Risk and Prognostic Factors for Malignant Glioma

Sara Sjöström

Department of Radiation Sciences, Oncology

Umeå University 2012

Responsible publisher under Swedish law: the Dean of the Medical Faculty

This work is protected by the Swedish Copyright Legislation (Act 1960:729)

Copyright © Sara Sjöström

New Series No. 1536

ISBN: 978-91-7459-521-5

ISSN: 0346-6612

Front cover: The horizon seen from Lövskatan, Nordmaling, Sweden

Elektronisk version tillgänglig på http://umu.diva-portal.org/

Printed by: Print & Media, Umeå University

Umeå, Sweden 2012

To my family

i

Table of Contents

Table of Contents i Abstract iii Abbreviations v Populärvetenskaplig sammanfattning på svenska ix Original papers xii Introduction 1

Glioma 1 Classification 1 Incidence 2 Diagnostics and treatment 3

Risk factors 4 Mobile phone 4 Genetic syndromes and familial aggregation 4 Ionizing radiation 5 Asthma and allergy 5 Low penetrance genes 8

Prognostic factors 10 Virus and immunologic response 11

Viruses 11 Herpesviridae 11

Cytomegalovirus 11 Epstein-Barr virus 11 Varicella zoster virus 12

Adenoviridae 12 Immunologic response 12 Viruses and Cancer 13

EGF/EGFR 13 Function 13 EGF/EGFR and glioma 14

VEGF/VEGFR 16 Function 16 VEGF/VEGFR and glioma 16

DNA repair 18 Mechanisms 18 Base excision repair 18 Mismatch repair 18 Nucleotide Excision Repair 19 Homologous recombination and non-homologous end joining 20 Direct repair 20 DNA-repair gene variants and glioma 21

ii

Genetics and association studies 22 SNPs and association studies 22 Haplotype and haplotype blocks 23

Aims 24 Material 25

Study population 25 Paper I 25

Northern Sweden Health and Disease Study 26 The Malmö Diet and Cancer Study 26 Diet, Cancer and Health 27

Papers II-IV 27 The INTERPHONE study 27

Confirmation 28 Papers II and III 28 Paper IV 28

Methods 29 Paper I 29 ELISA and immunoflourescence 29 Binary logistic regression 29 Papers II-IV 30 Medical records 30 SNP-selection and genotyping 31 Statistical analyses 31

Cox proportional hazards model 31 Correction for multiple testing 32

Results 33 Paper I 33 Papers II and III 34 Paper IV 35

Discussion 37 Paper I 37 Case-control studies 38 Papers II and III 39 Paper IV 41

Conclusions 44 Future perspectives 45 Acknowledgements 47 References 50 Original publications

Paper I

Paper II

Paper III

Paper IV

iii

Abstract

Background: Glioblastoma is the most common and aggressive type of

glioma and associated with poor prognosis. Apart from ionizing radiation

and some rare genetic disorders, few aetiological factors have been identified

for primary brain tumours. Inverse associations to asthma and low IgG levels

for varicella zoster virus have in previous studies indicated that the immune

system may play a role in glioma development. Little is known about

prognostic factors in glioma. Previous studies have shown an association

between age, Karnofsky performance status, O-6-methylguanine-DNA

methyltransferase (MGMT) hypermethylation, and prognosis.

Polymorphisms in different low penetrance genes, such as epidermal growth

factor (EGF), have in some studies been associated with glioma prognosis

The epidermal growth factor receptor, EGFR, is amplified in about 30-50%

of malignant glioma and in 50% of glioblastoma EGFR is mutated

(EGFRvIII), leading to a constitutively active receptor. EGFR overexpression

has been associated with poor prognosis in low grade glioma and anaplastic

astrocytoma. Vascular endothelial growth factor (VEGF) is a key component

in both angiogenesis and the development of malignant tumours. VEGF

overexpression has been found and associated with poorer prognosis in high

grade astrocytoma. Radiotherapy and chemotherapy, is apart from surgery,

the standard treatment for glioblastoma and both these treatments cause

damage to the DNA and therefore DNA repair genes could be hypothesized

to be of prognostic importance.

Material and methods: In paper I we analysed IgG levels for four

different viruses, Epstein-Barr virus (EBV), cytomegalovirus (CMV),

varicella zoster virus (VZV) and adenovirus (Ad), in prediagnostic blood

samples from 197 cases with glioma and 394 controls. The blood samples

were collected from three large cohorts: the Northern Sweden Health and

Disease Study, the Malmö Diet and Cancer Study and the Diet, Cancer and

Health cohort from Copenhagen. IgG levels were measured using Enzyme-

linked immunosorbent assay (ELISA). For EBV, IgG response to both the

nuclear antigen (EBNA1) and the viral capsid antigen (VCA) was measured,

while for VCA, immunoflourescence was used. IgG levels were divided into

quartiles and binary logistic regression was used to compare the quartiles in

cases and controls. All odds ratios were adjusted for age, sex, and cohort. In

papers II-IV, we studied 176 glioblastoma cases from Sweden and Denmark,

originally collected as part of the INTERPHONE study, a large international

study that investigated the association between mobile phone use and glioma

risk. We collected treatment and follow-up data on the cases. Loss of follow-

up, missing treatment data or poor DNA quality led to fewer cases available

iv

for final analyses in the different studies. We genotyped 30 tagging single

nucleotide polymorphisms (SNPs) in EGF, 89 in EGFR, 27 in VEGFR2 and

17 in VEGF. We also studied 1458 SNPs in 136 DNA-repair genes. Hazard

ratios were calculated using Cox regression; the major allele was set as

categorical variable and all HR were adjusted for age, sex, country, and

treatment. For the DNA repair gene results, we adjusted the p-values for

multiple testing. A separate dataset from The M. D. Anderson Cancer Center

(MDACC) was available for confirmation in the EGF/EGFR and

VEGF/VEGFR2 studies, and for the DNA-repair genes, a dataset from

northern UK was used for confirmation.

Results and Discussion: In paper I we found a trend towards higher IgG

VZV levels in controls compared to glioma cases, especially when restricting

the analyses to only include glioma cases with at least 2 years between blood

sample and diagnosis. This finding might indicate that there is an

aetiological and not a disease-related association. These findings confirm

previous findings in early studies of samples taken at diagnosis and support

that a strong immune system can detect and inhibit growth of small cancer

clusters. In EGF, we found seven SNPs in one haplotype block that were

significantly associated with glioblastoma survival. Four of the SNPs were

available for confirmation in the MDACC dataset; however, none of the SNPs

reached statistical significance. In analysing the data further, one

explanation could be that the cases in the MDACC cohort had a lower age at

diagnosis and longer median survival time than the Swedish/Danish cohort.

In EGFR, four SNPs associated with survival were found; however, as 89

polymorphisms were tested this was the expected outcome by chance. In

VEGF and VEGFR2, we found two SNPs associated with glioblastoma

survival, but they could not be confirmed in the MDACC dataset and, due to

multiple testing were considered to be false positives. Among the DNA-

repair genes, we found nine SNPs in three genes - MSH2, RAD51L1 and

RECQL4 - which were significantly associated with glioblastoma survival

after confirmation and adjustment for age, sex, country and treatment. After

adjusting for multiple testing, two SNPs remained significant, one in MSH2

and one in RECQL4.

Conclusions: Our studies provide additional knowledge to the aetiological

and prognostic factors important for glioma, emphasising the possible

importance of immune function mechanisms. We found limited evidence for

the role of genetic variants in glioma progression genes, and some for DNA

repair variants as prognostic factors for glioblastoma survival.

v

Abbreviations

5´UTR 5´Un-Translated Region

A Adenine

Ad Adenovirus

AP-site Apurinic/apyrimidic site

APE1 Apurinic/apyrimidic endonuclease 1

APEX1 APEX nuclease 1

ATM Ataxia telangiectasia mutated

ATP Adenosine triphosphate

ATR Ataxia telangiectasia and Rad3 related

BER Base excision repair

bp base pair

BRCA Breast cancer susceptibility gene

BTBD2 BTB domain containing 2

C Cytosine

CCDC26 Coiled-coil domain containing 26

CCSS Childhood cancer survival study

CD4+ Cluster of differentiation 4, T-helper cell

CD8+ Cluster of differentiation 8, Cytotoxic T Lymphocyte

CDKN2A Cyclin-dependent kinase inhibitor 2A (p16INK4A)

CDKN2B Cyclin-dependent kinase inhibitor 2B

CHAF1A Chromatin assembly factor 1, subunit A

CHEP Utah residents with northern and western Europe ancestry

CI Confidence interval

CMV Cytomegalovirus

CNS Central nervous system

CSA Cockayne syndrome A (ERCC8)

CSB Cockayne syndrome B (ERCC6)

CT Computed tomography

CTL Cytotoxic T lymphocyte

DBS Double strand break

DCLRE1B DNA cross-link repair 1B

DNA Deoxyribonucleic acid

DNA-pk DNA protein kinase

EBNA-1 IgG-anti-Epstein-Barr-Nuclear-Antigen-1

EBV Epstein-Barr virus

EGF Epidermal growth factor

EGFR Epidermal growth factor receptor

EGFRvIII Mutant epidermal growth factor receptor

ELISA Enzyme-linked immunosorbent assay

ErbB v-erb-b erytroblastic leukemia viral oncogene homolog

vi

ERCC1 Excision repair cross-complementing rodent repair deficiency

complementation group 1

EXO1 Exonuclease 1

FEN1 Flap structure-specific endonuclease 1

G Guanine

GGR Global genome repair

Gy Gray

GWAS Genome wide association study

HCMV Human cytomegalovirus

HHRAD23B Human homolog of RAD23 B

HIV Human immunodeficiency virus

HMGA2 High mobility group AT-hook 2

HNPCC Hereditary nonpolyposis colon cancer, Lynch syndrome

HPV Human papilomavirus

HR Homologous recombination

hTERC Human telomerase RNA component

hTERT Human telomerase reverse transcriptase

IDH Isocitrate dehydrogenase

IE1 Immediate-early 1

IF Immunoflourescence

Ifn Interferon

Ig Immunoglobulin

IL Interleukin

JCV John Cunningham virus, JC-virus

kB Kilo base

kU/L Kilo units per litre

LD Linkage disequilibrium

LIG Ligase

LTS Long-term survivors

MAF Minor allele frequency

MAPK Mitogen-activated protein kinase

MDACC MD Anderson Cancer Center

MDSC Malmö Diet and Cancer Study

MGMT O-6-methylguanine-DNA-methyltransferase

MLH MutL-homolog

MMR Mismatch repair

MONICA Monitoring Trends and Determinants in Cardiovascular

Disease

MRE11 Meiotic recombination 11

MRI Magnetic resonance imaging

MRN RAD50/MRE11/NBS1 complex

MSH Melanocyte-stimulating hormone

NBS1 Nijmegen breakage syndrome 1 (nibrin)

vii

NEIL3 Nei endonuclease VIII-like 3

NER Nucleotide excision repair

NF Neurofibromatosis

NHEJ Non-homologous end joining

NK Natural killer

nm Nanometre

No. Number

NSHDS Northern Sweden Health and Disease Study

OR Odds ratio

P3-kinase Phosphoinositide 3-kinase

PARP Poly ADP ribose polymerase

PCNA Proliferating cell nucleus antigen

PFS Progression-free survival

PHLDB1 Pleckstrin homology-like domain family B member 1

PKC Protein kinase C

PLC Phospholipase C

PLK Polo-like kinase

PMS Postmeiotic segregation increased

PNK Polynucleotide kinase

Pol Polymerase

POLD1 Polymerase delta 1

PTEN Phosphatase and tensin homolog

RB Retinoblastoma

RGS22 Regulator of G-protein signalling 22

RNA Ribonucleic acid

RPA Replication protein A

RR Relative risk

RTEL 1 Regulator of telomere elongation helicase 1

SES Socio economic status

SNOMED Systematized nomenclature of medicine

STS Short-term survivors

SV40 Simian virus 40

T Thymine

TCR Transcription coupled repair

TERT Telomerase reverse transcriptase

TFIIH Transcription factor II H

TH T-helper

TNF Tumour necrosis factor

TP53 Tumour protein 53

TSC Tuberous sclerosis

UCSC University of California, Santa Cruz

UK United Kingdom

UV Ultraviolet

viii

VCA Viral capsid antigen

VEGF Vascular endothelial growth factor

VEGFR Vascular endothelial growth factor receptor

VIP Västerbotten Intervention Program

VZV Varicella zoster virus

WHO World Health Organization

XPA Xeroderma pigmentosum complementation group A

XPC Xeroderma pigmentosum complementation group C

XPF Xeroderma pigmentosum complementation group F (ERCC4)

XPG Xeroderma pigmentosum complementation group G (ERCC5)

XRCC X-ray repair cross-complementing

ix

Populärvetenskaplig sammanfattning på svenska

Hjärnan är ett mycket komplext organ som består av flera olika typer av

celler, och tumörer i hjärnan kan därför ha olika ursprung vilket påverkar

växtsätt och aggressivitet. Den vanligaste typen av hjärntumör är gliom, en

typ av tumör som uppstår från gliaceller vilka är hjärnans stödjevävnad.

Gliom kan delas in i fyra grader där grad 4, glioblastom, är den mest

aggressiva formen med dålig prognos. Vi vet idag mycket lite om vad som

orsakar gliom, det finns familjer med ökad risk för att få ett gliom, vissa

ovanliga genetiska sjukdomar som t.ex. Li-Fraumeni och Lynch syndrom ger

en ökad risk för gliom och det finns beskrivet att joniserande strålning ökar

risken för att få en hjärntumör, däremot har inga starka samband mellan

mobiltelefonanvändning och risk att drabbas av hjärntumör hittats. Tidigare

studier har också visat att personer med astma och allergi samt personer

med höga antikroppsnivåer mot det herpesvirus som ger vattkoppor och

bältros (varicella zoster virus) har ett visst skydd mot att utveckla gliom. Idag

känner vi endast till ett fåtal faktorer som påverkar prognosen hos en person

som insjuknar i hjärntumör. Vi vet exempelvis att ålder och allmäntillstånd

vid insjuknande, hur mycket av tumören som går att operera bort och om

genen MGMT är aktiv har betydelse för prognosen. Patienter med en inaktiv

MGMT gen svarar bättre på behandling med Temozolomid, en typ av cellgift

som är en del av standardbehandlingen vid glioblastom.

Vår arvsmassa (DNA) är uppbyggd av 4 baser, adenin (A), tymin (T), cytosin

(C) och guanin (G). Dessa baser binds ihop parvis till två strängar och bildar

på så sätt en dubbelhelix som inrymmer alla våra gener. 99.9% av vår

arvsmassa är identisk, men 0.1 % skiljer sig mellan individer och består till

80 % av variationer i dessa baspar. Den här typen av variationer i olika

gener, som bland annat påverkar celltillväxt, kärltillväxt eller reparation av

DNA-skada, har visat sig ha betydelse för både uppkomst och prognos vid

olika typer av cancer, bl.a. gliom.

I arbete I har vi använt oss av blodprover från olika biobanker för att

undersöka om antikroppsnivåer mot fyra vanliga virus, cytomegalovirus

(CMV), Epstein-Barr virus (EBV), varicella zoster virus (VZV) och

adenovirus (Ad), är associerat till risk att utveckla gliom. Tidigare studier har

visat ett samband mellan höga antikroppsnivåer mot VZV och lägre risk för

gliom. I de studierna togs blodprov först när fallen insjuknat i gliom vilket

gör att både sjukdomen i sig och behandling kan ha påverkat resultatet.

Eftersom vi hade tillgång till prover från biobanker har vi kunnat använda

oss av blodprover som togs innan fallen insjuknade i gliom och jämföra med

friska kontroller. Vi kunde då fastställa samma samband mellan höga

x

antikroppsnivåer mot VZV och minskad risk för gliom. Däremot kunde vi

inte se någon association mellan risk för gliom och antikroppsnivåer för de

andra virusen.

I arbete II-IV har vi studerat 176 fall med glioblastoma från Sverige och

Danmark som insjuknade mellan åren 2000 och 2004 och då deltog i en stor

internationell studie om hjärntumörrisk vid mobiltelefonanvändning

(INTERPHONE). Hos dessa fall hade vi tillgång till behandlingsdata varför

alla våra resultat är kontrollerade för land, kön, ålder och behandling. En

sådan kontroll görs för att minimera risken att dessa faktorer påverkar

resultatet. Vårt syfte var att studera om genetiska variationer i gener som är

inblandade i celltillväxt (EGF, EGFR), kärltillväxt (VEGF, VEGFR2) och

reparation av DNA-skador, och därför viktiga i tumörutveckling, har någon

betydelse för överlevnad hos fall med glioblastom.

En genetisk variation är en variation i ett baspar på en given plats i

arvsmassan, dessa variationer finns naturligt i befolkningen. Om baserna på

den givna platsen i arvsmassan exempelvis är C och G så kan de vara

kombinerade på 3 olika sätt hos olika individer; CC, CG och GG. En av dessa

baser är vanligast förekommande i befolkningen på just den platsen i

arvsmassan och om vi i detta exempel antar att det är basen C så har vi

studerat om en person som har en av de ovanliga baserna, CG, eller två av de

ovanliga baserna, GG, lever kortare eller längre om de får ett glioblastom

jämfört med dem som har två av de vanliga baserna CC.

Vi analyserade 30 genetiska variationer i genen epidermal growth factor

(EGF), 89 i genen epidermal growth factor receptor (EGFR), 17 i genen

vascular endothelial growth factor (VEGF), 27 i genen vascular endothelial

growth factor receptor 2 (VEGFR2) och 1458 genetiska variationer i 136

olika DNA-reparationsgener. I EGF fann vi ett samband mellan 7 variationer

och överlevnad hos glioblastom. Fyra av dessa hade vi möjlighet att även

analysera i en annan grupp bestående av 638 glioblastom från MD Anderson

Cancer Centre (MDACC) i Texas, men där kunde vi inte se något samband

med överlevnad. En förklaring till detta kan vara att fallen från Texas var

yngre och hade en längre medianöverlevnad jämfört med de svenska och

danska fallen och vi hade inte heller tillgång till behandlingsdata för fallen

från Texas. I EGFR hittade vi ett samband mellan 4 genetiska variationer och

överlevnad, men eftersom vi testade 89 så beror detta mest sannolikt på

slumpen då vi använt oss av ett p-värde på 0.05 vilket ger en sannolikhet på

95 % att våra fynd är sanna. I VEGF hittade vi inget samband mellan de

genetiska variationer vi analyserade och överlevnad vid glioblastom. I

VEGFR2 hittade vi ett samband mellan 2 variationer och överlevnad. Dessa

hade vi också möjlighet att analysera i fallen från MDACC, vi fann dock inte

samma samband där och fyndet är mest sannolikt beroende på slumpen. I

det fjärde arbetet studerade vi sammanlagt 1458 genetiska variationer i 136

xi

DNA-reparationsgener. Vi analyserade först i de svenska och danska fallen

och sedan kontrollerade vi positiva fynd i 295 fall från norra England. De

variationer som fortfarande hade ett samband med överlevnad analyserade

vi sedan ånyo i det svenska och danska materialet men kontrollerade denna

gång för land, ålder, kön och behandling. Efter detta fann vi sammanlagt 9

variationer med ett samband till överlevnad, dessa var belägna i generna

MSH2, RAD51L1 och RECQL4.

Sammanfattningsvis så har vi bekräftat att immunförsvaret verkar spela en

viktig roll vid uppkomsten av gliom och vi fann vissa samband mellan

variationer i gener som är av betydelse för tumörprogress och reparation av

skador på DNA och överlevnad hos glioblastom. Genom att hitta faktorer

viktiga för både risk att utveckla hjärntumör och överlevnad hos patienter

med hjärntumör skapar man möjligheter att i framtiden hitta sätt att tidigare

diagnostisera tumören och möjliga angreppspunkter för nya behandlingar.

xii

Original papers

This thesis is based on the following studies, referred to in the text by their

roman numerals:

I. Human immunoglobulin G levels of viruses and associated

glioma risk.

Sjöström Sara, Hjalmars Ulf, Juto Per, Wadell Göran,

Hallmans Göran, Tjönneland Anne, Halkjaer Jytte, Manjer

Jonas, Almquist Martin, Melin Beatrice, Cancer Causes Control

September 2011 ;22(9): 1259-66

II. Genetic variations in EGF and EGFR and glioblastoma outcome.

Sjöström Sara, Andersson Ulrika, Liu Yanhong, Brännström

Thomas, Broholm Helle, Johansen Christoffer, Collatz-Laier

Helle, Henriksson Roger, Bondy Melissa, Melin Beatrice. Neuro

Oncol August 2010;12(8):815-21

III. Genetic variations in VEGF and VEGFR2 and glioblastoma

outcome.

Sjöström Sara, Wibom Carl, Andersson Ulrika, Brännström

Thomas, Broholm Helle, Johansen Christoffer, Collatz-Laier

Helle, Liu Yanhong, Bondy Melissa, Henriksson Roger, Melin

Beatrice. J Neurooncol September 2011 ; 104(2):523-7

IV. DNA-repair gene variants are associated with glioblastoma

survival.

Wibom Carl, Sjöström Sara, Henriksson Roger, Brännström

Thomas, Broholm Helle, Rydén Patrik, Johansen Christoffer,

Collatz-Laier Helle, Hepworth Sara, McKinney Patricia, Bethke

Lara, Houlston Richard, Andersson Ulrika, Melin Beatrice. Acta

Oncologica March 2012, Vol. 51, No. 3 , Pages 325-332

Reprints were made with permission from Elsevier (1-3) and Acta oncologica

(4).

1

Introduction

Glioma

There are several different types of brain tumours that arise from cells with

different origins and function in the brain. The most common type is glioma,

which arises from glial cells, a form of supportive cells in the brain and

spinal cord. There are several different types of glial cells, ependymal cells,

astrocytic cells, microglial cells, oligodendritic cells, Schwann cells and

müller cells.

Classification

Tumours arising from astrocytic cells, astrocytoma, are the most common

type of tumours and they are divided into four grades depending on

malignancy. Grade 1 can be characterized as clinically benign, often curable

by surgery. Grade 2 and 3 are malignant and they often progress to higher

and more malignant grades. The fourth grade, glioblastoma, is the most

aggressive form and has a very poor prognosis. Glioblastoma can either be

primary or secondary; the latter starts as a lower-grade that progress into a

higher-grade astrocytoma and finally into glioblastoma. Differences in

tumour progression and prognosis have been seen between primary and

secondary glioblastoma (Figure 1). Secondary glioblastoma more often has a

tumour protein 53 (TP53) mutation, while primary glioblastoma is more

likely to have epidermal growth factor receptor (EGFR) amplification (1).

Isocitrate dehydrogenase 1 (IDH1) mutations are more frequent in secondary

glioblastoma and have been associated with longer survival (2). Secondary

glioblastomas are rare and account for about 5%.

2

Incidence

The glioma incidence in Sweden in 2009 was 9 per 100,000 person-years

when looking at all regions and including all age groups. The standardized

incidence rate for high grade glioma (Astrocytoma III and IV) for the same

year was about 8 per 100,000 person-years (Figure 1). For all glioma

subtypes, the incidence is higher in men than women.

3

Diagnostics and treatment

There are several different symptoms of brain tumours: epileptic seizures,

altered personality, increasing neurological deficits, and signs of increased

intracranial pressure (headache, nausea) are the most common. Computed

tomography (CT) and magnetic resonance imaging (MRI) are methods used

to examine the brain, with MRI being the method of choice when

investigating a suspicious brain tumour. The first line of treatment for

malignant glioma is surgery. With a glioblastoma diagnosis, however, the

tumour is disseminated, with tumour cells that are not detectable through

MRI spread outside the main tumour bulk, making a microscopic radical

surgery nearly impossible. If possible, macroscopic total surgery is

conducted. If the patient is not suitable for surgery or the tumour location

does not permit radical surgery, a subtotal resection or biopsy is preferred to

verify the diagnosis. Previously, the treatment possibilities for glioblastoma

were very sparse, consisting of radiotherapy and different types of

chemotherapy combinations (CCNU, NOC (CCNU, Procarbacin, Vincristin)).

Today, treatment consists of concomitant radiotherapy, 2 Gray (Gy) per

fraction given daily, Monday to Friday, with a total dose of 60 Gy, and

Temozolomide (3), followed by adjuvant Temozolomide alone.

Figure 2 The age standardized incidence rates per 100,000 person-years in Sweden from 1970 to 2009. Ages 0 - >85 for astrocytoma grades III and IV ( IV=glioblastoma).

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Figure 2 The age standardized incidence rates per 100,000 person-years in Sweden from 1970 to 2009. Ages 0 - >85 for astrocytoma grades III and IV ( IV=glioblastoma).

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Figure 2 The age standardized incidence rates per 100,000 person-years in Sweden from 1970 to 2009. Ages 0 - >85 for astrocytoma grades III and IV ( IV=glioblastoma).

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4

Temozolomide is an alkylating agent that works by alkylating/methylating

DNA, usually at the N-7 or O-6 position of guanine, leading to DNA damage

and cell death. Some tumour cells, however, express an enzyme O-6-

methylguanine-DNA-methyltransferase (MGMT) which repairs the DNA

damage by removing the methyl-group, which leads to a poorer response to

Temozolomide. In some tumours, the MGMT gene is silenced through

methylation, promoting Temozolomide response (4). Recently, a monoclonal

antibody towards vascular endothelial growth factor (VEGF), Bevacizumab,

has been approved for second-line treatment of glioblastoma (5).

Risk factors

There are few known risk factors for glioma. Different potential risk factors

have been studied, such as nitrosamines (6, 7), x-ray (8, 9), electromagnetic

fields (10-12), head trauma (13-15), and epilepsy (16-18), with conflicting

results and no clear association with glioma risk. Smoking has also been

studied as a potential glioma risk factor, but no association has been found

(19, 20).

Mobile phone

Mobile phone use has been hypothesised to be a risk factor because of non-

ionizing radiation with radiofrequency close to the brain, but in a big case-

control study, INTERPHONE (21), including 2,765 glioma cases and 2,409

meningioma cases with matched controls from 13 countries, no clear

association was found for either glioma or meningioma after more than 10

years observation. For both meningioma and glioma, a reduced odds ratio

(OR) was found for regular mobile phone users. It has been speculated that

this reduction of risk could be due to recall bias among the participants or

methodological limitations. When looking at glioma cases with the highest

mobile phone use of ≥ 1640 h cumulative call time, an OR of 1.40; 95%

confidence interval (CI) 1.03-1.89 was found (22).

Genetic syndromes and familial aggregation

Studies have shown an association between a number of rare genetic

syndromes such as neurofibromatosis 1 (NF1), NF2, Li-Fraumeni, multiple

harmatoma, tuberous sclerosis 1 (TSC 1), TSC 2, retinoblastoma 1 (RB1),

Turcot syndrome, and brain tumour risk. These syndromes are rare and can

only account for few of the brain tumour cases (23, 24).

5

For first-degree relatives, a twofold increased risk for glioma has been seen

and glioma aggregation has been found in some families (25, 26). To further

study susceptibility loci in families with two or more glioma, an international

study called GLIOGENE (27) was started in 2007.

Ionizing radiation

Studies on ionizing radiation have shown an association to brain tumour

risk. This was first described in a study on Israeli children receiving radiation

therapy for tinea capitis as a prescribed treatment during immigration. They

were treated with doses from 1 Gy up to 6 Gy to the scalp and follow-up

showed an increase in brain tumour incidence for both meningioma (relative

risk (RR) 9.5; 95% CI 3.5-25.7) and glioma (RR 2.6; 95% CI 0.8-8.6). The

risk was dose-dependent (28-30).

Studies on atomic bomb survivors from Hiroshima and Nagasaki have

shown an increase in meningioma incidence among the exposed in

comparison with the unexposed. An increase in total central nervous system

(CNS) malignancy has also been seen among exposed cases (31-33).

In a follow-up study on childhood cancer survivals, the Childhood Cancer

Survival Study (CCSS), children treated with different type of radiotherapy to

the brain showed an increase in brain tumour incidence especially for glioma

and meningioma (34).

Asthma and allergy

Several studies have shown an inverse relationship between glioma and self-

reported atopic disease: asthma, allergy, and eczema (Table 1) (16, 35-42).

Association with immunoglobulin (Ig) E levels and glioma, where cases had

lower post-diagnostic IgE levels than controls, has also been reported (43,

44). It has been hypothesised that this might be caused either by the tumour

itself or different treatments given after diagnosis. In a more resent study of

169 cases with glioma and 520 controls, prediagnostic IgE levels were tested

for association with glioma risk. They found an inverse association with

borderline elevated total IgE levels (25-100 kU/L) and glioma risk (OR 0.63;

95% CI 0.42-0.93) compared with normal IgE levels (<25 kU/L). However

no association was found for elevated IgE (>100 kU/L) and glioma risk (OR

0.98; 95% CI 0.61-1.56) (45). Another study, on prediagnostic IgE levels in

275 cases with glioma and 963 matched controls, found an association

between elevated IgE levels and glioma risk, especially for high levels of IgE

in high-grade glioma (46). A recent study confirmed the inverse association

with IgE levels and glioma risk and also examined IgE levels in blood

6

samples taken more than 20 years before glioma diagnosis and showed that

the association is present at least 20 years before glioma diagnosis (47).

It has also been suggested that the findings of an inverse relationship

between self-reported history of atopic disease could be affected by recall

bias and, because the IgE levels in many of the studies were post-diagnostic,

it could be affected by the tumour itself. This has led to studies of

polymorphisms in asthma-related genes such as interleukin 4 (IL4),

IL4receptor (IL4R), and IL13 (48-51). However, no consistent evidence has

been found for an association between these immune genes and glioma risk.

In one study including 756 cases and 1190 controls, an association with

increased risk was found for the minor allele in a single nucleotide

polymorphism (SNP) in the IL4 gene. A minor allele association with

decreased risk was seen in an IL6 SNP (48). In another study on 110 cases

and 430 controls from Sweden, an inverse risk of glioblastoma was found for

four SNPs in IL4Ralpha and IL13 (49). This was, however, not confirmed in

a larger study on 217 cases and 1171 controls (50). In the latter study, an

association with increased glioma risk with IL4Ralpha polymorphism was

found. In a study on 456 glioma cases and 541 controls, IL4 and IL4R were

not associated with glioma risk, but polymorphisms in IL13 were associated

with case-control status and IgE levels (51).

7

8

Low penetrance genes

The association between single nucleotide polymorphisms in low penetrance

genes and glioma risk has over the years been studied, but often the study

populations have been too small to assure a true association or even detect

an existing association. In the last couple of years, large genome wide

association studies (GWAS) has been conducted and seven chromosomal

loci, in the telomerase reverse transcriptase (TERT), regulator of

telomerase elongation helicase 1 (RTEL 1), coiled-coil domain containing 26

(CCDC26), cyclin dependent kinase inhibitor 2A-cyclin dependent kinase

inhibitor 2B (CDKN2A-CDKN2B), pleckstrin homology-like domain family

B member 1 (PHLDB1), TP53, and EGFR genes, associated with glioma risk

have been identified (Table 2) (52-54). In one study of 1,878 cases and 3,670

controls, later validated in three additional independent datasets of 2,545

cases and 2,953 controls in total, risk loci in TERT, RTEL 1, CCDC26,

CDKN2A-CDKN2B, PHLDB1 were found (52). Two of the loci, in CDKN2B

and RTEL1, were found in another study published at the same time by

Wrensch et al. In the third GWAS, two loci in EGFR were found associated

with risk (54).

In a study by Andersson et al. from 2010 on 725 glioma cases (including 329

glioblastoma cases) and 1,610 controls, a polymorphism in EGFR

intron/exon boundary 7 (rs4947986) was found that was associated with

risk. In the same study, this finding was confirmed in a separate cohort of

713 glioblastoma cases and 2,236 controls from M.D. Anderson Cancer

Center (MDACC) in Texas (55). Recently, large GWAS have identified loci in

EGFR associated with glioma risk. In a pooled study of 1,056 glioblastoma

cases and 2,384 controls, three polymorphisms were found: one in the EGFR

promoter and two in intron 1 (56). In a study of 728 glioma and 1,600

controls two polymorphism associated with risk were found: one located in

the border between intron 1 and exon 2, and one at the border between

intron and exon 7 (rs4947986). The most recent and largest GWAS, on 4,147

glioma cases and 7,435 controls, identified two loci in EGFR, one of them in

intron 1, (rs11979158) and one (rs2252586) in a telomere region to EGFR

with a significance of p=2.08 x 10-8. Both SNPs were located at 7p11.2 and

were significant regardless of tumour grade, EGFR amplification status,

p16INK4A deletion or IDH mutation (54).

CCDC26, located on chromosome 8q24.21, has been associated with low-

grade glioma and oligodendroglioma, but variations in 8q24.21 have also

been associated with other types of cancer such as bladder (57), colorectal

(58), prostate (59) and breast cancer (60). PHLDB1 has also been associated

9

mainly with low-grade glioma (61). Both CCDC26 and PHLDB1 have been

associated with IDH1 mutation. IDH1 and IDH2 mutations have been found

in grade 2 and 3 glioma and also in secondary glioblastoma, and an

association between mutated IDH1 or IDH2 and better prognosis for low-

and high-grade glioma has been found (62). The role of PHLDB1 in

gliomagenesis is mostly unknown. It has been thought to respond to insulin

and enhance Akt (63). The tumour suppressor protein phosphatase and

tensin homolog PTEN is often lost in glioblastoma, which leads to Akt

activation (64), and in a study of astrocytic cells, activation of Akt led to

conversion to glioblastoma (65).

The CDKN2A-B region harbours p14 and p16. P16 is a known tumour

suppressor and is often lost in both copies in glioblastoma, but has also been

linked to other glioma subtypes such as low-grade glioma and

oligodendroglioma (61, 66).

RTEL1 and TERT are both telomerase regulating genes. Telomerase is an

enzyme that regulates the length of a region of repetitive nucleotide

sequences at the end of the chromosomes called telomeres. The length of the

telomeres are crucial for infinite proliferative potential, something acquired

by many malignant tumours giving them a possible immortal phenotype

(67). The telomerase activity is partly regulated by the reverse transcriptase

encoded by the TERT gene. The TERT gene has also been associated with

risk in other cancers such as pancreatic cancer, lung cancer, basal cell

carcinoma, and testicular cancer. In a recent study, two of these risk

polymorphisms (rs2736100, rs2853676) have, together with five other

polymorphisms in the human TERT (hTERT) and human telomerase RNA

component (hTERC) genes, been associated with telomere length at the age

of 60, but not at the age of 50 (68).

RTEL1 has primarily been associated with high-grade glioma and in

glioblastoma, RTEL1 has been associated with survival (61, 66, 69).

In a GWAS on cutaneous basal cell carcinoma, a SNP (rs78378222) in the

3´untranslated region of TP53 was found associated with risk. This

polymorphism was also tested in other cancers and a minor allele association

with risk in prostate cancer, colorectal adenoma, and glioma was found (70).

In a recently published paper, seven low-frequency SNPs at 8q24.21

significantly associated with glioma risk were found. One of the SNPs

(rs55705857) was significant after adjusting for the other six SNPs and was

found to be most significantly associated with oligodendroglioma and glioma

with mutated IDH1 or IDH2 (71).

10

Table 2 Genes associated with glioma risk

Gene Loci Association to glioma subtype

Study (reference)

TERT 5p15.33 High grade glioma Shete (52)

CCDC26 8q24.21 Low grade glioma Oligodendroglioma

Shete (52), Jenkins (71)

CDKN2A-CDKN2B

9p21.3 Low and high grade glioma Oligodendroglioma

Shete (52), Wrensch (53)

RTEL1 20q13.33 High grade glioma Shete (52), Wrensch (53)

PHLDB1 11q23.3 Low grade glioma Shete (52)

EGFR 7p11.2 Reglardless of subtype

Sanson (54)

TP53 Chromosome 17 Stacey (70)

Prognostic factors

Few prognostic factors have been recognised for glioma. The patient’s age

(72) and Karnofsky Performance Status at diagnosis (73) have been found to

affect prognosis as well as grade and histological type. The extent of surgery

affects survival (74), where macroscopically radical resection is favourable

(75). Methylation of the promoter of the MGMT gene has been associated

with prolonged overall survival in glioblastoma patients treated with

Temozolomide (4, 76). The recent discovery and use of Bevacizumab has, in

phase II trials, showed promising results for glioblastoma survival (77). It

has been approved for treatment of glioblastoma in the United States with

the reservation that larger phase III studies confirming the results are

needed; it has not been approved in Europe.

In oligodendroglioma, the loss of chromosomes 1p and 19q has been

associated with better prognosis (78). In astrocytic tumours EGFR, plays an

important role in tumour progression. EGFR is amplified in about 30-50 %

of malignant glioma, and this is associated with poorer survival in younger

patient with glioblastoma (age 55-60 years). Glioblastomas often have

11

mutated EGFR with loss in the extracellular part, which renders the receptor

consistently active (79). Low-grade tumours and anaplastic astrocytoma with

overexpression of EGFR are associated with poorer prognosis (80).

Virus and immunologic response

Viruses

Viruses are small infectious agents that are obligate intracellular and depend

on the host cell for replication. There are several different forms of viruses

that can be divided into two groups, RNA viruses and DNA viruses,

depending on the content of the viral genome. The DNA virus family can be

divided into two groups: enveloped, containing Herpesviridae, for example;

and naked capsid, containing Adenoviridae, for example. The virus particle

(virion) contains a nucleic acid genome packed into a capsid (protein coat) or

an envelope (membrane).

Herpesviridae

Herpes viruses are large DNA viruses, 120-200 nanometres (nm) in size.

They are enveloped and contain a double stranded and linear genome that is

surrounded by a capsid and then enclosed by an envelope containing

glycoproteins. In the space between the capsid and the envelope, there are

viral proteins and enzymes that can assist in the initiation of replication.

Cytomegalovirus

Cytomegalovirus (CMV) is a DNA virus and belongs to the Herpesviridae

family. It is widely spread in the population and, in immunocompetent

healthy adults, the infection is mostly asymptomatic or gives mononucleosis-

like symptoms. In infants or immunosuppressive patients, the infection can

be life threatening.

Epstein-Barr virus

Epstein-Barr virus (EBV) is also a member of the Herpesviridae family. It

infects the antibody presenting B-lymphocytes and is very common in the

population. The virus can cause mononucleosis, but the majority of infected

individuals are asymptomatic. After the acute infection, EBV remains latent

in B-lymphocytes.

12

Varicella zoster virus

Varicella zoster virus (VZV) is a DNA virus in the Herpesviridae family, very

similar to the herpes simplex virus but with a smaller genome. A primary

VZV infection causes chicken pox, and, after the infection has resolved, the

virus can enter a latent phase and remain dormant in the nervous system. A

reactivation may occur later in life and cause shingles (81).

Adenoviridae

Adenovirus (Ad) is a DNA virus and belongs to the Adenoviridae virus

family. They are naked capsid viruses about 100 nm in size and contain a 35

kB double stranded and linear genome (82). It causes upper respiratory

infections, mostly in children, but can also cause diarrhoea.

Immunologic response

The immune system is our defence against disease and responds to foreign

factors through two interacting pathways: the innate response (fever,

interferons, cytokines, mononuclear phagocyte system, natural killer (NK)

cells); and the antigen response, which can be divided further into humoral

(antibody) and cell-mediated (T-cell) immunity. Viruses attack host cells that

harbour or replicate the virus, requiring the immune system to eliminate

both the virus and the affected host cell. In the case of a viral infection,

interferons (Ifn) are released as part of the innate response. NK cells kill

virus-infected cells and macrophages can filter the blood from viral particles.

Macrophages also function as antigen-presenting cells, presenting viral

particles on their cell surface, which promotes T helper cell (TH or cluster of

differentiation 4 (CD4+) T cells) activation. Macrophages also release

cytokines, such as tumour necrosis factor (TNF) and interleukins (IL1, IL6),

which induces fever and promote TH cell activation. There are different

types of TH cells. Two of them are TH1, which promotes inflammatory

response, enhances phagocytic killing, and stimulates B cells to start

antibody production (Immunoglobulin (Ig) M and IgG). TH2 produces IL4,

IL5, IL6, and IL10, enhancing IgG production and promoting B-cell

differentiation into antibody-producing plasma cells or memory cells. TH2

can also enhance IgA and IgE production. Activation of CD4+ T cells leads to

activation of both cytotoxic T cells (CTL or CD8+ T cells) and B cells. The

CTL destroy infected cells and B cells produce antibodies (83, 84).

There are different types of immunoglobulins (Ig), which are produced in

different parts of the immune response. IgM is produced in the early

response and indicates a primary viral infection. After two to three days, the

13

production of IgA and IgG starts. IgG remain in the circulation for several

weeks, and can be detected life long for viruses that remains latent in the

body.

Viruses and Cancer

Viruses have been associated with the development of several different types

of cancer. Human papiloma virus (HPV) has been shown to cause cervical

cancer (85) and a subset of cancer in the oropharynx (86).

EBV has been associated with different cancers, such as Hodgkin’s

lymphoma, Burkitt’s lymphoma, nasopharyngeal carcinoma, and human

immunodeficiency virus (HIV) -associated CNS lymphoma (87).

In brain tumours, different viruses have been studied as potential causal

factors. Viral DNA or proteins from Simian virus 40 (SV40) and John

Cunningham virus (JC-virus) have been detected in brain tumour tissue (88,

89). Cytomegalovirus (CMV) gene products have been found in brain tumour

tissue (90-92). However, there are studies that have failed to replicate these

findings (93, 94). In a study by Cobb et al., researchers found an association

between a CMV protein, human CMV (HCMV) immediate early-1 (IE1), and

glioblastoma cell growth, indicating that CMV can affect different pathways

in glioblastoma (95). Adenovirus (Ad) has also been found in brain tumour

tissue (96).

EGF/EGFR

Function

The epidermal growth factor receptor (ErbB1, EGFR) is a transmembrane

tyrosine kinase receptor at the cell surface. Epidermal growth factor (EGF) is

a ligand that binds to one of four receptors in the EGF-receptor family (ErbB

1-4). When a ligand binds to EGFR, a dimerization of one or more of the

receptors in the EGFR family starts leading to the formation of either homo-

dimers, to receptors of the same kind, or hetero-dimers, to different

receptors from the ErbB family. After dimerization, the receptor is activated

and internalized. Activation of EGFR starts a cascade of downstream

signalling molecules and activation of different pathways such as mitogen-

activated protein kinase (MAPK), P13K/Akt, and phospholipase C gamma

(PLCγ), leading to transcription in the nucleus and cell proliferation. This

pathway plays an important role in cell growth, survival, proliferation, and

differentiation (97).

14

EGF/EGFR and glioma

EGF 61 A/G, a polymorphism located 61 bp downstream from the EGF

promoter in the 5´un-translated (5´UTR) region, has been studied in

association with glioma risk and prognosis (Table 3) (98-100). The rare

allele G has been found to be more common in glioblastoma tissue compared

to tumour-free brain tissue. This correlates to an increased EGF expression,

indicating a functional role of that variant (100, 101).

The EGFR gene plays a role in the progression of glioma, and is amplified in

30-50% of malignant glioma. However, no clear association with prognosis

has been found. In a study of 403 glioblastoma cases with available

treatment data, a better prognosis with EGFR expression was found.

However, in the same study astrocytoma with EGFR tumour overexpression

had a significantly worse prognosis. EGFR overexpression was more strongly

associated with survival than EGFR amplification in both astrocytoma and

glioblastoma (44). In a study of 41 glioblastoma cases, with available

treatment data and over the age of 50, no association between prognosis and

EGFR amplification was found (102) and the same results were found in a

larger study of 715 glioblastoma cases (103). A nonsignificant trend towards

less EGFR amplification was seen in a group of glioblastoma with long-term

survival (over 36 months) and available treatment data (104).

Overexpression in astrocytoma and low-grade glioma has been associated

with poorer survival (44, 105). Glioblastoma with amplification often

contains a mutation, with deletion of exon 2-7, leading to loss of the

extracellular part of the EGF-receptor, which renders the receptor to be

constantly active (EGFRvIII) (79).

15

16

VEGF/VEGFR

Angiogenesis is an important part of tumour growth and glioblastomas are

highly vascular tumours. Small cancer clusters depend on their ability to

create blood vessels for the delivery of oxygen and nutrients. Second-line

therapy with the antiangiogenic antibody Bevacizumab targeting vascular

endothelial growth factor (VEGF) has increased in recent years.

Function

The VEGF family consists of six members: VEGF-A, VEGF-B, VEGF-C,

VEGF-D, and the placental growth factor (PlGF). VEGF-A, also referred to as

VEGF, is the molecule mainly involved in tumour angiogenesis. VEGF

expression can be induced by different factors, such as low pH, hypoxia,

chemokines, growth factors, sex hormones, inflammatory cytokines, and also

through loss of tumour-suppressor genes or activation of oncogenes. VEGF

is expressed in elevated levels by nearly all human cancers and binds

primarily to VEGF receptor 2 (VEGFR-2). Endothelial cells express elevated

levels of VEGFR-2 and, when VEGF binds to the receptor, a cascade of

intracellular pathways affecting vascular permeability, mobilization,

proliferation, migration, and survival in the endothelial cells are activated.

VEGF also binds to VEGF receptor 1 (VEGFR-1) which regulates cell growth

induced by VEGFR-2 during angiogenesis (106). VEGF receptor 3 (VEGFR-

3) is activated mainly through the binding of VEGF-C and plays a role in

lymphoangiogenesis (107).

VEGF/VEGFR and glioma

VEGF secreted by tumour cells has a paracrine effects on tumour endothelial

cells and angiogenesis, but VEGF may also have an autocrine effect on cell

viability and tumour growth. Astrocytoma cells express VEGFR-2 and can

also secret VEGF leading to an autocrine effect through the c-Raf/MAPK,

P13K, and PLC/protein kinase C (PKC) pathways (108). VEGF levels have

been found to increase with higher glioma grade (109, 110). In glioblastoma

the tumour vessels are highly disorganized, dilated, and leaky, leading to

hypoxia and high VEGF levels (111). It has been hypothesised that this

hypoxia is one of the mechanisms of radiation resistance in the tumour (112)

and that anti-VEGF therapy or VEGFR-2 blockage could normalize tumour

blood vessels and oxygenate the tumour, which could lead to a possible

window for radiotherapy response (113, 114). However, other studies have

shown a radiation-induced up regulation of VEGF/VEGFR2 in mouse

models, indicating that these factors also play an important role in

17

radiotherapy failure (115). Increased blood flow and reduction of tumour

hypoxia by anti-VEGF therapy might also induce tumour growth but, at the

same time allow improved drug and chemotherapy delivery and effect on the

proliferating tumour cells (116) . Glioma stem-like cells, a type of cell similar

to normal neural stem cells with the ability to self-renew, differentiate, and

proliferate (117, 118), also promote tumour angiogenesis by producing

angiogenetic factors such as VEGF (119). High VEGF levels have been

associated with poor glioblastoma outcome (110, 120) and, in high-grade

astrocytoma, VEGF overexpression has been associated with poor prognosis

(108, 121, 122).

The signalling pathways in human glioma, including EGF/EGFR and

VEGF/VEGFR, are shown in Figure 3 (123).

Figure 3 Key signaling patways in human glioma. Genes that are

inactivated are red and activated are blue. Reprinted with permission

from Biochimica et Biophysica Acta (BBA)-Proteins and Proteomics,

Grzmil et al. 2009. Copyright © Elsevier B.V. All rights reserved.

18

DNA repair

An accurate DNA repair is crucial for cell survival and damage to the DNA is

a function of many effective cancer treatments. Radiotherapy and

chemotherapy often induce damage to the DNA and the tumour’s ability to

repair this damage is a key component in treatment failure. In glioblastoma,

radiotherapy and concomitant Temozolomide are the standard treatment

and both these treatments affect the DNA, with radiotherapy inducing

double strand breaks and Temozolomide acting as an alkylating agent.

Mechanisms

Base excision repair

Base excision repair (BER) responds to small damages in the DNA such as an

oxidised or alkalised base or single strand breaks.

A damaged base is recognised and removed by an enzyme that is a member

of the DNA glycosylase family creating an apurinic/apyrimidic site (AP-site)

(124). Poly ADP ribose polymerase (PARP) and polynucleotide kinase (PNK)

assists in recognition of abasic sites and single strand breaks. The damage

can then be repaired through two different pathways: the short-patch

pathway and the long-patch pathway (125, 126).

In the short-patch pathway, the AP-site is recognised by apurinic/apyrimidic

endonuclease 1 (APE1), which flips out the deoxyribose residue and cleaves

the DNA 5´site, recruiting the next enzyme, DNA polymeraseβ (polβ) (127),

to the site. This enzyme cleaves the 3´site and fills in the gap with a

polymerase domain and then the X-ray repair cross-complementing 1

(XRCC1)-ligase 3 closes the cut (128-131).

In the long-patch pathway the AP-site is filled by DNA polβ, polδ, or polε

through assistance of proliferating cell nucleus antigen (PCNA) protein. The

3´end of the damage strand is then cleaved by flap structure-specific

endonuclease 1 (FEN1) and DNA ligase 1 seals the gap (132-134).

Mismatch repair

Mismatch repair (MMR) is a pathway that repairs mismatched bases, base

deletions, or insertions, contributing to genetic stabilisation.

The mismatch site is first recognized by a melanocyte-stimulating hormone 2

(MSH2)/MSH6 dimer (MutSα) (135, 136) or a MSH2/MSH3 dimer (MutSβ),

19

and then a MutL-homolog 1 (MLH1)/Postmeiotic segregation increased 2

(PMS2) dimer (MutLα) or MLH1/MLH3 dimer (MutLβ) binds to the MutSα,

which leads to excision of the mismatch, resulting in a single strand gap and

recruitment of the exonuclease 1 (EXO1). The created gap is stabilised

through replication protein A (RPA) and then filled by DNA polδ and

proliferating cell nucleus antigen (PCNA), and DNA ligase 1 then seals the

gap (132, 137, 138).

Inactivation of the pathway in humans is associated with hereditary

nonpolyposis colon cancer (HNPCC), also known as Lynch syndrome, and

HNPCC associated cancer in other organs, such as the colon, rectum, uterine

endometrium, stomach, and ovaries. It is also involved in Turcot syndrome,

a rare genetic syndrome that predisposes people for colorectal adenomas and

primary brain tumours (139, 140). It has also been associated with sporadic

cancers in other organs such as breast, prostate, and lung cancer (141, 142).

Nucleotide Excision Repair

Nucleotide Excision Repair (NER) is involved in several different DNA

lesions caused, for example, by chemotherapy or radiotherapy.

NER contains of two different pathways: the global genome repair (GGR)

and transcription coupled repair (TCR).

TCA is a specific repair pathway that finds damage to the DNA that causes

blockage of RNA polymerase II movement. Two TCA specific genes,

Cockayne syndrome A (CSA) and Cockayne syndrome B (CSB), detect the

halted polymerase and remove it, enabling further repair of the damaged

DNA (143). NER starts by xeroderma pigmentosum complementation group

C (XPC) recognising a damaged site in the DNA and binding to human

homolog of RAD23B (HHRAD23B) (144), forming a site for binding of other

DNA repair proteins such as xeroderma pigmentosum complementation

group A (XPA), replication protein A (RPA), transcription factor II H

(TFIIH) (145, 146), and XPG (147). Excision repair cross-complementing

rodent repair deficiency complementation group 1 (ERCC1)-XPF, a

heterodimeric complex, is then recruited to the site and, together with XPG,

cuts the 3´and 5´ends of the damaged DNA. The damaged DNA is then

removed and, with help of PCNA, RPA, and RFS, the gap is filled by DNA

polyδ or ε and sealed by DNA ligase (148, 149).

Defects in these pathways are present in xeroderma pigmentosa, a condition

predisposed to cancer caused by ultraviolet (UV)-light (132, 148, 149) .

20

Homologous recombination and non-homologous end joining

Homologous recombination (HR) and non-homologous end joining (NHEJ)

are two pathways used in double strand break repair (150).

After a double strand break, ataxia telangiectasia mutated (ATM) is activated

through autophosphorylation and a signalling molecule encoded by ATM is

activated. ATM is also one factor involved in protein phosphorylation in both

DNA repair and regulation of the cell cycle (151). The RAD50/MRE11/NBS1

(MRN) complex is phosphorylated by ATM, leading to exposure of the 3´end

of the DNA at the DBS site, a process also involving breast cancer

susceptibility gene 1 (BRCA1) (152). After this, the repair goes through either

the HR pathway or the NHEJ pathway.

In HR, a sister chromatid is acquired and therefore this repair pathway only

occurs in S or G2 of the cell cycle (153). In the HR pathway, RAD51, BRCA2,

and DNA dependent ATPase RAD54 mediate an invasion of the 3´end to a

homologous section of the sister chromatid and DNA-polymerase then uses

the complementary strand and prolongs the 3´end past the damaged site.

After this, DNA-polymerase returns to the damaged strand and DNA ligase

ligands the two strands, resulting in a complex called Holiday junction (154).

NHEJ can work through the whole cell cycle and does not need a

homologous chromosome to function and is therefore major pathway for

DNA double-strand break repair (153, 155). In the NHEJ pathway, the DNA

protein kinase (DNA-pk), consisting of a catalytic subunit and a regulatory

subunit, is the main driver of the pathway. The regulatory subunit

(KU80/KU70 heterodimer) binds to the two double stranded ends (156) and

activates the catalytic subunit (DNA PKCS, which is a member of the

phosphinositide 3-kinase (P3-kinase) family). The catalytic subunit then

binds to and stabilizes the DNA ends, processing or trimming them together

with ATM-activated endonuclease Artemis to allow end joining (157). The

ends are then fused together by the XRCC4/DNA ligase IV complex (158).

This pathway is only possible in higher creatures with lots of non-coding

DNA (132, 159, 160).

Direct repair

There are several different mechanisms for direct repair of DNA damage.

Examples of this are the protein product of the methylguanine-DNA

methyltransferase (MGMT) gene that irreversibly removes alkyl groups

from the O6-position of guanine. MGMT silencing is associated with a better

21

response to Temozolomide treatment and better prognosis in glioblastoma

patients (4).

DNA-repair gene variants and glioma

Genetic variations in different DNA repair genes have been associated with

glioma risk. In a study of 771 glioma cases and 752 cancer-free controls 20

tagging SNPs in Ligase 4 (LIG4) and XRCC4 were studied for association

with glioma risk as well as possible gene-gene interaction. For one LIG4

SNP, researchers found an association with increased glioma risk and, for

one of the XRCC4 SNPs, an association with decreased risk. They also

showed that interactions between these two genes were associated with

glioma aetiology and that effects of one gene might not be strong enough to

be detected if it is linked to another functional gene (161).

In another study, 1,127 tagging and 388 putative functional SNPs in 136 DNA

repair genes were studied for association with glioma risk in 1,013 cases and

1,016 controls. Sixteen SNPs significantly associated with risk were found in

chromatin assembly factor 1, subunit A (CHAF1A), nei endonuclease VIII-

like 3 (NEIL3), ERCC1, RPA3, DNA cross-linked repair 1B (DCLRE1B),

TP53, ataxia telangiectasia and Rad3 related (ATR), POLD1, and

melanocyte-stimulating hormone 5 (MSH5). The strongest and most

significant association with risk was found in CHAF1A (162).

In another study on 373 glioma cases and 365 cancer-free controls, the 18

functional SNPs in DNA repair genes were studied for association with

glioma risk. Researchers found six polymorphisms located in ERCC1,

XRCC1, APEX1, PARP1, MGMT, and LIG1 associated with glioma risk, and,

in an analysis of the cumulative genetic risk, they found a significant gene-

dose association with increasing numbers of unfavourable genotypes of the

same SNPs and glioma risk. They found that MGMT was the predominant

risk factor for glioma and they also found a strong interaction between

exposure to ionizing radiation, PARP1, MGMT, and APEX nuclease 1

(APEX1) (163).

In a study of 119 glioma and 180 cancer-free controls researchers found a 3.5

times increased glioma risk with the G allele in XRCC1 Arg399Gln. In the

same study, they also found a plausible protective effect of heterozygote

genotype VA of PARP1 Val762Ala. This decrease in risk was, however, lost

when combined with the G allele in the XRCC1 locus (164). These results are

in line with the results found on XRCC1 and PARP1 in the previously

mentioned study by Liu et al. (163).

22

In another study of 590 glioblastoma 100 SNPs previously found associated

with glioma in GWAS were studied for association with survival. Two SNPs

in RTEL1 (rs2297440, rs6010620) with a minor allele association with better

prognosis and one SNP in regulator of G-protein signalling 22 (RGS22)

(rs4734443), one in BTB domain containing 2 (BTBD2) (rs11670188), one in

LIG4 (rs73259279), and one on chromosome 3 (rs13099725) with a minor

allele association to shorter survival were found. Polymorphisms were also

studied for association with short-term survivors (STS ≤ 12 months) and

long-term survivors (LTS ≥ 36 months) and an association between one SNP

in LIG4 (rs7325927) and one in BTBD2 (rs11670188) and STS was found.

Additionally one SNP in high mobility group AT-hook 2 HMGA2

(rs1563834), one in VPS8 (rs6765837), two in RTEL1 (rs2297440,

rs6010620), and two SNPs in CCDC26 (rs10464870, rs891835) associated

with LTS were also found. In a survival tree analysis age was found to be the

most important prognostic factor; older patients (> 50 years) homozygote

for the minor allele in LIG4 (rs7325927) had the worst prognosis, whereas

young patients (≤ 50 years) homozygote for the minor allele in RTEL1

(r22297440) and HMGA2 (rs1563834) had the best prognosis. LIG4,

BTBD2, HMGA2, and RTEL1 are all involved in the repair of double strand

breaks (69).

Genetics and association studies

SNPs and association studies

The deoxyribonucleic acid (DNA) strand consists of two long polymers of

nucleotides that run in the opposite direction of each other and form a spiral,

the double helix. A nucleotide is a molecule consisting of a sugar and a

phosphate group that bind together with a nitrogen base, adenine (A),

thymine (T), cytosine (C), and guanine (G). The nucleotides form pairs

where A binds with T and C binds with G (165). Genes consist of sequences

of several nucleotides and each individual has two variants of each gene, one

from the mother and one from the father. The genome consists of 98% non-

coding regions and 99.9% of an individual’s DNA sequence is identical to all

other individuals. In the 0.1 % of the genetic code that differs among

individuals approximately 80 % consist of single nucleotide polymorphisms

(SNPs).

SNPs are variations of a nucleotide which occurs naturally every 200-300

base pair (bp) in the population and creates different variants, alleles, of the

same gene. An individual can be heterozygote (having two different bases,

for example, AT or CG) or homozygote (having two of the same bases, for

23

example, TT, AA, CC, or GG) for a specific SNP. The frequency of different

alleles can vary between different populations, and the lowest allele

frequency at a specific location of the chromosome (loci), the minor allele

frequency (MAF), is the detected frequency of the rare allele in a specific

population. If a variant occurs in less than 1% of the population it is called a

mutation (166). SNPs often occur in the non-coding regions of the DNA, the

introns, but can also occur in the coding regions, the exons, which can lead

to changes in the amino acid sequence and altered protein expression.

These normal variations in the genome can be further studied through

genotyping and used in association studies, where risk or prognosis for a

specific disease can be studied in a population. The linkage disequilibrium

(LD) is the association of alleles in different loci, not necessary on the same

chromosome. LD can be used in association studies to investigate a

candidate gene using fewer SNPs, as alleles in strong LD with each other will

be transmitted together (167). When analysing results from association

studies, one must also keep in mind that the true functional variant might

not be the one measured in the analysis but a nearby allele in LD with the

measured SNP (168).

Haplotype and haplotype blocks

A haplotype is a group of alleles that are close to each other and located on

the same chromosome and therefore tend to be inherited together.

Haplotypes build up blocks, so-called haplotype blocks, where usually a few

common haplotypes, 3-5, cover about 90 % of the haplotype variants that

build up the block (169). In these blocks, there is a strong LD and little

evidence of recombination. Between the blocks, areas of more frequent

recombination can be found, so-called recombination hot spots (170).

Recombination occurs during meioses, the type of cell division creating

gametes (sex cells), when two homologue chromosomes come in contact with

each other and exchanges genetic material (171). Recombination is more

likely to occur for loci located far apart from each other. The sizes of

haplotype blocks can vary and block size has been associated with different

populations For example, European and Asians populations have longer

haplotypes blocks compared to African-Americans and Sub-Saharan

populations (172).

This knowledge of haplotype and haplotype blocks is very useful in

association studies. To cover all common variants in a haplotype and the

surrounding block, usually only a few SNPs, so-called haplotype tagging

SNPs, are needed because of the strong LD among SNPs in the same

haplotype and the limited number of different haplotypes in a block (172).

24

Aims

I. To study the association of IgG levels to varicella zoster virus,

adenovirus, Epstein-Barr virus, and cytomegalovirus and glioma risk.

II. To study if polymorphisms in EGF and EGFR are associated with

glioblastoma outcome.

III. To study if polymorphisms in VEGF and VEGFR2 are associated with

glioblastoma outcome.

IV. To study if polymorphisms in DNA repair genes are associated with

glioblastoma outcome.

25

Material

Study population

Paper I

In paper one, we studied 197 glioma cases and 394 controls originating from

three cohorts, The Northern Sweden Health and Disease Study – The

Medical Biobank (NSHDS), The Malmö Diet and Cancer Study (MDCS), and

the Diet, Cancer and Health cohort from Copenhagen. The glioma diagnosis

was identified through linkage to the cancer register and controls were

collected from living individuals matched for age, gender, and cohort, with

no brain tumour history at the time of case diagnosis. The median age at

blood sample for cases was 55.4 years and for controls 55.3 years, and

male/female ratio was 47.7%/52.3%. For NSHDS and MDSC Systematized

Nomenclature of Medicine (SNOMED) was available (Figure 4).

Figure 4 Glioma subclasses according to Systematized Nomenclature of

Medicine (SNOMED) for the three cohorts.

Study

population

197 cases

394 controls

NSHDS

79 cases

158 controls

MDSC

45 cases

90 controls

Diet Cancer

and Health

73 cases

146 controls

61

Glioblastoma

SNOMED

94403

8

Astrocytoma

Grade 1-2

SNOMED

94003

94203

94213

32

Astrocytoma

Grade 3

SNOMED

94013

14

Oligodendro-

glioma

SNOMED

94503

94513

94603

2

Oligoastro-

cytoma

SNOMED

93823

5

Malignant

glioma

SNOMED

93803

2

SNOMED

not

available

73

SNOMED

not

available

26

Northern Sweden Health and Disease Study

NSHDS is a large population-based cohort consisting 166,000 randomly

selected men and women and blood samples from 278,000 sample

occasions. NSHDS consists of three sub-cohorts, all containing blood

samples and questionnaires: The Västerbotten Intervention Program (VIP),

The Västerbotten Mammary Screening Program, and the Northern Sweden

MONICA (Monitoring Trends and Determinants in Cardiovascular Disease)

Project. In the VIP cohort, all individuals since 1985 have been asked to

participate in a health study the year they turn 40, 50, and 60, and, by June

2006, the cohort comprised 94,630 samples from 74,690 individuals.

Between 1995 and 2006, blood samples have been collected in the Mammary

Screening program (women aged 55-69 are screened for breast cancer with a

mammography every second year), and these have been added to the VIP

cohort. In 2007, there had been 48,000 sampling occasions from 27,500

women. About 50% of the women in the mammography cohort had also

attended VIP. The MONICA Project contains samples from a population-

based screening for risk factors associated with cardiovascular diseases. The

screening was carried out in 1986, 1990, 1994, 1999, and 2004. In all, 14,000

sampling occasions of 9,000 individuals aged 25-64, were collected. 50% of

the individuals are also included in VIP (173-175).

The Malmö Diet and Cancer Study

MDSC, a population-based prospective cohort study, was started in 1991 in

order to study the impact of diet on cancer incidence and mortality. Initially,

all living subjects in Malmö born between 1926 and 1945 were invited, and,

in 1995, the study was extended to include women born 1923-1950 and men

born 1923-1945. The rationale for including a larger group of young women

than men was to enable studies on breast cancer in premenopausal women.

The only exclusion criteria up front were language problems and mental

retardation. The overall participation rate was 40.8% for men and 38.3% for

women and the mean age at 1 January 1991 was 54.9 years for participants

and 54.3 years for non-participants. In summary, men and women between

the ages of 44 and 74 were recruited between 1 January 1991 and 25

September 1996. A total of 28,098 blood samples were collected and stored

in the medical biobank, and regular follow-up in the national registries of

cancer and mortality has been done. In 2001, a study of potential selection

bias between the participants in MDSC (n0=28,098) and the non-

participants (no=40,087) was conducted regarding cancer incidence and

mortality; researchers also conducted a mail health survey looking at

differences in subjective health, socio-demographic characteristics, and

lifestyle between participants and non-participants. They found that

27

mortality was higher among non-participants compared to participants

during the recruitment period and follow-up. A trend towards lower cancer

incidence prior to recruitment but higher cancer incidence during

recruitment was found for non-participants compared to participants. No

significant difference was found for socio-demographic structure for the two

groups (176, 177).

Diet, Cancer and Health

The Diet, Cancer and Health study from Denmark is a population-based

prospective cohort study that started in 1993 in order to study the relations

between dietary factors, lifestyle factors, and incidence of cancer and other

chronic diseases. From December 1993 to May 1997, 80,996 men and 79,726

women were invited to participate by answering a questionnaire on food and

lifestyle. Respondents underwent a physical examination including, for

instance, blood pressure measurement, height, and weight, and blood

samples were collected. Individuals between the ages of 50 and 64 born in

Denmark and with no previous cancer diagnosis registered in the Danish

Cancer Registry were included. In all, 27,179 men and 29,875 women

participated in the study and blood samples were obtained on 57,053

participants. Differences in socioeconomic factors ware found for

participants compared to non-participants, with a higher number of

educated and married persons among participants, who also had a higher

number of persons from higher socioeconomic groups compared to non-

participants (178).

Papers II-IV

In papers two, three, and four, we studied cases with glioblastoma collected

from 2000 to 2004 as part of the INTERPHONE study, an international

case-control study on mobile phone use and risk of developing a brain-

tumour. A total of 108 cases from Sweden and 68 cases from Denmark were

collected and a pathology review was conducted according to the 2007 WHO

criteria. There were 109 men and 67 women. The ages ranged from 20 to 69

and the median age at diagnosis was 56 years and did not differ between the

countries. The mean survival time for the whole group was 15.7 months, 16.1

for the Swedish cases and 15.1 for the Danish cases.

The INTERPHONE study

The INTERPHONE study is a large international case-control study in which

the association between brain tumour risk and mobile phone use was

investigated. The study included 16 study centres from 13 countries:

Australia, Canada, Denmark, Finland, France, Germany, Israel, Italy, Japan,

28

New Zealand, Norway, Sweden, and the UK. Cases were collected between

2000 and 2004 from neurological and neurosurgical facilities or cancer

registries and diagnosis confirmed either histologically or on unequivocal

diagnostic imaging. One control was matched to each case except for

Germany, where two controls were matched to each case. Controls were

matched to cases on age, sex, and region of residence, and for the subjects

from Israel, also on ethnic origin. On cases and controls, detailed

information on mobile phone use was collected through interviews. Proxies

were used when the study subject was too ill to participate or had died.

Information was collected on socio-demographic factors, occupational

exposure to electromagnetic fields and ionizing radiation, medical history,

smoking, medical ionizing radiation exposure, and non-ionizing radiation

exposure. Information on the anatomic location and histological location of

tumours was collected for the cases (22).

Confirmation

Papers II and III

Confirmation on significant SNPs in papers II and III was made using a

dataset from The M. D. Anderson Cancer Center (MDACC), consisting of 638

glioblastoma cases recruited from 1990 to 2008 with follow-up until April

2009. All cases were at least 18 years of age at diagnosis, caucasian, with

primary glioblastomas; 397 were male and 241 were female with a mean age

at diagnosis of 52.3 years. The cases were followed from date of diagnosis

until date of death or date of last contact for the cases still alive. At follow-up,

586 cases were deceased and 52 cases alive. Cases with a history of prior

cancer or who previously had treatment for their glioblastoma were

excluded. No treatment data was available in the confirmation cohort.

Paper IV

Confirmation on significant SNPs in the fourth paper was made using a

cohort containing 295 glioblastoma cases from northern UK. In 97 of the

cases, follow-up data was missing and 77 cases had poor DNA quality,

leaving 121 cases for confirmation. No treatment data was available. The

cohort consisted of 78 male and 43 female cases. The median age at

diagnosis was 55 years and the mean survival time 14.8 months.

29

Methods

Paper I

ELISA and immunoflourescence

Enzyme-linked immunosorbent assay (ELISA) can be used to detect a

substance, for example antigen, in a liquid sample.

We analysed levels of IgG antibodies against adenovirus, CMV, and VZV

using ELISA. For EBV we used ELISA to analyse IgG-anti-Epstein-Barr

Nuclear Antigen-1 (EBNA-1). EBNA-1 is a viral protein that is expressed in

latent EBV infections. It becomes present 2-4 months after the primary

infection and is then present life long.

For EBV, we also analysed IgG against Viral Capsid Antigen (VCA), which

appears within a week of an EBV infection and then is present life-long. For

this analysis we used immunoflourescence (IF), a technique where

antibodies are chemically conjugated to a fluorescent dye. The antibodies

bind to the antigen of interest and can then be measured by different IF

techniques. In our study, a microscope was used and the samples were read

and fluorescence activity graded by an experienced microscopist who was

blinded to case/control status.

Binary logistic regression

Binary logistic regression is a regression model that can be used when

working with binary variables (0/1, dead/alive, healthy/sick,

positive/negative). When calculating logistic regression, you get an odds

ratio (OR) describing how strong the association is for the variables you are

testing.

We studied the association between IgG levels and glioma risk using binary

logistic regression. We divided the control group into four same-size

quartiles using the IgG levels and then divided the cases in the same way,

based on the cut-off values from the control quartiles. We then compared the

quartiles in cases and controls using the lowest quartile as reference. The

odds ratios were adjusted for age at blood sample, sex, and cohort

(Denmark, Malmö, Umeå). We also repeated the test using only cases with at

least two years between blood sample and glioma diagnosis to limit the risk

of disease or treatment affecting our results.

30

Papers II-IV

Medical records

Clinical data was collected by a review of patient journals. Request of journal

copies were sent to the participating hospitals in Sweden and, for the cases

from Stockholm, the data was collected at the hospital. Details on date of

diagnosis, follow-up, surgery, chemotherapy, and radiotherapy were

retrieved from the journals with use of a standardised predefined form.

Treatment data are shown in Table 4. In all data was incomplete for 33 of the

cases. In 11 cases, date of diagnosis was missing and follow-up was missing

in an additional 10 cases. Follow-up date was set as either date of death or,

for living cases, date of last follow-up in patient record or 31 October 2006,

whichever came first. 89.8% of the cases were diseased at follow-up.

Table 4 Treatment data for the Swedish and Danish cases used in papers II-

IV.

Sweden

No. 108

Denmark

No. 68

Total (%) Missing (%)

Total (%) Missing (%)

Gross total

resection

6 (5.5) 1 (1.5)

Yes 26 (24.1) 24 (35.3)

No 76 (70.4) 43 (63.2)

Radiotherapy 7 (6.5) 2 (3)

Yes 90 (83.3) 57 (83.8)

No 11 (10.2) 9 (13.2)

Chemotherapy 13 (12.0) 10 (14.7)

Yes 69 (63.9) 14 (20.6)

No 26 (24.1) 44 (64.7)

31

SNP-selection and genotyping

In papers II and III, we used information from the dbSNP, HapMap, and

SNPper databases. We then used the Haploview software to identify tag

SNPs and LD to cover the genes of interest. In papers II and III, we used a

minimum r2 of o.9 and a minor allele frequency of 5% in a HapMap CEPH

(CEU) population (Utah residents with northern and western Europe

ancestry). In paper IV, over 35,000 SNPs in 141 known DNA repair genes

were selected from an inventory of DNA repair genes done in a previous

study (179). The genes were then updated using the University of California,

Santa Cruz (UCSC) Genome Browser Database and the National Center for

Biotechnology Information (NCBI) Entrez Gene database and SNPs were

selected using dbSNP. To shorten the list, r2>0.8 and MAF>1% in a HapMap

CHEP (CEU) population was used and, after elimination of SNPs unsuitable

for genotyping, 1,127 tagSNPs in 136 genes were selected and we also added

388 known functional SNPs using PupaSuite web-based software and the

Illumna in-house algorithm. R2 is a measurement of how strong the

correlation or LD is between two SNPs. A high r2 indicates a high correlation

and, at the maximum r2 of 1 the two SNPs are in perfect LD with each other.

DNA for genotyping was extracted using conventional methods and

quantified using PicoGreen. Genotype validation was performed on 14 family

trios with available HapMap data and the concordance was 100%. In 90

samples, all SNPs were tested twice for internal concordance, which was

100%. The call rate was 80% in papers II and III.

In paper IV, the samples were genotyped using customised Illumina

GoldenGate Arrays and it was determined that genotyping of a sample failed

if genotypes from less than 80% of all loci were returned and genotyping of a

SNP was considered to have failed if a genotype was returned for less than

95% of all samples. A GenCall score less then 0.25 was set as no-call.

Statistical analyses

Cox proportional hazards model

Cox proportional hazard model is a statistical model for studying survival.

The model explores the changes in hazard (risk) over time when covariates

(factors that might be predictive of outcome) are at baseline, as well as how

the hazard varies due to explanatory covariates. If the covariate is not

directly explanatory, they can be confounding, meaning that they do not

affect the outcome directly but affect the true explanatory covariate. It is

therefore important to identify and control for possible confounding factors

32

in the statistical analyses. The effects of covariates on hazard can be

described as hazard ratios.

In papers II-IV, we used the Cox proportional hazard ratio model in SPSS to

study a possible association between different polymorphisms in the

EGF/EGFR and VEGF/VEGFR pathways and genes involved in DNA repair

and glioblastoma outcome. The major allele was set as categorical variable

and all hazard ratios were adjusted for possible confounding factors such as

country, age, sex, and treatment.

Correction for multiple testing

In the forth paper, we analysed a total of 1,458 polymorphisms in 136 DNA

repair genes and possible association with outcome. Because of the large

amount of SNPs tested, we also corrected the results for multiple testing

using a method based on permutation. In this test the SNPs are randomly

assigned to a group and then p-values are calculated; the lowest p-value in

each group is saved and then the procedure is repeated a number of times (in

our study 10,000). The lowest p-values can then be plotted in a graph and

should form a normal distribution curve and its mean value is the lowest

average p-value that can be expected with a random division of the groups.

We used a cut-off of 95%, giving us a 5% false positive rate in the random

test (180).

33

Results

Paper I

In paper I, we studied whether IgG levels of CMV, EBV, Ad, and VZV are

associated with glioma risk in 197 cases compared to 394 controls. These are

very common viral infections in the population in general and we found that

a high number of both cases and controls had antibodies against the viruses,

but there were no significant differences in number of seropositives or the

mean age at blood sample between cases and controls. When comparing the

quartiles in cases and controls, we found no significant difference in Ad,

CMV, or EBV IgG levels. In VZV, we found a trend of lower OR with

increasing quartile. This trend was significant when restricting the analysis

to only cases with at least two years between blood sample and glioma

diagnosis (results shown in Table 5).

Table 5 Cases and controls OR and 95% CI for IgG for VZV. All glioma

cases, and cases with more than 2 years between blood sample and glioma

diagnosis.

Glioma cases versus controls Cases > 2 years between blood sample and glioma diagnosis versus controls

No. (%) OR (95% CI) No. (%) OR (95% CI)

1st quartile

55 (28.1%)

1.0 48 (29.3%)

1.0

2nd quartile

55 (28.1%)

0.85 (0.53-1.36) 47 (28.7%)

0.84 (0.51-1.37)

3rd quartile

43 (21.9%)

0.74 (0.45-1.23) 35 (21.3%)

0.70 (0.41-1.19)

4th quartile

43 (21.9%)

0.68 (0.41-1.13) 34 (20.7%)

0.63 (0.37-1.08)

P-trend 0.06 0.029

34

Papers II and III

In the second paper, we studied the association between polymorphisms in

EGF and EGFR and glioblastoma outcome. In order to make a

comprehensive tagging of the genes, 30 tagging SNPs in EGF and 89 tagging

SNPs in EGFR were chosen and evaluated. An initial screening of outcome

was conducted for each SNP using the homozygotes for the major allele as

categorical variable. All significant HR (p≤0.05) were then adjusted for age,

sex, country, and treatment.

In EGF seven SNPs significantly associated with glioblastoma survival were

found. All seven SNPs had a minor allele association with shorter survival

and were located in haplotype block 4. Two of the SNPs were located in the

promoter region and the other five in different introns (5, 7, 10, 11, 13). The

analyses were also made for the Swedish and Danish cases separately and

the same minor allele association with poor prognosis was seen. The median

survival time for homozygotes for the major allele in six of the seven SNPs

ranged from 14.4 to 15.1 months, and the median survival time for

homozygotes for the minor allele from 8.6 to 8.9 months. In one of the

promoter SNPs (rs6533477), there were no homozygote cases for the minor

allele; in this, an association with shorter survival in heterozygote cases (11.7

months) compared to homozygote cases for the major allele (13.1 months)

was seen.

Four of the SNPs were available for confirmation in the MDACC dataset. The

same trend towards minor allele association with shorter survival was seen

but, this was not significant. This trend was stronger and border-significant

when restricting the analyses to include only subjects over 50 years of age.

This was done to enrich for primary glioblastoma due to differences in

median age at diagnosis (56 in the Swedish/Danish dataset versus 54 in the

confirmation set), and median survival time (12.8 months in the

Swedish/Danish dataset versus 15 months in the confirmation set), which

could indicate more secondary glioblastoma, as the cases were younger and

lived longer in the confirmation set. Hazard ratios in the confirmation

dataset were adjusted only for age and sex, as treatment data was not

available.

In EGFR we found four SNPs significantly associated with glioblastoma

prognosis. All SNPs were located in different intrones (1, 4, 7, 9) and none of

the SNPs were located in the same haplotype block. In two of the SNPs, the

minor allele was associated with longer survival and, in the other two, the

35

minor allele was associated with shorter survival. None of the significant

SNPs were available for confirmation in the MDACC dataset.

In paper III, we studied the association between polymorphisms in VEGF

and VEGFR2 and association with glioblastoma survival. In VEGF, 27

tagging SNPs and, in VEGFR2, 17 tagging SNPs were analysed. No

significant association between any of the VEGF SNPS and glioblastoma

survival was found. In VEGFR2 we found one SNP located in intron 1

(rs1252008) with an association with longer survival for homozygotes for the

minor allele compared to homozygotes for the major allele, HR 0.45; 95% CI

(0.21-0.95). No association with survival was seen for the heterozygotes HR

1.09; 95% CI (0.74-1.62). The SNP was not available for confirmation in the

MDACC dataset.

In another VEGFR2 SNP located in the promoter (rs2071559) we saw an

association between heterozygotes and shorter survival when compared to

homozygotes for the major allele. No significant association with survival

was seen for homozygotes for the minor allele. The SNP was available for

confirmation in the MDACC dataset, but no association with survival was

found.

Paper IV

In paper IV, we studied the association between polymorphisms in DNA

repair genes and outcome in 172 glioblastoma cases from Sweden and

Denmark. First, a screening of all SNPs was conducted in the

Swedish/Danish dataset where a total of 159 glioblastoma were available

after genotyping as 13 had poor DNA quality and an additional 21 had

missing follow-up, leaving 138 cases for the analyses. In all, 142 SNPs

significantly (p<o.o5) associated with outcome were found. In the next step,

the 142 significant SNPs were validated in a separate dataset from northern

UK and 15 SNPs were found significantly associated with outcome. The SNPs

also affected survival in the same way (increased/decreased), as in the

Swedish/Danish dataset. These 15 SNPs were then analysed again in 121

glioblastoma from the Swedish/Danish dataset with available clinical data

and all HR were adjusted for country, sex, and therapy. After this step, nine

polymorphisms were significantly associated with glioblastoma survival

(p<0.05). In the last step, a permutation test was conducted, leaving two

SNPs significantly associated with glioblastoma survival. Both the significant

SNPs were located in the RECQL4 gene, were in strong LD with each other,

and had a minor allele association with longer shorter. When looking at the

seven SNPs significant before the permutation step but not after, two were

located in the MSH2 gene, and five were located in the RAD51L1 gene. In

36

MSH2 the two SNPs were in strong LD with each other and in both SNPs

heterozygotes had a shorter survival than homozygotes for the major allele

(no cases homozygotes for the minor allele were found). The remaining five

polymorphisms significant before the permutation step were all found in

RAD51L1 and were in strong LD with each other, and four of the SNPs were

located in the same haplotype block. The four SNPs on the same haplotype

block had an almost identical distribution of cases between heterozygotes

(32 cases and an additional 3 cases for rs6573805) and homozygotes for the

minor allele (three cases). And three of the SNPs had an identical

distribution in all groups (homozygotes for the major allele, heterozygotes

and homozygotes for the minor allele).

37

Discussion

Paper I

Viruses have been found to play an important role in the development of

different types of cancers (85-87). In astrocytoma products from viruses

such as BK-virus, JC-virus, and Simian virus 40 have been detected in

tumour tissue, but no clear role in glioma development has been found (88,

89, 181). CMV is a common virus in the population that can be reactivated

throughout life and is present in several different parts of the body. CMV

gene products have been found in glioblastoma cells but not in the

surrounding normal brain tissue (90). It has been hypothesised that cancer

cells might activate the immune system which then tries to eliminate the

cells as they are viewed as non-self and, by doing so, creates an inflammation

in the area. CMV might be carried into the inflamed area by infected

monocytes/macrophages and become reactivated and transmitted to tumour

cells, making it hard for the immune system to detect them (182). CMV has

been studied for association with glioma and has an affinity for glial cells

which could allow the virus to affect, for example, tumour progression,

angiogenesis, production of growth factors, and tumour invasiveness (91,

182). In glioma cell lines, CMV has been found to activate telomerase, an

enzyme crucial for cellular immortalization (183). These findings indicate

that CMV might have an oncogenic function and could potentially play a role

in glioma development. However how big the influence of viral proteins are

in glioma progression is still debated (184). Adenovirus is a neurotropic virus

that has been detected in paediatric brain tumours (96). EBV has also been

associated with human cancer and is present in and an important risk factor

for CNS lymphoma in immunosuppressed patients (185). VZV is a

neurotropic virus that remains dormant in the neural ganglia after the

primary infection. VZV can be reactivated and cause Shingles. However

reactivation occurs rarely, approximately once every 20 years.

Previous studies on allergy and asthma support the hypothesis that the

immune system might play an important role in glioma development (43, 44,

46). IgG levels for CMV, EBV, Ad and VZV have previously been studied in

glioma, and an inverse association with glioma risk for having high IgG

levels for VZV has been found (186, 187). These studies were done on

prevalent cases with blood taken at or after diagnosis, making it a possibility

that the findings were due to a confounder, such as the tumour or

antitumour treatment or steroids. Because of this, we used prediagnostic

samples from three different bio banks to minimize the risk of disease or

38

treatment affecting our results. We found that high IgG levels for VZV were

present in a higher percentage of controls compared to cases, especially

when restricting the analyses to only include cases with at least two years

between blood sample and glioma diagnosis. This was done to further limit

the risk of subclinical disease affecting our results. For CMV, EBV, and Ad no

association was found. These findings are in line with previous findings on

IgG levels measured at diagnosis and might suggest that the immune system

plays a role in glioma development. It has been hypothesised that a strong

immune system might be more alert in detecting and destroying small

cancer clusters, which could be one possible explanation of our findings. As

we did not see any association of IgG for the other viral infections, a non-

specific IgG bound protection against glioma seems unlikely. One could

speculate that a specific association with the VZV IgG is more likely. When

comparing these viruses, VZV is the most neurotropic and remains dormant

in the neuroganglia and perhaps even in neurons in the brain, lifelong. One

could therefore speculate that the immune system could be protective

against glioma if VZV has a role in glioma genesis. The negative results for

the other viruses might also depend on the fact that these are common

viruses in the population and larger studies are needed for efficient power to

detect an association in immune response to the other viruses and glioma

risk. Another possibility is that the VZV has special characteristics or

displays viral products on the cell surface of the tumour cell, which might

lead to glioma cells being easier to detect by VZV antibodies compared to

antibodies for other viruses. Association with other viruses that might act as

a confounder is another possibility, but there are no known associations

between VZV and other viruses and IgG is a very virus-specific antibody.

The findings of viral genome and DNA in glioma might be associated in some

way to glioma genesis. However it is important to consider that the virus

might be drawn to the immunosuppressive environment in the tumour; that

is the tumour might be there before the virus and not the other way around.

Even so, viruses drawn to the tumour might be part of the progression of

glioma but not the sole cause. The immune system can be looked upon as a

separate factor in glioma risk, and, as viruses might have a causal

association, the immune system might have a protective role. These, of

course, are two factors that interact and patients that easily get infected or

who more easily get reactivation of these viruses might have a weaker

immune response and in that way be at higher risk for developing glioma.

Case-control studies

We used a case-control study design to evaluate the potential role of IgG

levels for viruses on glioma risk. This method is preferable when studying

39

rare diseases as one can take cases that have already developed the disease

and compare them with disease-free controls for the exposure of interest.

This is much less time consuming than following cohorts exposed to a

specific agent to see if they develop the disease. One problem with this type

of design is that there might be unknown factors (confounders) affecting the

results. To minimize this risk, cases are often matched to controls on

potential confounders such as age, sex, and area of residence.

Papers II and III

In paper II, we studied the association of polymorphisms in EGF and EGFR

and glioblastoma outcome by performing a comprehensive tagging of both

genes. In EGF, we analysed 30 SNPs and found seven SNPs associated with

glioblastoma outcome, all located in haplotype block four and all with a

minor allele association with poor prognosis. In EGF, previous studies have

been focused on a functional SNP in EGF (EGF 61 A/G), in which the minor

allele has been associated with higher EGF expression (100), which is known

to promote tumour angiogenesis and tumour progression (188). This

functional polymorphism is located on the same haplotype block as the seven

SNPs significantly associated with prognosis in our study and they are

therefore likely to be transmitted together.

No clear association with prognosis for the EGF 61 A/G has been found in

previous studies. In a small study of 42 glioblastoma with available

treatment data (surgery, radiotherapy, and chemotherapy) an association

with both poor prognosis and increased tumour recurrence was seen in

heterozygotes or homozygotes for the rare allele G compared with

homozygotes for the common allele A (101). In a study of 197 glioma cases an

association for the EGF 61 A/G and glioma risk was found. A separate

analysis was made for outcome in the glioblastoma cases (n=44), but no

association was found (98). In a study of 209 glioblastoma cases with

available treatment data, no association with either risk or prognosis was

found for the EGF 61 A/G, but some effects on progression-free survival were

seen (100).

The seven SNPs we found significantly associated with survival were located

on the same haplotype block, in strong LD with each other, and had a minor

allele association with poor survival, which makes it possible that this is a

true finding. As EGF 61 A/G is located on the same haplotype block, it is

likely that this polymorphism is the functional variant in the region and, as

EGF 61 A/G in some previous studies has been found to have a minor allele

association with poor prognosis, this could be in line with our results.

40

However, other studies have failed to detect an association with prognosis.

One reason for this could be that these are small studies and, in one study,

treatment data was not available, making it possible that the extent of

surgery or postoperative treatment significantly affected the results. Four of

the significant polymorphisms in our study were available for confirmation

in the MDACC dataset. However, no significant association with prognosis

was seen. When looking at the characteristics of the Swedish/Danish cohort

in comparison to the MDACC cohort, a difference in median age at diagnosis

and median survival time was found, with lower median age at diagnosis and

longer median survival time in the MDACC cohort (54 vs. 56 years and 15 vs.

12.8 months). As age is a known prognostic factor, we decided to also

validate only in cases over 50 years of age in the MDACC cohort and found a

non-significant trend towards minor allele association with survival. No

treatment data was available for the MDACC cohort, making it possible that

the extent of surgery or postoperative treatment affected the results. The

cases in the MDACC cohort were collected between 1990 and 2008, while the

cases in the Swedish/Danish cohort were collected between 2000 and 2004,

making it possible that a larger number of cases in the MDACC cohort

received standard treatment with concomitant radiotherapy and

Temozolomide as first-line treatment. This has proven to be an important

treatment, doubling median survival (3). As most of the cases in the

Swedish/Danish cohort were diagnosed before this finding, fewer patients

received Temozolomide or received it later in the treatment course,

compared with cases in the MDACC cohort. EGFR mutation status was not

available in either the Swedish/Danish cohort or the MDACC cohort, which

might be of importance as a mutated and constantly active receptor reduces

the impact of elevated EGF levels. Not all glioblastoma have mutated EGFR

and the polymorphisms in EGF might be stronger prognostic factors for

those with unmutated receptors. It would be interesting to study these SNPs

in a cohort with known mutation status.

In EGFR we analysed 89 tagging SNPs and found four associated with

glioblastoma outcome, two with poorer and two with better prognosis. None

of the SNPs were available for confirmation in the MDACC dataset.

Activation of EGFR starts a cascade of downstream events that play an

important role in cell proliferation, differentiation, growth, and survival. In

glioma, EGFR has been found to participate in tumour progression and to be

a prognostic factor in low-grade and anaplastic astrocytoma (44, 105). In up

to 50% of all glioma the receptor is amplified and 20-30 % of glioblastoma

with EGFR amplification have a constantly active receptor due to a deletion

of exon 2-7 (EGFRvIII). EGFR amplification has been studied for association

with glioma and glioblastoma without finding a clear association. One of the

polymorphisms with a minor allele association with poorer survival

41

(rs4947986) is located in the exon7/intron border and is close to the

common deletion and, therefore, one could speculate that this SNP or a near

by SNP could have a functional role and be of importance for glioma

progression. In a later study, this polymorphism was associated with glioma

risk (55), and recently two loci in EGFR have been associated with glioma

risk through large GWA studies (52-54, 189), raising further evidence that

EGFR is important in glioma progression. However, as 89 SNPs were tested

and four were associated with survival, this is very close to what we should

find by chance with a p-value of 0.05, and therefore the role of EGFR in

glioblastoma survival is still unclear.

VEGFR2 is one of three receptors in the VEGFR family. Upon activation, this

receptor promotes angiogenesis, proliferation, and cell survival. In

glioblastoma, inhibition of VEGFR2 has been shown to increase cell death

caused by ionizing radiation. This suggests that VEGFR2 might be a factor in

both glioma development and prognosis. Therefore, we analysed 27 tagging

SNPs in VEGFR2 and 17 tagging SNPs in VEGF for association with

glioblastoma survival. We found no significant polymorphisms in VEGF

associated with outcome. In VEGFR2 we found two SNPs significantly

associated with glioblastoma survival, which is near the amount of

significant variants we would expect to find with a significance level of

p=0.05 and neither of the two SNPs had a dose-response pattern that

associated outcome with the major or minor allele. One of the two SNPs was

available for confirmation in an independent dataset with no association

with survival in that cohort. Taken together, all these reservations indicate

that the results are most likely due to chance. In recent years, a monoclonal

antibody against VEGF, Bevacizumab, has shown promising results in

second-line treatment of glioblastoma. This gives some evidence that the

VEGF/VEGFR pathway is of importance in glioblastoma. One reason that we

failed to detect an association with outcome might be that polymorphisms in

these genes are not directly associated with outcome but have an association

with treatment outcome when treated with Bevacizumab; since our cases

were diagnosed in 2000 to 2004 none of them received this treatment.

Paper IV

We studied 1,458 polymorphisms in 136 DNA repair genes for association

with glioblastoma outcome. After confirmation in a separate dataset and

adjusting for age, sex, and therapy we found nine SNPs significantly

associated with glioblastoma outcome (p<0.05) located in MSH2, RAD51L1,

and RECQL4. After adjusting for multiple testing, two of the polymorphisms

remained significant, both located in RECQL4 and both with a minor allele

association with better prognosis. RECQL4 has been suggested to interact

42

with RAD51 and participate in repairing double-strand breaks after

radiation, while MSH2 is part of the mismatch repair pathway. RAD51L1 is a

member of the RAD51 family and is involved in the DNA repair of double

strand breaks.

In the nine SNPs significant before controlling for multiple testing, strong

LD was seen for SNPs located in the same gene and they also had a nearly

identical distribution of cases heterozygote and homozygote for the minor

and major allele. These also had a clear dose-response pattern with a minor

allele association with either better or poorer prognosis. In validating data in

a separate dataset, adjusting for treatment and multiple testing, we tried to

minimise the risk of false positive findings that multiple tests, small sample

sizes, and rare polymorphisms might render. In doing so, the risk of type 2

errors is important to consider. Polymorphisms that are important factors in

treatment outcome might be eliminated when adjusting for treatment

parameters and correcting for multiple testing with a 10,000 permutation

test is very stringent and might lead to false negative findings.

In a previous study on 590 primary glioblastoma, an association between

four genes involved in the DNA double-strand break repair pathway, LIG4,

BTBD2, HMGA2, and RTEL1, and glioblastoma survival was found (69).

In a study on low-grade glioma, the same 1,458 tagging SNPs in 136 DNA

repair genes were studied for association with outcome. A cohort of 81 low-

grade (grade II) and anaplastic (grade III) glioma was used and significant

findings on a p<0.05 level were analysed in a control cohort of 72 grade II

and III glioma. After confirmation, a total of eight SNPs in five DNA repair

genes were found (ATM, NEIL1, NEIL2 ERCC6, and RPA4) associated with

outcome. After adjusting for treatment, gender, age, and country, one

polymorphism in ERCC6 was found significantly associated with improved

glioma outcome (190).

Several studies have also found an association between different DNA-repair

gene polymorphisms and glioma risk (161-164).

Repair of damaged DNA is crucial for cell survival and gene integrity. This

knowledge is something we take advantage of in treatment of cancer. In

glioblastoma, the standard non-surgical treatment is radiotherapy, which

induces DNA double strand breaks, and concomitant Temozolomide, an

alkylating agent that methylates DNA. The tumour cells’ ability to repair

these damages is an important reason for treatment failure. For example,

MGMT can repair DNA damaged by methylation and MGMT silencing

enables an effective treatment and is an important prognostic factor in

glioblastoma (4). Polymorphisms in different DNA repair genes could

therefore be both a direct prognostic factor involved in progression of the

43

tumour, as well as associated with treatment failure. These pathways could

therefore be important targets for future drugs to optimize treatment

outcome.

DNA repair gene polymorphisms also seem to play an important part in

glioma susceptibility. One of the few known risk factors for glioma is ionizing

radiation and one could hypothesise that people with compromised DNA

repair pathways therefore would be at higher risk of developing glioma.

44

Conclusions Based on the results from these studies, the following conclusions can be

made:

I. High levels of IgG for varicella zoster virus decrease the risk of glioma;

however, IgG levels for adenovirus, cytomegalovirus, and Epstein-Barr virus are not associated with glioma risk.

II. Polymorphisms in EGF are associated with glioblastoma prognosis; however, the association of polymorphisms in EGFR with glioblastoma outcome is more uncertain.

III. Polymorphisms in VEGF and VEGFR2 are not associated with glioblastoma outcome.

IV. Polymorphisms in the DNA repair genes RAD51L1, MSH2, and RECQL4 are associated with glioblastoma outcome.

45

Future perspectives

The idea that a strong immune system could protect against cancer and,

more specifically, glioma is an interesting thought. A validation of the

findings of higher IgG levels for VZV in controls compared to cases would be

an important next step, and to do so in a similar way with blood samples

taken before diagnosis to limit disease and treatment influences on the

results. It would be valuable to do this in a larger cohort as these are

common viral infections therefore confirmation should also be done for IgG

for the viruses where we did not find a significant association to ensure that

the negative findings were not due to small sample sizes. If these are true

findings with only high IgG levels for VZV associated with glioma risk, it is

more likely that it is something specific with either the VZV or the immune

response against this virus and not the immune system as a whole that is

associated with glioma risk, making it a highly interesting area for future

studies.

In recent years, several large GWAS have studied polymorphisms in low-

penetrance genes and their association with glioma risk, and seven risk loci

have been identified. There are fewer studies on polymorphisms in low-

penetrance genes and association with glioma outcome. It would be

interesting to study low-penetrance genes in larger cohorts to find potential

polymorphisms associated with outcome in both low and high-grade glioma,

as robust findings might give an opportunity for prognostic markers and

targeted treatments. EGF/EGFR and DNA repair pathways are highly

interesting for such studies as polymorphisms associated with both risk and

outcome have been found. However, the variants active in glioma

progression might not necessarily be the ones important for outcome, and

when studying outcome, one must consider that the polymorphisms might

not associate directly with glioma/glioblastoma outcome but rather with

treatment outcome, especially in the case of polymorphisms in DNA repair

genes that might be involved in restoring the damage done after antitumour

treatment. They might therefore be potential targets for new treatments or to

enhance treatment effects and also possibly tools to find responders up front.

Although we found no association between VEGF and VEGFR2 and

glioblastoma outcome, these are very interesting genes that should be

studied further. It would be interesting to study these genes in patients

treated with Bevacizumab to see if polymorphisms are associated with

treatment outcome and could be tools to select patients with a high chance to

respond up front.

46

Historically, very little could be done to alter the natural course of the

disease in glioma and especially glioblastoma patients. As we learn more

about the aetiology and prognostic factors for glioma, we come closer to

finding new ways of detecting cases early and new targets for treatment. The

future in glioma treatment and prognosis is promising as many new

discoveries have been made in the aetiology and genetic pathways involved

in glioma development. I am excited to see what lies beyond the horizon for

these patients.

47

Acknowledgements

Det är så många som på olika sätt bidragit och stöttat mig i arbetet med avhandlingen och utan vars hjälp den aldrig hade blivit verklighet. Jag vill speciellt omnämna några;

Till Beatrice Melin, min huvudhandledare och stora förebild, jag förstår inte hur du hinner med allt, jag är säker på att ett dygn för dig måste innehålla fler timmar än för oss andra. Tack för att du alltid ställer upp med allt från kloka råd till leverans av strömkabel till dator, för att du stöttat mig men även utmanat mig, fått mig att gå utanför min ”comfort zone” och därmed växa i arbetet men även som människa.

Till Ulrika Anderson min biträdande handledare, tack för att du tålmodigt

lotsat mig igenom detta arbete, alltid funnits där när jag behövt fråga eller

diskutera något och för att du alltid ser till att alla siffror stämmer.

Björn Tavelin, du har varit ett ovärderligt stöd i all statistik. Tack för att du

alltid tar dig tid att svara på alla mer eller mindre intelligenta statistik och

SPSS frågor.

Carina Ahlgren, Monica Sandström, Sara Huggert Ranta och

Katrin Sundh som på olika sätt hjälpt till med det administrativa. Carina

för ditt oerhörda tålamod och vänliga påminnelser när jag än en gång varit

sen med att lämna in papper eller svara på mail, förlåt.

Barbro Widmark, tack för all hjälp med att jaga journalkopior.

Irene Eriksson, tack för hjälpen med analyserna till arbete 1 och för att du

tog så väl hand om mig och visade hur analyserna går till.

Ulf Hjalmars, tack för din ovärderliga hjälp med arbete 1 under min

mammaledighet och för att du lugnt, vänligt och med stor förståelse mötte

mig och min son, som just innan vårt första möte kring manuset hade fått sin

3 månaders vaccination, och som för ovanlighetens skull skrek oavbrutet och

kräktes på både mig och golvet. Din kommentar, att det inte var konstigt att

han mådde dåligt då han just genomgått livets första trauma, kommer jag

aldrig att glömma.

Carl Wibom, tack för allt jobb med arbete 4 och för alla gånger du på ett

enkelt och pedagogiskt sätt förklarat för mig helt obegripliga saker som t.ex.

permutation.

To all other co-authors, Roger Henriksson, Thomas Brännström,

Helle Broholm, Göran Hallmans, Per Juto, Patrik Rydén,

Christoffer Johansen, Helle Collartz-Laier, Sara Hepworth,

Patricia McKinney, Lara Bethke, Richard Houlston, Göran Wadell

Anne Tjönneland, Jytte Halkjaer, Jonas Manjer, Martin Almquist,

Yanhong Liu, Melissa Bondy, thank you for your work and valuable

comments in the process of writing the papers. Melissa Bondy, thank you

for valuable input on Table of Contents.

48

Thomas Brännström och Helle Broholm tack för att jag fick sitta med

när ni eftergranskade proverna och för att ni tog er tid att visa och förklara.

Göran Hallmans och Per Juto för att ni tog er tid att svara på mina

frågor.

Till arbetsgruppen och VVLL, Soma, Ulrika, Calle, Anna D, Ulf, Karin,

Anna N, Christina, Anne, Ingrid, Camilla och Florentine, för

intressanta diskussioner och för att jag får ta del av ert fantastiska arbete.

Tack Soma för trevliga och stärkande luncher, lycka till!

Till alla mina kollegor och alla andra arbetskamrater på Cancercentrum, tack

för att ni gör det så roligt att gå till jobbet. Till Elisabeth Karlsson och

Göran Edbom verksamhetschef och biträdande verksamhetschef (tidigare

tvärt om) på Cancercentrum, för att jag fått tid till att göra detta arbete och

för att ni alltid uppmuntrar till forskning.

Till specialisterna i lymfomgruppen, Martin, Ann-Sofie, Karin, för att ni

är fantastiska förebilder och för att jag får tillhöra gruppen även om jag

varken springer fort eller långt (men jag har lärt mig gå ganska snabbt).

Till Ann-Sofie Johansson min kliniska handledare, när jag blir stor vill

jag bli som du!

Till mina underbara vänner och rumskamrater Anna, Berivan, Maja, och

Sussi, tack för att ni alltid finns där, för att ni stöttar och peppar när det går

tungt, för fantastisk kurdisk mat och hummus till frysen, kläder till barnen,

sena stockolmskvällar och personliga pepparkakor, för delat TV och

fruktintresse, för mysiga stugkvällar, goda middagar och mycket skratt. Ni är

ovärderliga!

Tack till alla våra vänner för livets alla trevligheter som så väl behövs under

ett sådant här arbete. Till gamla Vännäs/Berghem gänget Klas och Helena,

Sara och Stefan, Lina och André, Joakim och Johanna, Karolina och

Johan, för att även om det nu blir mer sällan är det alltid lika kul när vi

träffas! Till Joakim och Johanna för mysiga och goda middagar med ännu

godare viner. Till Björn och Cicci, för att ni är så trevliga och för att det

alltid är lika roligt och avslappnat när vi träffas. Till min äldsta och bästa

kompis Lillemor och hennes familj, för att du känner mig, för att oavsett

hur länge det går mellan vi träffas så är allt precis som vanligt och för att ni

tagit ert förnuft till fånga och flyttat hem!

Till Jesper och Theresé samt Birgitta och Patrik, för roliga

syskonmiddagar med sång och dans.

Till Lasse och Ing-Britt mina underbara svärföräldrar, tack för att ni alltid

ställer upp med stort och smått. Tack för hämtning på dagis, för el-dragning,

för limpor och saft och tack för mysiga fiskehelger.

Till mina syskon, Sandra, Kristoffer och Anna. För att vi alltid har så

roligt, för att jag inte känner mig lastgammal (annat än när jag ska

programmera videon) och för att jag vet att ni alltid finns där.

49

Sandra, du är en av dem som fått stå ut med mig och min oro denna höst.

Tack för kloka ord, för hjälp med kläder och fest, många samtal och mail,

tabletter och onsdagskillar, för att du alltid förstår precis och vet vad du ska

säga. Hoppas jag kan vara till samma glädje när det är din tur! Till Sandras

Jens, du är en så fantastisk människa att umgås med! Alltid glad och en

riktig busfarbror. Tack för hjälp med att ordna band.

Till alla mina älskade föräldrar, mamma och Göran och pappa och

Kristina. Tack mamma och pappa för att ni alltid trott på mig och stöttat

mig i allt. Tack för att vi alla är en stor familj, för gemensamma firanden,

middagar och mysiga jular. Tack mamma för att du alltid ställer upp på alla

sätt, för att du hjälper till med barnen oavsett om det gäller att hämta på

dagis, följa på barntimmar, ta en extra sjukdag eller vara barnvakt. Du är så

otroligt omtänksam och kärleksfull. Tack pappa för att du hjälpt mig hitta

lugnet i många stunder när pressen tagit över och för att du är värdens bästa

Offa. Till Göran och Kristina mina extra föräldrar, tack för att ni alltid

ställt upp och alltid finns där för mig och tack för all omsorg ni ger barnen.

Tack Göran för att barnen frågar sina kompisar vad deras Göran heter.

Till mormor Ruth och morfar Harald som varit en så stor del av min

uppväxt och trygghet men som inte finns hos mig längre. Jag saknar er!

Till min familj. Till Jonas min bättre hälft och själsfrände. För att du är du,

du känner mig bäst av alla, stöttar mig och står ut med alla mina sidor, du är

fantastisk. Tack för att du finns, jag älskar dig!

Elsa och Vilgot mina små älsklingar och livets mening. Ni är det bästa som

hänt mig och påminner mig om vad som verkligen är viktigt!

Till alla patienter som ställer upp i studier och gör sådant här möjligt. Till

alla patienter och anhöriga som jag dagligen möter, ni gör att jag har

världens bästa jobb!

Tack till ALF, Cancerforskningsfonden och vetenskapsrådet som

bidragit med finansiellt stöd till detta arbete.

50

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