al. (1984). Laminin and fibronectin in rectal adenocarcinoma:

relationship to tumour grade, stage and metastasis. Br J Cancer 50(1): 51-61.

Fournier, H.N., Albigès-Rizo, C. and Block, M.R. New insights into Nm23 control of cell

adhesion and migration. J Bioenerg Biomembr., 35(1): 81-87.

Friedl, P. and Wolf, K. (2003) Tumour-cell invasion and migration: Diversity and escape

mechanisms. Nature Reviews, 3: 362-374.

250

GeneCards. GeneCard for gene MTSS1 GC08M125632: Weizmann Institute of Science and

Xennex (9th February, 2005). http://bioinfo.weizmann.ac.il/cards-bin/carddisp

Genetics Home Reference - National Institute of Health – United States National Library of

Medicine – (April 11 2010). http://ghr.nlm.nih.gov/

Genomatix. MatInspector Release Professional 7.5 Database: Genomatix Software GmbH (11th

April, 2005). http://www.genomatix.de.

Gilbert MT., Haselkorn T., Bunce M., et al. (2007) The isolation of nucleic acids from fixed,

paraffin-embedded tissues-which methods are useful when? PLoS One 2: e537.

Giráldez, M.D., Castellví-Bel, S., Balaguer, F et al. (2008) Lynch syndrome in colorectal cancer

patients. Expert Rev Anticancer Ther.,8(4): 573-583.

Goldstein NS. (2001) Recent pathology related advances in colorectal adenocarcinomas. Eur J

Surg Oncol. ;27(5):446-50

Gonos, E.S. and Spandidos, D.A. (1993) Oncogenes in cellular immortalisation and

differentiation . Anticancer Res., 13(4): 1117-1122.

Gonzalez-Quevedo, R., Shoffer, M., Horng, L. and Oro, A.E. (2005) Receptor tyrosine

phosphatase-dependent cytoskeletal remodeling by the hedgehog-responsive gene MIM/BEG4.

The Journal of Cell Biology, 168(3): 453-463.

Gorzelniak, K., J. Janke, et al. (2001). Validation of endogenous controls for gene expression

studies in human adipocytes and pre-adipocytes. Horm Metab Res 33(10): 625-627.

Greaves, M., & Maley, C. C. (2012). Clonal evolution in cancer. Nature, 481(7381), 306-313.

http://bioinfo.weizmann.ac.il/cards-bin/carddisp

http://www.genomatix.de/

251

Greene F. AJCC cancer staging manual. American Joint Committee on Cancer ACS, editor.

New York: Springer-Verlag; 2002.

Greenlee, R.T., Hill-Harmon, M.B., Murray, T. and Thun, M. (2001) Cancer statistics, 2001. CA

Cancer J Clin., 51: 15-36.

Grewal, J., Grewal, H.K. and Forman, A.D. (2008) Seizures and epilepsy in cancer: etiologies,

evaluation, and management. Curr Oncol Rep., 10(1): 63-71.

Grønbaek, K., Hother, C. and Jones, P.A. (2007) Epigenetic changes in cancer. APMIS, 115(10):

1039-1059.

Guillem, J.G., Puig-La Calle, J. Jn., Cellini, C., et al. (1999) Varying features of early age-of-

onset “sporadic” and hereditary nonpolyposis colorectal cancer patients. Dis Colon Rectum., 42:

36-42.

Gul, O., Basaga, H. and Kutuk, O. (2008) Apoptotic blocks and chemotherapy resistance:

strategies to identify Bcl-2 protein signatures. Brief Funct Genomic Proteomic., 7(1): 27-34.

Guldberg, P., thor Straten, P., Birck, A., et al. (1997) Disruption of the MMAC1/PTEN gene by

deletion or mutation is a frequent event in malignant melanoma. Cancer Res., 57(17): 3660-

3663.

Gulmann, C. B. and R. Cummins (2012). Antibody based protein research in human pathology.

Biotechnology 12(1): 1-17.

Gupta, K., Anand, G., Yin, X., et al. (1998) Mmip1: a novel leucine zipper protein that reverses

the suppressive effects of Mad family members on c-myc. Oncogene, 16: 1149-1159.

252

Habuchi, T., Luscombe, M., Elder, P.A. and Knowles, M.A. (1998) Structure and methylation-

based silencing of a gene (DBCCR1) within a candidate tumor suppressor region at 9q32-q33.

Genomics, 48: 277-288.

Hackford, A.W. (1993) Biochemical markers for colorectal cancer: Diagnostic and therapeutic

implications. Surgical Clinics of North America, 73(1): 85-102.

Hahn, W.C. and Weinberg, R.A. (2002) Modelling the molecular circuitry of cancer. Nature

Reviews, 2: 331-341.

Haier, J., Nasralla, M. and Nicolson, G.L. (2000) Cell surface molecules and their prognostic

values in assessing colorectal carcinomas. Annals of Surgery, 231(1): 11-24.

Halford, S., Sasieni, P., Rowan, A., et al. (2002) Low-level microsatellite instability occurs in

most colorectal cancers and is a nonrandomly distributed quantitative trait. Cancer Research,62:

53-57.

Hamilton, S. R. (2008). Targeted therapy of cancer: new roles for pathologists in colorectal

cancer.Mod Pathol 21 Suppl 2: S23-30.

Hanahan D, Weinberg RA. The hallmarks of cancer. Cell, 100: 57-70, 2000.

Harley, C.B. (2008) Telomerase and cancer therapeutics. Nat Rev Cancer., 8(3): 167-179.

Harvey, N.T. and Ruszkiewicz, A. (2007) Serrated neoplasia of the colorectum. World J

Gastroenterol., 13(28): 3792-3798.

Hassig, C.A., Fleischer, T.C., Billin, A.N., et al. (1997) Histone deacetylase activity is required

for full transcriptional repression by mSin3A.

Cell, 89: 341-347.

253

Heavey, P.M., McKenna, D. and Rowland, I.R. (2004) Colorectal cancer and the relationship

between genes and the environment. Nutr Cancer., 48(2): 124-141.

Hedley, B.D., Allan, A.L. and Chambers, A.F. (2006) Tumor dormancy and the role of

metastasis suppressor genes in regulating ectopic growth. Future Oncol., 2(5): 627-641.

Heid CA, Stevens J, Livak KJ and Williams PM. Real time quantitative PCR. Genome research.

1996;6(10):986-94.

Hermsen,M., Postma,C., Baak,J. et al. (2002) Colorectal adenoma to carcinoma progression

follows multiple pathways of chromosomal instability. Gastroenterology,123, 1109–1119.

Hibi, K., Nakamura, H., Hirai, A., et al. (1996) Loss of H19 Imprinting in Esophageal Cancer.

Cancer Research 56, 480-482

Hibi, K., Rahj Robinson, C., Booker, S., et al. (1998) Molecular detection of genetic alterations

in the serum of colorectal cancer patients. Cancer Research, 58: 1405-1407.

Hisamuddin, I.M. and Yang, V.W. (2004) Genetics of colorectal cancer. MedscapeGeneral

Medicine, 6(3): 13.

Hobbs, F.D.R. (2000) ABC of colorectal cancer: The role of primary care. BMJ, 321:

1068-1070.

Hoffman, B., Amanullah, A., Shafarenko, M. and Liebermann, D.A. (2002) The protooncogene

c-myc in hematopoietic development and leukemogenesis. Oncogene, 21: 3414-3421.

Houbiers, J.G.A., Van der Burg, S.H., Van de Watering, L.M.G., et al. (1995) Antibodies

against p53 are associated with poor prognosis of colorectal cancer. Brit J Cancer, 72: 637- 641.

254

Humphries, M. J., M. Obara, et al. (1989). Role of fibronectin in adhesion, migration, and

metastasis. Cancer Invest 7(4): 373-393.

Hundt, S., Haug, U. and Brenner, H. (2007) Blood markers for early detection of colorectal

cancer: A systematic review. Cancer Epidemiol Biomarkers Prev., 16(10):

1935-1953.

Hunt, G. (1989). The role of laminin in cancer invasion and metastasis. Exp Cell Biol 57(3):

165-176.

Huret Jean-Loup - http://atlasgeneticsoncology.org/ - Atlas of Genetics and Cytogenetics in

Oncology and Haematology.

Hurst, D. R., & Welch, D. R. (2011). Metastasis suppressor genes: at the interface between the

environment and tumor cell growth. International review of cell and molecular biology, 286,

107.

Ilyas, M. and Tomlinson, I.P. (1996) Genetic pathways in colorectal cancer. Histopathology,

28(5): 389-399.

Iacopetta B. Are there two sides to colorectal cancer? (2002). Int. J. of Cancer ;101(5):403-8.

Irigaray, P., Newby, J.A., Clapp, R., et al. (2007) Lifestyle-related factors and environmental

agents causing cancer: an overview. Biomed Pharmacother., 61(10): 640-658.

Ito H, Kaneko K, Makino R, et al. (2007) Interleukin-1beta gene in esophageal, gastric and

colorectal carcinomas. Oncol Rep. 2007 Aug;18(2):473-81.

Janakiram, N.B. and Rao, C.V. (2008) Molecular markers and targets for colorectal cancer

prevention. Acta Pharmacol Sin., 29(1): 1-20.

255

Jänne, P.A. and Mayer, R.J. (2000) Chemoprevention of colorectal cancer. The New England

Journal of Medicine, 342(26): 1960-1968.

Janz, S. (2006) Myc translocations in B cell and plasma cell neoplasms. DNA Repair (Amst).,

5(9-10): 1213-1224.

Jascur, T. and Boland, C.R. (2006) Structure and function of the components of the human DNA

mismatch repair system. Int J Cancer., 119(9): 2030-2035.

Jass, J.R., Young, J. and Leggett, B.A. (2000) Hyperplastic polyps and DNA microsatellite

unstable cancers of the colorectum. Histopathology, 37(4): 295-301.

Jemal, A., Thomas, A., Murray, T. and Thun, M. (2002) Cancer statistics, 2002. CA

Cancer J Clin., 52: 23-47.

Jass, J. R. (2007). Classification of colorectal cancer based on correlation of clinical,

morphological and molecular features. Histopathology 50(1): 113-130.

Jemal, A., Murray, T., Samuels, A., Ghafoor, A., Ward, E. and Thun, M.J. (2003) Cancer

statistics, 2003. CA Cancer J Clin., 53: 5-26.

Jemal, A., Tiwari, R.C., Murray, T et al. (2004) Cancer statistics, 2004. CA Cancer J Clin.,

54(1): 8-29.

Jemal, A., Siegel, R., Ward, E., et al. (2008) Cancer statistics, 2008. CA Cancer J Clin., 58(2):

71-96.

Jemal, A., Bray, F., Center, M et al. (2011) Global cancer statistics. CA Cancer J Clin. :69-90

Jiang, W.G., Puntis, M.C.A. and Hallett, M.B. (1994) Molecular and cellular basis of

256

cancer invasion and metastasis: implications for treatment. British Journal of Surgery,

81: 1576-1590.

Jiang, X. N., Zhou R. L., et al. (1998). Effects of laminin glycopeptides on metastasis-related

behaviors of cancer cells. Cell Res 8(3): 231-240.

Jo, W-S. and Chung, D.C. (2005) Genetics of hereditary colorectal cancer. Seminars in

Oncology, 32: 11-23.

Johnen, H., Lin, S., Kuffner, T., et al..(2007) Tumor-induced anorexia and weight loss are

mediated by the TGF-beta superfamily cytokine MIC-1. Nature Medicine, 13(11): 1333-1340.

Kahnoski, K., Khoo, S.K., Nassif, N.T., et al. (2003) Alterations of the Birt-Hogg-Dubé gene

(BDH) in sporadic colorectal tumours. JMed Genet., 40: 511-515.

Kanda, S., Mivata, Y., Kanetake, H. and Smithgall, T.E. (2007) Non-receptor proteintyrosine

kinases as molecular targets for antiangiogenic therapy (Review). Int J Mol Med., 20(1): 113-

121.

Kapiteijn, E., Liefers G. J., et al. (2001). Mechanisms of oncogenesis in colon versus rectal

cancer. J Pathol 195(2): 171-178.

Kim, H-J., Yu, M-H., Kim, H., et al. (2008) Non-invasive molecular biomarkers for the detection

of colorectal cancer. BMB Reports., 41(10): 685-692.

Klagsbrun, M. (1989) The fibroblast growth factor family: structural and biological properties.

Prog Growth Factor Res., 1(4): 207-235.

Kobayashi, N. (2008) Artificial cells for the development of cell therapy. Cell Transplant., 17(1-

2): 3-9.

257

Kong, M., Kim, Y. et al. (2011). A strong synergistic epistasis between FAM134B and

NFRSF19 on the susceptibility to vascular dementia. Psychiatr Genet 21(1): 37-41.

Kopnin, B.P. (2000) Targets of oncogenes and tumor suppressors: key for understanding basic

mechanisms of carcinogenesis. Biochemistry (Mosc)., 65(1): 2-27.

Kosmider, S. and Lipton, L. (2007) Adjuvant therapies for colorectal cancer. World J

Gastroenterol., 13(28): 3799-3805.

Kuribayashi, K. and El-Deiry, W.S. (2008) Regulation of programmed cell death by thep53

pathway. Adv Exp Med Biol., 615: 201-221.

Kurien, B. T., Dorri, Y.et al. (2011). An overview of Western blotting for determining antibody

specificities for immunohistochemistry. Methods Mol Biol 717: 55-67.

Kurth, I. (2011). Hereditary Sensory and Autonomic Neuropathy Type II. Gene Reviews. R. A.

Pagon, T. D. Bird, C. R. Dolan, K. Stephens and M. P. Adam (Ed). Seattle (WA).

Kurth, I., Pamminger T., Hennings, J. et al. (2009). Mutations in FAM134B, encoding a newly

identified Golgi protein, cause severe sensory and autonomic neuropathy. Nat Genet 41(11):

1179-81.

Kwong D, Lam A, Guan X, Law S, Tai A, Wong J, et al. Chromosomal aberrations in

esophageal squamous cell carcinoma among Chinese: gain of 12p predicts poor prognosis after

surgery. Hum Pathol. 2004;35(3):309-16.

Lahtz, C., & Pfeifer, G. P. (2011). Epigenetic changes of DNA repair genes in cancer. Journal of

molecular cell biology, 3(1), 51-58.

Lam A.K. and Ho YH. Primary squamous cell carcinoma of the rectum in a patient on

immunosuppressive therapy. Pathology. 2006;38:74-6

258

Lam AK, Ong K, Ho YH. Aurora kinase expression in colorectal adenocarcinoma: correlations

with clinicopathological features, p16 expression, and telomerase activity. Hum Pathol.

2008;39:599-604.

Lam AK, Ong K, Giv MJ and Ho YH. p16 expression in colorectal adenocarcinoma: marker of

aggressiveness and morphological types. Pathology. 2008;40(6):580-5.

Lam, A. K., Gopalan V., et al. (2011). Altered JS-2 expression in colorectal cancers and its

clinical pathological relevance. Mol Oncol 5(5): 475-481.

Lam AK., Ong K. and Ho YH. Colorectal mucinous adenocarcinoma: the clinicopathologic

features and significance of p16 and p53 Expression. Dis Colon Rectum. 2006;49:175-1283.

Lam AK., Ong K. and Ho YH. hTERT expression in colorectal adenocarcinoma: correlations

with p21, p53 expressions and clinicopathological features. Int J Colorectal Dis. 2008;23:587-

94.

Lamberts, R. (1994). Hormone dependence of colorectal carcinomas. Z Gastroenterol 32(10):

592-596.

Lambert, R., Sauvaget, C., & Sankaranarayanan, R. (2009). Mass screening for colorectal cancer

is not justified in most developing countries. International Journal of Cancer, 125(2), 253-256.

Law FB, Chen YW, Wong KY, et al. Identification of a novel tumor transforming gene GAEC1

at 7q22 which encodes a nuclear protein and is frequently amplified and overexpressed in

esophageal squamous cell carcinoma. Oncogene. 2007;26:5877-88.

259

Lanfrancone, L., Pelicci, G. and Pelicci, P.G. (1994) Cancer genetics. Curr Opin GenetDev.,

4(1): 109-119.

Lawrance, I.C., Fiocchi, C. and Chakravarti, S. (2001) Ulcerative colitis and Crohn’s disease:

distinctive gene expression profiles and novel susceptibility candidate genes. Human Molecular

Genetics, 10(5): 445-456.

Lee, S.H., Kerff, F., Chereau, D et al.. (2007) Structural basis for the actin-binding function of

missing-in-metastasis. Structure, 15(2):145-155.

Lee, S., Neumann, M. et al. (1999). Transcription-dependent nuclear-cytoplasmic trafficking is

required for the function of the von Hippel-Lindau tumor suppressor protein. Mol Cell Biol

19(2): 1486-1497.

Leiderman, Y.I., Kiss, S. and Mukai, S. (2007) Molecular genetics of RB1 – the retinoblastoma

gene. Semin Ophthalmol., 22(4): 247-254.

Lemmens V. (2013) The Epidemiology of Colorectal Cancer in Older Patients (book chapter).

Management of Colorectal Cancers in Older People, pp 1-7

Leopoldo, S., B. Lorena, et al. (2008). Two subtypes of mucinous adenocarcinoma of the

colorectum: clinicopathological and genetic features. Ann Surg Oncol 15(5): 1429-1439.

Levine, A. J., & Puzio-Kuter, A. M. (2010). The control of the metabolic switch in cancers by

oncogenes and tumor suppressor genes. Science, 330(6009), 1340-1344.

Lieberman, H.B. (2008) DNA damage repair and response proteins as targets for cancer therapy.

Curr Med Chem., 15(4): 360-367.

Lin, J., Liu, J., Wang, Y et al. (2005) Differential regulation of contraction and N-WASP-

mediated actin polymerization by missing in metastasis (MIM) protein. Oncogene: 1-8.

http://link.springer.com/search?facet-author=%22Valery+E.+P.+P.+Lemmens+Ph.D.%22

http://link.springer.com/book/10.1007/978-0-85729-984-0

260

Lindsermo, R-O., Joh, Y-G. and Delaney, C.P. (2008) Surgical treatment for rectal cancer: An

international perspective on what the medical gastroenterologist needs to know. World J

Gastroenterol., 14(21): 3281-3289.

Lingappa, V.R. Gastrointestinal disease: 215-244. (In) Pathophysiology of disease. An

introduction to clinical medicine, first edition. McPhee, S.J., Lingappa, V.R., Ganong,

W.F. and Lang, J.D. (Eds.). Appleton & Lange, Connecticut, 1995.

Liotta, L. A., K. Tryggvason, et al. (1980). Metastatic potential correlates with enzymatic

degradation of basement membrane collagen. Nature 284(5751): 67-68.

Liotta, L.A. and Paweletz, C.P. Invasion and metastasis: 225-234. (In) The cancer handbook.

Alison, M.R. (Ed.). Nature Publishing Group, London, 2002.

Liu, H., Adler, A.S., Segal, E. and Chang, H.Y. (2007) A transcriptional program mediating

entry into cellular quiescence. PloS Genetics, 3(6, e91): 1-13.

Liu, Q. and Sommer, S.S. (1994) Parameters affecting the sensitivities of dideoxy fingerprinting

and SSCP. PCR Methods & Applications, 4(2): 97-108.

Livak, K. J. and Schmittgen T. D. (2001). Analysis of relative gene expression data using real-

time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 25(4): 402-408.

Lombardi, D., Lacombe, M.L. and Paggi, M.G. (2000) Nm23: Unraveling its biological function

in cell differentiation. J Cell Physiol., 182(2): 144-149.

Lundberg, A.S. and Weinberg, R.A. (1999) Control of the cell cycle and apoptosis. European

Journal of Cancer, 35(4): 531-539.

261

Lynch, H.T., Silva, E., Snyder, C. and Lynch, J.F. (2008) Hereditary breast cancer: part I.

Diagnosing hereditary breast cancer syndromes. Breast J., 14(1): 3-13.

Ma, S., Guan, X.Y., Lee, T.K. and Chan, K.W. (2007) Clinicopathological significance of

missing in metastasis B expression in hepatocellular carcinoma. Hum Pathol., 38(8): 1201-1206.

Macleod, K.F. and Jacks, T. (1999) Insights into cancer from transgenic mouse models. J

Pathol., 187(1): 43-60.

Maehara, Y., Saeki, H. et al. (2010). Molecular mechanisms of esophageal squamous cell

carcinogenesis: clues to improve treatment outcomes. Ann Thorac Cardiovasc Surg 16(6): 387-

388.

Malumbres, M. and Barbacid, M. (2001) To cycle or not to cycle: A critical decision in cancer.

Nature Reviews, 1: 222-231.

Mantovani, A., Romero, P., Palucka, A.K. and Marincola, F.M. (2008) Tumour immunity:

effector response to tumour and role of the microenvironment. Lancet, 371(9614): 771-783.

Maradiegue, A., Jasperson, K., Edwards, Q.T., et al. (2008) Scoping the family history:

assessment of Lynch syndrome (hereditary nonpolyposis colorectal cancer) in primary care

settings – a primer for nurse practitioners. J Am AcadNurse Pract., 20(2): 76-84.

Mareel, M. and Leroy, A. (2003) Clinical, cellular, and molecular aspects of cancer invasion.

Physiol Rev., 83: 337-376.

Martignoni, M.E., Kunze, P. and Friess, H. (2003) Cancer cachexia. Molecular Cancer, 2: 36.

Masterson, J. and O’Dea, S. (2007) Posttranslational truncation of E-cadherin and significance

for tumour progression. Cells Tissues Organs, 185(1-3): 175-179.

262

Mathers, C.D., Boschi-Pinto, C., Lopez, A.D. and Murray, C.J.L. (2001) Cancer incidence,

mortality and survival by site for 14 regions of the world. World Health Organisation, global

programme on evidence for health policy discussion paper no. 13:1-47.

http://whqlibdoc.who.int/hq/2001/a78632.pdf.

Matsuo, K., Hamajima, N. et al. (2002). Methionine Synthase Reductase Gene A66G

Polymorphism is Associated with Risk of Colorectal Cancer. Asian Pac J Cancer Prev 3(4):

353-359.

Mazzolini, G., Murillo, O., Atorrasagasti, C. et al. (2007) Immunotherapy and immunoescape in

colorectal cancer. World J Gastroenterol., 13(44): 5822-5831.

Medicines Australia. Clinical Trials (2008). http://www.medicinesaustralia.com.au/

pages/page39.asp

Melvold, R.W. and Sticca, R.P. (2007) Basic and tumor immunology: a review. Surg Oncol Clin

N Am., 16(4): 711-735.

Meulmeester, E. and Jochemsen, A.G. (2008) p53: a guide to apoptosis. Curr Cancer Drug

Targets, 8(2): 87-97.

Michor, F., Iwasa, Y. and Nowak, M.A. (2004) Dynamics of cancer progression. Nature

reviews, 4: 197-205.

Midgley, R. and Kerr, D. (1999) Colorectal cancer. The Lancet, 353: 391-399.

Midgley, R.S.J. and Kerr, D.J. (2000) Adjuvant therapy. BMJ., 321: 1208-1211.

Milde-Langosch, K. (2005) The Fos family of transcription factors and their role in

tumourigenesis. Eur J Cancer., 41(16): 2449-2461.

http://whqlibdoc.who.int/hq/2001/a78632.pdf

http://www.medicinesaustralia.com.au/

263

Millard, T.H., Sharp, S.J. and Machesky, L.M. (2004) Signalling to actin assembly via

the WASP (Wiskott-Aldrich syndrome protein)-family proteins and the Arp2/3 complex.

Biochem J., 380: 1-17.

Moasser, M.M. (2007) The oncogene HER2: its signaling and transforming functions

and its role in human cancer pathogenesis. Oncogene, 26(45): 6469-6487.

Mohammad, R., Giri, A. and Goustin, A.S. (2008) Small-molecule inhibitors of Bcl-2 family

proteins as therapeutic agents in cancer. Recent Patents Anticancer Drug Discov., 3(1): 20-30.

Mueller, J.D., Bethke, B. and Stolte, M. (2002) Colorectal de novo carcinoma: a review of its

diagnosis, histopathology, molecular biology, and clinical relevance. Virchows Arch., 440: 453-

460.

Murphy, S. M., Davidson, G. L. et al. (2012). Mutation in FAM134B causing severe hereditary

sensory neuropathy." J Neurol Neurosurg Psychiatry 83(1): 119-120.

Mwenifumbo, J. C. and Marra M. A. (2013). Cancer genome-sequencing study design. Nat Rev

Genet 14(5): 321-332.

Nagy, V.M. (2008) Updating the management of rectal cancer. J Gastrointestin Liver Dis.,

17(1): 69-74.

Nassif, N.T., Lobo, G.P., Wu, X., et al. (2004) PTEN mutations are common in sporadic

microsatellite stable colorectal cancer. Oncogene, 23: 617-628.

National Center for Biotechnology Information. http://www.ncbi.nlm.nih.gov/gene/54463.

Nicoletto, M.O., Donach, M., De Nicolo, A. et al.. (2001) BRCA-1 and BRCA-2 mutations as

prognostic factors in clinical practice and genetic counselling. Cancer Treat Rev., 27(5): 295-

304.

http://www.ncbi.nlm.nih.gov/gene/54463

264

Nowell, P.C. (1976) The clonal evolution of tumor cell populations. Science, 194(4260): 23-28.

Nowis, D., Makowski, M., Stokłosa, T., et al. (2005) Direct tumor damage mechanisms of

photodynamic therapy. Acta Biochimica Polonica, 52(2):339-352.

Ogino, S. and Goel A. (2008). Molecular classification and correlates in colorectal cancer. J Mol

Diagn 10(1): 13-27.

Oh, J-H., Ku, J-L., Yoon, K-A., et al (1999) Establishment and characterization of 12

human colorectal-carcinoma cell lines. Int J Cancer., 81: 902-910.

O’Hagan, R.C., Schreiber-Agus, N. et al. (2000) Gene-target recognition among members of the

Myc superfamily and implications for oncogenesis. Nature Genetics, 24: 113-119.

Ohnishi, T., Takahashi, A., Mori, E. and Ohnishi, K. (2008) p53 targeting can enhance cancer

therapy via radiation, heat and anti-cancer agents. Anticancer Agents Med Chem., 8(5): 564-570.

Okabe-Kado, J. and Kasukabe, T. (2003) Physiological and pathological relevance of

extracellular NM23/NDP kinases. J Bioenerg Biomembr., 35(1): 89-93.

Oliveira, A.M., Ross, J.S. and Fletcher, J.A. (2005) Tumor suppressor genes in breast cancer: the

gatekeepers and the caretakers. Am J Clin Pathol., 124 Suppl: S16-S28.

Oliveira, P.A., Colaco, A., Chaves, R., Guedes-Pinto, H., De-La-Cruz, P.L.F. and Lopes, C.

(2007) Chemical carcinogenesis. An Acad Bras Cienc., 79(4): 593-616.

Olschwang, S., Hamelin, R., Laurent-Puig, P., et al. (1997) Alternative genetic pathways in

colorectal carcinogenesis. Proc Natl Acad Sci., 94: 12122-12127.

265

Ostrand-Rosenberg, S. (2008) Immune surveillance: a balance between protumor and antitumor

immunity. Curr Opin Genet Dev., 18(1): 11-18.

Ou, J., Niessen, R.C., Lützen, A., et al. (2007) Functional analysis helps to clarify the clinical

importance of unclassified variants in DNA mismatch repair genes. Hum Mutat., 28(11): 1047-

1054.

Paggi, M.G., Baldi, A., Bonetto, F. and Giordano, A. (1996) Retinoblastoma protein family in

cell cycle and cancer: A review. Journal of Cellular Biochemistry, 62: 418- 430.

Palmieri, D., Horak, C.E., Lee, J.H., et al. (2006) Translational approaches using metastasis

suppressor genes. J Bioenerg Biomembr., 38(3-4): 151-161.

Pantel, K. and Brakenhoff, R.H. (2004) Dissecting the metastatic cascade. Nature Reviews, 4:

448-456.

Papazahariadou, M., Athanasiadis, G.I., Papadopoulos, E., et al. (2007) Involvement of NK cells

against tumors and parasites. Int J Biol Markers., 22(2): 144-153.

Pardee, A. B. (1989). G1 events and regulation of cell proliferation. Science 246(4930): 603-608.

Park, S. Y., H. S. Lee, et al. (2006). Clinicopathological characteristics, microsatellite

instability, and expression of mucin core proteins and p53 in colorectal mucinous

adenocarcinomas in relation to location. Virchows Arch 449(1): 40-47.

Parkin, D.M., Pisani, P. and Ferlay, J. (1999) Global cancer statistics. CA Cancer J Clin., 49: 33-

64.

Parkin, D.M., Bray, F., Ferlay, J. and Pisani, P. (2005) Global cancer statistics, 2002. CA Cancer

J Clin., 55: 74-108.

266

Patwardhan, M.B., Samsa, G.P., McCrory, D.C., et al. (2006) Cancer care quality measures:

Diagnosis and treatment of colorectal cancer. Evidence Report/Technology Assessment, 138: 1-

336.

Paunola, E., Mattila, P.K. and Lappalainen, P. (2002) WH2 domain: a small, versatile adapter for

actin monomers. FEBS Letters, 513: 92-97.

Pavlovic-Calic, N., Muminhodzic, K., Zildzic, M., et al. (2007) Genetics, clinical manifestations

and management of FAP and HNPCC. Med Arh., 61(4): 256-259.

Pawlik TM, Raut CP, Rodriguez-Bigas MA. (2004) Colorectal carcinogenesis: MSI-H versus

MSI-L. Dis Markers.;20(4-5):199-206.

Paz-Elizur, T., Sevilya, Z., Leitner-Dagan, Y., et al. (2008) DNA repair of oxidative DNA

damage in human carcinogenesis: potential application for cancer risk assessment and

prevention. Cancer Lett., 266(1): 60-72.

Penland, S., Keku, T., Torrice, C. et al. (2007) RNA expression analysis of formalin-fixed

paraffin-embedded tumors. Lab Invest. 87-4

Perez-Cabornero, L., Infante, M. et al. (2013). Genotype-phenotype correlation in MMR

mutation-positive families with Lynch syndrome. Int J Colorectal Dis.132(3)

Petersen, S., Wolf, G., Bockmuhl, U., et al. (1998) Allelic loss on chromosome 10q in human

lung cancer: association with tumour progression and metastatic phenotype. Br J Cancer., 77(2):

270-276.

Pignataro, L., Sambataro, G., Pagani, D. and Pruneri, G. (2005) Clinico-prognostic value of D-

type cyclins and p27 in laryngeal cancer patients: a review. Acta Otorhinolaryngol Ital., 25(2):

75-85.

267

Pirone, J. R., D'Arcy,M. et al. (2012). Age-associated gene expression in normal breast tissue

mirrors qualitative age-at-incidence patterns for breast cancer. Cancer Epidemiol Biomarkers

Prev 21(10): 1735-1744.

Pollard, T.D., Blanchoin, L. and Mullins, R.D. (2000) Molecular mechanisms controlling actin

filament dynamics in nonmuscle cells. Annu Rev Biophys Biomol Struct., 29: 545-576.

Popescu, N.C. and Zimonjic, D.B. (2002) Chromosome-mediated alterations of the MYC gene in

human cancer. J Cell Mol Med., 6(2): 151-159.

Pough, F.H. Homeostasis and energetics: water balance, temperature regulation, and energy use:

123-159. (In) Vertebrate life, fourth edition. Pough, F.H., Heiser, J.B. and McFarland, W.N.

(Eds.). Prentice Hall, New Jersey, 1996.

Powell, I. J., Dyson G., et al. (2013). Genes associated with prostate cancer are differentially

expressed in African American and European American men. Cancer Epidemiol Biomarkers

Prev 22(5): 891-897.

Prestwich, G.D. (2008) Evaluating drug efficacy and toxicology in three dimensions: using

synthetic extracellular matrices in drug discovery. Acc Chem Res., 41(1): 139- 148.

Quirke, P. and Morris, E. (2007) Reporting colorectal cancer. Histopathology, 50: 103-112.

Raja, S., Finkelstein, S.D., Baksh, F.K., et al. (2001) Correlation between dysplasia and

mutations of six tumor suppressor genes in Barrett’s esophagus. Ann Thorac Surg., 72:1130-

1135.

Rao, U.N.M., Bakker, A., Swalsky, P.A. and Finkelstein, S.D. (1999) Max interacting protein 1:

Loss of heterozygosity is frequent in desmoplasmic melanoma. Mod Pathol., 12(4): 344-350.

268

Rekhadevi, P.V., Sailaja, N., Chandrasekhar, et al. (2007) Genotoxicity assessment in oncology

nurses handling anti-neoplastic drugs. Mutagenesis, 22(6): 395-401.

Renehan, A.G., Booth, C. and Potten, C.S. (2001) What is apoptosis, and why is it important?

BMJ., 322(7301): 1499-1500.

Ridley AJ, Schwartz MA, Burridge K, et al. (2003) Cell migration: integrating signals from front

to back. Science.;302(5651):1704-9.

Riley, T., Sontag, E., Chen, P. and Levine, A. (2008) Transcriptional control of human p53-

regulated genes. Nat Rev Mol Cell Biol., 9(5): 402-412.

Ritzenthaler, J. D., Han, S. et al. (2008). Stimulation of lung carcinoma cell growth by

fibronectin-integrin signalling. Mol Biosyst 4(12): 1160-1169.

Rizzardi, A. E., Johnson, A. T. et al. (2012). Quantitative comparison of immunohistochemical

staining measured by digital image analysis versus pathologist visual scoring. Diagn Pathol 7:

42.

Rose, M. Animal models: 65-82. (In) Animal welfare and our use of animals in science. An

introduction to the ethics and scientific issues. University of New South Wales & University of

Sydney, 2008.

Rottmann, S. and Lüscher, B. (2006) The Mad side of the Max network: antagonizing the

function of Myc and more. Curr Top Microbiol Immunol., 302: 63-122.

Roy, P.G. and Thompson, A.M. (2006) Cyclin D1 and breast cancer. Breast, 15(6): 718-727.

Rozen S. and Skaletsky H. J. (2000). Primer3 version 0.4.0 (http://frodo.wi.mit.edu/primer3/).

Whitehead Institute for Biomedical Research.


269

Ruo, L., Cellini, C., La-Calle, J.P. et al. (2001) Limitations of family cancer history assessment

at initial surgical consultation. Dis Colon Rectum., 44(1): 103-104.

Rustgi, A.K. (2007) The genetics of hereditary colon cancer. Genes & Development, 21:2525-

2538.

Sabeh, F., Shimizu-Hirota, A. T. et al. (2009). Protease-dependent versus -independent cancer

cell invasion programs: three-dimensional amoeboid movement revisited. J Cell Biol 185(1): 11-

19

Saikumar, P., Dong, Z., Mikhailov, V., et al. (1999) Apoptosis: Definition, mechanisms, and

relevance to disease. The American Journal of Medicine, 107: 489-506.

Saint, F., Le Frere Belda, M-A., Quintela, R., et al. (2007) Nras and Kras mutation in Japanese

lung cancer patients: Genotyping analysis using Right Cycler. Oncol Rep., 18(3): 623-628.

Saleh S, Lam AK, Ho YH. (2008) Real-time PCR quantification of human telomerase reverse

transcriptase (hTERT) in colorectal cancer. Pathology. ;40(1):25-30

Sato, Y., Sugie, R,.Tsuchiya, N. et al. (2004) Comparison of the DNA Extraction Methods for

Polymerase Chain Reaction Amplification from Formalin-Fixed and Paraffin-Embedded Tissues.

Histochem. and Cell Bio. 122:3; 211-218

Sayar, N. and Banerjee, S. Colon: Colorectal adenocarcinoma. Atlas Genet Cytogenet

Oncol Haematol. (May, 2007). http://AtlasGeneticsOncology.org/Genes/colon5006.html.

Scheijen, B. and Griffin, J.D. (2002) Tyrosine kinase oncogenes in normal hematopoiesis and

hematological disease. Oncogene, 21(21): 3314-3333.

Scholefield, J.H. (2000) ABC of colorectal cancer: Screening. BMJ, 321: 1004-1006.

http://link.springer.com/journal/418

270

Schuh, R., Kremmer, E. et al. (1992). Determination of monoclonal antibody specificity by

immunoadsorption and western blotting. J Immunol Methods 152(1): 59-67.

Schweiger M., Kerick, M., Timmermann, B., et al. (2009) Genome-Wide Massively Parallel

Sequencing of Formaldehyde Fixed-Paraffin Embedded (FFPE) Tumor Tissues for Copy-

Number- and Mutation-Analysis. PLoS One 4(5):e5548.

Scoumanne, A. and Chen, X. (2008) Protein methylation: a new mechanism of p53 tumor

suppressor regulation. Histol Histopathol., 23(9): 1143-1149.

Secco, G. B., Fardelli, R. et al. (1994). Primary mucinous adenocarcinomas and signet-ring cell

carcinomas of colon and rectum. Oncology 51(1): 30-34.

Seidal T, Balaton AJ, Battifora H. (2001) Interpretation and quantification of immunostains. Am

J Surg Pathol;25(9):1204-7.

Seiki, M. (2003). Membrane-type 1 matrix metalloproteinase: a key enzyme for tumor invasion.

Cancer Lett 194(1): 1-11.

Sessink, P.J. and Bos, R.P. (1999) Drugs hazardous to healthcare workers. Evaluation of

methods for monitoring occupational exposure to cytostatic drugs. Drug Saf., 20(4): 347-359.

Silver, N., Best, S., Jiang, J. and Thein, S.L. (2006) Selection of housekeeping genes for gene

expression studies in human reticulocytes using real-time PCR. BMC Mol Biol., 7:33.

Simpson, A.J. and Camargo, A.A. (1998) Evolution and the inevitability of human cancer. Semin

Cancer Biol., 8(6): 439-445.

Sjöström, J. and Bergh, J. (2001) How apoptosis is regulated, and what goes wrong in cancer.

BMJ., 322: 1538-1539.

271

Skotheim, R.I., Monni, O., Mousses, S., et al. (2002) New insights into testicular germ cell

tumorigenesis from gene expression profiling. Cancer Research, 62: 2359-2364.

Small, R., Lubezky, N. and Ben-Haim, M. (2007) Current controversies in the surgical

management of colorectal cancer metastasis to the liver. IMAJ., 9: 742-747.

Sobin, L.H. and Wittekind, Ch. Digestive system tumours, colon and rectum: 72-76.

(In) TNM classification of malignant tumours, sixth edition. Sobin, L.H. and Wittekind, Ch.

(Eds.). Wiley-Liss, New York, 2002.

Sobin, L.H. and Wittekind, Ch. Introduction. The history of the TNM system: 1-18. (In) TNM

classification of malignant tumours, sixth edition. Sobin, L.H. and Wittekind, Ch.(Eds.). Wiley-

Liss, New York, 2002.

Specht,K,, Richter,T., Müller,U ., et al. (2001) Quantitative gene expression analysis in

microdissected archival formalin-fixed and paraffin-embedded tumor tissue. Am J Pathol.

;158(2):419-29

Speleman, F., C. Kumps, et al. (2008). Copy number alterations and copy number variation in

cancer: close encounters of the bad kind. Cytogenet Genome Res 123(1-4): 176-182.

Stafford, L.J., Vaidya, K.S. and Welch, D.R. (2008) Metastasis suppressor genes in cancer. Int J

Biochem Cell Biol., 40(5): 874-891.

Stagg, J. and Smyth, M.J. (2007) NK cell-based cancer immunotherapy. Drug News Perspect.,

20(3): 155-163.

Steeg, P.S. (2003) Metastasis suppressors alter the signal transduction of cancer cells. Nature

Reviews, 3: 55-63.

272

Stetler-Stevenson, W. G., Aznavoorian, S., et al. (1993). Tumor cell interactions with the

extracellular matrix during invasion and metastasis. Annu Rev Cell Biol 9: 541-573.

Strate, L.L. and Syngal, S. (2005) Hereditary colorectal cancer syndromes. Cancer Causes and

Control, 16: 201-213.

Studzinski, G.P. (1989) Oncogenes, growth, and the cell cycle: an overview. Cell Tissue Kinet.,

22(6): 405-424.

Sun, A., Bagella, L., Tutton, S., et al. (2007) From G0 to S phase: a view of the roles played by

the retinoblastoma (Rb) family members in the Rb-E2F pathway. J Cell Biochem., 102(6): 1400-

1404.

Taipale, J. and Keski-Oja, J. (1997) Growth factors in the extracellular matrix. FASEB.,11: 51-

59.

Tamura, G. (2006) Alterations of tumor suppressor and tumor-related genes in the development

and progression of gastric cancer. World J Gastroenterol., 12(2): 192-198.

Tang, D.G. and Honn, K.V. (1995) Adhesion molecules and tumor metastasis: an update.

Invasion Metastasis, 14(1-6): 109-122.

Tang, W. K., Chui, C. H. et al. (2007). Oncogenic properties of a novel gene JK-1 located in

chromosome 5p and its overexpression in human esophageal squamous cell carcinoma. Int J

Mol Med 19(6): 915-23.

Tang W., David FB., Wilson MM., Barwick BG., et al. (2009) DNA extraction from formalin-

fixed, paraffin-embedded tissue. Cold Spring Harb Protoc. 2009 Feb;2009(2)

Timmerman, R.D., Bizekis, C.S., Pass, H.I., et al. (2009) Local surgical, ablative, and radiation

treatment of metastases. A Cancer Journal for Clinitians, 59: 145-170.

273

Tomkova, K., Tomka, M. and Zajac, V. (2008) Contribution of p53, p63, and p73 to the

developmental diseases and cancer. Neoplasma, 55(3): 177-181.

Tomlinson, I., Ilyas, M. and Novelli, M. (1997) Molecular genetics of colon cancer. Cancer and

Metastasis Reviews, 16: 67-79.

Tomlinson, I., Ilyas, M., Johnson, V., et al. (1998) A comparison of the genetic pathways

involved in the pathogenesis of three types of colorectal cancer. Journal of Pathology, 184: 148-

152.

Toro, J.R., Wei, M.H., Glenn, G.M., et al. (2008) BDH mutations, clinical and molecular

genetic investigations of Birt- Hogg-Dubé syndrome: a new series of 50 families and a review of

published reports. J Med Genet., 45(6): 321-331.

Tripathy, D. Neoplasia: 49-68. (In) Pathophysiology of disease. An introduction to clinical

medicine, first edition. McPhee, S.J., Lingappa, V.R., Ganong, W.F. and Lang, J.D. (Eds.).

Appleton & Lange, Connecticut, 1995.

Turner, R.R., Li, C. and Compton, C.C. (2007) Newer pathologic assessment techniques for

colorectal carcinoma. Clin Cancer Res., 13(22 Suppl.): 6871s-6876s.

Tyagi, P., Wu, P-C., Chancellor, M., et al. (2006) Recent advances in intravesical drug/gene

delivery. Mol Pharm., 3(4): 369-379.

UCSC Genome Bioinformatics Group - http://genome.ucsc.edu

Umpleby, H. C., Ranson, D. L. et al. (1985). Peculiarities of mucinous colorectal carcinoma. Br

J Surg 72(9): 715-718.

http://genome.ucsc.edu/

274

University of Pennsylvania. TRANSFAC Database, version 4.0: Transcription Element Search

System, TESS (11th April, 2005). http://www.cbil.upenn.edu/tess.

U.S. National Library of Medicine. Nucleotide Sequence Database (GenBank) and the Protein

Sequence Database: Entrez, National Centre for Biotechnology Information (12th December,

2001). http://www.ncbi.nlm.nih.gov.

U.S. National Library of Medicine. Nucleotide Sequence Database (GenBank) and the

Protein Sequence Database: Entrez, National Centre for Biotechnology Information (17th July,

2005). http://www.ncbi.nlm.nih.gov.

Utikal, J., Gratchev, A., Muller-Molinet, I., et al. (2006) The expression of metastasis

suppressor MIM/MTSS1 is regulated by DNA methylation. Int J Cancer., 119: 2287- 2293.

Vandesompele, J., De Preter, K. et al. (2002). "Accurate normalization of real-time quantitative

RT-PCR data by geometric averaging of multiple internal control genes." Genome Biol 3(7):

RESEARCH0034.

Van der Voort van Zijp, J., Hoekstra, H.J. and Basson, M.D. (2008) Evolving management of

colorectal cancer. World J Gastroenterol., 14(25): 3956-3967.

Van Dross, R., Browning, P.J. and Pelling, J.C. (2006) Do truncated cyclins contribute to

aberrant cyclin expression in cancer? Cell Cycle, 5(5): 472-477.

Velculescu, V.E. (2008) Defining the blueprint of the cancer genome. Carcinogenesis, 29(6):

1087-1091.

Wark, P.A., Van der Kuil, W., Ploemacher, J., et al. (2006) Diet, lifestyle and risk of K-ras

mutation-positive and –negative colorectal adenomas. Int J Cancer., 119(2): 398-405.

http://www.cbil.upenn.edu/tess


275

Washington, M.K. (2008) Colorectal carcinoma. Selected issues in pathologic examination and

staging and determination of prognostic factors. Arch Pathol Lab Med., 132: 1600-1607.

Wei, E. K., Wolin, K. Y., & Colditz, G. A. (2010). Time course of risk factors in cancer etiology

and progression. Journal of Clinical Oncology, 28(26), 4052-4057.

Weinberg, R.A. (1991) Tumor suppressor genes. Science, 254: 1138-1152.

Wheeler, J.M.D., Bodmer, W.F., Wheeler, J.M.D. and Mortensen, N.J. McC. (2000) DNA

mismatch repair genes and colorectal cancer. Gut, 47(1): 148-153.

Whenham, N., D’Hondt, V. and Piccart, M.J. (2008) HER2-positive breast cancer: from

trastuzumab to innovatory anti-HER2 strategies. Clin Breast Cancer., 8(1): 38-49.

Wilkins, J.A. and Sansom, O.J. (2008) C-Myc is a critical mediator of the phenotypes of Apc

loss in the intestine. Cancer Res., 68(13): 4963-4966.

Willett, C.G., Czito, B.G. and Bendell, J.C. (2007) Radiation therapy in stage II and III rectal

cancer. Clin Cancer Res., 13(22 Suppl): 6903s-6908s.

Willmore-Payne, C., Holden, J. A. et al. (2006). Detection of EGFR- and HER2-activating

mutations in squamous cell carcinoma involving the head and neck. Mod Pathol 19(5): 634-640.

Willmore-Payne, C., Holden, J. A. et al. (2005). Human malignant melanoma: detection of

BRAF- and c-kit-activating mutations by high-resolution amplicon melting analysis. Hum Pathol

36(5): 486-493.

Winkels, R. M., Botma, A., Van Duijnhoven, F. J., Nagengast, F. M., Kleibeuker, J. H., Vasen,

H. F., & Kampman, E. (2012). Smoking increases the risk for colorectal adenomas in patients

with Lynch syndrome. Gastroenterology, 142(2), 241-247.

276

Wittwer, C. T., Reed, G. H. et al. (2003). High-resolution genotyping by amplicon melting

analysis using LCGreen. Clin Chem 49(6 Pt 1): 853-860.

Wong, W.W. and Puthalakath, H. (2008) Bcl-2 family proteins: the sentinels of the

mitochondrial apoptosis pathway. IUBMB Life., 60(6): 390-397.

World Health Organization. The Global Burden of Disease: 2004 Update. Geneva: World Health

Organization; 2008.

Worthley, D.L., Whitehall, V.L., Spring, K.J. and Leggett, B.A. (2007) Colorectal

carcinogenesis: Road maps to cancer. World J Gastroenterol., 13(28): 3784-3791.

Wu, A. H., Paganini-Hill, A. et al. (1987). Alcohol, physical activity and other risk factors for

colorectal cancer: a prospective study. Br J Cancer 55(6): 687-694.

www.genecards.org version 3 – Weizmann institute of science – 21 March 2010

www.ncbi.nlm.nih.gov/ - National Center for Biotechnology Information, U.S. National Library

of Medicine

www.scbt.com/datasheet-101986-jk-1-y-20-antibody.html - Santa-Cruz Biotechnology - JK-1

antibody datasheet information

Xin, B., Platzer, P., Fink, S.P et al. (2004) Colon cancer secreted protein-2 (CCSP-2), a novel

candidate serological marker of colon neoplasia. Oncogene, Online publication, 6 December

2004: 1-8.

Xiong, Z., Wu, A.H., Bender, C.M., et al. (2001) Mismatch repair deficiency and CpG island

hypermethylation in sporadic colon adenocarcinomas. Cancer Epidemiol Biomarkers Prev.,

10(7): 799-803.

http://www.genecards.org/


http://www.nlm.nih.gov/

http://www.nlm.nih.gov/

277

Xu, S. F., Li, D. P. et al. (2008). Refined mapping of heterozygosity loss on chromosome 5p15

in sporadic colorectal cancer. Zhonghua Zhong Liu Za Zhi 30(6): 413-417.

Yamaguchi H., Wyckoff J., Condeelis J. (2005) Cell migration in tumors. Current opinion in cell

biology.;17(5):559-64.

Yamamoto, S., Mochizuki, H. et al. (1993). Assessment of clinicopathologic features of

colorectal mucinous adenocarcinoma. Am J Surg 166(3): 257-261.

Yayon, A. and Klagsbrun, M. (1990) Autocrine regulation of cell growth and transformation by

basic fibroblast growth factor. Cancer Metastasis Rev., 9(3): 191- 202.

Zlobec, I., Minoo, P. et al. (2010). Role of tumor size in the pre-operative management of rectal

cancer patients. BMC Gastroenterol 10: 61.

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