The effect of molecular targeted agents used in combination with ...€¦ · targeted cytostatic...
Transcript of The effect of molecular targeted agents used in combination with ...€¦ · targeted cytostatic...
The effect of molecular targeted agents used in combination with chemotherapy to inhibit the repopulation of tumour cells and xenografts
by
Andrea Sabrina Fung
A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Graduate Department of Medical Biophysics
University of Toronto
© Copyright by Andrea Sabrina Fung 2010
ABSTRACT
The effect of molecular targeted agents used in combination with chemotherapy to inhibit the repopulation of tumour cells and xenografts
Andrea Sabrina Fung
Doctor of Philosophy, 2010 Graduate Department of Medical Biophysics
University of Toronto Chemotherapy is often administered once every three weeks to allow repopulation of
essential normal tissues such as the bone marrow. Repopulation of surviving tumour cells
can also occur between courses of chemotherapy and can decrease the efficacy of
anticancer treatment. This thesis aims to characterize repopulation, to study the effect of
targeted cytostatic agents to inhibit repopulation, and to determine the optimal scheduling
of chemotherapy and molecular targeted treatment.
The distribution of proliferating and apoptotic cells in human squamous cell
carcinoma (A431) xenografts was studied following chemotherapy using fluorescence
immunohistochemistry. There was an initial decrease in cell proliferation and in the total
functional blood vessels, and an increase in apoptosis observed following treatment with
paclitaxel chemotherapy. A rebound in cell proliferation occurred approximately 12 days
following treatment, which corresponded with a rebound in vascular perfusion.
The effect of gefitinib, an epidermal growth factor receptor (EGFR) inhibitor, to
inhibit repopulation between courses of chemotherapy was determined using EGFR-
overexpressing A431 cells and xenografts. Furthermore, concurrent and sequential
schedules of combined chemotherapy and molecular targeted treatment were compared.
Gefitinib inhibited the repopulation of A431 cells in culture when administered
sequentially between chemotherapy; sequential treatment was more efficacious than
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concurrent treatment probably because concomitant scheduling rendered quiescent cells
less responsive to chemotherapy. However, in vivo studies using chemotherapy in
combination with gefitinib or temsirolimus, a mammalian target of rapamycin (mTOR)
inhibitor, showed that concurrent scheduling of combined treatment was more effective at
delaying regrowth of xenografts than sequential treatment; this was likely due to
dominant effects on the tumour microenvironment.
The work completed in this thesis has shown that repopulation occurs in A431
xenografts following paclitaxel treatment, and these changes are associated with changes
in the tumour vasculature. Repopulation of A431 cells was inhibited by gefitinib
administered sequentially with paclitaxel. However, studies in mice showed better
inhibitory effects when chemotherapy was given concomitantly with cytostatic agents
such as gefitinib or temsirolimus. Our in vivo data highlight the importance of
characterizing changes in the tumour microenvironment when determining optimal
scheduling of chemotherapy and molecular targeted treatment.
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CO-AUTHORSHIP All experiments completed in this thesis were performed under the supervision of Dr. Ian
Tannock. In chapters 2 and 3, the immunofluorescence staining was performed by staff at
the Pathology Research Program (PRP) at the University Health Network (UHN). The
data presented in chapter 4 was published in Clinical Cancer Research – the work was
shared equally and the publication was co-authored with Dr. Licun Wu. In addition, Carol
Lee provided technical support for some of the cell culture experiments (i.e. clonogenic
assays) completed in chapter 4, and PTEN staining was completed by James Ho.
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ACKNOWLEDGEMENTS
First and foremost, I would like to thank my supervisor Dr. Ian Tannock for giving me the opportunity to explore cancer research through my graduate studies. Dr. Tannock, thank you for your guidance and encouragement throughout my degree, and thank you for your support through professional and personal hardships. I have learned so much, and I have become truly passionate for the research that we do. You have been a great mentor, and you inspire me to be the best that I can be in both my professional and personal life. A special thanks to my supervisory committee members, Dr. Ming-Sound Tsao, Dr. Fei-Fei Liu, and Dr. Kate Vallis, for your encouragement, guidance and support during my graduate studies. Your help and insight has been instrumental in teaching me the skills necessary for my graduate and professional career. To all the members of the Tannock lab, past and present: Carol, Wu, Krupa, Andy, Rama, Olivier, Jas, Susie, Alaina, Patricia and Vithika. You have been amazing colleagues and you have all become wonderful friends. A special thanks to Dr. Licun Wu and Carol Lee for your help, support and friendship over the years. I would like to thank all members of the Pathology Research Program (Kelvin, Melanie, Ye, Carmelita, Natalia, Ceceil, and Arturo), and the Advanced Optical Microscopy Facility (James, Miria, and Judy) for technical support throughout my degree. Through the years I have been blessed with opportunities to broaden my understanding and knowledge of medical research. I would like to thank Dr. Paul Kubes for giving me a chance to discover research following my first year of undergraduate studies. I will be forever grateful to him for introducing me to research and inspiring my interest in the field. I would also like to thank Dr. Bruce Elliott for introducing me to cancer research; his research gave me the tools I needed to continue in graduate school and peaked my interest in translational cancer research. I am truly blessed to have amazing friends that have supported and encouraged me throughout the years. Steph, Luan, Adrienne, and Audrey, I am thankful to have wonderful friends like you to share happy moments with, but most importantly I thank you all for your unconditional support, understanding, and positive spirits, which have gotten me through the tough times. True friends are hard to find, and I am lucky to have all of you! To the PMH gang (Krupa, Ramya, Mamta, Mahadeo, and Mariam), I have enjoyed all of the time we have spent together over the past few years at PMH. Thank you for the research discussions, the philosophical discussions, the numerous coffee/lunch/birthday/picture gatherings, and most importantly for being great friends over the years! I cherish the time we have spent together, and I know we’ll remain friends no matter what life brings or where we may end up. KP, you have become one of my closest friends and I am truly happy to have met you. The past 6 years have been an
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amazing journey and I’m glad that we were able to embark on it together. Thanks for always being there! Most importantly, I want to thank my wonderful parents for their love and support throughout my life. Thank you for your unwavering encouragement through my many years of study, for celebrating my achievements, and supporting me through my failures. I am so fortunate to have parents who support my dreams and believe in me, even when I lose faith in myself. You have taught me to be the best that I can in everything I do. Thanks for everything! I love you both very much & I couldn’t have done it without you! I would like to dedicate my thesis to my dad, Uncle Philip, and Uncle Raymond – your courage and strength through the hardships and struggles of cancer have been the inspiration and passion driving me forward in our search for a cure. And to my mom for your unwavering strength during the last few years – we couldn’t have gotten through it without you!
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TABLE OF CONTENTS Abstract ………………………………………………………………………………… ii Co-Authorship …………………………………………………………………………. iv Acknowledgements …………………………………………………………………...... v Table of Contents ……………………………………………………………………... vii List of Tables ……………………………………………………………………………xi List of Figures ………………………………………………………………………… xii Abbreviations …………………………………………………………………………. xv Chapter 1. Introduction ……………………………………………………………….. 1
1.1 Molecular pathways of cancer ………………………………………………… 2
1.2 Chemotherapy ………………………………………………………………..... 5 1.2a Chemotherapy agents ………………………………………………. 5
1.3 Chemotherapy and drug resistance ……………………………………………. 6 1.3a Cellular and molecular mechanisms of drug resistance ……………. 6
1.3b Mechanisms of drug resistance associated with the tumour microenvironment ………………………………………………... 10
1.4 Repopulation …………………………………………………………………. 10 1.4a Repopulation and radiation therapy ………………………………. 11 1.4b Repopulation and chemotherapy …………………………………. 12 1.4c Models of repopulation …………………………………………… 14
1.5 Effect of the tumour microenvironment on repopulation in solid tumours ….. 16 1.5a Drug distribution ………………………………………………….. 16 1.5b Tumour vasculature ………………………………………………. 19 i. Targeting the tumour vasculature ……………………………. 20 ii. Measuring tumour vasculature ……………………………… 23
1.5c Hypoxia …………………………………………………………… 25 1.5d Stem cells …………………………………………………………. 28
1.6 Inhibition of repopulation ……………………………………………………. 34 1.6a Potential targets & properties of an ideal inhibitor ……………….. 34 1.6b EGFR ……………………………………………………………... 35 i. Structure and function ………………………………………... 36 ii. Other ErbB receptors ………………………………………... 37 iii. ErbB receptors in normal development and oncogenesis …... 37 iv. EGFR and angiogenesis …………………………………….. 38
1.6c EGFR inhibitors …………………………………………………... 38 i. Monoclonal antibodies (mAbs) ……………………………… 39 ii. Tyrosine kinase inhibitors …………………………………... 39
iii. Pharmacokinetics of gefitinib ………………………………. 40 iv. Clinical trials: Gefitinib (Iressa) and Erlotinib (Tarceva) …... 40 v. Gefitinib and tumour vasculature …………………………..... 41
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1.6d mTOR inhibitors ………………………………………………….. 42 i. Mammalian target of rapamycin (mTOR) …………………… 42
ii. mTOR inhibitors—rapamycin and its analogues …………… 44 iii. Temsirolimus (CCI-779) …………………………………… 46 iv. Pharmacokinetics of temsirolimus ………………………...... 47
v. mTOR inhibitors and angiogenesis ………………………….. 48 1.7 Combining cytotoxic and cytostatic therapies ……………………………….. 49
1.8 Rationale ……………………………………………………………………... 50
1.9 Hypotheses …………………………………………………………………... 50
1.10 Objectives & Specific Aims ………………………………………………... 51
Chapter 2. The characterization of repopulation in solid tumours following
anticancer treatment and the effects of the tumour mircorenvironment on treatment efficacy ………………….……..……………...…............…… 52
2.1 Statement of Translational Relevance ……………………………………….. 53
2.2 Abstract …………………………………………………………………….... 54
2.3 Introduction ………………………………………………………………….. 55
2.4 Materials and Methods ………………………………………………………. 57
2.4.1 Cell lines …………………………………………………………… 57 2.4.2 Drugs and reagents ………………………………………………… 57 2.4.3 Effect of paclitaxel and gefitinib on growth of xenografts …......….. 58 2.4.4 Effect of paclitaxel and gefitinib on cell proliferation and apoptosis..58 2.4.5 Image Analysis and Quantification ………………………………… 59 2.4.6 Analysis of blood vessels and hypoxia in tumour xenografts ……… 60 2.4.7 Statistical Analysis …………………………………………………. 61
2.5 Results ………………………………………………………………………... 62
2.5.1 Effect of paclitaxel of A431 xenografts ……………………………. 62 2.5.2 Effect of paclitaxel of the distribution of cell proliferation in A431
xenografts …………………………………………………………... 62 2.5.3 Distribution of apoptotic cells in A431 xenografts following
paclitaxel treatment ………………………………………………… 66 2.5.4 Effect of gefitinib on high EGFR (A431) and low EGFR (MCF-7)
expressing xenografts ………………………………………………. 66 2.5.5 Distribution of proliferating cells (Ki67) and apoptotic cells (cleaved
caspase-3) in A431 xenografts following gefitinib treatment …........ 66 2.5.6 Distribution of proliferating cells (Ki67) and apoptotic cells
(cleaved caspase-3) in MCF-7 xenografts following paclitaxel or gefitinib treatment …...……………………………………………... 71
2.5.7 Changes in functional vasculature following treatment with paclitaxel or gefitinib in A431 and MCF-7 xenografts …………….. 76
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2.5.8 Changes in the percentage of hypoxia per tumour area following treatment with paclitaxel or gefitinib in A431 and MCF-7 xenografts …………………………………………………………... 79
2.6 Discussion ……………………………………………………………………. 85
2.7 References ……………………………………………………………………. 93 Chapter 3. Scheduling of paclitaxel and gefitinib to inhibit repopulation for
optimal treatment of cells and xenografts that overexpress the epidermal growth factor receptor ……....……………………...………...... 95
3.1 Statement of Translational Relevance ……………………………………….. 96
3.2 Abstract ………………………………………………………………...……. 97
3.3 Introduction …………………………………………………………...……... 98
3.4 Materials and Methods ……………………………………………………... 100
3.4.1 Cell lines ………………………………………………………….. 100 3.4.2 Drugs and reagents ……………………………………………...... 100 3.4.3 Effects of gefitinib on cell growth ………………………………... 101 3.4.4 Effects of paclitaxel and gefitinib treatment ……………………… 101 3.4.5 Clonogenic Assays ………………………………………………... 102 3.4.6 Flow Cytometry …………………………………………………... 102 3.4.7 Effect of paclitaxel and gefitinib on growth of A431 and MCF-7
xenografts …………………………………………………………. 103 3.4.8 Effect of paclitaxel and gefitinib on cell proliferation and
vasculature in A431 xenografts …………………………………... 104 3.4.9 Statistical Analysis ……………………………………………...... 106
3.5 Results …………………………………………………………………….... 106
3.5.1 Expression of EGFR ……………………………………………… 106 3.5.2 Inhibition of cell growth with gefitinib ………………………....... 106 3.5.3 Paclitaxel and gefitinib treatment ………………………………… 106 3.5.4 Effects on Cell cycle and Apoptosis ……………………………… 110 3.5.5 Effects of paclitaxel and gefitinib on growth of A431 xenografts ... 114 3.5.6 Effect of paclitaxel and gefitinib on cell proliferation, apoptosis,
and tumour vasculature in A431 xenografts ……………………… 114 3.5.7 Effect of paclitaxel and gefitinib on cell proliferation, apoptosis,
and tumour vasculature in MCF-7 xenografts ……………………. 117 3.5.8 Effect of paclitaxel and gefitinib on the percentage of hypoxia in
A431 and MCF-7 xenografts ……………………………………... 123
3.6 Discussion …………………………………………………………………... 125
3.7 References …………………………………………………………………... 132
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Chapter 4. Concurrent and sequential administration of chemotherapy and the mTOR inhibitor temsirolimus in human cancer cells and xenografts …. 134
4.1 Statement of Translational Relevance ……………………………………… 135
4.2 Abstract …………………………………………………………...………... 136
4.3 Introduction …………………………………………………………...….… 137
4.4 Materials and Methods ………………………………………………...….... 139
4.4.1 Cell lines and mice ……………………………………………… 139 4.4.2 Drugs and preparation ……………………………………....…... 139 4.4.3 Effects of temsirolimus and chemotherapy on cell proliferation
in vitro ………………………………………………………....... 140 4.4.4 Concurrent or sequential treatment of cultured cells …………… 140 4.4.5 Cell cycle analysis ………………………………………………. 142 4.4.6 Concurrent or sequential treatment of xenografts ………………. 142
4.5 Results ………………………………………………………………………. 143
4.5.1 Effects of temsirolimus and chemotherapy in vitro …………….. 143 4.5.2 Effects of temsirolimus and chemotherapy on xenografts ……… 145
4.6 Discussion …………………………………………………………………... 151
4.7 References …………………………………………………………………... 157 Chapter 5. Conclusions & Future Directions ……………………………………… 160
5.1 Characterization and Inhibition of Repopulation …………………………… 161
5.1.1 Summary ………………………………………………………... 161 5.1.2 Implications of Study …………………………………………… 164 5.1.3 Limitations and Future Directions ……………………………… 165
5.2 Combining Molecular Targeted Agents with Chemotherapy ………………. 167
5.2.1 Summary: Chemotherapy in Combination with the EGFR Inhibitor Gefitinib ………………………………………………. 168
5.2.2 Implications of Study ………………………………………….... 170 5.2.3 Limitations and Future Directions ……………………………… 171 5.2.4 Summary: Chemotherapy in Combination with the mTOR
Inhibitor Temsirolimus …………………………………………. 171 5.2.5 Implications of Study ………………………………………....… 173 5.2.6 Limitations and Future Directions ……………………………… 173
5.3 Concluding Remarks ………………………………………………………... 175 Chapter 6. References ……………………………………………………………...... 178 Appendix I. Image Quantification: Future Considerations ….…………………… 195
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LIST OF TABLES Table 1.1 Putative cancer stem cell markers …………………………………………… 32
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LIST OF FIGURES Chapter 1: Introduction Figure 1.1 Molecular pathways of cancer ………………………………………………. 4 Figure 1.2 Drug resistance in solid tumours …………………...……………..………… 9 Figure 1.3 “Dog-leg” diagram of repopulation following radiation or chemotherapy
treatment ………………………………………………………………….... 13 Figure 1.4 Models depicting the repopulation of tumour cells during chemotherapy
treatment ………………………………………………………………….... 15 Figure 1.5 Regulation of tumour vasculature …………………...…………………….. 21 Figure 1.6 Effect of chemotherapy on tumour vasculature ………………………….... 24 Figure 1.7 Signalling upstream and downstream of the mammalian target of
rapamycin (mTOR) ………………………………………………………… 45 Chapter 2 Figure 2.1 The effect of paclitaxel on growth of A431 xenografts …………...……..... 63 Figure 2.2 Photomicrographs of the distribution of proliferating cells in relation to
blood vessels and hypoxia following paclitaxel treatment …….…………... 64 Figure 2.3 The effect of paclitaxel on cell proliferation in A431 xenografts …...…….. 65 Figure 2.4 Photomicrographs of the distribution of apoptotic cells in relation to blood
vessels and hypoxia following paclitaxel treatment ……………………….. 67 Figure 2.5 The effect of paclitaxel on apoptosis in A431 xenografts ……………...….. 68 Figure 2.6 The effect of gefitinib on growth of A431 or MCF-7 xenografts …...…….. 69 Figure 2.7 The effect of gefitinib on cell proliferation in A431 xenografts …….…….. 70 Figure 2.8 The effect of gefitinib on apoptosis in A431 xenografts ……..…...……….. 72 Figure 2.9 The effect of paclitaxel on growth of MCF-7 xenografts ………………...... 73 Figure 2.10 The effect of paclitaxel or gefitinib treatment on cell proliferation in
MCF-7 xenografts ………………………………………………………... 74
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Figure 2.11 The effect of paclitaxel or gefitinib treatment on apoptosis in MCF-7 xenografts ………………………………………………………….……... 75
Figure 2.12 Changes in tumour vasculature in A431 xenografts following paclitaxel
treatment ………………………………………………………………..... 77 Figure 2.13 Changes in tumour vasculature in A431 xenografts following gefitinib
treatment ………………………………………………………………..... 78 Figure 2.14 Changes in tumour vasculature in MCF-7 xenografts following
paclitaxel treatment ……………………………………………………..... 80 Figure 2.15 Changes in tumour vasculature in MCF-7 xenografts following gefitinib
treatment ………………………………………………………………..... 81 Figure 2.16 The percentage of hypoxia in A431 xenografts following paclitaxel or
gefitinib treatment ……………………………………………….…..…… 82 Figure 2.17 The percentage of hypoxia in MCF-7 xenografts following paclitaxel or
gefitinib treatment ……………………………………………….…..…… 84 Chapter 3 Figure 3.1 Epidermal growth factor receptor expression in A431 and MCF-7 cells
and xenografts …………………………………………………………….. 107 Figure 3.2 Effect of gefitinib on growth of A431 and MCF-7 cells …………………. 108 Figure 3.3 The effect of sequential or concurrent paclitaxel and gefitinib treatment
on clonogenic survival of A431 cells …………………………...………… 109 Figure 3.4 The effect of sequential or concurrent paclitaxel and gefitinib treatment
on survival of MCF-7 cells ………………...…………………...………… 111 Figure 3.5 Cell cycle analysis of A431 cells following gefitinib treatment …………. 112 Figure 3.6 Cell cycle analysis of A431 cells following sequential or concurrent
paclitaxel and gefitinib treatment ……………………………………...….. 113 Figure 3.7 The effect of sequential or concurrent paclitaxel and gefitinib treatment
on A431 or MCF-7 xenografts ………………..………………...………… 115 Figure 3.8 The effect of sequential or concurrent paclitaxel and gefitinib treatment
on cell proliferation in A431 xenografts ………………...……...………… 116
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Figure 3.9 The effect of sequential or concurrent paclitaxel and gefitinib treatment on apoptosis in A431 xenografts ………………...............……...………… 118
Figure 3.10 The effect of sequential or concurrent paclitaxel and gefitinib treatment
on tumour vasculature in A431 xenografts …………………...………… 119 Figure 3.11 The effect of sequential or concurrent paclitaxel and gefitinib treatment
on cell proliferation in MCF-7 xenografts …………………....………… 120 Figure 3.12 The effect of sequential or concurrent paclitaxel and gefitinib treatment
on apoptosis in MCF-7 xenografts ……………….........……...………… 121 Figure 3.13 The effect of sequential or concurrent paclitaxel and gefitinib treatment
on tumour vasculature in MCF-7 xenografts ………….……...………… 122 Figure 3.14 The effect of sequential or concurrent paclitaxel and gefitinib treatment
on the percentage of hypoxia in A431 or MCF-7 xenografts ………...… 124 Figure 3.15 The effect of one day of gefitinib treatment on functional tumour
vasculature in A431 xenografts …………………………………..…...... 129
Chapter 4 Figure 4.1 Schedule of chemotherapy and temsirolimus treatment ………………….. 141 Figure 4.2 Effect of temsirolimus on cell number and cell cycle distribution in PC-3,
LnCaP, and MDA-468 cells ………………………………….…………… 144 Figure 4.3 Cell cycle analysis of PC-3, LnCaP, and MDA-468 cells following
sequential or concurrent chemotherapy and temsirolimus treatment …….. 146 Figure 4.4 The effect of sequential or concurrent chemotherapy and temsirolimus
treatment on clonogenic PC-3, LnCaP, and MDA-468 cells ……………... 147 Figure 4.5 The effect of sequential or concurrent chemotherapy and temsirolimus
treatment on PC-3 and MDA-468 xenografts ……….…………..………... 148 Figure 4.6 The effect of sequential or concurrent chemotherapy and temsirolimus
treatment on LnCaP xenografts ……………………………….………….. 150 Figure 4.7 The PC-3 and LnCaP sub-G1 cell population following sequential or
concurrent docetaxel and temsirolimus treatment …………………...…… 153 Appendix I Figure A1.1 Effect of paclitaxel on cell proliferation: New quantification method … 200
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ABBREVIATIONS 4E-BP1 4E binding protein 1
5-FU 5-fluorouracil
α-MEM Alpha minimal essential medium
ABC ATP binding cassette
ALDH1 Aldehyde dehydrogenase 1
AML Acute myeloid leukemia
AOI Area of interest
ATP Adenosine triphosphate
BrdU Bromodeoxyuridine
CEP Circulating endothelial progenitor
CSC Cancer stem cell
DAB Diaminobenzidine
DHFR Dihydrofolate reductase
DMEM Dulbecco’s modified Eagle’s medium
DMSO Dimethyl sulfoxide
DNA Deoxyribonucleic acid
DOC Docetaxel
EGF Epidermal growth factor
EGFR Epidermal growth factor receptor
eIF4E Eukaryotic initiation factor 4E
EpCAM Epithelial cell adhesion molecule
EPO Erythropoietin
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ESA Epithelial specific antigen
FBS Fetal bovine serum
FFPE Formalin fixed paraffin embedded
FITC Fluorescein isothiocyanate
FKBP12 FK506 binding protein 12
FRAP FK506 binding protein 12-rapamycin associated protein
GI Gastrointestinal
HER2 Human epidermal growth factor receptor 2
HIF Hypoxia inducible factor
HRE Hypoxia responsive element
IFP Interstitial fluid pressure
IGF Insulin-like growth factor
IP Intraperitoneal
IV Intravenous
Jak Janus kinase
mAb Monoclonal antibody
MAPK Mitogen activated protein kinase
MDR Multi-drug resistant
mRNA Messenger ribonucleic acid
MRP1 Multi-drug resistance protein 1
MTD Maximum tolerated dose
mTOR Mammalian target of rapamycin
mTORC Mammalian target of rapamycin complex
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OCT Optimal cutting temperature
PBS Phosphate buffer solution
PECAM Platelet endothelial cell adhesion molecule
Pgp P-glycoprotein
PI Propidium iodide
PI3K Phosphoinositide 3 kinase
PROCR Protein C receptor
PTEN Phosphatase and tensin homolog
RPMI Roswell park memorial institute medium
RTK Receptor tyrosine kinase
STAT Signal transducers and activators of transcription
TGF Transforming growth factor
TSC Tuberous sclerosis complex
VCAM Vascular cell adhesion molecule
VEGF Vascular endothelial growth factor
VEGFR Vascular endothelial growth factor receptor
CHAPTER 1
INTRODUCTION
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1.1 MOLECULAR PATHWAYS OF CANCER
Many molecular pathways are involved in the regulation of processes such as cell
metabolism, proliferation, apoptosis, angiogenesis, invasion and metastasis. Cancer is
thought to arise from the accumulation of successive genetic changes, whereby
alterations in signalling pathways can result in progression to a malignant phenotype, and
to the outgrowth of drug resistant cell populations.
Malignant tumours are often characterized by properties such as autonomous
growth signalling, insensitivity to anti-proliferative signals, unlimited growth potential,
evasion of cell death, increased angiogenesis, or the potential for invasion and metastasis
(1) (Figure 1.1). Many of these factors might influence repopulation within solid
tumours, as well as the efficacy of anticancer treatments, such as chemotherapy, since
they impact on the proliferation and survival of tumour cells, and on the tumour
microenvironment that supports tumour growth.
Tumour cells can develop independence in signalling pathways, whereby they are
stimulated without the ‘normal’ regulation. For example, the overexpression or
deregulation of the epidermal growth factor receptor (EGFR) in various cancers results in
increased proliferation and survival of tumour cells expressing the receptor (2) (see
Section 1.6b for a review of the EGFR). In addition, ligand-independent growth factor
receptor signalling, changes in extracellular matrix (ECM) interactions, or alterations in
downstream growth signalling might contribute to altered proliferation and death of
tumour cells (1). Tumour growth can also be perpetuated by a decreased sensitivity to
anti-proliferative signals, such as the retinoblastoma protein (Rb), a protein that regulates
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cell cycle progression (1). Loss of tumour suppressor proteins, such as p53 and PTEN,
can result in decreased induction of apoptosis by DNA sensing mechanisms (3), or
increased survival signalling through the PI3 kinase pathway (4), respectively. Evasion of
cell death causes an increase in tumour cell survival, but might also affect the
susceptibility of tumour cells to anticancer treatments such as chemotherapy.
There are various factors in the tumour microenvironment that also contribute to
tumour progression. Solid tumours are dependent on an adequate vascular system for
growth, and are characterized by angiogenesis due to higher expression of proangiogenic
factors, such as vascular endothelial growth factor (VEGF) (5). However, the irregular
vasculature in tumours often results in altered tumour metabolism due to regions of low
oxygen (hypoxia) and nutrients, or to the presence of an acidic environment as a result of
the build up of metabolic waste products (6). Signalling downstream of VEGF receptors
involve the MAPK and PI3K pathways (7). The PI3K pathway is implicated in various
cancers and is often activated in response to changes in the tumour microenvironment (8).
For example, the mammalian target of rapamycin (mTOR), which is downstream of Akt
in the PI3K pathway, is an important regulator of metabolic processes within tumour cells
(9, 10) (see Figure 1.7 and Section 1.6d for a review of mTOR). Changes in the tumour
microenvironment can affect how tumour cells respond to treatments and likely affects
tumour repopulation following treatment.
Figure 1.1 Molecular pathways of cancer. Seven acquired characteristics that can contribute to malignant tumour progression. These factors might also impact anticancer treatment efficacy and tumour repopulation. Modified from Hanahan and Weinberg, Cell 2000;100:57-70.
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1.2 CHEMOTHERAPY
Chemotherapy is utilized frequently in the treatment of various cancers. Most
anticancer agents are targeted towards rapidly proliferating cells within tumours;
however, proliferating cells in normal tissues, such as bone marrow and intestinal
mucosa, may also be affected. Therefore, chemotherapeutic agents are often administered
at three-week intervals to ensure adequate replenishment of normal cells and tissues.
Unfortunately, there are many human cancers, such as colon, and many lung cancers, that
have a relatively poor response to chemotherapeutic agents. Furthermore, some cancers
(i.e. breast, ovarian, and small-cell lung cancers) can respond initially to chemotherapy,
but acquire resistance to additional treatments.
1.2a Chemotherapy Agents
There are many different types of chemotherapeutic agents used in the treatment
of human cancers. These agents are often classified according to their respective
mechanisms of action. It is of particular importance to understand the mechanism of
action of chemotherapy drugs when combining these agents with other anticancer
therapies such as molecular targeted agents.
Major classes of chemotherapeutic agents include alkylating agents, platinum
agents, antimetabolites, topoisomerase inhibitors, and agents that target microtubules.
Alkylating agents, such as nitrogen mustard, melphalan, and cyclophosphamide, exert
toxicity in cells through the formation of DNA crosslinks, single-strand DNA breaks and
DNA adducts (11). Platinum anticancer drugs, including cisplatin and carboplatin, bind to
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DNA creating DNA adducts, which result in cytotoxicity (11). Antimetabolites interfere
with macromolecular synthesis, thereby preventing replication. Most antimetabolites are
cell cycle specific and act mostly on proliferating cells; they include drugs such as
methotrexate, 5-fluorouracil (5-FU), and gemcitabine (11). Topoisomerase inhibitors
(e.g. topotecan, etoposide, and anthracyclines such as doxorubicin and mitoxantrone)
stabilize the DNA-topoisomerase complex, which prevents religation of DNA, leading to
subsequent DNA strand breaks (11). Vinca alkaloids and taxanes (e.g. paclitaxel and
docetaxel) are agents that interact with microtubules and target microtubular stability by
preventing normal microtubular processes involved in cell division (11, 12). Paclitaxel is
most effective near the G2 to M phase progression, whereas docetaxel acts mainly during
S phase (11).
1.3 CHEMOTHERAPY AND DRUG RESISTANCE 1.3a Cellular and Molecular Mechanisms of Drug Resistance
Many cellular and molecular mechanisms have been identified that may
contribute to the development of drug resistance. Some types of drug resistance are due
to stable mutation or amplification of genes, but resistance may also be transient. These
mechanisms are referred to as epigenetic, and include processes such as transient gene
amplification, changes in DNA methylation, and other factors that affect gene expression.
Both genetic and epigenetic mechanisms of drug resistance are clinically relevant and
may lead to alterations in drug uptake or excretion, drug metabolism, drug targets, DNA
repair, or apoptosis.
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Decreases in drug uptake can lead to clinical drug resistance. Many
chemotherapeutic agents are transported into a cell by carrier proteins in the cell
membrane. Alterations in the binding affinity of drugs to carrier proteins can affect the
transport of these agents into the cell.
A common form of drug resistance is the export of anticancer drugs from within
cells through drug efflux pumps, which include members of the ATP-binding cassette
(ABC) transporter family of proteins such as P-glycoprotein or the multidrug-resistance
protein 1 (MRP1). Drug efflux pumps protect cells by removing toxic substances,
including a number of chemotherapeutic agents. Chemotherapy drugs such as
anthracyclines (e.g. doxorubicin) and taxanes (e.g. paclitaxel and docetaxel) have been
shown to be substrates for P-glycoprotein, and some anthracyclines are also substrates for
MRP1 (13). Hence, removal of chemotherapy agents will protect tumour cells from
cytotoxicity.
Alterations in drug metabolism also play a role in drug resistance. Some
anticancer agents administered as pro-drugs require enzymatic activation into the active
form; alterations in enzyme activity can render drugs ineffective due to the inability to
convert them to their active forms, or due to rapid breakdown or inactivation of drugs.
Drug targets are often overexpressed in cancers and might acquire mutations that
render them less sensitive to anticancer treatment. Examples include overexpression or
mutation of dihydrofolate reductase (DHFR), which can lead to methotrexate resistance,
or mutations in growth factor receptors such as the epidermal growth factor receptor
(EGFR). Mutant forms of EGFR can become constitutively active and are initially
sensitive to targeted therapies such as the EGFR inhibitors gefitinib and erlotinib;
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however, resistance to these agents may develop following acquisition of additional
mutations (14).
Chemotherapy agents can exert their cytotoxic effects through the formation of
DNA breaks or through the induction of cell death. However, many tumour cells have
increased DNA repair mechanisms or altered cell death pathways, leading to drug
resistance as tumour cells escape drug-mediated cell death (15). For instance, wild-type
p53 can induce apoptosis in cells that have sustained DNA damage; however, many
tumour cells have mutations in p53 that allow them to escape an apoptotic death (16-18).
There is a survival advantage for stable drug resistant cell populations leading to
their emergence as the dominant cell population within a tumour. The development of
this drug resistant population of tumour cells can therefore decrease efficacy of
chemotherapy treatments (Figure 1.2).
Figure 1.2 Drug resistance in solid tumours. In solid tumours, there is a gradient of proliferation, with highly proliferative cells located near functional blood vessels and low cell proliferation distal from blood vessels. There are also cells within tumours that possess cellular and/or molecular alterations (e.g. drug efflux pumps, altered DNA repair mechanisms, etc.) that render them resistant to anticancer treatment. Chemotherapy often targets rapidly proliferating cells and will likely preferentially kill cells near blood vessels due to the higher proliferative rate of these cells, as well as the limited penetration of chemotherapy drugs. Following treatment, repopulation of suriving tumour cells can occur, probably as a result of improvements in the distribution of oxygen and nutrients within the tumour. The survival of drug resistant cells following chemotherapy treatment might lead to their presence as the dominant cell population within a tumour following multiple courses of chemotherapy. Modified from Tredan et al., J Natl Cancer Inst 2007; 99(19):1441-54.
Chemotherapy
Repopulation
Multiple courses of treatment
Low cell proliferation
High cell proliferation
Drug-resistant cell
9
1.3b Mechanisms of Drug Resistance Associated with the Tumour Microenvironment
In addition to cellular mechanisms of drug resistance, there are factors related to
the tumour microenvironment that can lead to decreased efficacy of various anticancer
drugs. Although not as extensively studied as cellular and molecular mechanisms of drug
resistance, this area of research is important in determining the causes of clinical drug
resistance, especially for patients with solid tumours. The response of tumour cells in
culture may differ substantially from that of tumour cells within solid tumours (19); an
effect that is associated with the complex nature of the tumour microenvironment. In
solid tumours, cells are in close contact and are surrounded by a complex extracellular
matrix. The presence of a poorly formed and irregular vascular system leads to regions in
the tumour deprived of oxygen and other nutrients, along with an accumulation of
breakdown products of metabolism, resulting in an acidic microenvironment (6, 20, 21).
Furthermore, the inadequate vasculature, high cell density, long intercapillary distances,
and high interstitial fluid pressure within solid tumours may all contribute to insufficient
drug penetration and distribution within the tumour tissue (6, 22, 23). Finally,
repopulation of surviving tumour cells between courses of cytotoxic treatments might
greatly decrease treatment efficacy, leading to clinical drug resistance (24).
1.4 REPOPULATION
Repopulation occurs due to the proliferation of surviving cells following cytotoxic
treatment, such as radiation therapy or chemotherapy. Anticancer treatment is usually
administered at intervals to allow for normal tissue recovery through proliferation of
surviving progenitor cells. In particular, the interval between treatments must permit
10
repopulation of white blood cells within the body, which are imperative for mounting an
effective immune response. However, repopulation of tumour cells may also occur during
the intervals between doses of radiation or chemotherapy. Various factors within the
tumour microenvironment, including tumour vasculature and hypoxia, as well as drug
distribution, may affect the repopulation of cancer cells in solid tumours.
1.4a Repopulation and Radiation Therapy
Repopulation has been studied as a potential reason for decreased efficacy of
radiation treatment. Studies of fractionated radiation therapy have shown that the
proliferation of surviving tumour cells between daily doses can lead to poor local tumour
control (11). In experiments using transplantable mouse tumours, different groups
reported similar findings, indicating a faster rate of tumour cell repopulation following a
single dose of radiation, compared to the rate of cell proliferation in non-irradiated
control tumours (25, 26). Furthermore, studies with human tumour xenografts in mice
have suggested accelerated repopulation with successive treatments, as well as an
increase in the radiation dose required to control 50% of tumours in order to overcome
repopulation when the course of treatment is protracted (24, 27). Clinical data compiled
from different institutions have also shown an increase in total radiation doses required to
control 50% of head and neck squamous cell carcinomas with treatments that lasted more
than 4 weeks; this has been attributed to an initial lag phase with little or no repopulation
up to 4 weeks of treatment, followed by accelerated repopulation of tumour cells after 4
weeks of radiation therapy (28). Other studies have also indicated that a delay (‘lag
11
12
period’) in onset of repopulation occurs following treatments with radiation and
chemotherapy (29) (Figure 1.3).
Repopulation may become more problematic with longer overall radiation
treatment times (24). Efforts have been made to alter treatment scheduling with
radiotherapy in order to shorten total treatment times by reducing the intervals between
each treatment dose. With accelerated fractionation of radiotherapy, doses are given more
than once daily, thereby reducing overall treatment time and decreasing the opportunity
for repopulation of tumour cells (30, 31).
1.4b Repopulation and Chemotherapy
Repopulation of tumour cells between courses of chemotherapy could also lead to
decreased efficacy of treatment, thereby contributing to drug resistance within solid
tumours. The longer intervals between each course of chemotherapy (as compared to
daily intervals between doses of radiotherapy) allows substantial opportunity for
repopulation of surviving tumour cells, but studies into the effect of repopulation on
chemotherapeutic efficacy are limited. Amongst the studies that have been conducted,
most have focused on repopulation in animal tumours and/or multicellular tumour
spheroids. Results have shown an increase in the rate of repopulation following
chemotherapy, as compared to untreated tumours, and limited data suggest that this rate
increases with successive courses of chemotherapy (32, 33). The distribution of
repopulation within solid tumours has not been extensively studied. One study by
Huxham et al. showed that repopulation first occurs in regions distal to blood vessels
Figure 1.3 “Dog-leg” diagram of repopulation following radiation or chemotherapy treatment. Repopulation of tumour cells can occur following treatment, and this might lead to an increase in treatment dose necessary to control tumour growth (i.e. increase in radiation or chemotherapy drug dose or dose fraction). Studies suggest that a delay in the onset of repopulation might occur following radiation treatment. This is often referred to as the “dog-leg” pattern of repopulation. Modified from Armpilia et al., The British Journal of Radiology 2004; 77:765-767.
13
within colorectal xenografts following gemcitabine treatment (34). However, further
studies are important as these observations may be dependent upon the tumour type, the
chemotherapy agent used, and changes in various microenvironmental factors. Little is
known about repopulation in human tumours.
1.4c Models of Repopulation
Clinically, many solid tumours show initial response to chemotherapy, but with
continued treatment, re-growth of the tumour is observed. Models of repopulation have
been suggested, which aid in the conceptualization of these observations (Figure 1.4). If
the rate of repopulation is rapid, such that cell proliferation between treatments adds more
cells than are killed by each treatment, tumours will continue to increase in size despite
cell death due to chemotherapy (Figure 1.4a). Furthermore, if tumours undergo
accelerated repopulation with successive courses of chemotherapy, an initial decrease in
cell number may be followed by an increase in cell number. Therefore, these models
indicate that the clinical observation of initial tumour shrinkage in response to
chemotherapy followed by re-growth with subsequent courses of treatment can occur
without changes in intrinsic drug sensitivity of the tumour cells (Figures 1.4b and 1.4c).
14
Figure 1.4 Models depicting the repopulation of tumour cells during chemotherapy treatment. Chemotherapy is often administered once every three weeks, and in the above diagram it has been assumed that approximately 70% of tumour cells are killed with each course of chemotherapy. a) Assuming a constant rate of repopulation of surviving tumour cells, there will be an overall decrease in the relative number of tumour cells following multiple courses of chemotherapy if there is a slow rate of repopulation; however, with rapid repopulation of tumour cells between courses of treatment, there might be no significant difference in the number of cells present in a tumour despite multiples courses of treatment. b) If the rate of repopulation of surviving tumour cells increases with each successive course of chemotherapy, there might be an initial decrease and subsequent increase in the relative number of cells present in a tumour despite continual chemotherapy treatment. c) There is likely a delay in onset of repopulation after each cycle of chemotherapy, followed by repopulation of surviving tumour cells. An initial reduction in tumour size followed by regrowth of tumours during chemotherapy is commonly observed in clinical practice, without any change in the intrinsic drug sensitivity of the tumour cells. Modified from Kim and Tannock, Nat Rev Cancer 2005;5(7):516-25.
15
1.5 EFFECT OF THE TUMOUR MICROENVIRONMENT ON REPOPULATION IN SOLID TUMOURS
In solid tumours, cells farther away from blood vessels form a quiescent or
slowly-proliferating population that has a high rate of cell death due to lack of oxygen
and other nutrients and/or to high concentrations of toxic breakdown products of
metabolism such as lactic and carbonic acid. Following cytotoxic treatment with
radiotherapy or chemotherapy, the cells closest to blood vessels are more likely to be
killed because drugs are present at cytotoxic concentrations in regions closer to blood
vessels; furthermore, greater access to nutrients and oxygen means that proximal cells
often have a higher rate of proliferation than more distal cells, thereby rendering them
more susceptible to cycle-active chemotherapy (24, 34). The removal of proximal cells
that have been killed by cytotoxic treatment may result in an increase in the supply of
oxygen and nutrients made available to more distant cells (24). This may lead to a
decrease in the rate of cell death and an increase in cell proliferation within the
previously quiescent cell population, which may account for the increased repopulation
observed following treatment (34). Results from studies with multicellular tumour
spheroids and human xenografts support this model of repopulation (34-36).
1.5a Drug Distribution
Chemotherapeutic efficacy is highly dependent on the ability of drugs to localize
to tumour cells in cytotoxic concentrations. Studies have shown that drug distribution
within solid tumours is limited, and thus may be an important factor in clinical drug
resistance. Poor drug penetration may also impact repopulation in tumours.
16
Inadequate drug delivery within solid tumours may result in regions of the tumour
with viable cells that have little to no exposure to cytotoxic agents. Drug concentration
gradients of anticancer agents have been observed in studies using multicellular spheroids
(37, 38), and more recently in multilayered cell cultures (39, 40). Lankelma et al. showed
that gradients of doxorubicin were present in biopsies taken from breast cancer patients,
with higher drug concentrations observed in the periphery compared to regions in the
center of tumour islets (22). Work by Primeau et al. demonstrated similar results; it was
observed that at increasing distances from blood vessels, viable tumour cells were
exposed to limited doxorubicin after it was injected into mice (41). Studies of the
distribution of other anticancer agents showed that taxanes, such as paclitaxel and
docetaxel, have limited penetration in a multilayered cell culture system and in tumour
xenografts (40). Viable tumour cells that are not exposed to chemotherapeutic agents
have the potential to repopulate between courses of chemotherapy. Therefore, despite the
cell kill in regions proximal to blood vessels, tumours may continue to grow and increase
in size due to the outgrowth of tumour cells from regions far from blood vessels that were
not killed during treatment. In addition, the death of cells proximal to blood vessels may
also improve the diffusion of nutrients and oxygen to more distal cells, which will also
increase their rate of proliferation and allow for repopulation from these previously
quiescent cell populations (6, 34).
Drug distribution within solid tumours is dependent on various factors, including
molecular size and half-life in the blood, as well as other pharmacokinetic and
pharmacodynamic parameters. Diffusion of larger molecules within tumour tissue might
be more limiting compared to drugs with a small molecular size (42). In addition, drugs
17
with a longer half-life might penetrate further into tumour tissue due to the longer
presence of the drug in the blood (6, 42). Drug consumption might also affect drug
distribution because if drugs are consumed by cells proximal to bloods vessels, there will
be less available to penetrate into regions further from the vasculature; for example, the
binding of monoclonal antibodies (e.g. cetuximab or trastuzumab) to their target
receptors (43-45), as well as tight binding of anticancer drugs (e.g. doxorubicin) to DNA
(39, 46-48), might limit further drug penetration into the tumour. Furthermore, drug
properties, such as charge, might decrease drug distribution due to retention of drugs
within the cell; for example, basic drugs such as doxorubicin have been found to be
sequestered in acidic endosomes within tumour cells, thereby limiting the availability of
the drug to reach cells more distal from blood vessels (49).
Targeted biological agents, such as the epidermal growth factor receptor (EGFR)
inhibitor cetuximab and the HER-2 inhibitor trastuzumab, have shown relatively uniform
distribution within tumour xenografts 24 hours after treatment (unpublished data by Lee
et al.; submitted to BMC). Moreover, McKillop et al. showed that the EGFR inhibitor
gefitinib has good penetration into tumour tissue (50). Conversely, doxorubicin gradients
in tumour biopsies could still be detected up to 24 hours after drug injection (22). The
differences in drug distribution within tumours could be associated with longer half lives
of targeted agents, such as monoclonal antibodies cetuximab and trastuzumab, compared
to doxorubicin in mice (51-53). The improved bio-distribution of these targeted agents in
solid tumours might contribute to their anti-tumour efficacy observed in the clinic.
A potential approach to improve treatment efficacy is through the modification of
the tumour environment to allow for more effective drug distribution within the tumour;
18
this might lead to a decrease in tumour repopulation due to adequate exposure of cells to
drugs in regions both proximal and distal to blood vessels. Studies by Patel et al. in our
laboratory are investigating the effect of proton pump inhibitors in preventing endosomal
accumulation of chemotherapy drugs (thereby decreasing consumption in proximal cells)
as a means of improving drug distribution (unpublished data). Other studies have
investigated the effect of tumour cell density on drug penetration, and the possibility of
modifying cell density (i.e. through changes in the extracellular matrix) as a strategy to
improve drug penetration (54-56).
1.5b Tumour Vasculature
Tumour vasculature plays an important role in the growth of solid tumours. In
order for a tumour to grow, cells within it require sufficient nutrients and adequate
oxygenation; therefore, angiogenesis (the growth of new blood vessels) is essential for
the process of tumour growth and repopulation. It has been shown that growth of a
tumour beyond a size of 1-2mm in diameter is dependent on the establishment of new
blood vessels (57). In addition, some studies have shown that although tumour cells
continue to proliferate, tumours might not grow in size due to a similar rate of cell death;
this has been attributed to a lack of vasculature, which contributes to a state of tumour
dormancy (58-60).
The architecture of tumour vessels is markedly different from that of normal
vessels (61-63). Unlike normal blood vessels, tumour vasculature is often irregular in
shape, size, and branching, and lacks normal vascular organization (i.e. the arteriole,
capillary, and venule hierarchy) (62, 63).
19
Endothelial cells in normal mature vessels are usually quiescent and slow growing
(64, 65); conversely, the production of pro-angiogenic proteins, such as vascular
endothelial growth factor (VEGF), from tumour cells often promotes tumour vessel
proliferation (58). Vermeulen et al. and others have suggested that tumour associated
endothelial cells proliferate 50-200 times faster than normal endothelial cells (66, 67).
The growth of tumour blood vessels is regulated by a balance in the expression of various
pro- and anti-angiogenic factors, such as VEGF and thrombospondin-1, respectively (5,
68) (Figure 1.5).
Due to the irregular vasculature in tumours, there are also differences in blood
flow within tumours compared to normal tissues, which might affect drug delivery to the
tumour cells (69, 70). Tumour vessels are leaky due to poorly organized endothelial cell
contacts and basement membrane (63, 71, 72). Due to a lack of functional lymphatics
within solid tumours, fluids that leak out of tumour vessels are not adequately cleared,
thereby causing an increase in the interstitial fluid pressure (IFP) within the tumour (69,
70). This increased IFP can greatly alter the extravasation of anticancer drugs (by
diffusion or convection) from blood vessels into the tumour tissue (42, 69). Therefore, the
dysfunctional vasculature present in solid tumours can lead to decreased drug distribution
in tumours.
i. Targeting the tumour vasculature
Many studies have focused on the inhibition of tumour angiogenesis as a potential
treatment modality for inhibiting tumour growth (73). In order for tumour cells to
repopulate a tumour, the presence of a functional vascular network is necessary.
20
Figure 1.5 Regulation of tumour vasculature. Normal vasculature is highly organized and well perfused. There is a regulated balance between proangiogenic factors, such as vascular endothelial growth factor (VEGF), and antiangiogenic factors, such as thrombospondin-1; this balance ensures normal vascular remodeling and adequate perfusion of tissues within the body. Tumour growth is accompanied by an increase in the production of VEGF and other proangiogenic factors, thereby interrupting the balance between proangiogenic and antiangiogenic factors. In contrast to normal blood vessels, tumour vasculature is highly disorganized (i.e. shunting, blunt ends) and tumour vessels are often leaky and contain regions with irregular and insufficient perfusion. Modified from Jain RK et al., Nature Rev Neurosci 2007;8:610-622.
21
Therefore, cutting off the supply of oxygen and nutrients by targeting tumour vasculature
might reduce the repopulation of tumour cells following treatment. There are many types
of antiangiogenic agents being studied or used in the clinic, including inhibitors against
vascular endothelial growth factor (VEGF) or the VEGF receptors.
The cytotoxic effects of chemotherapy are non-specific and might therefore affect
the tumour microenvironment, particularly the tumour vasculature, in addition to
targeting tumour cells. Limited studies have examined the effects of chemotherapy on
vasculature; however, since drug effects against solid tumours depend on drug delivery
through the tumour blood vessels, this is an important topic of study. Research has shown
that taxanes, such as paclitaxel and docetaxel, have effects that inhibit endothelial cell
proliferation and migration in vitro, as well as vascular disrupting properties in vivo that
may result in decreased vascular density within treated tumours (74-77). Studies reported
in this thesis (chapter 2) have shown a similar decrease in total and perfused tumour
vasculature following a single dose of paclitaxel in xenografts grown in nude mice.
Browder et al. and others have studied the antiangiogenic properties of
chemotherapy when administered more frequently at lower doses (78-81).
Antiangiogenic chemotherapy, also known as metronomic chemotherapy, has the
potential to cause more endothelial cell apoptosis due to the continuous administration of
chemotherapy, in contrast to the scheduling of chemotherapy at close to its maximum
tolerated dose (MTD) at approximately 3-week intervals (78, 81-84).
Recent studies have suggested that chemotherapy administered at doses near the
MTD may also have effects on tumour vasculature (85). Shaked et al. examined the
effects of various chemotherapy drugs administered at MTD on tumour vasculature (85).
22
23
It was observed that taxanes such as paclitaxel and docetaxel, as well as 5-FU, were able
to cause a decrease in microvascular density and a corresponding increase in the
recruitment of circulating endothelial progenitors (CEPs), which might contribute to
vascular rebound following treatment (85). Conversely, chemotherapeutic agents such as
gemcitabine, cisplatin, and doxorubicin did not have such effects on vascular density or
circulating endothelial progenitors (85) (Figure 1.6).
Anticancer drugs, such as chemotherapy or molecular targeted agents, can also
affect vascular perfusion in tumours. Chemotherapeutic agents (e.g. paclitaxel) have been
shown to decrease vascular perfusion in tumour xenografts (85). In addition, a study by
Moasser et al. showed that treatment with the molecular targeted agent gefitinib (an
EGFR inhibitor) led to increased perfusion in human breast cancer xenografts (86).
ii. Measuring tumour vasculature
A possible caveat to disrupting tumour blood vessels is that functional vasculature
is also necessary for delivery of cytotoxic agents and anticancer drugs in the treatment of
solid tumours. Thus, it is important to study the effects of anticancer agents on the
structure and functionality of tumour blood vessels. When studying the vasculature of
solid tumours grown in mice, it is important to understand the similarities and differences
between mouse and human blood vessels. Mouse endothelial cells have been shown to
express many similar cell surface markers to human endothelial cells, including CD34,
CD36, endoglin (CD105), CD146, VCAM1 (CD106), Tie1, CD31, and VEGFR2;
however, the levels of expression can vary in different murine endothelial cell lines (87).
CD31 (also known as platelet endothelial cell adhesion molecule, PECAM-1) is an
Figure 1.6 Effect of chemotherapy on tumour vasculature. Some chemotherapeutic agents (e.g. paclitaxel, docetaxel, and 5-FU) have been shown to have antiangiogenic effects on tumour vasculature when administered at maximum tolerated doses (MTD). Agents, such as paclitaxel, led to a decrease in the microvascular density and vascular perfusion, while other drugs, including gemcitabine, cisplatin, and doxorubicin, did not have effects to decrease tumour vasculature within solid tumours. Following treatment with paclitaxel, docetaxel, or 5-FU, there was a subsequent increase in the recruitment of circulating endothelial progenitors (CEPs) leading to a rebound in the tumour vasculature (85).
24
adhesion molecule found on both mouse and human endothelial cells that is often used as
a marker of tumour vasculature (87, 88). In addition, various agents can be used to
examine the perfusion of tumour vasculature. Hoescht 33342 is an autofluorescent dye
that binds tightly to DNA and is often used as a marker of perfused vessels (89). The
carbocyanine derivative DiOC7 is an autofluorescent dye that is retained in cells and
outlines perfused blood vessels by staining the first layer of cells surrounding the vessel
(90). Lectins are plant extracts that bind to O-linked or N-linked glycans present on
endothelial cells and can be used to measure vascular perfusion in tumours (91, 92).
1.5c Hypoxia
Tumour vasculature is often irregular and poorly organized, with shunting and
variable flow in solid tumours, thereby leading to regions with low oxygen and nutrient
concentrations (93). Acute (or transient) hypoxia occurs due to changes in the perfusion
of tumour vasculature, whereas chronic hypoxia typically arises at distances of greater
than 70μm from functioning vessels due to the limited diffusion of oxygen to these
distances (94-96). Anoxia, the absence of oxygen, results in immediate cell cycle arrest,
which is often followed by cell death (20, 96). Regions of necrosis are often seen at
distances of ~150μm from blood vessels in human tumours, and ~100μm from blood
vessels in mouse tumours, suggesting that cell death occurs due to severe lack of oxygen
and other nutrients, or the build up of toxic catabolites (6, 97).
The presence of hypoxia activates the transcription factor hypoxia-inducible
factor 1 (HIF-1), which has been implicated in angiogenesis, cell survival, metabolism,
pH regulation, and metastasis (21, 97, 98). HIF is a heterodimer with 3 different alpha
25
subunits (HIF-1α, HIF-2α, and HIF-3α) and a beta subunit (HIF-1β) (21, 98). The HIF-1β
subunit is constitutively expressed, and it is the expression/stabilization of the HIF-1α
subunit under hypoxic conditions that allows association of HIF-1α with the HIF-1β
subunit, thereby leading to HIF-1 activation (21).
HIF-1 regulates expression of target genes through hypoxia-responsive elements
(HRE) located on these genes (21). Some of these targets include erythropoietin (EPO),
vascular endothelial growth factor (VEGF), insulin-like growth factor (IGF2),
transforming growth factor-α (TGF-α), multidrug resistance protein 1 (MDR1), and many
others (21, 98, 99). The cellular response to hypoxic conditions can vary in different cell
types dependent upon the interaction of HIF-1 with numerous potential transcription
factors, which might activate different downstream target genes (98).
The effects of hypoxia are complex. Hypoxia can lead to cell death following the
induction of apoptosis through p53-dependent and p53-independent mechanisms (96).
Conversely, under sustained hypoxic conditions, radiation therapy is less effective due to
decreased formation of oxygen free radicals (100), and tumour cells may become
quiescent, thereby rendering them radio-resistant. Furthermore, hypoxic cells may also
develop proteomic or genomic alterations, which could lead to a more aggressive
phenotype (96).
Hypoxic conditions can lead to cell death through apoptosis. It has been suggested
that p53-dependent apoptosis is likely to occur under severe hypoxia or anoxia (21).
Under transient hypoxic conditions, p53-independent mechanisms of apoptosis may be
regulated by HIF-1 activation. For example, the pro-apoptotic Bcl-2 family member
BNIP3 is upregulated by HIF-1 under hypoxic conditions, but is not regulated by p53
26
(21). BNIP3 can induce cell death through effects on the mitochondria and formation of
reactive oxygen species (ROS); however, its effects to promote cell death may also be
negated by HIF-1 mediated expression of growth factors and their receptors (21). This
highlights the paradox of pro- and anti-apoptotic responses of HIF-1 under hypoxia.
Tumour hypoxia is often associated with poor clinical outcome (96). Hypoxic
tumours may be resistant to chemotherapy due to various factors such as limited drug
distribution into hypoxic regions, as well as the activation of genes associated with
angiogenesis and cell survival (6). It has also been suggested that hypoxia allows for
selection of a cell population that has increased proliferation and survival, and is more
resistant to treatment (21). Tumour cells with p53 mutations are commonly found in
hypoxic regions, which may lead to a more aggressive phenotype and increased
repopulation of the tumour (101).
It is hypothesized that repopulation may occur in areas of transient hypoxia due to
improved availability of oxygen and nutrients to cells in these regions as cells proximal to
blood vessels are killed by chemotherapy; these previously hypoxic cells re-enter the cell
cycle and begin proliferating thereby repopulating the tumour. Therefore, use of a
hypoxia-activated cytotoxic agent might complement cell kill in proximal regions by
targeting tumour cells that are distal to functional vasculature. By targeting cells in
hypoxic areas it may be possible to increase treatment efficacy by preventing
repopulation.
Tirapazamine is a hypoxia-activated cytotoxic agent that has been studied in
clinical trials (102, 103). Tirapazamine exerts its cytotoxic effects through the formation
of double-strand breaks in a topoisomerase II-dependent process (104). Tirapazamine
27
showed some promising results in early-phase clinical trials; however, a limiting factor
for the use of tirapazamine in combined treatment regimens is its toxicity to normal
tissues, especially neurotoxicity (105).
Another hypoxia-activated prodrug is AQ4N, which is converted to AQ4, an
analogue of mitoxantrone, under hypoxic conditions (106-108). Studies in mice showed
that over time, AQ4/AQ4N distributed into hypoxic regions of solid tumours (107).
Combined AQ4/AQ4N and mitoxantrone treatment was well distributed within tumour
tissue and was also effective at delaying tumour growth (107). Other hypoxia-activated
prodrugs currently being evaluated include PR-104 and TH-302. PR-104 is a
dinitrobenzamide mustard that is metabolized in hypoxic regions, and it is proposed that
its metabolites cause cytotoxicity through DNA-crosslinking; PR-104 is currently being
studied in clinical trials (109, 110). Bromo-isophosphoramide (Br-IPM) is the cytotoxic
component of TH-302, and it also acts as a DNA cross-linking agent (111). Clinical
studies with TH-302 monotherapy showed antitumour activity with toxicites mainly
limited to oral and gastrointestinal mucositosis; clinical trials of TH-302 used in
combination with chemotherapy are ongoing (112).
1.5d Stem Cells
Normal human tissues contain a subset of “stem cells” that have the capacity to
self-renew or differentiate into separate and distinct cell populations (113, 114). Stem
cells are important for normal tissue development, as well as regeneration of normal
tissues such as the bone marrow (114). It has been suggested that stem cells are present
within solid tumours and may be involved in repopulation of the tumour between courses
28
of treatment. The presence of cancer stem cells was suggested by studies with human
acute myeloid leukemia (AML) whereby a small population of CD34+CD38- cells
(approximately 0.1-1% of total cell population) was able to recapitulate human leukemia
when injected into immunodeficient mice (115, 116). Further studies have identified
putative cancer stem cells in various solid tumours, including breast, pancreatic, brain,
and colorectal tumours (117, 118).
The origin of cancer stem cells is not clearly defined. It has been hypothesized
that tumour stem cells might originate from the transformation of a normal stem cell, or
from the transformation of a committed progenitor cell (119). There are many models
used to describe tumour regeneration capacity. One model is the cancer stem cell (CSC)
model, which suggests that there are cells with stem-like properties that can self-renew
and differentiate to propogate tumour growth in a hierarchical manner (116, 120).
Another model, the clonal evolution model, suggests that all undifferentiated cells have
the capacity to regenerate the tumour, and the dominant population (mainly composed of
mutated tumour cells that possess a growth advantage) is likely responsible for tumour
growth propogation (120, 121).
Normal stem cells are thought to reside in a microenvironment, known as the stem
cell niche, that supports and maintains stem cell fate by regulating their self-renewal
and/or differentiation through cell-cell interactions and secreted factors (122). The
presence of a stem cell niche was first described by Schofield in 1978 (123); recently,
stem cell niches have been characterized for intestinal, neural, epidermal, and
hematopoietic stem cells (124). Studies have shown that hematopoietic stem cells appear
to reside in more than one type of microenvronment: an osteoblastic niche situated near
29
osteoblasts in the bone marrow, and a vascular niche localized near endothelial cells of
the sinusoidal vessels in the bone marrow or the spleen (125-128). It has been suggested
that the osteoblastic niche is where stem cells reside in their quiescent state, and when
stem cell differentiation is required, they migrate to the vascular niche (128-131). The
osteoblastic niche is hypoxic, suggesting that hypoxia might favour and support stem cell
quiescence; in contrast, the presence of higher levels of oxygen in the vascular niche
might aid in the differentiation of stem cells (122, 129, 132, 133).
Despite limited data, it has been proposed that cancer stem cells might also reside
within a niche. Some studies suggest the presence of a niche in bone marrow that is
occupied by acute myeloid leukemia (AML) stem cells (129, 134, 135). The presence of
a cancer stem cell niche in solid tumours is more difficult to define. A study by Calabrese
et al. showed that putative cancer stem cells in brain tumours (i.e. CD133+ and Nestin+
cells) were selectively localized near endothelial cells, suggesting the presence of a
perivascular niche (136).
Various studies have identified putative CSCs in transplanted murine tumours
through serial transplantation in mice that result in tumours with similar phenotypes; in
addition, stem-like cancer cells in primary human tumours have been identified through
xenotransplantation in mice to determine whether putative CSCs are able to establish
tumours with properties/phenotype similar to the primary human tumour (137). However,
isolation and characterization of putative stem cells from a solid tumour is quite difficult.
For instance, it is necessary to determine the capacity of potential CSCs to initiate
tumours that possess the same characteristics as the primary tumour in numerous serial
transplantations in different generations of mice. It is important to implant tumours
30
31
orthotopically, which might be difficult depending on the tumour site. Moreover, there
are many limiting factors that prevent tumour growth when human cancer cells are
injected into mice (i.e. xenotransplantation), such as the lack of compatible growth
stimuli, which might limit the ability to study CSCs from human cancers (137, 138).
Recently, potential cancer stem cell markers have been identified (Table 1.1),
which might aid in the identification of putative cancer stem cells (117, 118, 137). Some
common markers include CD133, CD44, CD24, and ALDH1. CD44+CD24-/low breast
cancer cells were shown to initiate tumour formation when injected in low quantities (as
few as 200 cells) into immunocompromised mice (139). Similarly, CD133+ cells have
been found to initate formation of human brain tumours in immunocompromised mice
(140) and has aided in the identification of putative cancer stem cells (CSCs) in colorectal
cancer (141, 142). Recent data have described the isolation of putative cancer stem cells
in prostate and lung cancer with CD44+/α2 integrin+/β1 integrinhi/CD133+ and CD133+
phenotypes, respectively (143, 144); however, further in vivo studies are necessary to
distinguish their serial tansplantation and self-renewal capabilities. Aldehyde
dehydrogenase 1 (ALDH1) has been used as a putative stem cell marker in various
cancers, including lung and breast cancer (145, 146); however, studies in ovarian cancer
suggest that ALDH1 might be a favourable prognostic marker (147). The ability to
definitively distinguish stem cells by the presence of a combination of markers has not
been reproducible for many tumour types and might therefore differ between cancers, as
well as in tumours of the same cancer type (137).
Clinically, some solid tumours can respond initially to therapy only to regrow
months or years following treatment. It has been hypothesized that this is due to the
Table 1.1 Putative cancer stem cell markers
Cancer Type
Putative stem cell markers
Experimental data
Acute myeloid leukemia (AML)
CD34+CD38- CD34+CD38- cells induced AML in SCID mice, and retained self-renewal and differentiation properties following serial transplantation (115, 116)
Brain CD133+ CD133+ cells initiated brain tumour formation in NOD-SCID mice upon serial transplantation; self-renewal and proliferative properties similar to primary tumours (140)
Breast CD44+CD24-/low
CD44+CD24-/low cells formed breast tumours in NOD/SCID; similar self-renewal and differentiation properties observed. Serial transplantation studies completed (139)
ESA+ (Epithelial specific antigen)
CD44+CD24-/low ESA+ cells consistently formed breast tumours in NOD/SCID mice; ESA+ subset of CD44+CD24-/low cells showed more tumourigenic potential compared to the ESA- fraction (139)
PROCR+ (Protein C receptor, CD201)
PROCR has been found to be present on all CD44+CD24-/low breast cancer cells (118, 148)
ALDH1 (Aldehyde dehydrogenase-1)
Human breast tumour cells with high ALDH activity were isolated and xenotransplantation in NOD/SCID mice resulted in tumours that recapitulated the parental tumour heterogeneity (145)
Colorectal CD133+ Colon cancer-initiating cells were found in the CD133+ population; this cell population was capable of tumour formation, self-renewal, and differentiation (141, 142)
Epithelial cell adhesion molecule (EpCAM)high/CD44+ CD166+
EpCAMhigh/CD44+ cells isolated from patient tumours and/or xenografts were injected into NOD/SCID mice and tumours were initiated that had a similar phenotype to the primary tumour (149) CD166 can be used for further enrichment of CSCs in the EpCAMhigh/CD44+ population
Head and neck
CD44+ CD44+ cells isolated from patient samples were able to form tumours in NOD/SCID mice. Serial transplantation studies resulted in tumours with similar heterogeneity as the primary tumours (150)
Lung CD133+ CD133+ cells from patient tumours were able to form lung cancer spheres in culture, and tumours in SCID mice. The xenografts were morphologically similar to original tumours. Serial transplantation studies were not completed (144)
ALDH1+ Lung cancer cells with high ALDH1 activity were capable of forming tumours in Swiss nu/nu mice. Serial transplantation was not completed (146)
Pancreatic CD44+CD24+ epithelial specific antigen (ESA)+
CD44+CD24+ ESA+ cells were highly tumourigenic with as few as a 100 cells causing tumour formation in ~50% of the NOD/SCID mice injected. Tumours were histologically similar to the original human samples (151, 152)
Prostate CD44+CD24- Tumour formation was observed following injection of as few as 1000 CD44+CD24- prostate tumour cells in NOD/SCID mice (153)
CD44+α2integrin+β1 integrinhiCD133+
CD44+α2integrin+β1integrinhiCD133+ cells showed self-renewal and differentiation capabilities in vitro. Future studies should be undertaken in vivo (143)
32
presence of cancer stem cells that were not abrogated through standard cancer treatment,
thereby allowing the regrowth of tumours over time. Studies have shown that tumour
cells (and possibly cancer stem cells) may remain dormant within the body for months or
years due to lack of functional vasculature or anti-proliferative signals (58-60, 119, 154,
155). Hence, there is much interest in identifying putative cancer stem cells in order to
further determine the effects of therapies on these cells, as well as to develop targeted
therapies directed at CSCs (118). By targeting stem cell populations, we may be able to
reduce tumour regrowth after drug treatment. However, direct targeting of cancer stem
cells may be difficult as there is no definitive way to isolate stem cells to date, nevermind
testing the effects of drugs on this specific sub-population. Moreover, it is important to
better understand the origin of cancer stem cells (i.e. cancer stem cell vs. clonal evolution
models) in order to effectively target these sub-populations to prevent tumour regrowth.
Drug resistance has been described in many solid tumour models and this might
be due to resistance of cancer stem cells to conventional anticancer treatments (119, 156).
If cancer stem cells possess qualities similar to normal stem cells, then their low
proliferative rate might render them less susceptible to treatments that preferentially
target proliferating cells such as many chemotherapy agents and radiotherapy (119, 137,
156). In addition, many putative cancer stem cells express drug efflux pumps that would
also render them less susceptible to anticancer agents (119, 156).
A possible caveat to targeting stem cells within tumours is the potential for
normal tissue toxicity, specifically in tissues that rely on stem cells for repopulation such
as bone marrow, the GI tract, and hair follicles (119, 156). It is therefore important to
33
identify distinguishing features between normal and cancer stem cells that can aid in
targeting treatment to CSCs specifically.
1.6 INHIBITION OF REPOPULATION
Strategies to inhibit repopulation following chemotherapy include dose-dense
chemotherapy, metronomic chemotherapy, or combined treatment with cytostatic
biological agents. Dose-dense chemotherapy follows a similar principle as accelerated
radiotherapy fractionation in that intervals between treatments are reduced. Growth
factors are administered to stimulate bone marrow repopulation, thereby shortening
intervals between courses of chemotherapy to two weeks; this decreases the amount of
time between cycles thereby reducing tumour cell repopulation (24). Others have studied
the effects of low-dose chemotherapy administered at more frequent intervals; this is also
known as metronomic chemotherapy (78-81, 157). Another treatment strategy is to
combine cytostatic agents with chemotherapy to try to inhibit repopulation between
cycles of treatment.
1.6a Potential Targets & Properties of an Ideal Inhibitor
Most chemotherapy drugs are anti-proliferative and affect all dividing cells within
the body; this limits their use in the clinic due to normal tissue toxicity. Anticancer agents
have been developed that can target biological molecues important for tumour growth
and progression; these drugs are known as molecular-targeted agents. Targeted
therapeutic agents have been studied extensively for their activity against human cancer.
34
These agents may target components of cell signalling pathways, hormone receptors,
growth receptors, or other targets. The use of targeted drugs as single agents provides an
avenue for targeting a specific molecular pathway that might be more active in cancer
cells. Although molecular targets might not be specific to tumour cells (i.e. they are also
present in normal cells), they are often overexpressed or mutated in tumours, thereby
making tumour cells more susceptible to targeted therapies. In addition, targeted
treatments can be combined with standard therapy (i.e. radiation or chemotherapy) to
increase treatment efficacy.
Biological targeted agents might be used to inhibit repopulation between cycles of
chemotherapy. Ideally, such agents should be tumour-specific, have a rapid onset of
activity, and possess a short half-life, in order to decrease repopulation but also allow
tumour cells to re-enter the cell cycle, and regain susceptibility to further cycle-active
anticancer chemotherapy. Inhibitors that have a rapid onset of activity can provide
growth inhibition immediately following drug administration; this will provide less
opportunity for repopulation. Since most chemotherapy agents target proliferating cells, a
short inhibitor half-life is necessary so that tumour cells can begin proliferating within a
short time after removal of the inhibitor; this increases susceptibility of tumour cells to
chemotherapy.
1.6b Epidermal growth factor receptor (EGFR)
In many normal tissues, growth factors stimulate the repopulation of cells. Some
growth factor receptors, including the epidermal growth factor receptor (EGFR), are
overexpressed and/or deregulated in many human cancers. Ionizing radiation has been
35
shown to activate EGFR signalling, which may lead to increased tumour cell
proliferation; high EGFR levels have been correlated to poor outcomes following
radiotherapy (158-162). Increased EGFR signalling, due to overexpression of the
receptor, may also play a role in repopulation during chemotherapy. Therefore, the
epidermal growth factor receptor may be a potential target for inhibiting repopulation
between courses of radiation and chemotherapy treatment.
i. Structure and Function
The epidermal growth factor receptor (EGFR) (also known as erbB1 or HER1) is
a member of the erbB family of tyrosine kinase receptors, along with the
erbB2/HER2/neu, erbB3/HER3, and erbB4/HER4 receptors. Overexpression of each of
these receptors has been identified for various cancers, including lung, breast, colon, and
pancreatic cancer, among others.
The EGF receptor is composed of an extracellular (N-terminal) ligand-binding
domain, a transmembrane segment, and an intracellular (C-terminal) tyrosine kinase
domain. The two main ligands that bind with high affinity to the epidermal growth factor
receptor are epidermal growth factor (EGF) and transforming growth factor-α (TGF-α)
(2, 163). Upon binding to the receptor, the ligand causes receptor dimerization,
autophosphorylation, and activation of downstream signalling pathways. Receptor
dimerization results in the formation of homo- or hetero-dimeric receptor pairs, which
initiate distinct biological responses (164). Activation of different signalling pathways
can occur and is dependent upon the specific receptor dimers that are formed. The
formation of heterodimeric receptor pairs leads to great diversity in the signalling from
36
erbB receptors. For example, receptors that are not activated by a specific ligand may be
cross-activated if the ligand-specific receptor is present in the dimer (2). Three major
signalling pathways are associated with EGFR activation: (a) the Ras-Raf-MAPkinase
pathway; (b) the phosphatidyl-inositol-3 (PI-3) kinase and Akt pathway; and (c) the
stress-activated protein kinase pathway involving Jak/Stat and protein kinase C (165).
The MAPK pathway has been implicated in regulation of cellular processes such as cell
proliferation, differentiation, movement, and cell death. The PI3K and Akt pathway has
been shown to promote survival and inhibit apoptotic processes (2).
ii. Other ErbB Receptors
The erbB2 (HER2/neu) receptor has homology to EGFR, and it is a more potent
oncoprotein (2). It also has an inactive ligand-binding domain, and lacks specific ligands;
therefore, the erbB2 receptor is the preferred dimerization partner for other erbB
receptors (164).
The erbB3 and erbB4 receptors are structurally similar; however, their functions
are less well described. The erbB3 receptor contains an inactive tyrosine kinase domain;
therefore, receptor signalling can only be initiated through receptor dimerization with
other members of the erbB family (2). Furthermore, signalling through the erbB3 and
erbB4 receptors seems to occur preferentially through the PI-3 kinase pathway (2).
iii. ErbB Receptors in Normal Development and Oncogenesis
ErbB receptors are important in normal biological development, specifically in
the development of the nervous system, the cardiovascular system, and the mammary
gland (166). The epidermal growth factor receptor (EGFR) is essential in the regulation
37
of normal cell growth and differentiation (2). However, overexpression, deregulation, or
mutation of EGFR has been found in many cancers, contributing to tumour growth and
progression (167). For example, stimulation of the EGFR in cancer has been shown to
promote processes such as proliferation, angiogenesis, invasion, metastasis, and
inhibition of apoptosis (2, 167).
iv. EGFR and Angiogenesis
The epidermal growth factor receptor (EGFR) has been implicated in
angiogenesis, and has been found to be expressed on blood vessels in various tumour
types (154-164). A study by Amin et al. reported that normal endothelial cells express
erbB2, erbB3, and erbB4 receptors; however, tumour-derived endothelial cells express
EGFR, erbB2, and erbB4 (168). The switch from erbB3 to EGFR in tumour endothelial
cells seems to promote angiogenesis through: 1) increased cell proliferation due to
increased EGFR activation and signalling; and 2) loss of growth inhibition from erbB3
expression (168).
1.6c EGFR Inhibitors
The epidermal growth factor receptor (EGFR) has been targeted for cancer
therapy due to its role in various cancers. Four possible approaches for the inhibition of
EGFR signalling include: (a) monoclonal antibodies to block the extracellular domain of
EGFR; (b) inhibition of their intracellular tyrosine kinase (RTK) domains; (c) inhibition
of receptor trafficking to the cell membrane; and (d) inhibition of EGFR production
through the use of antisense oligonucleotides (165). As yet, only monoclonal antibodies
38
and RTK inhibitors have been tested in clinical trials. Due to EGFR overexpression in
cancer, inhibitors targeted to the epidermal growth factor receptor may be more tumour-
specific than traditional chemotherapeutic agents. As these agents are initially cytostatic,
they might be more useful at inhibiting tumour cell repopulation.
i. Monoclonal Antibodies (mAbs)
Several monoclonal antibodies have been developed that target the EGFR, which
can compete for ligand binding to its extracellular domain, thereby inhibiting receptor
activation and subsequent downstream signalling (2). Cetuximab (Erbitux), a chimeric
human-mouse monoclonal antibody, has been studied in various clinical trials. It blocks
ligand-induced receptor activation, autophosphorylation, and internalization, causing cell
cycle arrest (2). It inhibits growth of EGFR-expressing cancer cells in vitro, and causes
reduction in tumour volume and increased mouse survival in vivo (2). Moreover,
cetuximab has shown activity in metastatic colorectal cancer with a modest increase in
survival in phase III clinical trials (169, 170), as well as increased survival when
combined with radiation for head and neck cancer (likely due to inhibition of
repopulation) (171, 172). Other mAbs directed at the EGFR function by increasing
receptor internalization and degradation, or through the recruitment of immune effector
cells to induce immune cytotoxicity (2).
ii. Tyrosine Kinase Inhibitors
The small-molecule EGFR tyrosine kinase inhibitors gefitinib (Iressa; ZD-1839)
and erlotinib (Tarceva) have also been evaluated in clinical trials as therapeutic agents
39
against various types of cancer. They are orally active synthetic anilinoquinazolines that
inhibit the tyrosine kinase of the epidermal growth factor receptor (2, 167). Gefitinib and
erlotinib compete with ATP binding to the tyrosine kinase portion of the EGF receptor;
upon binding, the catalytic activity of the receptor is blocked and signal transduction
pathways are inhibited (173).
iii. Pharmacokinetics of Gefitinib
The pharmacokinetics of gefitinib are well described in humans. A single oral
dose (250 mg) of gefitinib achieves a maximum plasma concentration of approximately
200 ng/mL within 3-7 hours after dosing (174, 175). Gefitinib is mainly cleared by the
liver; studies have shown a plasma clearance rate of 36L/h and a terminal half-life of
approximately 20-48 hours after oral or intravenous (i.v.) administration in humans (174,
175). The clearance rate is defined as the volume of body fluid from which a drug is
removed by biotransformation and/or excretion per unit time.
Pharmacokinetic data in mice are not as well established. McKillop et al.
measured gefitinib concentrations in mouse plasma and tumour xenografts (50). They
found the elimination half-life of gefitinib was approximately 3 hours in plasma and
ranged from 4.7-5.8 hours in the three tumour xenografts tested (LoVo, human colorectal
adenocarcinoma; A549, human lung carcinoma; and Calu-6, human lung anaplastic
carcinoma) (50).
iv. Clinical Trials: Gefitinib (Iressa) and Erlotinib (Tarceva)
Various preclinical studies have shown anti-proliferative effects of gefitinib and
erlotinib in tumour cell cultures in vitro and human tumour xenografts in vivo (167, 176).
40
In both phase I and phase II clinical trials, a subset of patients showed inhibition of
tumour growth and symptom improvement with gefitinib treatment (165). Likewise,
phase II trials with erlotinib resulted in symptom improvement in some non-small-cell
lung cancer patients (177). Phase III trials conducted with erlotinib resulted in prolonged
survival in patients with non-small-cell lung cancer that had previously received first- or
second-line chemotherapy (178). However, results obtained from phase III trials
(INTACT 1 and INTACT 2) performed to evaluate the effects of gefitinib plus anticancer
agents (gemcitabine, cisplatin, paclitaxel, and carboplatin), chemotherapy alone, or
placebo, in advanced non-small-cell lung cancer patients were not encouraging. Gefitinib
in combination with chemotherapy did not show improved survival when compared to
chemotherapy alone (179, 180).
A recent study by Mok et al. examined the efficacy of gefitinib treatment used
alone as first-line therapy in a subset of non-small-cell lung cancer patients with EGFR
mutations (non-smokers or former light smokers), compared to standard chemotherapy
(carboplatin-paclitaxel). Gefitinib treatment resulted in longer progression-free survival
in patients with EGFR mutations compared to patients who received chemotherapy alone
(181).
v. Gefitinib and tumour vasculature
Due to the role of EGFR in angiogenesis, many studies have focused on the
antiangiogenic properties of EGFR inhibitors. Recent studies have shown that the EGFR
inhibitor gefitinib harbours antiangiogenic properties (168, 182). Amin et al. used a
melanoma xenograft model in which the tumour blood vessels expressed the epidermal
41
growth factor receptor, whereas the tumour cells themselves did not express the EGFR
(182). They showed that gefitinib was able to slow tumour growth compared to control
tumours suggesting effects of the inhibitor on the tumour vasculature (182). The level of
EGFR phosphorylation rather than the expression of EGFR was decreased on the tumour-
derived endothelial cells following gefitinib treatment (182, 183). Interestingly,
endothelial cells derived from tumours treated with gefitinib did not show high levels of
EGFR activity or response to EGF stimulation when grown in culture; however, these
endothelial cells expressed higher levels of the vascular endothelial growth factor
receptor 2 (VEGFR-2) indicating an increase in VEGF receptor signalling following
gefitinib treatment in these tumours (182). Many studies have suggested that tumour cells
might develop alternative signalling thereby leading to a decrease in sensitivity to
inhibitor treatment (182); this could also apply to tumour-derived endothelial cells.
1.6d mTOR Inhibitors i. Mammalian target of rapamycin (mTOR)
The PI3 kinase pathway is implicated in various cancers due to its role in cell
proliferation, cell survival, and inhibition of apoptosis. Activation of PI3K and Akt leads
to an increase in phosphorylation of downstream effectors (S6K1 and 4E-BP1) through
mTOR activation (184). Activation of Akt prevents the formation of the regulatory
TSC1/TSC2 complex through phosphorylation of TSC2, thereby stopping the repression
of mTOR activity (185-187).
42
The mammalian target of rapamycin (mTOR), also known as FRAP, is a 289 kDa
serine/threonine kinase located downstream of Akt in the PI3 kinase signalling pathway,
and plays a regulatory role in various cellular processes including cell cycle progression,
DNA damage and DNA repair (184, 188). mTOR activity is mainly regulated through
growth factors that activate signalling through PI3K and Akt, as well as by increased
nutrient and ATP levels, although this mechanism is currently unknown (9, 10, 184, 189-
193).
mTOR is composed of two multiprotein complexes, mTORC1 and mTORC2
(194). In cells stimulated by growth factors or nutrients, the mTORC1 complex regulates
two proteins involved in protein synthesis: the serine-threonine kinase p70s6k (S6K1) and
the translational-repressor protein 4E-BP1 (194, 195). mTOR activates the ribosomal
kinase S6K1, and phosphorylates and inactivates 4E-BP1, which acts as a suppressor of
the eukaryotic initiation factor 4E (eIF4E) (196-198). The function and mechanism of
mTORC2 activation is unclear (194).
mTOR function is maintained through many regulatory proteins, including raptor
(regulatory-associated protein of mTOR), and the tuberous sclerosis complex (TSC)
proteins (TSC1 and TSC2) (184). The role of raptor is not clearly understood; however,
raptor and the TSC1/TSC2 complex are thought to regulate mTOR in reponse to nutrient
signals (184).
Aberrant signalling in the PI3K and Akt pathway is common in cancer, especially
in prostate and breast cancers; this in turn affects signalling through mTOR (199-201). In
addition, overexpression of upstream growth or hormone receptors (i.e. HER-2/neu or the
estrogen receptor) or the loss of the tumour suppressor protein phophatase and tensin
43
44
homolog (PTEN) can increase Akt activity and subsequent signalling through mTOR
(184). Tumours with high Akt activity have been found to be more sensitive to treatment
with mTOR inhibitors (184, 188, 200).
ii. mTOR inhibitors—rapamycin and its analogues
The mTOR is an attractive target for inhibiting tumour cell growth and
proliferation (Figure 1.7). Inhibitors targeting the mTOR protein, such as rapamycin and
its analogues temsirolimus (CCI-779; Wyeth), everolimus (RAD001; Novartis), and
deforolimus (AP23573; ARIAD Pharmaceuticals), have been investigated in preclinical
and clinical studies (194, 202-205). Rapamycin was first used in the clinic for its
immunosuppressant properties, and it was extensively studied for its anti-proliferative
qualities. Rapamycin has poor aqueous solubility and several synthetic analogues of
rapamycin have been developed (188).
These inhibitors act by forming a complex with FKBP12 (a peptidyl-prolyl-cis-
trans isomerase), which then binds mTOR and inhibits its kinase activity (184, 188).
Subsequently, inhibition of mTOR leads to a block in the activation of the 40S ribosomal
protein S6 kinase (through p70s6k), as well as the eukaryotic initiation factor 4E (eIF4E)
(188). p70s6k is involved in the regulation of translation of mRNAs that encode for
proteins involved in protein synthesis, whereas 4E-BP1 regulates translation of mRNAs
that encode for proteins such as growth factors and cell cycle regulators (184, 188). Thus,
inhibition of mTOR causes cell cycle arrest in the G1 phase (188, 206, 207). Studies have
shown that mTOR inhibitors (i.e. rapamycin and temsirolimus) might also induce
Figure 1.7 Signalling upstream and downstream of the mammalian target of rapamycin (mTOR). The mammalian target of rapamycin (mTOR) lies downstream of Akt in the PI3 kinase pathway. It is activated by Akt and regulates two proteins involved in protein synthesis, the serine-threonine kinase S6K1 and the translational-repressor protein 4E-BP1. Inhibitors of mTOR bind to the protein and block its kinase activity.
45
apoptosis, particularly in cancer cells and tumours that lack functional tumour
suppressors, such as p53 and PTEN (200, 206, 208, 209).
Most mTOR inhibitors selectively inhibit the mTORC1 complex; however, it has
been shown that mTORC2 can phosphorylate Akt upstream of mTORC1, which might
explain resistance to some mTOR inhibitors (194).
iii. Temsirolimus (CCI-779)
Temsirolimus has been studied extensively in clinical trials (205, 210-213) and
was recently approved by the FDA for use in the treatment of renal cell carcinoma. Phase
I trials tested the toxicity of temsirolimus treatment when administered using different
schedules. Due to potential immunosuppression with continuous treatment, a weekly IV
infusion was evaluated in comparison to a daily IV infusion given for 5 days every 2
weeks (205, 212). Common toxicities included dermatological effects and
myelosuppression, among others; the maximum tolerated dose (MTD) for the daily IV
infusions for 5 days every 2 weeks was between 15-19 mg/m2/day, whereas the
maximum tolerated dose for the weekly IV infusion was not determined since antitumour
effects were observed at doses below the MTD (205, 212).
Phase II clinical trials that studied effects of temsirolimus (75 or 250 mg/m2,
given IV weekly) in patients with advanced or metastatic breast cancer showed
antitumour effects with acceptable toxicities (202). Likewise, patients with advanced
renal cell carcinoma treated with 25, 75, or 250 mg/m2 of temsirolimus showed anti-
tumour activity in each of the treatment groups, with limited toxicity (210).
46
A randomized phase III trial showed that temsirolimus improved overall survival
and disease-free progression survival compared to standard interferon-α treatment in
patients with advanced renal-cell carcinoma; however, there was no improved survival
when the two treatments were combined (213).
Temsirolimus could be used to inhibit repopulation between cycles of
chemotherapy. There are limited studies of temsirolimus used in combination with
chemotherapy. A study of temsirolimus administered concomitantly with gemcitabine for
the treatment of pancreatic cancer in mice showed that combination therapy was more
effective at inhibiting tumour xenograft growth than with either agent alone (214).
Grunwald et al. showed slower prostate xenograft growth with combined doxorubicin
and temsirolimus treatment as compared to doxorubicin alone (215). In addition, our
studies have shown delayed regrowth of prostate tumour xenografts treated with
temsirolimus in combination with docetaxel when compared to either agent alone
(chapter 4).
A Phase I trial testing the effect of temsirolimus and 5-FU and leucovorin in
patients with advanced solid tumours showed partial tumour responses in 3 of 26
patients; however, the study was stopped due to high toxicity observed in patients in the
combined treatment arm (216).
iv. Pharmacokinetics of temsirolimus
In phase I clinical trials of temsirolimus administered intravenously either daily
for 5 days every two weeks, or once weekly with a 30 minute continuous infusion, to
patients with advanced cancers, temsirolimus had a mean terminal half-life of
47
approximately 13-25 hours (205, 212). Sirolimus (also known as rapamycin), the main
metabolite, was detected early after i.v. infusion and increased over time, with a half life
in the range of 40-100 hours, depending on the dose and treatment schedule (205, 212).
Limited data are available on the distribution and pharmacokinetics of
temsirolimus in tumour tissue. One study of gliomas surgically resected from patients
found that temsirolimus and its metabolite sirolimus were able to penetrate into brain
tumour tissue; however, kinetic data were not determined (217).
v. mTOR inhibitors and angiogenesis
In clinical trials, concentrations of mTOR inhibitors are often present at levels
that are associated with minor anti-proliferative effects, and concentrations needed to
induce apoptosis might not be obtained in patients; therefore, it is possible that the
efficacy of these inhibitors might be due to effects on the tumour vasculature (194).
It has been reported that mTOR inhibitors, such as rapamycin (sirolimus) and
temsirolimus, have effects on endothelial cells and tumour angiogenesis (218, 219).
Rapamycin has been shown to block vascular endothelial cell growth factor (VEGF)
signalling, and to have antiangiogenic effects on tumour blood vessels and endothelial
cells grown in culture (218, 220). A study by Del Bufalo et al. showed that treatment
with temsirolimus decreased VEGF production in breast cancer cells, and directly
inhibited endothelial cell growth in vitro and vessel formation in Matrigel plugs in vivo
(219). Temsirolimus treatment also resulted in a significant decrease in microvascular
density in multiple myeloma xenografts grown in mice (206).
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1.7 COMBINING CYTOTOXIC AND CYTOSTATIC THERAPIES
Repopulation occurs in the intervals between chemotherapy treatments and a
potential treatment strategy is to combine an inhibitor with conventional chemotherapy to
inhibit repopulation. Most inhibitors are cytostatic agents (i.e. they decrease proliferation,
often due to cell cycle arrest); therefore, when combining these agents with cycle-active
chemotherapy, it is important to consider cell cycle effects and scheduling of combined
treatment to ensure optimal efficacy.
Some phase III studies of targeted agents used in conjunction with chemotherapy
have not resulted in improved patient survival when compared to monotherapy. A
potential explanation of these results could be due to the treatment scheduling used in the
trials. Various studies have evaluated different treatment schedules when combining
cytotoxic and cytostatic agents; however, results have been conflicting. It is likely that
the solid tumour environment plays a role in the efficacy of combined treatments;
therefore, in addition to cell cycle effects, microenvironmental factors, including changes
in functional vasculature, hypoxia, or drug distribution, should be considered.
49
1.8 RATIONALE Studies have shown that repopulation of surviving tumour cells occurs between courses
of chemotherapy and this may hinder the overall efficacy of anticancer treatment. Using a
cytostatic agent to inhibit repopulation between courses of chemotherapy might cause
decreased proliferation thus rendering cells less susceptible to cycle-active chemotherapy.
In addition, chemotherapeutic drugs can have cytostatic effects on tumour cells (at low
concentrations), and some anticancer agents might lead to a decrease in the percentage of
functional tumour vasculature; these factors can alter the tumour microenvironment, drug
distribution, and treatment efficacy when combining therapies. Understanding the effects
of anticancer agents on repopulation and the tumour microenvironment will aid in
determining the optimal time to administer cytostatic agents in combination with
chemotherapy to inhibit repopulation.
1.9 HYPOTHESES 1. Repopulation in solid tumours occurs in regions distal from blood vessels, and is
likely dependent on changes in the tumour microenvironment
2. Targeted inhibitors, such as gefitinib and temsirolimus, can inhibit tumour cell
repopulation between courses of chemotherapy
3. Sequential administration of chemotherapy and inhibitor treatment will be more
effective than concomitant administration of combined therapy
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1.10 OBJECTIVES & SPECIFIC AIMS The aims of this thesis are to characterize repopulation following chemotherapy,
determine the effects of various targeted cytostatic agents to inhibit repopulation, and to
evaluate different treatment schedules when using combined cytostatic and cytotoxic
treatment.
Objectives:
I. Characterize the repopulation of tumour cells in solid tumours following
chemotherapy treatment
II. To determine the most effective treatment schedule when combining cytotoxic
and cytostatic agents to inhibit repopulation
III. To evaluate the effect of combined drug therapy on tumour vasculature and
the tumour microenvironment
51
Chapter 2
The characterization of repopulation in solid tumours following anticancer treatment and the effects of the tumour microenvironment
on treatment efficacy
Andrea S. Fung and Ian F. Tannock Data from this chapter has been been prepared as a manuscript for submission to Clinical Cancer Research.
52
2.1 Statement of Translational Relevance Repopulation of tumour cells between courses of chemotherapy can greatly decrease
treatment efficacy. Therefore, it is important to study factors that might affect
repopulation, including time-dependent changes in cell proliferation and cell death in
relation to the tumour microenvironment following anticancer treatment. We have shown
that repopulation occurs in human squamous cell carcinoma xenografts following
paclitaxel treatment, and that the increase in cell proliferation after treatment appears to
depend on changes in the functional tumour vasculature. In addition, gefitinib, an
inhibitor of the epidermal growth factor receptor (EGFR), effectively decreases tumour
cell proliferation in high EGFR-expressing xenografts, thereby illustrating the potential
of targeted agents to inhibit repopulation between courses of chemotherapy. The present
study highlights the importance of determining the effects of anticancer agents on the
tumour microenvironment and illustrates the potential of cytostatic agents to inhibit
repopulation within solid tumours.
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2.2 Abstract
Purpose: Surviving tumour cells are known to repopulate the tumour between courses of
chemotherapy. However, the temporal and spatial distribution of repopulation within
solid tumours remains poorly characterized. The present study characterizes repopulation
of surviving cells in a human tumour xenograft following paclitaxel treatment, and
determines the role of the tumour microenvironment in supporting tumour repopulation.
In addition, we evaluate the potential of gefitinib, an epidermal growth factor receptor
(EGFR) inhibitor, to inhibit repopulation. Experimental Design: Human squamous cell
carcinoma A431 xenografts, and human breast cancer MCF-7 xenografts, were treated
with paclitaxel or gefitinib. Changes in the distribution of cell proliferation (Ki67) and
apoptosis (cleaved caspase-3) in relation to tumour blood vessels were quantified using
fluorescence microscopy. The percentage of functional tumour vasculature and hypoxia
was also quantified. Results: Decreases in functional tumour vasculature and in cell
proliferation, and an increase in apoptosis, were observed in A431 xenografts following
treatment with either paclitaxel or gefitinib. A rebound in functional vasculature was
noted ~12 days following paclitaxel treatment, which corresponded with an increase in
cell proliferation observed at this time. Cell proliferation increased ~5 days following the
last dose of gefitinib. There were no major effects of paclitaxel or gefitinib treatment on
cell proliferation, apoptosis, or tumour vasculature in MCF-7 xenografts. Conclusions:
Repopulation occurred in A431 xenografts treated with paclitaxel, and appeared to be
dependent on changes in the functional tumour vasculature. Gefitinib was able to inhibit
cell proliferation in EGFR-overexpressing tumour xenografts, suggesting a potential for
use in combination with chemotherapy to inhibit repopulation.
54
2.3 Introduction
Limited studies have shown that surviving tumour cells can repopulate a tumour
between courses of chemotherapy (1-3); however, there is little information about the
microenvironment in which cells repopulate within a solid tumour. In untreated tumours,
it has been shown that cells proximal to functional blood vessels have a higher rate of
proliferation compared to more distal tumour cells; this is likely due to the availability of
nutrients and oxygen in regions close to functional vasculature (2-5). Many
chemotherapeutic agents selectively target cells that are rapidly proliferating, and most
drugs achieve a higher concentration in these proximal regions (4); therefore, cells closer
to blood vessels are more likely to be killed following chemotherapy.
Regions further from blood vessels contain viable tumour cells that may not be
exposed to cytotoxic concentrations of chemotherapy, and have a lower rate of
proliferation; these cells might repopulate the tumour if their nutrition improves
following death and removal of more proximal cells. We hypothesize that repopulation
will occur predominantly from regions of solid tumours distal from the vasculature
following chemotherapy. In support of this hypothesis, Huxham et al. showed that
following gemcitabine treatment, tumour cells in human colon cancer xenografts began
proliferating in regions distal to blood vessels (i.e. hypoxic regions) approximately 6 days
following chemotherapy (2). However, repopulation has not been studied in other
xenografts or human tumours, or following treatment with different chemotherapeutic
agents.
55
Many microenvironmental factors can influence the repopulation of tumour cells
within a solid tumour. Changes in tumour vasculature can modify nutrient and oxygen
gradients within a tumour, thereby affecting the distribution of proliferating cells and
dying cells within the tumour. Targeting the tumour vasculature can have both beneficial
and detrimental effects – decreasing the tumour vasculature can limit the supply of
nutrients and oxygen to tumour cells thereby leading to antitumour effects; however,
decreased vasculature can also limit access of tumour cells to anticancer agents
administered through the blood stream (6-8). Hypoxia also has a paradoxical effect on
tumour growth. Prolonged or sustained hypoxia can lead to anoxia, which results in cell
death within the tumour (9-10); however, some tumour cells exposed to hypoxia might
also acquire mutations that could lead to a more aggressive phenotype (10). Since many
anticancer agents have effects on the tumour microenvironment, it is imperative to
understand how these factors contribute to repopulation within solid tumours.
The present study aims to characterize the process of repopulation in A431
xenografts, a human squamous cell carcinoma that overexpresses the epidermal growth
factor receptor (EGFR), and in human breast cancer MCF-7 xenografts, following
treatment with the chemotherapeutic agent paclitaxel; to determine the potential of
gefitinib (an EGFR inhibitor) to inhibit repopulation; and to characterize changes in
functional tumour vasculature and tumour hypoxia following treatment with
chemotherapy.
56
2.4 Materials and Methods
2.4.1 Cell lines. Experiments were performed using the human vulvar epidermoid
carcinoma cell line A431 (reported to over-express EGFR) and the human breast
carcinoma cell line MCF-7 (reported not to over-express EGFR) (11). A431 cells were
purchased from the American Type Culture Collection (ATCC; Manassas, VA). A431
cells were maintained in Dulbecco’s Modified Eagle’s Medium supplemented with 10%
fetal bovine serum, and MCF-7 cells were grown in α-MEM with 10% fetal bovine serum
(FBS; Hyclone, Logan, UT). All media was obtained from the hospital media facility.
Cells were grown in a humidified atmosphere of 95% air and 5% CO2 at 37ºC. Routine
tests to exclude mycoplasma were performed. Epidermal growth factor receptor (EGFR)
expression was evaluated and confirmed by immunohistochemistry using the mouse anti-
human EGFR (Clone 31G7) antibody (Zymed Laboratories, San Francisco, CA).
2.4.2 Drugs and reagents. Gefitinib (Iressa) was provided by AstraZeneca (Macclesfield,
Cheshire, UK). Gefitinib was dissolved in 100% DMSO (Fisher Scientific, Pittsburgh,
PA) to make a 1mg/mL stock solution, which was stored at 4°C. Paclitaxel was
purchased from the hospital pharmacy as a 6mg/mL stock solution and stored at room
temperature. EF5 was provided by the National Cancer Institute (NCI), and Cy5-
conjugated mouse anti-EF5 antibody was purchased from Dr. C. Koch. EF5 powder was
dissolved in distilled water and 2.4% ethanol and 5% dextrose to make a 10mM stock
solution that was stored at room temperature. DiOC7 was purchased from AnaSpec Inc.
(San Jose, CA) and a stock solution (2.5mg/mL) was made by dissolving DiOC7 powder
57
in DMSO. The stock was diluted 1:10 in PBS and 10% Solutol HS 15 (BASF Chemical
Company, Ludwigshafen, Germany).
2.4.3 Effect of paclitaxel and gefitinib on growth of xenografts. Female athymic nude
mice (4 to 6 weeks old) (Harlan Sprague-Dawley (HSD), Madison, WI) were injected
subcutaneously on both flanks with 1x106 A431 cells or 4x106 MCF-7 cells per side;
prior to injection of MCF-7 cells, mice were implanted with 17β estradiol tablets (60 day
release; Innovative Research of America, Sarasota, FL). Two perpendicular diameters
were measured with a caliper and once tumours reached a diameter of 5-8mm, treatment
commenced. Tumour volume was calculated using the formula: 0.5(ab2), where a is the
longest diameter, and b is the shortest diameter.
To determine the effects of paclitaxel, mice were treated once every five days for
a total of three doses with 0, 10, 20, or 30 mg/kg of paclitaxel administered
intraperitoneally. To test the effects of gefitinib alone, gefitinib (50 or 100mg/kg) was
administered by oral gavage daily for 3 days per week for a total of two weeks. Tumour
size and body weight were measured every other day throughout the course of treatment;
measurements were continued until tumours grew to a maximum diameter of 1.5 cm or
caused ulceration, when mice were killed humanely. To avoid possible bias, mice were
ear tagged and randomized, and measurements were made without knowledge of the
treatment history.
2.4.4 Effect of paclitaxel and gefitinib on cell proliferation and apoptosis. Once tumours
reached a size of 5-8 mm in diameter, mice were treated with paclitaxel alone or gefitinib
58
alone. Tumour samples were taken on days 0, 2, 4, 6, 8, 10, and 12. The hypoxia-
selective agent EF5 was injected intraperitoneally approximately two hours prior to
killing the mice (0.2 mL of a 10 mM stock per mouse), and the perfusion marker DiOC7
(1 mg/kg) was injected intravenously 1 minute prior to killing the mice. Tumours were
excised, immersed in OCT compound and frozen in liquid nitrogen. Tumours were cut
into 10 μm sections and imaged using an Olympus BX50 fluorescence microscope.
Tumour sections were first imaged for the perfusion marker DiOC7 using a FITC
filter set. Sections were then stained for blood vessels using antibodies specific for the
endothelial cell marker CD31 [rat anti-CD31 primary antibody (1:100), BD Biosciences;
and Cy3-conjugated goat anti-rat IgG secondary antibody (1:400)], hypoxic regions were
identified using a Cy5-conjugated mouse anti-EF5 antibody (1:50), proliferating cells
were stained for Ki67 [rabbit anti-human Ki67 antibody (1:1000), Novus; HRP
chromogen], and apoptotic cells were stained for cleaved caspase-3 [rabbit anti-human
cleaved caspase-3 antibody (1:800), Cell Signalling; HRP chromogen]. Tumour sections
were imaged for CD31 using the Cy3 (530-560 nm excitation/573-647 nm emission)
filter set, and EF5 using the Cy5 far-red filter set. Ki67 and cleaved caspase-3 were
imaged using transmitted light.
2.4.5 Image Analysis and Quantification. Composite images were generated and image
analysis was undertaken using Media Cybernetics Image Pro PLUS software, using a
protocol similar to that described by Primeau et al. (41). The DiOC7 fluorescence image
(indicative of perfused blood vessels) was converted to a black and white binarized
image, where perfused blood vessels were represented with a pixel intensity of 255 and
59
background pixels an intensity of 0. The Ki67/cleaved caspase-3 brightfield image was
converted to an 8-bit greyscale image with a pixel intensity range of 1-254. These two
images were overlaid to form a composite image of the tumour section with proliferating
or apoptotic cells (Ki67 or cleaved caspase-3 staining, respectively) shown in relation to
perfused blood vessels (DiOC7 staining).
Solid tumours are 3-dimensional; therefore, blood vessels out of the plane of view in the
2-dimensional tissue sections might contribute to noise in the quantification of cell
proliferation in regions further from blood vessels. To account for this, cell proliferation
(Ki67 staining) was also measured in relation to the nearest hypoxic region (EF5
staining) to obtain a more accurate view of proliferation in distal regions from functional
blood vessels. The EF5 fluorescence image was converted to a black and white binarized
image, with hypoxia represented by a pixel intensity of 255, and was overlaid with the
corresponding Ki67 8-bit greyscale image to form a composite image of proliferating
cells in relation to the nearest region of hypoxia.
Multiple areas of interest (AOI) were selected after excluding areas of necrosis
and artifacts in tumour sections. They were analyzed using a customized algorithm
(created by Dr. Augusto Rendon), which scans individual pixels in an AOI and records
the intensity of each pixel and the distance to the nearest blood vessel. The mean intensity
was plotted as a function of distance to the nearest blood vessel.
2.4.6 Analysis of blood vessels and hypoxia in tumour xenografts. Tumour vasculature
and hypoxia was quantified using Media Cybernetics Image Pro PLUS software. The
total number of blood vessels was measured using a black and white binarized image of
60
CD31 staining – objects with a pixel intensity of 255 (i.e. CD31-positive) were counted
in each tumour section. The tumour area was recorded and areas of necrosis or artifacts
were excluded from quantification. The mean number of total blood vessels per tumour
area was plotted. To calculate the percentage of functional blood vessels, the total
number of objects in DiOC7 binarized images was calculated and the number of DiOC7-
positive objects was divided by the number of CD31-positive objects in each tumour
section.
Hypoxia was measured using black and white binarized EF5 images. The
percentage of hypoxia was calculated by taking the area of EF5-positive staining and
dividing it by the total tumour area.
2.4.7 Statistical Analysis. Linear regression was used to evaluate changes in the mean
intensity (as a function of distance to the nearest blood vessel) following drug treatment.
The slopes and Y-intercepts were calculated and compared for all tumour samples.
Differences in the slope and Y-intercepts indicated changes in the spatial distribution of
the measured marker (e.g. Ki67 for cell proliferation) in relation to functional blood
vessels; however, for markers with a relatively uniform spatial distribution, only the Y-
intercepts were compared to determine changes in the levels of expression. A one-way
ANOVA, followed by the Tukey’s post-hoc test, was performed to determine statistical
differences between treatment groups, and P<0.05 was used to indicate statistical
significance. For changes in functional tumour vasculature and hypoxia, t-tests were
performed to determine significant differences in means between different treatment
groups. P<0.05 was used to indicate statistical significance; all tests were 2-sided.
61
2.5 Results 2.5.1 Effect of paclitaxel on A431 xenografts
Various concentrations of paclitaxel were administered to nude mice bearing
A431 tumour xenografts. There were moderate dose-dependent effects of paclitaxel on
tumour growth with no significant loss of body weight of the mice for the range of doses
evaluated (Figure 2.1).
2.5.2 Effect of paclitaxel on the distribution of cell proliferation in A431 xenografts
Cell proliferation was quantified by fluorescence imaging of the proliferation
marker, Ki67 (Figure 2.2 and 2.3). There was a high intensity of Ki67 staining in
untreated (Day 0) tumours and cell proliferation decreased with increasing distance from
the nearest functional blood vessel (Figure 2.3A). The increase in Ki67 staining in the
first 20μm from the nearest blood vessel likely represents perivascular cells.
At 4 and 8 days after a single 25 mg/kg dose of paclitaxel, there was a decrease in
cell proliferation in regions close to blood vessels, but no significant changes in more
distal regions (Figure 2.3A). On day 12 following paclitaxel treatment, there was a
rebound in Ki67 staining, and cell proliferation was increased in regions further from
blood vessels as compared to untreated tumours (Figure 2.3A).
There was a low level of Ki67 staining near hypoxic regions in untreated tumours,
and cell proliferation increased with greater distance from hypoxic regions (Figure 2.3B).
Cell proliferation remained low near hypoxic regions in tumour sections taken on days 4
62
A.
Time (days)
0 2 4 6 8 10 12 14
Mea
n Tu
mou
r Vol
ume
(mm
3 )
100
1000Control10 mg/kg Paclitaxel20 mg/kg Paclitaxel30 mg/kg Paclitaxel
B.
Time (days)
0 2 4 6 8 10 12 14
Body
Wei
ght (
g)
18
20
22
24
26
28Control10mg/kg Paclitaxel20mg/kg Paclitaxel30mg/kg Paclitaxel
Figure 2.1. The effect of paclitaxel (10-30mg/kg i.p. once every five days for 3 total doses) on (A) growth of A431 xenografts in nude mice [points, mean for five mice per group; bars, SE]. (B) Graph of changes in body weight.
63
Day 0
Day 2 Day 4
Day 6 Day 8
Day 10 Day 12
Figure 2.2. The distribution of proliferating cells (blue) in relation to functional blood vessels (red) and regions of hypoxia (green) in A431 xenografts on days 0 (untreated), 2, 4, 6, 8, 10, and 12 following paclitaxel treatment. Scale bars, 100μm.
64 64
A.
0
5
10
15
20
25
30
35
0 20 40 60 80 100 120 140Distance to nearest blood vessel (μm)
Mea
n In
tens
ity (K
i67)
Day 0Day 4Day 8Day 12
B.
0
5
10
15
20
25
30
35
40
0 20 40 60 80 100 120 140Distance to nearest hypoxic region (μm)
Mea
n In
tens
ity (K
i67)
Day 0Day 4Day 8Day 12
Figure 2.3. The effect of a single dose of paclitaxel (25mg/kg) on cell proliferation in A431 xenografts, as measured by fluorescence intensity of Ki67 staining in relation to distance from the nearest (A) functional blood vessel and (B) hypoxic region. Lines, mean of 4-6 tumours per treatment group; error bars represent SE. (A) Day 0 vs 4, p=0.003; day 0 vs 8, p=0.004; day 4 vs 12, p=0.005; day 8 vs 12, p=0.009. (B) Day 0 vs 4, p=0.02; day 4 vs 12, p=0.008; day 8 vs 12, p=0.01.
65
and 8 following paclitaxel treatment, but by day 12, there was an increase in the
proliferation of cells in areas near hypoxic regions (Figure 2.3B).
2.5.3 Distribution of apoptotic cells in A431 xenografts following paclitaxel treatment
The distribution of apoptotic cells was characterized in A431 xenografts
following a single dose of paclitaxel (25 mg/kg; Figure 2.4 and 2.5). There was an
increase in the intensity of cleaved caspase-3 staining on days 4, 8, and 12 after paclitaxel
treatment. Apoptotic cells were distributed in regions both proximal and distal from
functional blood vessels (Figure 2.5).
2.5.4 Effect of gefitinib on high EGFR (A431) and low EGFR (MCF-7) expressing xenografts
Gefitinib inhibited growth of A431 (high EGFR-expressing) xenografts in a dose-
dependent manner (Figure 2.6A). There was no effect of gefitinib to inhibit the growth of
low EGFR-expressing MCF-7 xenografts compared to control tumours (Figure 2.6B).
2.5.5 Distribution of proliferating cells (Ki67) and apoptotic cells (cleaved caspase-3) in A431 xenografts following gefitinib treatment
Following 3 days of gefitinib treatment, there was a substantial decrease in the
level of Ki67 staining (proliferating cells) in regions proximal to functional blood vessels
(Figure 2.7). There was a rebound in cell proliferation close to functional blood vessels in
tumour samples taken on day 8 (Figure 2.7).
66
Day 0
Day 4
Day 8
Day 12
Day 2
Day 6
Day 10
Figure 2.4. The distribution of apoptotic cells (yellow) in relation to functional blood vessels (red) and regions of hypoxia (green) in A431 xenografts on days 0 (untreated), 2, 4, 6, 8, 10, and 12 following paclitaxel treatment. Scale bars, 100μm.
67
0
2
4
6
8
10
12
14
0 20 40 60 80 100 120 140
Distance to nearest blood vessel (μm)
Mea
n In
tens
ity (C
leav
ed C
aspa
se-3
)
Day 0Day 4Day 8Day 12
Figure 2.5. The effect of a single dose of paclitaxel (25mg/kg) on apoptosis in A431 xenografts, as measured by fluorescence intensity of cleaved caspase-3 staining in relation to distance from the nearest functional blood vessel. Lines, mean of 4-6 tumours per treatment group; error bars represent SE. Day 0 vs 8, p=0.002; day 0 vs 12, p=0.005.
68
A.
Time (days)
0 2 4 6 8 10 12 14 16
Mea
n Tu
mou
r Vol
ume
(mm
3 )
100
1000Control50mg/kg Gefitinib100mg/kg Gefitinib
B.
Time (days)
0 5 10 15 20 25 30
Mea
n Tu
mou
r Vol
ume
(mm
3 )
100
1000
Control100mg/kg Gefitinib
Figure 2.6. The effect of gefitinib (50 or 100mg/kg by oral gavage, 3 days per week for 2 weeks) on growth of (A) A431 [points, mean of two independent experiments, ten mice per group; bars, SE] or (B) MCF-7 [points, mean of five mice per group; bars, SE] xenografts in nude mice.
69
Day 4 Day 8 Day 0
0
2
4
6
8
10
12
14
16
18
20
0 20 40 60 80 100 120 14Distance to nearest blood vessel (μm)
Mea
n In
tens
ity (K
i67)
0
Day 0Day 4Day 8
Figure 2.7. The effect of gefitinib (100mg/kg by oral gavage, 3 days per week) on cell proliferation in A431 xenografts – measured by fluorescence intensity of Ki67 staining in relation to distance from the nearest functional blood vessel. Micrographs: blue = Ki67 (proflierating cells); red = DiOC7 (functional blood vessels); and green = EF5 (hypoxia). Lines, mean of 4-6 tumours per treatment group; error bars represent SE. Day 0 vs 4, p=0.02; day 4 vs 8, p<<0.05.
70
There was an increase in apoptosis in tumour samples taken on days 4 and 8 when
compared to untreated tumours and the level of cleaved caspase-3 staining was slightly
higher in regions more distal to functional blood vessels following gefitinib treatment
(Figure 2.8).
2.5.6 Distribution of proliferating cells (Ki67) and apoptotic cells (cleaved caspase-3) in MCF-7 xenografts following paclitaxel or gefitinib treatment
There was a moderate delay in MCF-7 xenograft growth following paclitaxel
treatment (Figure 2.9). Analysis of Ki67 staining in MCF-7 tumour sections showed a
relatively uniform distribution of cell proliferation in untreated tumours (Figure 2.10A).
There was no significant change in the distribution of Ki67 staining following a single 25
mg/kg dose of paclitaxel (Figure 2.10A).
On day 3 of gefitinib treatment, there was an increase in cell proliferation (Ki67
staining) near blood vessels (Figure 2.10B); cell proliferation decreased in tumours taken
on day 5 (i.e. two days after the last dose of gefitinib) to levels similar to untreated
controls (Figure 2.10B).
There was no change in the distribution of apoptotic cells in MCF-7 tumours
taken on days 3 and 5 following either paclitaxel or gefitinib treatment (Figure 2.11).
71
Day 0 Day 4 Day 8
0
2
4
6
8
10
12
14
16
18
20
0 20 40 60 80 100 120 140
Distance to nearest blood vessel (μm)
Mea
n In
tens
ity (C
leav
ed C
aspa
se-3
) Day 0Day 4Day 8
Figure 2.8. The effect of gefitinib (100mg/kg by oral gavage, 3 days per week) on apoptosis in A431 xenografts – measured by fluorescence intensity of cleaved caspase-3 staining in relation to distance from the nearest functional blood vessel. Micrographs: yellow = cleaved caspase-3 (apoptotic cells); red = DiOC7 (functional blood vessels); and green = EF5 (hypoxia). Lines, mean of 4-6 tumours per treatment group; error bars represent SE. Day 0 vs 4, p=0.001; day 0 vs 8, p=0.001.
72
A.
Time (days)
0 20 40 60 80
Mea
n Tu
mou
r Vol
ume
(mm
3 )
10
100
1000
Control25mg/kg Paclitaxel
B.
20
21
22
23
24
25
26
27
28
29
30
0 2 6 9 13 16 20 23 27 30 34 38 42 45 49 52 56 60 63 66 70Time (days)
Bod
y W
eigh
t (g)
Control25mg/kg Paclitaxel
Figure 2.9. The effect of paclitaxel (25mg/kg i.p. once every five days for 3 total doses) on (A) growth of MCF-7 xenografts in nude mice [points, mean for five mice per group; bars, SE]. (B) Graph of changes in body weight.
73
A.
0
5
10
15
20
25
30
35
0 20 40 60 80 100 120 140
Distance to nearest blood vessel (μm)
Mea
n In
tens
ity (K
i67)
UntreatedDay 3 PaclitaxelDay 5 Paclitaxel
B.
0
5
10
15
20
25
30
35
0 20 40 60 80 100 120 140Distance to nearest blood vessel (μm)
Mea
n In
tens
ity (K
i67)
UntreatedDay 3 GefitinibDay 5 Gefitinib
Figure 2.10. The effect of (A) a single dose of paclitaxel (25mg/kg), or (B) 3 days of gefitinib treatment, on cell proliferation in MCF-7 xenografts, as measured by fluorescence intensity of Ki67 staining in relation to distance from the nearest functional blood vessel. Lines, mean of 4-6 tumours per treatment group; error bars represent SE. (A) All groups, p>0.05. (B) Untreated vs day 3, p=0.04; day 3 vs 5, p=0.002.
74
A.
0
2
4
6
8
10
12
14
16
18
20
0 20 40 60 80 100 120 140Distance to nearest blood vessel (μm)
Mea
n In
tens
ity (C
leav
ed C
aspa
se-3
)UntreatedDay 3 PaclitaxelDay 5 Paclitaxel
B.
0
2
4
6
8
10
12
14
16
18
20
0 20 40 60 80 100 120 140Distance to nearest blood vessel (μm)
Mea
n In
tens
ity (C
leav
ed C
aspa
se-3
)
UntreatedDay 3 GefitinibDay 5 Gefitinib
Figure 2.11. The effect of (A) a single dose of paclitaxel (25mg/kg), or (B) 3 days of gefitinib treatment, on apoptosis in MCF-7 xenografts, as measured by fluorescence intensity of cleaved caspase-3 staining in relation to distance from the nearest functional blood vessel. Lines, mean of 4-6 tumours per treatment group; error bars represent SE.
75
76
2.5.7 Changes in functional vasculature following treatment with paclitaxel or gefitinib in A431 and MCF-7 xenografts
There was a significant decrease in the percentage of functional blood vessels in
A431 xenografts on days 4 and 8 following paclitaxel treatment when compared to
untreated tumours (Figure 2.12A and 2.12B; p=0.006 and p=0.008, respectively); the
percentage of functional vasculature appeared to rebound in tumours taken 12 days after
paclitaxel treatment. The total blood vessels (as measured by CD31 staining per tumour
area) in A431 xenografts decreased following paclitaxel treatment and was significantly
lower in tumours taken on days 4 and 12 following paclitaxel treatment compared to
untreated tumours (Figure 2.12C; p=0.007 and p=0.004, respectively). There was a
significant decrease in the total number of functional blood vessels measured 4 days
following paclitxel (Figure 2.12D; p=0.0001) followed by a rebound on days 8 and 12,
although the number of functional vessels remained lower than in untreated tumours
(Figure 2.12D; day 4 vs. day 12, p=0.01).
Three days of gefitinib treatment caused no significant change in the percentage
of functional vasculature in A431 tumours taken on day 4 or day 8 compared to untreated
tumours (Figures 2.13A and 2.13B; p>0.05). There was a significant decrease in the total
number of blood vessels (i.e. CD31-positive vessels) in tumours taken on days 4 and 8
compared to untreated tumours (Figure 2.13C; p<0.05). Similarly, the total number of
functional blood vessels was lower in A431 xenografts taken on days 4 and 8 compared
to untreated tumours (Figure 2.13D; p<0.05).
A.
Day 0 Day 4 Day 8 Day 12
B.
C.
D.
Figure 2.12. (A) Photomicrographs of tumour blood vessels (red=CD31, yellow=DiOC7). The change in (B) the percentage of functional tumour vasculature, (C) total blood vessels, and (D) total functional blood vessels following a single dose of paclitaxel (25mg/kg, i.p.) in A431 xenografts. (B) Day 0 vs 4, p=0.006; day 0 vs 8, p=0.008. (C) Day 0 vs 4, p=0.007; day 0 vs 12, p=0.004. (D) Day 0 vs 4, p=0.0001; day 4 vs 12, p=0.01.
77
A.
78
Day 4 Day 8 Control
B.
0
10
20
30
40
50
60
70
80
90
100
Control Day 4 Day 8
% Functional Blood Vessels
C.
0
200
400
600
800
1000
1200
1400
Control Day 4 Day 8
Blood Vessels / tumour area
D.
0
100
200
300
400
500
600
700
800
900
1000
Control Day 4 Day 8
Total Functional Blood Vessels
Figure 2.13. (A) Photomicrographs of tumour blood vessels (red=CD31, yellow=DiOC7). The change in (B) the percentage of functional tumour vasculature, (C) total blood vessels, and (D) total functional blood vessels in A431 xenografts treated with gefitinib (100mg/kg, days 0-3). (B) All groups, p>0.05. (C) Control vs day 4 and 8, p<0.05. (D) Control vs day 4 and 8, p<0.05.
MCF-7 xenografts treated with a single dose of paclitaxel had no significant
change in the percentage of functional vasculature (Figure 2.14A and 2.14B) or total
blood vessels, as measured by CD31 staining, following chemotherapy (Figure 2.14C).
The total number of functional blood vessels was calculated and is plotted in Figure
2.14D – there was no significant change in the number of total functional blood vessels
measured.
Following three days of gefitinib treatment, there was no significant difference
between the percentage of functional blood vessels in MCF-7 tumours taken on day 3 and
day 5 when compared to untreated tumours (Figure 2.15A and 2.15B); however, there
was a significant increase in the percentage of functional blood vessels between tumours
taken on day 3 (during gefitinib treatment) and on day 5 (two days following the last dose
of gefitinib) (Figure 2.15B; p=0.01). There was a siginificant decrease in the total blood
vessels measured by CD31 staining in tumours taken on day 5 compared to untreated
tumours (Figure 2.15C; p=0.001). Similarly, there was a decrease in the total number of
functional blood vessels measured in tumours taken on day 3 and day 5; however, this
decrease was not significantly different from untreated tumours (Figure 2.15D; p>0.05).
2.5.8 Changes in the percentage of hypoxia per tumour area following treatment with paclitaxel or gefitinib in A431 and MCF-7 xenografts
In A431 xenografts treated with a single dose of paclitaxel, there was no
significant change in the percentage of hypoxia (per tumour area) in tumours taken on
days 4, 8, and 12 following treatment compared to untreated controls (Figures 2.16A).
79
A.
Control Day 3 Day 5 B.
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30
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Control Day 3 Day 5
% F
unct
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Control Day 3 Day 5
Blo
od V
esse
ls /
tum
our a
rea
D.
0
200
400
600
800
1000
1200
Control Day 3 Day 5
Total Functional Blood Vessels
Figure 2.14. (A) Photomicrographs of tumour blood vessels (red=CD31, yellow=DiOC7). The change in (B) the percentage of functional tumour vasculature, (C) total blood vessels, and (D) the total functional blood vessels following a single dose of paclitaxel (25mg/kg, i.p.) in MCF-7 xenografts. (B-D) All groups, p>0.05.
80
A.
Day 3 Day 5Control B.
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Control Day 3 Day 5
% F
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Figure 2.15. (A) Photomicrographs of tumour blood vessels (red=CD31, yellow=DiOC7). The change in (B) the percentage of functional tumour vasculature, (C) total blood vessels, and (D) the total functional blood vessels in MCF-7 xenografts treated with gefitinib (100mg/kg, days 0-3). (B) Day 3 vs 5, p=0.01. (C) Control vs day 5, p=0.001. (D) All groups, p>0.05.
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A.
B.
Figure 2.16. Changes in percentage of hypoxia per tumour area in A431 xenografts following (A) paclitaxel or (B) gefitinib treatment. (A) All groups, p>0.05. (B) Day 0 vs 8, p=0.01.
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Following gefitinib treatment, there was a significantly higher percentage of
hypoxia in A431 xenografts taken on day 8 (approximately five days after the last dose of
gefitinib) compared to untreated controls (p=0.01; Figure 2.16B).
Following paclitaxel treatment, there was an increase in the percentage of hypoxia
in MCF-7 tumours taken on day 3; however, this change was not significant (Figure
2.17A). The level of hypoxia was significantly decreased from day 3 to day 5 after
paclitaxel treatment (p=0.02; Figure 2.17A)
There was a significantly higher percentage of hypoxia in MCF-7 xenografts
taken on day 3 (during gefitinib treatment) compared to untreated tumours (p=0.04) and
tumours taken on day 5, two days after gefitinib treatment (p=0.02; Figure 2.17B).
83
A.
B.
Figure 2.17. Changes in percentage of hypoxia per tumour area in MCF-7 xenografts following (A) paclitaxel or (B) gefitinib treatment. (A) Day 3 vs 5, p=0.02. (B) Day 0 vs 3, p=0.04; day 3 vs 5, p=0.02.
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2.6 Discussion
The repopulation of surviving tumour cells after chemotherapy is likely affected
by many factors within the tumour microenvironment, including changes in tumour
vasculature and hypoxia. Furthermore, the efficacy of anticancer treatments in solid
tumours is dependent on the distribution of drug within the tumour tissue, which can
impact the spatial distribution of repopulation.
Treatment of A431 xenografts with paclitaxel resulted in a moderate delay in
tumour growth in nude mice (Figure 2.1). There was also a decrease in cell proliferation,
specifically in regions close to blood vessels (Figure 2.3A). Cell proliferation within the
tumour decreased initially and then increased at 12 days following paclitaxel treatment
and cell proliferation was observed in regions both proximal and distal from functional
vasculature (Figure 2.3A). In addition, there was a corresponding decrease in the
percentage of functional blood vessels following chemotherapy treatment (Figure 2.12B).
It is important to note that Ki67 staining does not differentiate between surviving and
lethally-damaged cells; therefore, at early intervals, Ki67-positive cells might include
lethally-damaged cells that have not undergone cell lysis. The effect of paclitaxel on cell
proliferation could be two-fold: 1) an initial decrease in cell proliferation in regions
proximal to blood vessels might have been due to cytotoxic effects of paclitaxel, which is
likely well distributed in proximal regions; and 2) the prolonged depression of cell
proliferation might have been due to effects of paclitaxel to decrease functional
vasculature. With less functional vasculature there is likely a subsequent decrease in the
85
oxygen and nutrients available to cells within the tumour, which could lead to cell death
(10, 12-14).
Huxham and colleagues described the distribution of repopulation in human
colorectal carcinoma xenografts following chemotherapy (i.e. gemcitabine) treatment (2).
They showed that repopulation occurred in regions further from blood vessels
approximately 6 days following gemcitabine treatment (2). It is possible that the more
rapid repopulation in these studies occurred because gemcitabine appeared not to change
the percentage of functional tumour vasculature (2). Studies by Shaked et al. showed that
some drugs, such as paclitaxel, are able to decrease microvascular density, whereas
others, including gemcitabine, have little or no effect on tumour vaculature (15).
The concentration of cells within solid tumours may also affect vascular
perfusion, and this might be modified following chemotherapy (16). Griffon-Etienne et
al. showed that there was an increase in blood vessel diameter and vascular flow (as
measured by red blood cell velocity) approximately 48-96 hours after paclitaxel treatment
in a human soft tissue sarcoma xenograft (16). Furthermore, 24 hours following
chemotherapy cell death was observed in areas surrounding blood vessels and by 48
hours there were no intact cells in this region, which likely accounted for the
corresponding reduction in the number of collapsed vessels in the tumour (16). Changes
in vascular perfusion can lead to improvements in the distribution of anticancer agents;
however, there is also the possibility of improved nutrient and oxygen availability, which
could lead to repopulation of the tumour cells (16). Our data suggest that the rebound in
the percentage of functional tumour vasculature in A431 xenografts approximately 12
86
days after paclitaxel treatment might be associated with a corresponding rebound in cell
proliferation observed at this time (Figures 2.3A and 2.12B).
We observed a significant decrease in the number of blood vessels (as measured
by CD31 staining) in A431 xenografts at various time points after paclitaxel treatment
(Figure 2.12C). The percentage of functional vasculature, as well as the total number of
functional blood vessels, appear to rebound by day 12 (Figures 2.12B and 2.12D). The
rebound in cell proliferation observed around day 12 corresponds with the increase in
functional vasculature, suggesting that changes in functional blood vessels are likely
more important than changes in total blood vessels. These results highlight the
importance of using perfusion markers in conjunction with CD31 staining; CD31 is a
marker of total blood vessels, but does not provide information on vessel function (17).
Surprisingly, there was no significant change in the percentage of hypoxia (per
tumour area) in A431 tumours taken 4, 8, and 12 days after paclitaxel treatment when
compared to untreated controls despite the observed decrease in functional tumour
vasculature (Figure 2.16A).
Paclitaxel treatment had moderate effects to delay growth of MCF-7 xenografts in
nude mice (Figure 2.9A). The lack of change in functional vasculature (Figure 2.14)
could explain the relatively small changes in cell proliferation observed (Figure 2.10A).
Analysis of cleaved caspase-3 staining following paclitaxel treatment showed no change
in apoptosis over time (Figure 2.11A) suggesting that MCF-7 tumours are not highly
susceptible to paclitaxel cytotoxicity.
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Various studies have suggested that drug-induced apoptosis can decrease cell
density, which might improve drug penetration into solid tumours (16, 18, 19). A study
by Kuh et al. showed that paclitaxel penetrated through 10-15 cell layers in human
squamous cell carcinoma FaDu xenografts approximately 24 hours after treatment, and
was well distributed in the tumours 48 hours after treatment (18). Kuh et al. observed
apoptosis in FaDu xenografts 24 hours after treatment, which corresponded with an
observed increase in paclitaxel penetration within the tumour. The percentage of
apoptotic cells, as well as the paclitaxel penetration, continued to increase over time, and
was consistent with their hypothesis that the increase in drug penetration could be due to
reduced cellularity resulting from drug-induced apoptosis (18). Our data show an increase
in apoptosis, as determined by cleaved caspase-3 staining, approximately 4 days
following paclitaxel treatment in A431 xenografts; furthermore, the staining for cleaved
caspase-3 increased and remained elevated in tumours taken on days 8 and 12 (Figure
2.5). Fluorescent micrographs (Figure 2.4) show that apoptotic cells have a relatively
uniform distribution within the tumour (Figure 2.5).
Targeted agents have been used to treat various types of cancer and might be used
to inhibit repopulation in solid tumours between courses of chemotherapy. An ideal
inhibitor is fast acting and has inhibitory effects that are not prolonged once the inhibitor
is removed, thus allowing cells to re-enter cycle prior to the next course of cycle-active
chemotherapy. Gefitinib inhibited proliferation of EGFR-overexpressing A431
xenografts in regions both proximal and distal to functional blood vessels (Figure 2.7).
Cell proliferation rebounded by day 8, approximately 5 days after the last dose of
gefitinib was administered. Growth delay studies in mice bearing A431 xenografts
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showed that following three courses of gefitinib treatment, there was rapid re-growth of
the tumour once gefitinib treatment was stopped (Figure 3.7A, Chapter 3). In addition,
our study showed moderate effects of gefitinib to change the percentage of functional
vessels (Figures 2.13B), which could account for the more rapid rebound in cell
proliferation near perfused vessels following gefitinib compared to treatment with
paclitaxel.
Gefitinib has anti-angiogenic properties and can inhibit endothelial cell
proliferation (20, 21). It is possible that gefitinib was able to inhibit endothelial cell
proliferation since we observed a decrease in the total number of blood vessels following
treatment (Figure 2.13C), as well as a decrease in the total number of functional blood
vessels (Figure 2.13D).
Following gefitinib treatment, there was an increase in the percentage of hypoxia
within A431 xenografts (Figure 2.16B) – this is likely due to the observed decrease in
total perfused vessels, which could have resulted in a decrease in oxygen concentration
within the tumour.
Amin et al. showed that following gefitinib treatment, tumour-derived endothelial
cells became less susceptible to gefitinib treatment and expressed a higher level of
VEGFR2 suggesting that these cells might become more dependent on VEGF signalling
(22). This might modify the effect of subsequent doses of gefitinib on the tumour
vasculature. Future studies should determine the effect of multiple doses of gefitinib on
changes in cell proliferation, apoptosis, cell signalling, and the tumour microenvironment
(i.e. tumour vasculature and hypoxia).
89
MCF-7 xenografts are low-EGFR expressing tumours and should not be affected
by gefitinib treatment. As expected, there was no effect of gefitnib to inhibit cell
proliferation or to change apoptosis within MCF-7 tumours. Similarly, there was no
significant difference in the total number of functional blood vessels in tumours on days 3
and 5 compared to untreated controls.
Although there was no significant difference in the total functional vasculature in
MCF-7 xenografts during gefitinib treatment, there was a marked increase in the
percentage of hypoxia (Figure 2.17B). It is not clear why hypoxia levels increased with
gefitinib treatment, and whether these changes are transient or chronic; future studies
should be undertaken to determine the mechanisms leading to these effects.
A potential limitation to our method using EF5 staining to study changes in
hypoxia is that it does not distinguish between transient and chronic regions of hypoxia in
tumour sections. Real-time, live animal imaging or staining with multiple markers of
hypoxia at different times (i.e. before and after drug treatment) would be more
informative in showing changes in hypoxia over time. Another limitation of the current
study is the lack of time-matched controls, which would help to account for changes in
hypoxia that might be due to changes in tumour size rather than drug effects.
It is hypothesized that survival signalling downstream of the EGFR (i.e. through
the PI3K and MAPK pathways) might correspond with changes in cell proliferation
following treatment with gefitinib or combined chemotherapy and EGFR inihibitor
treatment. To determine changes in signalling through the PI3K and MAPK pathways,
various antibodies used to detect signalling molecules downstream of the EGFR were
90
tested, including antibodies for recognizing P-Akt (Cell Signalling, lot #3767 and #9277),
and P-erk (Cell Signalling, lot #9101 and #4376). Positive staining for these markers was
not observed following antibody optimization. This is likely due to the use of frozen
tissue sections; many antibodies are better suited for use in formalin fixed paraffin
embedded (FFPE) tissues. However, due to the short half life of the perfusion marker
(DiOC7) that we used (23), our samples were flash frozen in liquid nitrogen rather than
undergoing the formalin fixation process; therefore, we have not been successful in
finding antibodies to use for immunofluorescence staining to detect signalling molecules
such as phospho-Akt or phospho-erk. Future studies should continue to test new
antibodies developed for their ability to detect these markers in frozen tissues.
In summary, we have shown that repopulation occurs in A431 xenografts
following paclitaxel treatment, and proliferation of surviving cells occurs in regions both
proximal and distal to functional blood vessels. Furthermore, our study highlights the
interaction between repopulation and changes in tumour vasculature (specifically
functional blood vessels). Gefitinib has the potential to inhibit repopulation between
courses of chemotherapy due to its ability to effectively decrease cell proliferation during
drug treatment, while also allowing cells to re-enter cycle soon after removal of the drug.
Future studies should be undertaken to 1) compare the distribution of EGFR signalling
and cell proliferation within solid tumours following drug treatment, 2) investigate the
effect of multiple doses of paclitaxel or gefitinib treatment on cell proliferation,
apoptosis, and changes in tumour vasculature, and 3) determine the mechanism behind
changes in hypoxia during gefitinib treatment.
91
ACKNOWLEDGEMENTS Supported by a grant from the Canadian Institutes of Health Research [# MOP 15388].
We thank all members (Kelvin, Ye, Carmelita, Natalia, Ceceil, and Arturo) of the
Pathology Research Program (PRP), with special thanks to Melanie Peralta for her help
optimizing the immuno-fluorescence staining techniques; and thanks to all members
(James, Miria, and Judy) of the Advanced Optical Microscopy Facility (AOMF).
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2.7 REFERENCES
1. Wu, L. and Tannock, I. F. Repopulation in murine breast tumors during and after
sequential treatments with cyclophosphamide and 5-fluorouracil. Cancer Res, 63: 2134-2138, 2003.
2. Huxham, L. A., Kyle, A. H., Baker, J. H., Nykilchuk, L. K., and Minchinton, A. I. Microregional effects of gemcitabine in HCT-116 xenografts. Cancer Res, 64: 6537-6541, 2004.
3. Kim, J. J. and Tannock, I. F. Repopulation of cancer cells during therapy: an important cause of treatment failure. Nat Rev Cancer, 5: 516-525, 2005.
4. Primeau, A. J., Rendon, A., Hedley, D., Lilge, L., and Tannock, I. F. The distribution of the anticancer drug Doxorubicin in relation to blood vessels in solid tumors. Clin Cancer Res, 11: 8782-8788, 2005.
5. Tredan, O., Galmarini, C. M., Patel, K., and Tannock, I. F. Drug resistance and the solid tumor microenvironment. J Natl Cancer Inst, 99: 1441-1454, 2007.
6. Jang, S. H., Wientjes, M. G., Lu, D., and Au, J. L. Drug delivery and transport to solid tumors. Pharm Res, 20: 1337-1350, 2003.
7. Folkman, J. Angiogenesis. Annu Rev Med, 57: 1-18, 2006. 8. Fukumura, D. and Jain, R. K. Tumor microenvironment abnormalities: causes,
consequences, and strategies to normalize. J Cell Biochem, 101: 937-949, 2007. 9. Hockel, M. and Vaupel, P. Tumor hypoxia: definitions and current clinical,
biologic, and molecular aspects. J Natl Cancer Inst, 93: 266-276, 2001. 10. Vaupel, P. and Mayer, A. Hypoxia in cancer: significance and impact on clinical
outcome. Cancer Metastasis Rev, 26: 225-239, 2007. 11. Rusnak DW, Alligood KJ, Mullin RJ, et al. Assessment of epidermal growth
factor receptor (EGFR, ErbB1) and HER2 (ErbB2) protein expression levels and response to lapatinib (Tykerb®, GW572016) in an expanded panel of human normal and tumour cell lines. Cell Prolif, 40: 580-594, 2007.
12. Vaupel, P., Kallinowski, F., and Okunieff, P. Blood flow, oxygen and nutrient supply, and metabolic microenvironment of human tumors: a review. Cancer Res, 49: 6449-6465, 1989.
13. Olive, P. L., Vikse, C., and Trotter, M. J. Measurement of oxygen diffusion distance in tumor cubes using a fluorescent hypoxia probe. Int J Radiat Oncol Biol Phys, 22: 397-402, 1992.
14. Dewhirst, M. W. Concepts of oxygen transport at the microcirculatory level. Semin Radiat Oncol, 8: 143-150, 1998.
15. Shaked Y, Henke E, Roodhart JM, et al. Rapid chemotherapy-induced acute endothelial progenitor cell mobilization: implications for antiangiogenic drugs as chemosensitizing agents. Cancer Cell, 14: 263-273, 2008.
16. Griffon-Etienne, G., Boucher, Y., Brekken, C., Suit, H. D., and Jain, R. K. Taxane-induced apoptosis decompresses blood vessels and lowers interstitial fluid pressure in solid tumors: clinical implications. Cancer Res, 59: 3776-3782, 1999.
17. Scholz D, Schaper J. Platelet/endothelial cell adhesion molecule-1 (PECAM-1) is localized over the entire plasma membrane of endothelial cells. Cell Tissue Res 1997;290:623-631.
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18. Kuh, H. J., Jang, S. H., Wientjes, M. G., Weaver, J. R., and Au, J. L. Determinants of paclitaxel penetration and accumulation in human solid tumor. J Pharmacol Exp Ther, 290: 871-880, 1999.
19. Grantab R, Sivananthan S, Tannock IF. The penetration of anticancer drugs through tumor tissue as a function of cellular adhesion and packing density of tumor cells. Cancer Res 2006;66(2):1033-9.
20. Hirata A, Uehara H, Izumi K, Naito S, Kuwano M, Ono M. Direct inhibition of EGF receptor activation in vascular endothelial cells by gefitinib ('Iressa', ZD1839). Cancer science 2004;95(7):614-8.
21. Amin DN, Hida K, Bielenberg DR, Klagsbrun M. Tumor endothelial cells express epidermal growth factor receptor (EGFR) but not ErbB3 and are responsive to EGF and to EGFR kinase inhibitors. Cancer Res 2006;66(4):2173-80.
22. Amin DN, Bielenberg DR, Lifshits E, Heymach JV, Klagsbrun M. Targeting EGFR activity in blood vessels is sufficient to inhibit tumor growth and is accompanied by an increase in VEGFR-2 dependence in tumor endothelial cells. Microvascular research 2008;76(1):15-22.
23. Trotter MJ, Chaplin DJ, Olive PL. Use of a carbocyanine dye as a marker of functional vasculature in murine tumours. Br J Cancer, 59: 706-709, 1989.
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Chapter 3
Scheduling of Paclitaxel and Gefitinib to Inhibit Repopulation for Optimal Treatment of Cells and Xenografts that Overexpress the
Epidermal Growth Factor Receptor
Andrea S. Fung and Ian F. Tannock
Data from this chapter has been been prepared as a manuscript for submission to the British Journal of Cancer.
95
3.1 Statement of Translational Relevance Limited studies have shown that repopulation of tumour cells between courses of
chemotherapy can diminish treatment efficacy. Cytostatic agents, such as gefitinib, might
be used to inhibit repopulation, but might also decrease the efficacy of cycle-dependent
chemotherapy. As clinical therapy moves towards combining cytostatic agents with
chemotherapeutic drugs, it is important to understand the effects of combined treatment
on factors such as cell cycle and the tumour vasculature and microenvironment: cytostatic
agents might put cells out of cycle thereby rendering cycle-active chemotherapeutic
agents less effective, and changes in tumour vasculature can affect drug delivery and
tumour growth. Our in vitro data illustrates the cell cycle effects of combined paclitaxel
and gefitinib treatment on repopulation, while our in vivo studies demonstrate the effect
of combined therapy on the tumour microenvironment. Our study highlights important
factors that should be considered when using cytotoxic and cytostatic agents in
combination in the clinic.
96
3.2 Abstract Purpose: In most clinical studies evaluating the combination of chemotherapy and
molecular targeted agents, treatments have been applied concurrently, despite it being
counter-intuitive to give a cytostatic agent concurrent with cycle-active chemotherapy.
One strategy to enhance efficacy might be to give the agents sequentially, thus allowing
selective inhibition of repopulation of cancer cells between doses of chemotherapy. Phase
III trials have not shown improved survival when treatment with chemotherapy and
concurrent gefitinib, an inhibitor of the Epidermal Growth Factor Receptor (EGFR), was
compared to chemotherapy alone. Here we evaluate the hypothesis that sequential
administration might allow inhibition of repopulation by gefitinib, with tumour cells re-
entering cycle to allow sensitivity to subsequent chemotherapy. Experimental Design:
Sequential and concurrent administration of paclitaxel and gefitinib were studied in vitro
and in xenografts using the EGFR over-expressing human cancer cell line A431. We
evaluated cell cycle distribution and repopulation at various times during treatment.
Results: The sequential use of gefitinib and paclitaxel in vitro decreased repopulation
compared to chemotherapy alone, and there was greater cell kill compared to concurrent
treatment. In contrast, combined treatment with paclitaxel and gefitinib led to greater
growth delay than use of gefitinib alone for concurrent but not for sequential treatment of
mice bearing xenografts. Concurrent treatment had greater effects to reduce functional
vasculature in the tumours. Conclusion: These studies highlight the importance of
considering effects on the cell cycle, and on the solid tumour microenvironment,
including tumour vasculature, when scheduling cytostatic and cytotoxic agents in
combination.
97
3.3 Introduction
Courses of chemotherapy are usually given at intervals of about 3 weeks to allow
recovery of critical normal tissues such as bone marrow. Such recovery occurs because
proliferation of surviving precursor cells leads to repopulation. Repopulation of cancer
cells also occurs between courses of chemotherapy and may decrease the effectiveness of
treatment (1). Tumour cell repopulation has been documented following treatment with
various chemotherapeutic agents in experimental tumours, and the rate of repopulation
can increase with each subsequent dose of chemotherapy (2-9). Studies of repopulation in
human tumours are limited, but accelerating repopulation is one of several potential
mechanisms to explain why some cancers respond initially to chemotherapy, but develop
resistance with continued treatment (1). Agents that selectively inhibit repopulation of
tumour cells might therefore overcome clinical drug resistance.
The epidermal growth factor receptor (EGFR; erbB1) is over-expressed, mutated,
or deregulated in various cancers, including breast, colorectal, and non-small-cell lung
cancer (10). Homo- or hetero-dimerization of the EGFR with members of the erbB
receptor family leads to signalling from erbB receptors, resulting in downstream
activation of Ras-Raf-MAP kinase and phosphatidyl-inositol-3 (PI-3) kinase pathways
(10). Activation of these pathways leads to cell proliferation and inhibition of apoptosis
(10, 11). Several inhibitors of the EGFR have been developed including the small
molecule tyrosine kinase inhibitors gefitinib and erlotinib, and the monoclonal antibody
cetuximab (12). These agents inhibit proliferation of EGFR over-expressing tumour cells
in vitro and in xenografts.
98
Clinical trials with gefitinib and erlotinib have led to low rates of tumour
response, and increased time to progression when used alone (13-15). Phase III trials
conducted with erlotinib resulted in prolonged survival in patients with non-small-cell
lung cancer that had previously received first-line or second-line chemotherapy (14);
however, erlotinib did not show improved survival when tested in combination with
chemotherapy (16). Similarly, phase III trials of gefitinib in combination with
chemotherapy for non-small-cell lung cancer did not show improved survival when
compared to chemotherapy alone (17, 18). In these trials the EGFR inhibitors were given
concurrently with chemotherapy, and a possible reason for their lack of benefit is that
cytostatic effects of the EGFR inhibitor might have reduced the efficacy of cycle-active
chemotherapy. We hypothesize that altering the dosing schedule to sequential
administration of chemotherapy and EGFR inhibitors might improve the efficacy of
combined treatment. Administration of the EGFR inhibitor in the intervals between
chemotherapy would be expected to inhibit repopulation of tumour cells, whereas
removal of the cytostatic agent prior to the next course of chemotherapy might allow cells
to re-enter the cell cycle, thereby retaining the cytotoxic effects of cycle-active
chemotherapy.
In the present study we evaluate the above hypothesis by determining the effects
of paclitaxel and gefitinib, given either concurrently or in sequence, when used to treat
the human EGFR over-expressing cell line A431 in vitro or as xenografts in nude mice.
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3.4 Materials and Methods
3.4.1 Cell lines. Experiments were performed using the human vulvar epidermoid
carcinoma cell line A431 (reported to over-express EGFR) and the human breast
carcinoma cell line MCF-7 (reported not to over-express EGFR) (19). A431 and MCF-7
cells were purchased from the American Type Culture Collection (ATCC; Manassas,
VA). A431 cells were maintained in Dulbecco’s Modified Eagle’s Medium
supplemented with 10% fetal bovine serum (FBS; Hyclone, Logan, UT). MCF-7 cells
were grown in α-MEM with 10% fetal bovine serum. All media was obtained from the
hospital media facility. Cells were grown in a humidified atmosphere of 95% air and 5%
CO2 at 37ºC. Routine tests to exclude mycoplasma were performed. Epidermal growth
factor receptor (EGFR) expression on both cell lines was evaluated by
immunohistochemistry using the mouse anti-human EGFR (Clone 31G7) antibody
(Zymed Laboratories, San Francisco, CA).
3.4.2 Drugs and reagents. Gefitinib (Iressa) was provided by AstraZeneca (Macclesfield,
Cheshire, UK). Gefitinib was dissolved in 100% DMSO (Fisher Scientific, Pittsburgh,
PA) to make a 1 mg/mL stock solution, which was stored at 4°C. Paclitaxel was
purchased from the hospital pharmacy as a 6 mg/mL stock solution and stored at room
temperature. EF5 was provided by the NCI, and Cy5-conjugated mouse anti-EF5
antibody was purchased from Dr. C. Koch. EF5 powder was dissolved in distilled water
and 2.4% ethanol and 5% dextrose to make a 10 mM stock solution that was stored at
room temperature. DiOC7 was purchased from AnaSpec Inc. (San Jose, CA) and a stock
solution (2.5 mg/mL) was made by dissolving DiOC7 powder in DMSO. The stock was
100
diluted 1:10 in PBS and 10% Solutol HS 15 (BASF Chemical Company, Ludwigshafen,
Germany).
3.4.3 Effects of gefitinib on cell growth. To test the response of A431 and MCF-7 cells to
gefitinib treatment, 3-5x104 cells were plated on day 0. Various concentrations (0.01,
0.1, 1, 5 and 10 μM) of gefitinib were diluted with media and each concentration was
added on day 0 and drug was replaced in fresh media every 2 days for a total of 10 days;
control cells were exposed to 0.5% DMSO. Separate flasks were trypsinized every two
days and cell counts were measured using a Coulter counter (Beckman Instruments,
Fullerton, CA).
3.4.4 Effects of paclitaxel and gefitinib treatment. A431 cells were plated at a
concentration of 1x105 cells/mL, and treatment was commenced the next day following
cell adherence. Treatment groups included: (a) paclitaxel alone, (b) gefitinib alone, (c)
sequential paclitaxel and gefitinib, and (d) concurrent paclitaxel and gefitinib. Paclitaxel
was administered at a dose of 0.01 μM for 24 hours once weekly for three weeks.
Gefitinib was administered at a concentration of 1 μM for four days each week for three
weeks, and then replaced with fresh media for the remainder of the week. For sequential
treatment, paclitaxel was administered weekly for 24 hours followed by the 4-day
treatment with gefitinib. For the concurrent treatment group, gefitinib was administered
one day prior to each 24-hour paclitaxel treatment, and continued for a total of 4 days.
Cell counts and clonogenic assays were performed before and after each chemotherapy
101
treatment (days 0, 1, 7, 8, 14, 15, 21). Similar experiments were performed with the
MCF-7 cell line.
3.4.5 Clonogenic Assays. Cells were counted and placed into a 13 mL tube at a
concentration of 105 cells/mL. Serial dilutions were made to 104 and 103 cells/mL, and
each concentration was plated in triplicate into 6-well plates. After approximately 14
days, colonies were stained with methylene blue (Fisher Scientific, Pittsburgh, PA) and
counted. The average colony count for each concentration was recorded and the
surviving fraction was calculated using the following formula:
[average # of treated colonies / total # treated cells plated] [average # of control colonies / total # control cells plated]
3.4.6 Flow Cytometry. To test the effects of gefitinib on cell cycle, approximately 3x106
A431 cells were seeded into flasks 2-3 days prior to the commencement of the
experiment to allow cells to adhere and grow. On day 0, cells were treated with 1 μM
gefitinib or diluent (control) and gefitinib was continued for three consecutive days. On
day 3, cells were washed with PBS and fresh media was added to all remaining flasks.
Cell cycle analysis was undertaken by flow cytometry on days 0, 1, 2, 3, and 4 of
treatment. The BD Biosciences protocol for detection of BrdU incorporation1 was used
to prepare samples for analysis. Briefly, cells were incubated with 10 μM BrdU (Sigma-
Aldrich Inc., St. Louis, MO) for 1 hour prior to trypsinization. Cells were fixed in 70%
ethanol for 20 minutes at room temperature, washed, and exposed to a denaturing acid
solution for 20 minutes at room temperature; acid was neutralized with 0.1M sodium 1 BD Biosciences flow protocol: http://www.bdbiosciences.com/pharmingen/protocols/BrdU_Incorporation.shtml
102
borate for 2 minutes. For BrdU detection, cells were incubated in a 1:50 dilution of
mouse anti-human BrdU primary antibody (BD Biosciences, San Jose, CA) for
approximately 30 minutes, washed, and then incubated in 1:50 of a FITC-conjugated goat
anti-mouse secondary antibody (BD Biosciences, San Jose, CA) for 30 minutes. Finally,
cells were washed and incubated with propidium iodide (BD Biosciences, San Jose, CA)
for 30 minutes. Analysis was completed on the Becton Dickinson FACScan (Franklin
Lakes, NJ) using the Cell Quest software. The FL1 (530/30nm) filter was used for BrdU-
FITC detection and the FL3 (650nm) filter was used for PI detection.
3.4.7 Effect of paclitaxel and gefitinib on growth of A431 and MCF-7 xenografts. Female
athymic nude mice (4 to 6 weeks old) (Harlan Sprague-Dawley (HSD), Madison, WI)
were injected subcutaneously on both flanks with 1x106 A431 cells or 4x106 MCF-7 cells
per side; prior to injection of MCF-7 cells, mice were implanted with 17β estradiol tablets
(60 day release; Innovative Research of America, Sarasota, FL). Two perpendicular
diameters were measured with a caliper and once tumours reached a diameter of 5-8 mm,
treatment commenced. Tumour volume was calculated using the formula: 0.5(ab2), where
a is the longest diameter, and b is the shortest diameter.
To determine the effects of paclitaxel, mice were treated once every five days for
a total of three doses with 0, 10, 20, or 30 mg/kg of paclitaxel administered
intraperitoneally. To test the effects of gefitinib alone, gefitinib (50 or 100 mg/kg) was
administered by oral gavage daily for 3 days per week; treatment was continued for a
total of three weeks. The effects of sequential or concurrent paclitaxel and gefitinib
treatments were evaluated as follows. Mice were divided randomly into one of five
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treatment groups: a) control, b) paclitaxel alone (25 mg/kg i.p. once every five days for 3
doses), c) gefitinib alone (100 mg/kg by oral gavage three consecutive days per course),
d) sequential paclitaxel and gefitinib, or e) concurrent paclitaxel and gefitinib. In the
sequential group, each dose of paclitaxel was followed by 3 days of gefitinib. For
concurrent treatment, gefitinib was administered one day prior to paclitaxel and
continued for a total of 3 consecutive days. Each treatment was continued for a total of
three courses. Tumour size and body weight were measured every other day throughout
the course of treatment; measurements were continued until tumours grew to a maximum
diameter of 1.5 cm or caused ulceration, when mice were killed humanely. All mice were
ear tagged and randomized to avoid bias with measurements.
3.4.8 Effect of paclitaxel and gefitinib on cell proliferation and vasculature in A431
xenografts. When tumours were 5-8 mm in diameter, mice were randomized into control,
paclitaxel alone, gefitinib alone, or sequential or concurrent combined treatment groups
as described above. Tumour samples were taken on days 0, 3, and 5. The hypoxia-
selective agent EF5 was injected intraperitoneally approximately two hours prior to
killing the mice (0.2 mL of a 10 mM stock per mouse) and the perfusion marker DiOC7
(1 mg/kg) was injected intravenously 1 minute prior to killing the mice. Tumours were
excised, immersed in OCT compound and frozen in liquid nitrogen. Tumours were cut
into 10 μm sections and imaged using an Olympus BX50 fluorescence microscope.
Tumour sections were first imaged for the perfusion marker DiOC7 using a FITC
filter set. Sections were then stained for blood vessels using antibodies specific for the
endothelial cell marker CD31 [rat anti-CD31 primary antibody (1:100), BD Biosciences;
104
and Cy3-conjugated goat anti-rat IgG secondary antibody (1:400)], hypoxic regions were
identified using a Cy5-conjugated mouse anti-EF5 antibody (1:50), proliferating cells
were stained for Ki67 [mouse anti-Ki67 antibody (Dako, clone MIB-1), HRP
chromogen], and apoptotic cells were stained for cleaved caspase-3 [rabbit anti-human
cleaved caspase-3 antibody (1:800), Cell Signalling; HRP chromogen]. Tumour sections
were imaged for CD31 using the Cy3 (530-560 nm excitation/573-647 nm emission)
filter set, and EF5 using the Cy5 far-red filter set. Ki67 and cleaved caspase-3 were
imaged using transmitted light.
Composite images were generated and image analysis was undertaken using
Media Cybernetics Image Pro PLUS software as described by Primeau et al. (20). The
DiOC7 fluorescence image (indicative of perfused blood vessels) was converted to a
black and white binary image, where perfused blood vessels were represented with a
pixel intensity of 255 and background pixels an intensity of 0. The Ki67 brightfield
image was converted to an 8-bit grey-scale image with a pixel intensity range of 1-254.
These two images were overlaid to form a composite image of the tumour section with
proliferating cells (Ki67 staining) shown in relation to perfused blood vessels (DiOC7
staining).
Multiple areas of interest (AOI) were selected in tumour sections by excluding
areas of necrosis and artifacts. They were analyzed using a customized algorithm, which
scans individual pixels in an AOI and records the intensity of each pixel and the distance
to the nearest blood vessel. The mean intensity was plotted as a function of distance to
the nearest blood vessel.
105
3.4.9 Statistical Analysis. T-tests were performed to determine significant differences in
means between different treatment groups. P<0.05 was used to indicate statistical
significance; all tests were 2-sided. Linear regression analysis was performed as
described in Chapter 2.
3.5 Results
3.5.1 Expression of EGFR
Immunohistochemistry confirmed overexpression of EGFR on A431 cells and
xenografts, and low/absent expression on MCF-7 cells and xenografts (Figure 3.1).
3.5.2 Inhibition of cell growth with gefitinib
Growth curves for A431 cells and MCF-7 cells in varying concentrations of
gefitinib are shown in Figure 3.2. There was inhibition of growth of A431 cells in culture
when treated with gefitinib at concentrations of 0.1 μM and greater (Figure 3.2A,
P<0.05); effects on growth of MCF-7 cells were not significant except at the highest
concentration of 10 μM gefitinib (P>0.05; Figure 3.2B).
3.5.3 Paclitaxel and gefitinib treatment
A431 cells were treated with paclitaxel alone, gefitinib alone, or with combined
paclitaxel and gefitinib using either sequential or concurrent treatment regimens.
Clonogenic cell survival is plotted as a function of time in Figure 3.3. In the presence of
gefitinib alone the number of clonogenic cells remained constant. When given
sequentially with paclitaxel, gefitinib led to partial inhibition of repopulation (Figure
3.3A). Sequential treatments led to greater killing of A431 tumour cells than concurrent
106
A.
A431 cells High EGFR
MCF-7 cells Low EGFR
B.
Figure 3.1. Epidermal growth factor receptor (EGFR) expression in (A) human squamous cell carcinoma, A431, and human breast cancer, MCF-7, cells and (B) A431 and MCF-7 xenografts.
MCF-7 xenograft Low EGFR
A431 xenograft High EGFR
107
A.
Time (days)
0 2 4 6 8 10 12
Cel
l Num
ber
1e+3
1e+4
1e+5
1e+6
1e+7Control0.01 uM Gefitinib0.1 uM Gefitinib1 uM Gefitinib5 uM Gefitinib10 uM Gefitinib
B.
Time (days)
0 2 4 6 8 10 12
Cel
l Num
ber
1e+3
1e+4
1e+5
1e+6
1e+7Control0.01 uM Gefitinib0.1 uM Gefitinib1 uM Gefitinib5 uM Gefitinib10 uM Gefitinib
Figure 3.2. Growth of (A) EGFR+ A431 cells and (B) EGFR- MCF-7 cells in various concentrations of gefitinib. Points, mean of three independent experiments; bars, SE.
108
A.
Time (days)
0 5 10 15 20 25
Clo
noge
nic
Sur
viva
l Fra
ctio
n
0.001
0.01
0.1
1
10 Paclitaxel aloneSequentialGefitinib alone
B.
Time (days)
0 5 10 15 20 25
Clo
noge
nic
Surv
ival
Fra
ctio
n
0.001
0.01
0.1
1
SequentialConcurrent
Figure 3.3. (A) The effect of 3 weekly treatments of paclitaxel alone (●), gefitinib treatment alone (3 consecutive days per week, ▲), and sequential treatment (■) on survival of A431 cells (evaluated by a colony-forming assay) as a function of time. (B) The effect of paclitaxel and gefitinib given sequentially (■) or concurrently (▼) over 3 weeks on survival of A431 cells as a function of time. Points, mean of three independent experiments; bars, SE.
109
treatments, largely because of reduced levels of cell kill when paclitaxel was
administered in the presence of gefitinib (Figure 3.3B). Gefitinib did not inhibit
repopulation of MCF-7 cells between courses of paclitaxel compared to paclitaxel
treatment alone (Figure 3.4).
3.5.4 Effects on cell cycle and apoptosis
The distribution of A431 cells in G1, S, and G2/M phases during and after a 3-day
treatment with gefitinib was studied (Figure 3.5). There was an increase in the G1
population and decrease in S-phase cells during treatment, consistent with growth arrest
in G1. Following removal of gefitinib on day 3, the cell cycle distribution returned to
untreated conditions; analysis at later times was not meaningful due to cell crowding and
contact inhibition.
Cell cycle distribution was determined by flow cytometry 7 days after treatment
with paclitaxel alone or after combined paclitaxel and gefitinib treatment administered by
either sequential or concurrent scheduling (Figure 3.6A). This time was chosen for
analysis because a) lethally-damaged cells due to paclitaxel treatment were unlikely to
confound the results, and b) this is the time that a second dose of paclitaxel would be
applied. There was no significant difference in the cell cycle distribution between the
sequential and concurrent treatment groups, and control groups (Figure 3.6A), indicating
resumption of normal cell cycling by this time.
110
A.
Time (days)
0 5 10 15 20 25
Tota
l Cel
l Num
ber
1e+4
1e+5
1e+6
1e+7
1e+8
1e+9ControlPaclitaxelGefitinibSequentialConcurrent
B.
Time (days)
0 2 4 6 8 10 12 14 16
Clo
noge
nic
Surv
ival
Fra
ctio
n
0.1
1
10ControlPaclitaxelGefitinibSequentialConcurrent
Figure 3.4. The effect of 3 weekly treatments of diluent (●), paclitaxel alone (■), gefitinib treatment alone (3 consecutive days per week, ▲), or paclitaxel and gefitinib treatment administered sequentially (▼) or concurrently (♦) on (A) total or (B) clonogenic (evaluated by a colony-forming assay) MCF-7 cells as a function of time.
111
0
10
20
30
40
50
60
70
80
90
100
0 1 2 3 4Time (days)
% g
ated
pop
ulat
ion
G1SG2
Figure 3.5. The effect of three days of gefitinib treatment (day 0-3; 1μM) on cell cycle distribution in A431 cells. Bars, mean of 3 experiments; error bars represent SE.
112
A.
0
10
20
30
40
50
60
70
80
90
Control Paclitaxel Gefitinib Sequential Concurrent
% g
ated
pop
ulat
ion
G1SG2
B.
0
5
10
15
20
25
30
35
Control Paclitaxel Gefitinib Sequential Concurrent
% g
ated
sub
-G1
popu
latio
n
Figure 3.6. (A) Cell cycle analysis of A431 cells on day 7 following treatment with paclitaxel alone (days 0-1), gefitinib alone (days 0-3), or with sequential or concurrent treatment. (B) Plot of sub-G1 population (representative of apoptotic cells) on day 7 following treatment. Bars, mean of three independent experiments; error bars, SE.
113
There was a greater sub-G1 population (representative of apoptotic cells) on day 7
following sequential treatment compared to concurrent treatment (Figure 3.6B).
3.5.5 Effects of paclitaxel and gefitinib on growth of A431 xenografts
Gefitinib (50 and 100 mg/kg) given on 3 consecutive days by oral gavage caused
dose-dependent growth delay of A431 xenografts (Chapter 2, Figure 2.6a). Modest
growth delay was observed following treatment with paclitaxel in the range of 10-30
mg/kg (Chapter 2, Figure 2.1a). Repeated treatment of A431 xenografts with gefitinib
(100 mg/kg, 3 days per week for 3 weeks) resulted in substantial growth delay (Figure
3.7A), but tumour regrowth was quite rapid following the removal of gefitinib.
Sequential treatment with paclitaxel did not lead to greater growth delay than use of
gefitinib alone. Tumour regrowth was significantly delayed with combined paclitaxel and
gefitinib treatment administered concurrently when compared to gefitinib alone or to
sequential treatment (Figure 3.7A; P<0.05). There was no effect of gefitinib alone on
MCF-7 xenograft growth compared to control tumours, and combined paclitaxel and
gefitinib administered sequentially or concurrently did not delay tumour growth more
than paclitaxel alone (Figure 3.7B).
3.5.6 Effect of paclitaxel and gefitinib on cell proliferation, apoptosis, and tumour vasculature in A431 xenografts
As expected, proliferation of tumour cells, indicated by Ki67 staining, decreased
with distance from functional blood vessels in A431 xenografts (Figure 3.8). On day 3
after initiation of treatment, there was a decrease in cell proliferation in both the
sequential and concurrent paclitaxel and gefitinib groups compared to untreated tumours
114
A.
Time (days)0 10 20 30 40
Mea
n Tu
mou
r Vol
ume
(mm
3 )
10
100
1000
ControlPaclitaxelGefitinibSequentialConcurrent
B.
Time (days)
0 20 40 60 80
Mea
n Tu
mou
r Vol
ume
(mm
3 )
10
100
1000
ControlPaclitaxelGefitinibSequentialConcurrent
Figure 3.7. The effect of three courses of paclitaxel alone (25mg/kg i.p. once every five days, ■), gefitinib alone (100mg/kg oral gavage, 3 days per course, ▲), and sequential (▼) or concurrent (♦) treatment on (A) A431 or (B) MCF-7 xenograft growth in nude mice. Points, mean of two independent experiments, ten mice per group; bars, SE.
115
A.
0
2
4
6
8
10
12
14
16
18
0 20 40 60 80 100 120 140
Distance to nearest functional blood vessel (μm)
Mea
n In
tens
ity (K
i67)
UntreatedDay 3 SequentialDay 5 Sequential
B.
0
2
4
6
8
10
12
14
16
18
0 20 40 60 80 100 120 140Distance to nearest functional blood vessel (μm)
Mea
n In
tens
ity (K
i67)
UntreatedDay 3 ConcurrentDay 5 Concurrent
Figure 3.8. The effect of (A) sequential or (B) concurrent paclitaxel and gefitinib treatment on cell proliferation in A431 xenografts, as measured by fluorescence intensity of Ki67 staining in relation to distance from the nearest functional blood vessel. Lines, mean of 3-6 tumours per treatment group, error bars represent SE.
116
(Figure 3.8, P<0.05). By day 5 there was a subsequent rebound in cell proliferation in
both sequential and concurrent treatment groups with no significant difference between
them (Figure 3.8).
There was an increase in cleaved caspase-3 staining (indicative of apoptosis) in
A431 xenografts on day 3 following either sequential or concurrent combined treatment
(P<0.05); there was no siginificant difference between treatment groups (Figure 3.9). The
amount of apoptosis decreased to untreated levels by day 5 in both the sequential and
concurrent treatment groups.
The effect of treatment on tumour vasculature was studied by comparing the
number of perfused vessels (DiOC7 staining) to total vessels (CD-31 staining; Figure
3.10). On day 3 following the start of treatment, both sequential and concurrent paclitaxel
and gefitinib treatment led to a decrease in the percentage of functional blood vessels. By
day 5, there was a significantly higher percentage of functional vessels following
sequential treatment compared to concurrent treatment (P=0.02; Figure 3.10B).
3.5.7 Effect of paclitaxel and gefitinib on cell proliferation, apoptosis, and tumour vasculature in MCF-7 xenografts
There was no significant change in the cell proliferation or apoptosis observed in
MCF-7 xenografts following combined treatment administered sequentially or
concurrently (Figures 3.11 and 3.12). In addition, the percentage of functional and total
vasculature present following combined paclitaxel and gefitinib treatment was similar in
both the sequential and concurrent groups (Figure 3.13).
117
A.
0
5
10
15
20
25
0 20 40 60 80 100 120 140
Distance to nearest blood vessel (μm)
Mea
n In
tens
ity (C
leav
ed C
aspa
se-3
)UntreatedDay 3 SEQDay 5 SEQ
B.
0
5
10
15
20
25
0 20 40 60 80 100 120 140
Distance to nearest blood vessel (μm)
Mea
n In
tens
ity (C
leav
ed C
aspa
se-3
)
UntreatedDay 3 CONCDay 5 CONC
Figure 3.9. The effect of (A) sequential or (B) concurrent paclitaxel and gefitinib treatment on apoptosis in A431 xenografts, as measured by fluorescence intensity of cleaved caspase-3 staining in relation to distance from the nearest functional blood vessel. Lines, mean of 3-6 tumours per treatment group, error bars represent SE.
118
Day 5 SEQ Day 5 CONCA.
B.
0
10
20
30
40
50
60
70
80
90
100
Control Paclitaxel Sequential Concurrent
% F
unct
iona
l Blo
od V
esse
ls
ControlDay 3Day 5
C.
0
100
200
300
400
500
600
700
800
900
Control Paclitaxel Sequential Concurrent
Tota
l Blo
od V
esse
ls (C
D31
) ControlDay 3Day 5
Figure 3.10. The effect of sequential (SEQ) or concurrent (CONC) paclitaxel and gefitinib treatment on the percentage of functional tumour blood vessels in A431 xenografts. (A) Fluorescence images of tumour blood vessels; total blood vessels represented by CD31 staining (pseudo-colored red) and perfused blood vessels represented by DiOC7 staining (colocalization of DiOC7 with CD31 is pseudo-colored yellow). Plot of (B) the percentage of functional blood vessels or (C) total blood vessels in A431 xenografts: bars, mean of 3-6 tumours per group; error bars, SE.
119
A.
0
5
10
15
20
25
30
35
0 20 40 60 80 100 120 140Distance to nearest blood vessel (μm)
Mea
n In
tens
ity (K
i67)
UntreatedDay 3 SequentialDay 5 Sequential
B.
0
5
10
15
20
25
30
35
0 20 40 60 80 100 120 140
Distance to nearest blood vessel (μm)
Mea
n In
tens
ity (K
i67)
UntreatedDay 3 ConcurrentDay 5 Concurrent
Figure 3.11. The effect of (A) sequential or (B) concurrent paclitaxel and gefitinib treatment on cell proliferation in MCF-7 xenografts, as measured by fluorescence intensity of Ki67 staining in relation to distance from the nearest functional blood vessel. Lines, mean of 3-6 tumours per treatment group, error bars represent SE.
120
A.
0
2
4
6
8
10
12
14
16
18
20
0 20 40 60 80 100 120 140
Distance to nearest blood vessel (μm)
Mea
n In
tens
ity (C
leav
ed C
aspa
se-3
)UntreatedDay 3 SequentialDay 5 Sequential
B.
0
2
4
6
8
10
12
14
16
18
20
0 20 40 60 80 100 120 140
Distance to nearest blood vessel (μm)
Mea
n In
tens
ity (C
leav
ed C
aspa
se-3
)
UntreatedDay 3 ConcurrentDay 5 Concurrent
Figure 3.12. The effect of (A) sequential or (B) concurrent paclitaxel and gefitinib treatment on apoptosis in MCF-7 xenografts, as measured by fluorescence intensity of cleaved caspase-3 staining in relation to distance from the nearest functional blood vessel. Lines, mean of 3-6 tumours per treatment group, error bars represent SE.
121
A.
0
10
20
30
40
50
60
70
80
90
100
Control Paclitaxel Gefitinib Sequential Concurrent
% F
unct
iona
l Blo
od V
esse
ls
ControlDay 3Day 5
B.
0
200
400
600
800
1000
1200
1400
1600
1800
2000
Control Paclitaxel Gefitinib Sequential Concurrent
Blo
od V
esse
ls /
tum
our a
rea Control
Day 3Day 5
C.
0
200
400
600
800
1000
1200
1400
Control Paclitaxel Gefitinib Sequential Concurrent
Tota
l Fun
ctio
nal B
lood
Ves
sels
ControlDay 3Day 5
Figure 3.13. The effect of sequential or concurrent paclitaxel and gefitinib treatment on the (A) percentage of functional tumour vasculature, (B) total blood vessels and (C) total functional blood vessels in MCF-7 xenografts.
122
3.5.8 Effect of paclitaxel and gefitinib on the percentage of hypoxia in A431 and MCF-7 xenografts
There was an increase in the percentage of hypoxia observed in A431 xenografts
following paclitaxel alone and combined paclitaxel and gefitinib treatment. There was no
significant difference in the percentage of hypoxia measured in tumours taken on day 3
and day 5 following combined treatment administered sequentially; however, when
paclitaxel and gefitinib were administered concomitantly, there was a lower percentage of
hypoxia measured in day 3 tumours compared to tumours taken on day 5 (P=0.01; Figure
3.14a).
The percentage of hypoxia in MCF-7 tumours treated with paclitaxel and gefitinib
(sequentially or concurrently) was similar to untreated controls; however, in tumours
treated with paclitaxel alone or gefitinib alone, there was a marked increase in the
percentage of hypoxia present in day 3 tumours (P<0.05; Figure 3.14b).
123
A.
0
1
2
3
4
5
6
7
8
Control Paclitaxel Sequential Concurrent
% H
ypox
ia /
tum
our a
rea
ControlDay 3Day 5
B.
0
0.5
1
1.5
2
2.5
3
Control Paclitaxel Gefitinib Sequential Concurrent
% H
ypox
ia /
tum
our a
rea
ControlDay 3Day 5
Figure 3.14. The effect of sequential or concurrent paclitaxel and gefitinib treatment on percentage of hypoxia per tumour area in (A) A431 xenografts or (B) MCF-7 xenografts.
124
3.6 Discussion
Chemotherapeutic agents are most effective against proliferating cells and many
of them act at specific phases of the cell cycle. Most molecular targeted agents are
initially cytostatic, and when administered in combination might decrease the efficacy of
chemotherapy by putting cells out of cycle. This may be the reason that a randomized
clinical trial showed better effects of using the initially cytostatic agent tamoxifen after
adjuvant chemotherapy for breast cancer rather than concurrently (21). Shorter-acting
targeted cytostatic agents that have minimal effects on critical normal tissues are ideal
candidates for inhibition of tumour cell repopulation between cycles of chemotherapy;
however, these agents may also influence angiogenesis and the tumour
microenvironment, and might up-regulate cell death pathways, so that their interactions
with chemotherapy can be complex.
Several studies have investigated the sequence dependence of combined
treatments with chemotherapy and targeted agents (22-26). Studies of bladder cancer
showed that gefitinib enhanced the anti-proliferative and apoptotic effects of docetaxel
only when it was administered following docetaxel in vitro and in vivo; pretreatment with
gefitinib prior to docetaxel was found to be inferior to chemotherapy alone, most likely
due to its effects on cell cycle (23). One study compared combination therapy of three
different anti-EGFR agents paired with either a platinum derivative or a taxane. Results
showed antagonistic effects when each EGFR inhibitor was administered prior to
chemotherapy, but, when chemotherapy was followed by treatment with an EGFR
inhibitor, there was a synergistic anti-proliferative effect accompanied by apoptosis and
cell cycle arrest in the G2/M phases (26). Conversely, some studies have found that
125
treatment with molecular targeted agents causes greater effects when administered prior
to chemotherapy. Solit et al. showed that pulsatile administration of gefitinib was
superior to continuous administration when given in combination with paclitaxel in vivo,
and that pretreatment with gefitinib prior to chemotherapy was more efficacious due to
the ability to escalate the dose of the EGFR inhibitor with minimal effects on toxicity.
Increased doses of gefitinib may have led to greater sensitization to chemotherapy
because of increased inhibition of pro-survival/anti-apoptotic pathways, or may have
impaired angiogenesis in tumours leading to greater efficacy of the combined treatment
(22). Results obtained in these preclinical studies have led to ongoing clinical trials to
test the effects of sequence on combined treatment in patients (22, 23).
We hypothesized that administration of gefitinib following paclitaxel treatment
would be most beneficial in inhibiting repopulation between courses of chemotherapy.
However, following inhibition by a cytostatic agent, it is imperative to allow tumour cells
to re-enter cycle prior to the subsequent course of chemotherapy in order to achieve
maximal cytotoxic effects of cycle-active chemotherapy. We found greater cell killing
when paclitaxel and gefitinib were administered sequentially in vitro as compared to
concomitantly as determined by colony-forming assays and flow cytometry (Figure 3.3B
and Figure 3.6B). This is most likely due to the G1 cell cycle arrest caused by
administration of gefitinib (Figure 3.6A), which thereby decreases the efficacy of
paclitaxel, a cycle-active chemotherapy agent that targets cells during S phase.
Gefitinib used in combination with paclitaxel (i.e. sequential or concurrent
treatment) had no significant inhibitory effect on the growth of low EGFR-expressing
126
MCF-7 cells and xenografts (Figure 3.7B and Figure 3.4) when compared to paclitaxel
treatment alone. Furthermore, there was no significant change in cell proliferation or
apoptosis in MCF-7 xenografts treated with sequential or concurrent paclitaxel and
gefitinib treatment (Figure 3.11 and Figure 3.12).
We observed significant inhibition of A431 xenograft growth with gefitinib
treatment alone, and only modest effects with paclitaxel alone (Figure 3.7A). Contrary to
our original hypothesis (and to our data obtained for cells in culture), there were additive
effects to delay xenograft growth when the two agents were used in combination only
when paclitaxel and gefitinib treatment were given concurrently, and not when used
sequentially (Figure 3.7A). This occurred despite similar recovery of cell proliferation in
xenografts prior to the next course of chemotherapy, as measured by Ki67 staining,
following treatment (Figure 3.8).
The effects of gefitinib in tumours may differ from those observed in vitro
because drug distribution within the body is complex and exposure to a drug depends on
multiple factors, such as drug half-life, clearance, tissue penetration, and effects of the
tumour microenvironment. Furthermore, both gefitinib and paclitaxel have been reported
to have anti-angiogenic effects (27, 28).
Drug-induced apoptosis has been shown to decrease cell density within solid
tumours, thereby leading to improved vascular function and drug distribution (29, 30).
Therefore, pre-treatment with a drug that induces apoptosis might allow for improved
drug delivery of subsequent anticancer treatments; this was observed in a study by Jang et
al. where pre-treatment with paclitaxel caused the induction of apoptosis and improved
127
the delivery of a successive dose of chemotherapy (31). Our data has shown that gefitinib
treatment can cause an increase in apoptosis in A431 xenografts (Chapter 2, Figure 2.8);
therefore, it is possible that administration of gefitinib prior to paclitaxel in the concurrent
treatment group resulted in better distribution of paclitaxel due to drug-induced apoptosis
in areas surrounding blood vessels.
To study the effect of combined paclitaxel and gefitinib treatment on tumour
vasculature, we measured changes in the percentage of functional blood vessels. A study
by Moasser and colleagues showed that gefitinib treatment given prior to paclitaxel led to
an improvement in vascular perfusion and reduced interstitial fluid within breast cancer
xenografts; they proposed that the vascular changes could result in improved drug
distribution within the tumour (32). In the present study, we observed an increase in the
percentage of functional blood vessels following one day of gefitinib treatment given
prior to chemotherapy in the concurrent treatment arm, which could have resulted in
better paclitaxel distribution in A431 xenografts (p=0.01; Figure 3.15).
There was a similar decrease in the percentage of functional blood vessels on day
3 following combined treatment administered sequentially or concomitantly; however,
tumour samples taken on day 5 following treatment showed a rebound in functional
vasculature with a significantly higher percentage of functional blood vessels in the
sequential treatment group compared to the concurrent treatment group (Figure 3.10B).
Studies by Shaked et al. have shown that treatment with some chemotherapeutic
agents (including paclitaxel) can lead to a rebound in angiogenesis through the
recruitment of circulating endothelial progenitors (CEPs) to blood vessels (28). This
increase in tumour vasculature might aid in the repopulation of a tumour. Administration
128
0
10
20
30
40
50
60
70
80
90
100
Untreated Gefitinib
% F
unct
iona
l Blo
od V
esse
ls
Figure 3.15. The effect of one day of gefitinib treatment (100mg/kg, oral gavage) on the percentage of functional tumour vasculature in A431 xenografts.
129
of the antiangiogenic agent DC 101 (anti-VEGFR2 antibody) prior to paclitaxel treatment
led to decreased recruitment of CEPs and was associated with a decrease in tumour
volume and microvascular density (28). The larger effect of concurrent administration of
paclitaxel and gefitinib to decrease the proportion of functional blood vessels might
contribute to the greater delay in tumour regrowth that we observed for A431 xenografts.
Our study has limitations. The A431 xenografts were grown subcutaneously and
it is possible that the effects of gefitinib on tumour vasculature may differ in spontaneous
or orthotopic tumours. Also, we observed a great inhibitory effect of gefitinib on A431
xenografts when compared to paclitaxel treatment alone, which is opposite to the effects
usually seen in the clinic where chemotherapy usually has greater antitumour effects than
that of molecular targeted agents. Future experiments might use lower doses of gefitinib,
or a more efficacious chemotherapy agent, to determine whether similar results are
observed with combined treatment when chemotherapy has better antitumour effects than
gefitinib alone in mice.
In summary, we have demonstrated that tumour cell repopulation and cell kill in
vitro are influenced by varying the schedule of cytotoxic and cytostatic drugs
administered in combination. Schedule-dependent effects were also observed in vivo, but
were not predicted by the results of experiments in tissue culture. It is likely that the
effect of paclitaxel and gefitinib on tumour vasculature had greater effects to influence
tumour growth than cell cycle effects in vivo. It is important to understand the influence
of combined therapy not only on cell cycle distribution, but also on the tumour
130
131
vasculature and microenvironment, when formulating optimal treatment schedules in the
clinic.
ACKNOWLEDGEMENTS
Supported by a grant from the Canadian Institutes of Health Research [# MOP 15388].
We thank Dr. Licun Wu for technical support with in vivo studies. Figure 3.1B (MCF-7
EGFR staining) image provided by Carol Lee.
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Chapter 4
Concurrent and sequential administration of chemotherapy and the mTOR inhibitor temsirolimus in human cancer cells and xenografts
Andrea S. Fung1, Licun Wu1, Ian F. Tannock
1The first two authors contributed equally to this work This data chapter was published in Clinical Cancer Research, and is presented with supplemental figures in this thesis: Fung AS, Wu L, Tannock IF. Concurrent and sequential administration of chemotherapy and the mTOR inhibitor temsirolimus in human cancer cells and xenografts. Clinical Cancer Research 2009; 15(17): 5389-95
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4.1 Statement of Translational Relevance
Temsirolimus, an inhibitor of the mammalian target of rapamycin (mTOR), was
approved recently by the FDA for the treatment of renal cancer. Limited studies have
investigated the effects of temsirolimus in combination with chemotherapy. Our study
investigates the effects of temsirolimus and chemotherapy on prostate and breast cancer
cells and xenografts, with emphasis on scheduling (sequential or concurrent) of combined
therapy and possible effects of temsirolimus to inhibit repopulation between cycles of
chemotherapy. We have shown that temsirolimus administered concomitantly with
docetaxel is more effective in delaying regrowth of prostate PC-3 and LnCaP xenografts
in nude mice when compared to either agent alone. Further studies should determine
optimal dosing and scheduling in the clinic, but our studies suggest that combined
treatment with temsirolimus and docetaxel might be beneficial in the treatment of
prostate cancer.
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4.2 Abstract Purpose: Optimal scheduling of cycle-active chemotherapy with (initially cytostatic)
molecular targeted agents is important to maximize clinical benefit. Concurrent
scheduling might allow up-regulation of cell death pathways at the time of chemotherapy,
while sequential treatments might maximize inhibition of repopulation and avoid putting
tumour cells out of cycle when administering cycle-active chemotherapy. We compared
the effects of concurrent and sequential administration of chemotherapy and the mTOR
inhibitor temsirolimus (CCI-779) on tumour cells and xenografts. Experimental Design:
Human prostate cancer PC-3 and LnCaP, and human breast cancer MDA-468 cells and
xenografts were treated with chemotherapy (docetaxel and 5-fluorouracil respectively)
and temsirolimus, using concurrent and sequential treatment schedules. Cell killing and
repopulation were evaluated by clonogenic assays. Cell cycle analysis was performed
using flow cytometry. Effects on xenografts were assessed by tumour growth delay.
Results: The proliferation of all cell lines was inhibited by temsirolimus in a dose-
dependent manner; PTEN negative PC-3 and mutant LnCaP cells were more sensitive
than PTEN negative MDA-468 cells. Temsirolimus inhibited cell cycle progression from
G1 to S phase in all cell lines. Combined treatment had greater effects than temsirolimus
or chemotherapy alone: for PC-3 and LnCaP xenografts, concurrent treatment appeared
superior to sequential scheduling, whereas MDA-468 cells and xenograft tumours did not
show schedule dependence. Conclusions: Combined treatment with temsirolimus and
chemotherapy had a greater therapeutic effect than monotherapy; concurrent scheduling
was more effective for PC-3 and LnCaP cells and xenografts that were sensitive to
temsirolimus.
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4.3 Introduction
Clinical benefit from chemotherapy is limited by systemic toxicity and by drug
resistance. Most studies of drug resistance have concentrated on cellular and molecular
mechanisms operating at the level of a single cell (reviewed in 1), but limited drug
distribution within tumours and repopulation of surviving tumour cells between cycles of
chemotherapy are important and neglected causes of clinical drug resistance (2-5).
Repopulation of tumour cells between successive courses of chemotherapy may
accelerate, and may lead to acquired resistance in the absence of changes in the intrinsic
sensitivity of the tumour cells (2,3,6). Many molecular targeted agents are being
introduced in the clinic; their initial effects are usually cytostatic, and these agents have
considerable potential for inhibiting repopulation. For example, cetuximab, an inhibitor
of the epidermal growth factor receptor (EGFR), has been shown to increase survival of
patients receiving radiotherapy for head and neck cancer (7), and the most likely
mechanism is inhibition of repopulation during the course of radiotherapy. Inhibition of
repopulation by cytostatic agents between cycles of chemotherapy is more complex
because most chemotherapy drugs are more active against cycling cells, and the outcome
may depend markedly on schedule. Concurrent scheduling might allow up-regulation of
cell death pathways at the time of chemotherapy, while sequential treatments might
maximize inhibition of repopulation and avoid putting tumour cells out of cycle when
administering cycle-active chemotherapy.
Temsirolimus (CCI-779), an inhibitor of the mammalian target of rapamycin
(mTOR), is a molecular targeted agent that has shown considerable activity in pre-
clinical and clinical studies (8-15). The mTOR pathways are important in promoting cell
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proliferation and cell survival, and temsirolimus has marked effects to inhibit cell
proliferation. The product of the PTEN tumour suppressor gene is a phosphatase that
down-regulates the PI3K/Akt (PKB) pathway. Loss of PTEN is correlated with up-
regulated mTOR activity and can render tumours particularly sensitive to mTOR
inhibitors (9). Rapamycin and its analog temsirolimus down-regulate translation of
specific mRNAs required for cell cycle progression from G1 to S phase (8,9).
Temsirolimus has shown anti-proliferative activity against a wide range of cancers in
preclinical models and clinical trials and is now approved by the FDA for the treatment
of renal cancer (11,13,15). Tumours with PTEN mutations are particularly sensitive to
temsirolimus; for example, our previous data indicated that PTEN negative human
prostate cancer PC-3 cells and xenografts are quite sensitive to temsirolimus (14).
There are few clinical studies that have addressed sequencing of cytotoxic
chemotherapy with molecular targeted agents. Tamoxifen has been used concurrently or
sequentially after chemotherapy, in trials of adjuvant therapy for breast cancer. The
randomized Intergroup Trial 0100 showed that sequential treatment was more beneficial
than concurrent administration for postmenopausal women with node-positive, estrogen
receptor or progesterone receptor-positive disease (16,17), and a second trial reported
similar trends (18). Preclinical studies also suggest that inhibitors of the EGFR tyrosine
kinase such as gefitinib lead to better outcome when administered sequentially with
chemotherapy, as compared to concurrent treatment (19,20). We were unable to identify
studies that have investigated concurrent or sequential scheduling of chemotherapy and
temsirolimus.
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In the present study, we evaluate the effects of concurrent and sequential
administration of chemotherapy and the mTOR inhibitor temsirolimus on human prostate
and breast cancer cells and xenografts.
4.4 Materials and Methods
4.4.1 Cell lines and mice. Human prostate cancer PC-3 cells and LnCaP cells were
maintained in Ham's F-12K medium supplemented with 2 mmol/L L-glutamine and
RPMI, respectively, and human breast cancer MDA-468 cells were cultured in α-MEM.
All media contained 10% fetal bovine serum, 1% penicillin and streptomycin. All cell
lines were purchased from the American Type Culture Collection (Manassas, VA).
Athymic nude mice (4 to 6 weeks old) were purchased from the Harlan Sprague-
Dawley (HSD, Madison, WI) laboratory animal center and acclimatized in the animal
colony for 1 week before experimentation. The animals were housed in microisolator
cages, five per cage, in a 12-hour light/dark cycle. The animals received filter sterilized
water and sterile rodent food ad libitum.
4.4.2 Drugs and preparation. The mTOR inhibitor temsirolimus was obtained from
Wyeth-Ayerst Laboratories, (Pearl River, NY); it was stored as a dry powder at 4°C and
suspended in 100% ethanol on the day of use. A stock solution of temsirolimus was
diluted to a concentration of 2 mmol/L using 5% Tween 80 (Sigma, St. Louis, MO) and
5% polyethylene glycol 400 (Sigma). Docetaxel (Aventis Pharmaceuticals, Inc.,
Bridgewater, NJ) and 5-fluorouracil (5-FU, Mayne Pharma Inc., Kirkland, Quebec) were
obtained from the hospital pharmacy.
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4.4.3 Effects of temsirolimus and chemotherapy on cell proliferation in vitro. PC-3 and
LnCaP cells (106) were plated into multiple 25-cm2 flasks and treated with various doses
of temsirolimus (0, 100, 500, and 1000 nM) for 3 days; or docetaxel (DOC, 0, 5, 10, 50,
and 100 nM) for 24 hours, and then washed with PBS 3 times. MDA-468 cells were
evaluated in similar experiments using 5-FU (10 μM) for 24 hours. Cells were counted
using a Coulter Counter to determine the effect of the above treatment on cell growth.
Colony-forming assays were performed to evaluate the surviving fraction.
4.4.4 Concurrent or sequential treatment of cultured cells. Optimal doses of temsirolimus
and DOC or 5-FU selected from the above experiments were utilized in studies
evaluating combined treatment. PC-3 and LnCaP cells (106) were plated and allowed to
grow for 1 day. Temsirolimus was added concurrently with or sequentially after DOC
(Figure 4.1A). For concurrent treatment both drugs were added for 24 hours, followed by
three washes with PBS, and temsirolimus was added for a further 2 days and then washed
out. For sequential treatment DOC was added for 24 hours, followed by washing, and
after a further 24 hours, temsirolimus was added for 3 days and then washed out.
Controls included cells exposed to the diluents for DOC and/or temsirolimus, with
similar washes. After treatment, fresh medium was added and cells were harvested on
day 7. Cells were counted and serial dilutions were plated to determine cell survival in a
colony-forming assay.
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A.
B.
Figure 4.1. Sequence of chemotherapy and temsirolimus (CCI-779) used (A) in vitro and (B) in nude mice bearing xenografts. The sequence was repeated weekly for 3 weeks for treatment of xenografts.
141
Human breast cancer MDA-468 cells were treated with either 5-FU or
temsirolimus, or both in combination (or their diluents), using the same schedule as for
PC-3 and LnCaP cells.
4.4.5 Cell cycle analysis. Cell cycle analysis was performed by flow cytometry. Cells
that were exposed to various doses of temsirolimus for 3 days were harvested after
exposure, and cells treated with concurrent or sequential scheduling were harvested on
day 7 and fixed in 80% ethanol on ice. All cell samples were kept in a –20oC freezer
until flow cytometry was performed. Once cells were taken out of the freezer, 1 ml of
cold PBS was added and samples were centrifuged. After washing with cold PBS twice,
the cells were then treated with 0.5 ml propidium iodide/RNase Staining Buffer (BD
Biosciences Pharmingen, San Diego, CA) for at least 6 hours. Samples were analyzed for
cell cycle distribution on a FACScan (Becton Dickinson, Franklin Lakes, NJ) using the
Cell Quest software.
4.4.6 Concurrent or sequential treatment of xenografts. To generate xenografts, PC-3
cells (2×106) and LnCaP cells (4x106 in 0.1 mL matrigel) were injected subcutaneously
into both flanks of male nude mice, and MDA-468 cells (2×106) were injected similarly
in female nude mice. All animals were tagged and sorted randomly into groups (as
described below), and each group had at least 10 tumours. Once tumours reached a size
of approximately 50 mm3, treatments were initiated: the first day of treatment was
referred to as day 0. When treatments were completed, the animals were regrouped in
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order to avoid observer bias. Tumour volumes were plotted as a function of time
following initiation of treatment. All experiments were repeated.
Different groups of mice received the following treatments (Figure 4.1B): (1)
control: vehicle solution 0.1 ml i.p.; (2) temsirolimus alone: 10 mg/kg i.p. 3 consecutive
days per week for 3 weeks on days 0-2, 7-9, and 14-16; (3) DOC or 5-FU alone: DOC 15
mg/kg or 5-FU 100 mg/kg i.p. once weekly for 3 doses on days 0, 7, and 14; (4) DOC or
5-FU plus temsirolimus (concurrent): DOC or 5-FU on days 1, 8, and 15, with
temsirolimus on days 0-2, 7-9, and 14-16; (5) DOC or 5-FU followed by temsirolimus
(sequential): DOC or 5-FU on days 0, 7, and 14, and temsirolimus on days 2-4, 9-11, and
16-18.
4.5 Results
4.5.1 Effects of temsirolimus and chemotherapy in vitro
The growth of PC-3, LnCaP and MDA-468 cells was inhibited by temsirolimus in
a dose-dependent manner (Fig. 4.2A). PC-3 and LnCaP cells were slightly more sensitive
to temsirolimus than MDA-468 cells, especially at the lowest concentration of 0.1 uM.
There was no significant difference at higher concentrations. Close to maximum
suppression of growth for all cell lines was obtained following exposure to 0.5 uM
temsirolimus.
Using a colony-forming assay, the mean surviving fractions (+/-SEM) of PC-3
cells after 24h treatment with 5 nM or 10 nM DOC were found to be 38±9% and 21±8%
respectively. LnCaP cells were more responsive to 24h treatment with the same doses of
DOC, with surviving fractions of 6±5% and 0.2±0.1% respectively. The surviving
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Figure 4.2. Effect of 3 days of treatment with temsirolimus on (A) number of PC-3 (▲), LnCaP (♦), and MDA-468 (■) cells (as compared to control cultures treated with diluent). Cell cycle analysis of (B) PC-3, (C) LnCaP, and (D) MDA-468 cells after 3-day exposure to 0.5uM temsirolimus. Data represents mean of three independent experiments; error bars, SEM.
144
fractions of MDA-468 cells after 24h treatment with 10 μM or 50 μM 5-FU were 65±4%
and 15±4% respectively.
Cell cycle analysis showed that for all three cell lines the percentage of G1 phase
cells increased after a 3-day treatment with temsirolimus (0.5 uM), whereas the
percentage of S phase cells decreased (Figure 4.2B-D). The percentage of G2/M phase
cells did not change significantly. There was no significant difference in the cell cycle
distribution of PC-3 or LnCaP cells on day 7 following temsirolimus alone or either
concurrent or sequential scheduling with DOC and temsirolimus, or for 5-FU and
temsirolimus with MDA-468 cells (Figure 4.3A-C; P>0.05 in each group).
The numbers of reproductively viable PC-3 and LnCaP cells on day 7 after
various treatments, as determined by a colony-forming assay, are shown in Figure 4.4a
and Figure 4.4B, respectively; there was no significant difference between the sequential
or concurrent scheduling groups, or between combined treatment and docetaxel alone
(Figures 4.4A and 4.4B).
There was no significant difference in the number of colony-forming MDA-468
cells treated with temsirolimus 0.5 μM and 5-FU 10 μM concurrently or sequentially, and
no effect to reduce the number below controls (Figure 4.4C).
4.5.2 Effects of chemotherapy and temsirolimus on xenografts
Growth inhibition of prostate cancer PC-3 xenografts following various treatments
is shown in Figure 4.5A. There was no observable difference in mean tumour size
between concurrent and sequential treatment until day 28, but concurrent scheduling was
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A.
Figure 4.3. Cell cycle analysis of (A) PC-3, (B) LnCaP, and (C) MDA-468 cells on day 7 after sequential or concurrent treatment with 10nM DOC or 10uM 5-FU and 0.5uM temsirolimus. Most data represent means of three independent experiments; error bars, SEM.
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Figure 4.4. Effects of concurrent and sequential scheduling of chemotherapy and temsirolimus (see Figure 1a for schedules) on number of colony-forming cells present at day 7 in cultures of (A) PC-3, (B) LnCaP, and (C) MDA-468 cells. Bars, mean of four independent experiments; error bars, SEM.
147
Figure 4.5. Effects of concurrent and sequential schedules of chemotherapy and temsirolimus on growth of (a) PC-3 xenografts (chemotherapy = docetaxel) and (b) MDA-468 xenografts (chemotherapy =5-FU). Both plots represent one experiment, with repeat experiments showing similar trends; error bars represent SEM.
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148
more effective in delaying subsequent regrowth of the xenografts. Mean tumour volume
at day 52 was 167±32 mm3 and 461±114 mm3 for concurrent and sequential treatment,
respectively (P=0.038). Both combined treatment groups showed significantly greater
tumour growth delay than treatment with temsirolimus alone, DOC alone, and especially
when compared to controls.
LnCaP xenografts were difficult to grow in nude mice; and once established, the
tumours grew slowly. There was no effect of temsirolimus treatment alone to influence
the growth of LnCaP xenografts, while DOC treatment had small effects to inhibit
tumour growth. Concurrent but not sequential administration of DOC and temsirolimus
had greater effects to cause tumour shrinkage and inhibit tumour regrowth than docetaxel
alone (Figure 4.6). In addition, tumour growth was observed in the prostate region of the
mice in the docetaxel alone, temsirolimus alone, and sequential combined treatment
groups (i.e. around day 145); however, there were no tumours noted in the prostate region
of the mice in the concurrent group.
MDA-468 tumours grew quite slowly in nude mice, and there were relatively
small effects of 5-FU alone, temsirolimus alone, or combined treatment to increase
growth delay (Fig. 4.5B). There was no significant difference between the effects of
concurrent and sequential treatment. No significant differences in body weight were
observed between groups, suggesting limited toxicity with combined treatment.
149
Time (days)
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Figure 4.6. Effects of concurrent and sequential schedules of docetaxel and temsirolimus on growth of LnCaP xenografts. Plot represents two independent experiments; error bars represent SEM.
150
4.6 Discussion
Our previous study showed that the PTEN-negative human prostate cancer PC-3
cell line is more sensitive to treatment with temsirolimus than the DU145 prostate cancer
cell line with wild type PTEN (14). Therefore, the PC-3 tumour line was used in the
present study to compare concurrent and sequential treatments with temsirolimus and
docetaxel (the preferred drug for treatment of human prostate cancer, 21,22) in cells and
tumour xenografts, and we also tested the PTEN-mutant human prostate cancer cell line,
LnCaP (23). The human breast cancer MDA-468 cell line was selected for this study
because it is reported to be PTEN negative and sensitive to temsirolimus, with an IC50 in
the nanomolar range, due to over-expression of S6K1 and expression of phosphorylated
Akt/PKB (8,24). In preliminary experiments we confirmed that the MDA-468 cell line
was more sensitive to temsirolimus than other breast cancer cell lines, such as MDA-231,
MDA-435 and MCF-7. However, temsirolimus was more effective against human
prostate cancer PC-3 cells and xenografts than human breast cancer MDA-468 cells and
xenografts when used alone or in combination with chemotherapy. Temsirolimus also led
to greater growth delay of PC-3 xenografts than docetaxel alone; this effect is greater
than that expected from the in vitro sensitivity, and differs from the general experience in
treatment of human prostate cancer, where chemotherapy has shown greater activity than
molecular targeted agents. In contrast, for LnCaP cells, temsirolimus had similar
inhibitory effects to those observed with PC-3 cells in culture, but no significant effect on
LnCaP xenografts.
Concurrent administration of temsirolimus and docetaxel led to better outcome
than sequential scheduling for PC-3 tumours and for LnCaP tumours, but there was no
151
significant difference between the two treatment schedules for the MDA-468 tumours.
We hypothesized that temsirolimus administered sequentially between docetaxel
treatments would be more effective at inhibiting repopulation compared to concurrent
treatment, mainly due to effects of the inhibitor on cell cycle. Temsirolimus puts cells out
of cycle (G1 growth arrest); therefore, concomitant administration of temsirolimus with
docetaxel may decrease the efficacy of cycle-active chemotherapy. However, our in vitro
results showed no difference in cell cycle distribution between sequential and concurrent
combined treatment on day 7, prior to the subsequent course of chemotherapy in PC-3
cells and LnCaP cells (Figure 4.3). The distribution of the S-phase population in the
sequential treatment group is similar to that observed on day 7 following temsirolimus
treatment alone suggesting that the effects of temsirolimus might have been dominant at
this time with the combined treatment (Figure 4.3). Docetaxel treatment led to a lower S-
phase population and a slight increase in the G1 and G2/M populations compared to both
combined treatment groups (Figure 4.3). Growth arrest at G1 and G2/M has been
previously observed following taxane treatment (25; and data from our laboratory). This
result suggests that docetaxel treatment continued to have effects on cell cycle at day 7
following treatment; however, this did not translate into a difference in survival as
indicated by similar clonogenic cell numbers in the docetaxel alone and combined
treatment groups (Figure 4.4A-B). In addition, a higher sub-G0/G1 population, which has
been shown to represent apoptotic cells, was observed in PC-3 cells following docetaxel
alone as compared to sequential or concurrent combined treatment (Figure 4.7A; p<0.05),
which might also account for the differences in cell cycle distribution. It is not clear why
gefitinib might have changed the effects on cell cycle of docetaxel in the combined
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ated
pop
ulat
ion
Figure 4.7. Plot of (a) PC-3 and (b) LnCaP sub-G1 cell populations (representative of apoptotic cells) on day 7 after sequential or concurrent treatment with 10nM DOC and 0.5uM temsirolimus. Most data represent means of three independent experiments; error bars, SEM.
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treatment groups. There was no significant difference between the sub-G0/G1 population
in LnCaP cells following paclitaxel alone or combined treatment (Figure 4.7B).
Despite similar cell cycle effects between concurrent and sequential treatments in
our in vitro experiments, in vivo growth delay studies showed better delay of tumour
regrowth with concurrent temsirolimus and docetaxel treatment as compared to
sequential treatment in the prostate xenografts. Preclinical studies and clinical trials that
have compared sequential versus concurrent administration of chemotherapy with
tamoxifen or inhibitors of the EGFR have favored sequential treatment (16-20). We had
hypothesized that sequential scheduling might be superior because of inhibition of
repopulation by temsirolimus between courses of chemotherapy. However, it is possible
that the main effects of combined treatment on tumour repopulation were not due to cell
cycle factors, but rather effects of treatment on the tumour microenvironment.
Studies have suggested that both docetaxel and temsirolimus have antiangiogenic
properties (26,27). Sweeney and colleagues showed that docetaxel inhibited endothelial
cell growth and capillary formation in vitro in a dose-dependent manner (26). Studies in
our laboratory have shown antiangiogenic effects of paclitaxel (a related taxane) in vivo
(unpublished data), and ongoing studies in our laboratory are evaluating the effects of
docetaxel on tumour vasculature in human prostate xenografts. Temsirolimus may inhibit
tumour growth through antiangiogenic mechanisms associated with the targeting of the
mTOR/HIF-1α/VEGF signalling pathway, as indicated by decreased levels of hypoxia-
inducible factor-1alpha (HIF-1α), vascular endothelial growth factor (VEGF) expression
and microvessel density (27). A decrease in tumour vasculature would likely lead to less
repopulation within tumours and increased cell death.
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As temsirolimus was the dominant treatment in our studies with PC-3
xenografts, cells may have remained out of cycle when the second and third docetaxel
doses were given in the sequential schedule. Our in vivo results suggest that three daily
doses of temsirolimus given three times at weekly intervals are able to completely
abrogate growth of PC-3 xenografts for 21 days, whereas effects against single cells in
culture appear to be more transient. The effects of temsirolimus and docetaxel to delay
tumour growth appear to be at least additive, especially for the concurrent schedule;
therefore, for treatment of PC-3 xenografts, the dominant effect of temsirolimus may
have been to upregulate mechanisms leading to cell death (28).
There was a slight delay in the regrowth of MDA-468 breast cancer xenografts
following combined treatment as compared to treatment with either agent alone (Figure
4.5B); however, the effects were not as prominent as those observed with PC-3
xenografts (Figure 4.5A). The minimal effect of temsirolimus alone on MDA-468 cells
and xenografts might be attributed to changes in signalling events following mTOR
inhibition: a study by Sun et al. showed that treatment with rapamycin (an inhibitor of
mTOR) in various cancer cell lines led to a decrease in the amount of phosphorylated
p70S6K (a downstream marker of mTOR activity), which is indicative of mTOR
inhibition; however, rapamycin also induced a subsequent increase in p-Akt and p-eIF4E
levels following treatment (29). These results were attributed to a feedback mechanism
associated with PI3K dependent activation of the Akt and eIF4E proteins (29), which
would likely result in downstream signalling events leading to cell survival and
proliferation.
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Temsirolimus has been studied extensively in clinical trials as a single agent
(30); however, there are limited studies of the combination of temsirolimus and
chemotherapy. A study of temsirolimus administered concomitantly with gemcitabine for
the treatment of pancreatic cancer showed that combination therapy was more effective at
inhibiting tumour growth than either agent alone (31). A Phase I trial testing the effect of
temsirolimus and 5-FU and leucovorin in patients with advanced solid tumours showed
partial tumour responses in 3 of 26 patients; however, the study was stopped due to high
toxicity observed in patients in the combined treatment arm (32). In that study, treatment
with temsirolimus was initiated on day 8, prior to leucovorin/5-FU (32).
Our study shows that combined docetaxel and temsirolimus treatment is more
effective at delaying tumour regrowth than either agent alone in human prostate tumours.
In addition, combined treatment administered concurrently was more efficacious than
sequential administration of these agents for both PC-3 and LnCaP xenografts. Clinical
trials should evaluate optimal dosing and scheduling of combined chemotherapy and
growth inhibitor treatment. Our study suggests that combined docetaxel and temsirolimus
treatment might be beneficial in the treatment of men with prostate cancer.
ACKNOWLEDGEMENTS
Supported by a grant from the Canadian Institutes of Health Research. Special thanks to
Carol Lee and James Ho for technical support.
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4.7 References
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3. Kim JJ, Tannock IF. Repopulation of cancer cells during therapy: an important cause of treatment failure. Nat Rev Cancer 2005;5:516-25
4. Minchinton AI, Tannock IF. Drug penetration in solid tumours. Nat Rev Cancer 2006;6:583-92.
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6. Wu L, Tannock IF. Repopulation in murine breast tumors during and after sequential treatments with cyclophosphamide and 5-fluorouracil. Cancer Res 2003;63:2134-8
7. Bonner JA, Harari PM, Giralt J, et al. Radiotherapy plus cetuximab for squamous-cell carcinoma of the head and neck. N Engl J Med 2006;354:567-78
8. Yu K, Toral-Barza L, Discafani C. mTOR, a novel target in breast cancer: the effect of CCI-779, an mTOR inhibitor, in preclinical models of breast cancer. Endocr Relat Cancer 2001;8: 249-58
9. Shi Y, Gera J, Hu L, et al. Enhanced sensitivity of multiple myeloma cells containing PTEN mutations to CCI-779. Cancer Res 2002;62:5027-34
10. Peralba JM, DeGraffenried L, Friedrichs W et al. Pharmacodynamic Evaluation of CCI-779, an Inhibitor of mTOR, in Cancer Patients. Clin Cancer Res 2003;9: 2887-92
11. Aktins MB, Hidalgo M, Stadler WM et al. Randomized phase II study of multiple dose levels of CCI-779, a novel mammalian target of rapamycin kinase inhibitor, in patients with advanced refractory renal cell carcinoma. J Clin Oncol 2004;22: 909-18
12. Frost P, Moatamed F, Hoang B, et al. In vivo antitumor effects of the mTOR inhibitor CCI-779 against human multiple myeloma cells in a xenograft model. Blood. 2004;104:4181-7
13. Raymond E, Alexandre J, Faivre S, et al. Safety and pharmacokinetics of escalated doses of weekly intravenous infusion of CCI-779, a novel mTOR inhibitor, in patients with cancer. J Clin Oncol 2004;22: 2336-47
14. Wu L, Birle D, Tannock IF. Effects of the mammalian target of rapamycin inhibitor CCI-779 used alone or with chemotherapy on human prostate cancer cells and xenografts. Cancer Res 2005;65:2825-31
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15. Hudes G, Carducci M, Tomczak P, et al. Temsirolimus, interferon alfa, or both for advanced renal-cell carcinoma. New England Journal of Medicine 2007; 356: 2271-81
16. Albain KS, Green SJ, Ravdin PM, et al. Adjuvant chemohormonal therapy for primary breast cancer should be sequential instead of concurrent: initial results from intergroup trial 0100 (SWOG 8814). Proc Am Soc Clin Oncol 2002;21:37a
17. Goldhirsch A, Wood WC, Gelber RD. Meeting highlights: updated international expert consensus on the primary therapy of early breast cancer. J. Clin. Oncol 2003;21:3357-65
18. Pico C, Martin M, Jara C, et al. Epirubicin-cyclophosphamide adjuvant chemotherapy plus tamoxifen administered concurrently versus sequentially: Randomized phase III trial in postmenopausal node-positive breast cancer patients. A GEICAM 9401 study. Annals of Oncology 2004;15:79-87
19. Morelli MP, Cascone T, Troiani T, et al. Sequence-dependent antiproliferative effects of cytotoxic drugs and epidermal growth factor receptor inhibitors. Ann Oncol 2005;16:iv61-iv68
20. Kassouf W, Luongo T, Brown G, Adam L, Dinney CPN. Schedule dependent efficacy of gefitinib and docetaxel for bladder cancer. J Urol 2006;176:787-792
21. Tannock IF, de Wit R, Berry WR, et al: Docetaxel plus prednisone or mitoxantrone plus prednisone for advanced prostate cancer. N Engl J Med 2004;351:1502-12
22. Petrylak DP, Tangen CM, Hussain MH, et al. Docetaxel and estramustine compared with mitoxantrone and prednisone for advanced refractory prostate cancer. N Engl J Med 2004;351:1513-20
23. Huang H, Cheville JC, Pan Y, Roche PC, Schmidt LJ, Tindall DJ. PTEN induces chemosensitivity in PTEN-mutated prostate cancer cells by suppression of Bcl-2 expression. The Journal of Biological Chemistry 2001;276:38830-38836
24. Noh WC, Mondesire WH, Peng J, et al. Determinants of rapamycin sensitivity in breast cancer cells. Clin. Cancer Res 2004;10:1013-23
25. Li Y, Li X, Hussain M, Sarkar FH. Regulation of microtubule, apoptosis, and cell cycle-related genes by taxotere in prostate cancer cells analyzed by microarray. Neoplasia 2004; 6:158-167
26. Sweeney CJ, Miller KD, Sissons SE, et al. The antiangiogenic property of docetaxel is synergistic with a recombinant humanized monoclonal antibody against vascular endothelial growth factor or 2-methoxyestradiol but antagonized by endothelial growth factors. Cancer Res 2001;61:3369-3372
27. Wan X, Shen N, Mendoza A, et al. CCI-779 inhibits rhabdomyosarcoma xenograft growth by an antiangiogenic mechanism linked to the targeting of mTOR/Hif-1alpha/VEGF signalling. Neoplasia 2006;8:394-401
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28. Hu X, Pandolfi PP, Li Y, et al. mTOR promotes survival and astrocytic characteristics induced by Pten/AKT signalling in glioblastoma. Neoplasia 2005; 7:356-68
29. Sun S, Rosenberg LM, Wang X, et al. Activation of Akt and eIF4E survival pathways by rapamycin-mediated mammalian target of rapamycin inhibition. Cancer Res 2005;65:7052-7058
30. Rini BI. Temsirolimus, an inhibitor of mammalian target of rapamycin. Clin Cancer Res 2008;14:1286-1290
31. Ito D, Fujimoto K, Mori T, et al. In vivo antitumor effect of the mTOR inhibitor CCI-779 and gembcitabine in xenograft models of human pancreatic cancer. Int J Cancer;118:2337-2343
32. Punt CJA, Boni J, Bruntsch U, Peters M, Thielert C. Phase I and pharmacokinetic study of CCI-779, a novel cytostatic cell-cycle inhibitor, in combination with 5-fluorouracil and leucovorin in patients with advanced solid tumors. Annals of Oncology; 14:931-937
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CHAPTER 5
CONCLUSIONS & FUTURE DIRECTIONS
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5. CONCLUSIONS & FUTURE DIRECTIONS
Many new drugs for cancer are directed at specific molecular targets, which can
aid in focusing drug treatment to cancer cells with less normal tissue toxicity.
Repopulation might be inhibited by using molecular targeted agents in conjunction with
chemotherapy. Chemotherapeutic agents and molecular targeted therapies likely have
different effects on cell proliferation, cell death, and the tumour microenvironment.
Hence, with the addition of targeted molecular therapies to standard anticancer treatment,
such as chemotherapy, it is important to focus research efforts on understanding the
effects of these agents on solid tumours and the tumour microenvironment when used
alone and in combination. This research thesis has focused on characterizing
repopulation, studying the effect of potential cytostatic agents that can be used to inhibit
repopulation of tumour cells within a solid tumour, and determining the effect of
scheduling of combined cytotoxic and cytostatic treatments on the solid tumour
microenvironment and therapeutic efficacy.
5.1 Characterization and Inhibition of Repopulation 5.1.1 Summary
In experiments described in Chapter 2, I aimed to characterize repopulation within
solid tumours by studying the distribution of cell proliferation and apoptosis in A431 and
MCF-7 xenografts following chemotherapy. Paclitaxel caused an initial decrease in cell
proliferation in regions close to blood vessels (likely due to the limited penetration of
chemotherapeutic agents from blood vessels), as well as a decrease in the functional
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vasculature. The initial decrease in functional vasculature probably limited the nutrient
and oxygen supply to tumour cells, thereby causing the observed decrease in cell
proliferation and increase in the amount of cell death within the tumour. We hypothesized
that repopulation would be dependent on changes in the tumour microenvironment and
would occur maximally in regions distal from functional blood vessels. My data show
that repopulation occurs as a result of changes in the tumour microenvironment.
However, repopulation of tumour cells was observed in regions both distal and proximal
to functional blood vessels approximately 12 days following paclitaxel treatment.
Importantly, a rebound in the percentage of functional blood vessels was noted around
the same time suggesting that an improvement in the delivery of nutrients and oxygen
might account for repopulation of tumour cells within a solid tumour.
A related study by Huxham et al. showed that repopulation of colorectal
carcinoma xenografts was first observed in regions distal from functional blood vessels –
the proliferation in these regions reached control levels approximately 4-6 days following
gemcitabine treatment; however, there was also cell proliferation noted in regions
proximal to blood vessels at this time at approximately 50% of control levels (34).
Contrary to our original hypothesis that repopulation would occur maximally in regions
distal from functional vasculature, we observed cell proliferation in regions both
proximal and distal to blood vessels following chemotherapy. A possible explanation
could be that paclitaxel had only moderate effects on A431 xenografts, which could have
resulted in proximal cells remaining intact, thereby acting as a source of repopulation.
Studies of repopulation in MCF-7 xenografts following treatment with paclitaxel
showed a slight increase in cell proliferation close to blood vessels, no change in
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apoptosis, and no significant change in the total number of functional blood vessels.
There were only moderate effects of paclitaxel to delay tumour growth compared to
untreated controls, and the observed changes in cell proliferation, apoptosis, and
functional vasculature suggest that MCF-7 tumours are not highly susceptible to
paclitaxel treatment. Paclitaxel is often effective in treating breast cancer in the clinic,
with response rates of 50% or more in patients who have not received prior
chemotherapy. Unfortunately, neither of the two xenograft models for breast cancer that I
studied mimic drug-sensitive tumours in the clinic. A study by Kubota et al. showed good
antitumour effects with paclitaxel treatment in MCF-7 xenografts; however, in their
studies, paclitaxel was administered at higher doses and more often than in our study,
namely 25 mg/kg daily for five days compared to 25 mg/kg once weekly (221).
In chapter two, I also described the effect of gefitinib to inhibit repopulation
through the characterization of changes in cell proliferation, apoptosis, and the tumour
vasculature, following drug treatment. Cell proliferation was decreased in A431
xenografts during gefitinib treatment (administered on days 0-3) in regions proximal to
blood vessels; this is consistent with the properties of cytostatic agents, which cause an
initial arrest in cell growth. Some cytostatic agents have also been shown to cause cell
death (222), which explains the increase in apoptosis observed in A431 tumours
following gefitinib treatment.
The rebound in cell proliferation observed in tumours treated with gefitinib
occurred sooner than in tumours treated with paclitaxel (i.e. five days following the last
dose of gefitinib compared to ~12 days following paclitaxel treatment). It is possible that
the faster rebound in cell proliferation was due to the more predominant cytostatic effects
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of gefitinib on tumour cells compared to cytotoxic effects observed following paclitaxel
treatment.
5.1.2 Implications of the Study
Few studies have investigated the process of repopulation within solid tumours
following chemotherapy. By studying the changes in the distribution of proliferating cells
following drug treatment, we showed that tumour cells within solid tumours repopulate
following chemotherapy, and that repopulation appears to be dependent on changes in the
tumour microenvironment, specifically changes in functional tumour vasculature.
Determining when repopulation occurs following treatment can aid in scheduling of drug
treatment. Moreover, by characterizing the spatial distribution of repopulation, we can
better determine which targeted therapies might be efficacious at inhibiting repopulation
(i.e. a cytostatic agent that distributes well into both proximal and distal regions of the
tumour). Lastly, the observation that repopulation appears to depend on the rebound in
functional tumour vasculature within solid tumours suggests that targeting the tumour
vasculature might also aid in the inhibition of repopulation between courses of
chemotherapy.
5.1.3 Limitations and Future Directions
In our characterization of repopulation in solid tumours, we followed changes in
cell proliferation and apoptosis after a single dose of chemotherapy. A potential
limitation of these studies is the lack of time-matched or tumour-volume matched
controls. It would be beneficial to include untreated control tumours that are either
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similar in the duration of growth or similar in size to treated tumours – this would allow
one to distinguish between variations in cell proliferation, cell death, and the tumour
microenvironment, that are due to changes in tumour size rather than drug effects. In
addition, as most clinical treatment regimens include multiple courses of chemotherapy,
future studies should characterize the repopulation of tumour cells in solid tumours
following multiple treatments.
The tumour microenvironment plays an important role in repopulation following
chemotherapy. The present study characterized repopulation through the use of frozen
tumour tissue taken from tumours grown subcutaneously in mice. Some studies suggest
that the vasculature within spontaneous or orthotopic tumours is different from vessels in
transplanted subcutaneous tumours (223, 224); therefore, due to the observed relationship
between changes in tumour vasculature and repopulation, it will be important to study the
effects of chemotherapy on repopulation and the tumour microenvironment in other
tumour models. Future studies should characterize repopulation in spontaneous or
orthotopic tumours, or patient tumour samples (if available).
Additionally, as most changes in cell proliferation, cell death, or the tumour
microenvironment occur over time and continue to change following drug treatment,
determining a clear picture of the fluidity of the tumour environment is difficult using the
current methodology. Studying repopulation in a 3-dimensional model might provide
more information about changes within the tumour that occur due to blood vessels that
are out of the plane in our two dimensional system. In addition, using a real time in vivo
model would be beneficial. With the advancement of imaging techniques it might now be
feasible to measure changes in cell proliferation and apoptosis in solid tumours following
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chemotherapy in live animals. For example, studies using a window-chamber model
system would allow for accessible imaging of changes in tumour cells and vasculature
within a solid tumour; furthermore, since this technique is minimally invasive and
animals recover well from anesthesia used during imaging, animals could be imaged at
multiple time points following drug treatment in a continuous long-term study (225).
Studies have used confocal microscopy to examine changes in blood vessels and cell
viability using a window-chamber model following photodynamic therapy (PDT); the
resolution of the confocal images allowed for detection of changes at the cellular level
(i.e. around 50μm), within solid tumours (225). Other imaging modalities, such as
Doppler Optical Coherence Tomography (DOCT), have been used to detect changes in
blood vessel function in solid tissues grown in the window-chamber model by measuring
the flow velocity with a resolution of <10μm (226). A potential disadvantage of this
system is that a window-chamber system provides an artificial environment for tumour
growth, and the limit for tissue growth is approximately 400μm (225). Bioluminescence
imaging is a potential tool for measuring changes in the tumour in its innate environment.
However, to date, resolution of bioluminescence imaging is not sensitive enough to detect
changes at the cellular level (i.e. micrometer range). Therefore, bioluminescence imaging
might be used to determine whether cell proliferation (repopulation) occurs following
anticancer treatment (227); however, it is presently not feasible to evaluate the spatial
distribution of changes in cell proliferation in relation to functional blood vessels using
this imaging modality.
My data have shown that repopulation occurs in regions both proximal and distal
(i.e. hypoxic regions) from functional blood vessels. Changes in hypoxia within the
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tumour were observed following chemotherapy and molecular targeted treatment. We
identified regions of hypoxia within tumours using EF5 staining; however, we were not
able to distinguish between transient and chronic regions of hypoxia. Since repopulation
might occur through the outgrowth of tumour cells in regions of either transient or
chronic hypoxia, it is important that future studies further characterize changes in
hypoxia over time to determine how these changes affect the distribution of repopulation.
Moreover, it is important to choose a molecular targeted agent that can distribute well in
regions both proximal and distal from functional vasculature when trying to inhibit
repopulation of solid tumours between courses of chemotherapy. Hypoxia-activated
agents might be effective at inhibiting repopulation that occurs in regions distal from
functional blood vessels between courses of chemotherapy. If the distribution of
repopulating cells can be measured in relation to changes in hypoxic regions, this might
aid in determining an optimal treatment schedule when combining hypoxia-activated
drugs with chemotherapy.
5.2 Combining Molecular Targeted Agents with Chemotherapy
The interaction between components of the tumour microenvironment is complex.
We have shown that changing aspects of the microenvironment, such as the tumour
vasculature, is associated with the proliferation and death of cancer cells; moreover, it
might alter the response of tumours to additional therapies. Therefore, studying the
effects of combined therapies on repopulation and the solid tumour microenvironment is
an essential topic of research. We and others have shown that a single treatment with
some chemotherapy agents can decrease the functional vasculature (Chapter 2) (85),
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which might limit the delivery and distribution of subsequent drugs within the tumour.
These factors are important to consider when combining molecular targeted therapies
with chemotherapy. Moreover, determining the optimal schedule for combined
treatments is essential to ensure adequate treatment efficacy.
The third and fourth chapters of this thesis focused on determining the potential of
two molecular targeted agents (i.e. gefitinib or temsirolimus) to inhibit repopulation
between multiple courses of chemotherapy. In addition, our study compared the
concurrent and sequential administration of chemotherapy and molecular targeted
treatment. Chemotherapy is often administered once every 3 weeks in humans because
this interval allows for recovery (i.e. repopulation) of normal human bone marrow. Mice
have been shown to recover from chemotherapy treatment approximately three times
faster than humans hence we chose to administer chemotherapy once weekly in our
animal studies. Based on the half lives for the chosen targeted agents, as well as cell cycle
analysis we performed, we chose a sequential treatment schedule that would allow time
for cells to begin cycling following removal of the cytostatic agent, prior to the next
course of chemotherapy.
5.2.1 Summary: Chemotherapy in Combination with the EGFR Inhibitor Gefitinib
In chapter three, I hypothesized that the targeted cytostatic agent gefitinib would
be effective at inhibiting repopulation between courses of chemotherapy. My in vitro
repopulation studies showed that gefitinib was able to inhibit the regrowth of A431 cells
between courses of paclitaxel. In addition, my in vivo data showed that gefitinib
administered between courses of paclitaxel was able to cause a decrease in cell
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proliferation within A431 xenografts. Therefore, my data indicate that repopulation can
be inhibited with cytostatic agents such as gefitinib between courses of chemotherapy.
Cell cycle effects of treatment must be considered when combining cytostatic
agents with cycle-active chemotherapy. In chapter 3, I compared sequential and
concurrent scheduling of chemotherapy with a molecular targeted agent. We
hypothesized that the sequential administration of chemotherapy and gefitinib would be
better than concurrent treatment because of inhibition of repopulation of tumour cells
between courses of chemotherapy, without hindering chemotherapeutic efficacy. In vitro
repopulation studies supported our hypothesis – gefitinib administered sequentially
between courses of chemotherapy (i.e. paclitaxel) inhibited the repopulation of A431
cells better than chemotherapy or gefitinib treatment alone and concurrent combined
treatment. As hypothesized, combined treatment with chemotherapy and a molecular
targeted agent was dependent on cell cycle changes, as there was decreased cell death
observed when chemotherapy was given concomitantly with gefitinib. However, our cell
culture data did not translate into similar in vivo results – growth delay studies showed
better inhibition of xenograft growth when chemotherapy was administered concurrently
with gefitinib. This discrepancy between in vitro and in vivo results is likely due to
effects of these agents on the tumour microenvironment (specifically changes in
functional tumour vasculature), which seem to be dominant over cell cycle effects within
solid tumours.
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5.2.2 Implications of the Study
Our data comparing concurrent and sequential administration of chemotherapy
and the molecular targeted agent gefitinib highlights the limitations of single-cell in vitro
models for solid tumours. My data show the importance of using caution when
interpreting in vitro studies, as these results might not translate into similar effects in
solid tumours. Contrary to my hypothesis (and my in vitro data), I found that the
concurrent administration of chemotherapy and gefitinib resulted in better delay of
tumour regrowth than sequential treatment. A probable explanation is that changes in the
tumour microenvironment are more dominant than cell cycle effects in determining the
efficacy of combined chemotherapy and molecular targeted treatment in solid tumours.
Furthermore, it is possible that the administration of gefitinib prior to chemotherapy in
the concurrent group led to up-regulation of cell death pathways or sensitization of
tumour cells to paclitaxel treatment. The effect of gefitinib used in combination with
chemotherapy in phase III clinical trials has been rather disappointing (179, 180) and
further studies that highlight the effects of these agents on the solid tumour
microenvironment and repopulation might increase the likelihood that their incorporation
into treatment regimens would be beneficial. My data have shown some effect of
combined concurrent treatment on the tumour vasculature, and further studies should
examine other mechanisms that are dependent on the tumour microenvironment, such as
changes in drug distribution, which might affect treatment efficacy.
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5.2.3 Limitations and Future Directions
In chapter 3, we chose the A431 cell line for our study due to its overexpression
of the EGFR. However, a potential limitation is that we have not confirmed our results
with another EGFR overexpressing cell line from target tissues such as the lung, brain, or
colon. In addition, many studies have highlighted the role of EGFR mutations in
treatment efficacy (228, 229), as well as acquired resistance to targeted EGFR therapy.
The present study did not investigate the effect of EGFR mutations on repopulation or
therapeutic efficacy of combined chemotherapy and gefitinib treatment. However, my
ongoing studies aim to determine the potential of gefitinib to inhibit repopulation
between courses of chemotherapy in EGFR-mutant cells and xenografts.
Interestingly, our studies in chapters 3 and 4 showed that molecular targeted
agents seemed to be more effective at inhibiting xenograft growth in mice than
chemotherapy; this observation has been noted in other studies (220), but is opposite to
what is often observed in clinic. This is a potential limitation of our study, and caution
should be used when translating pre-clinical results into clinical studies.
5.2.4 Summary: Chemotherapy in Combination with the mTOR Inhibitor Temsirolimus
Temsirolimus is an inhibitor of the mammalian target of rapamycin (mTOR),
which is located downstream of various growth factor receptors in the PI3 kinase
pathway (187, 188) (see Figure 1.7). Previous studies in our laboratory showed that
temsirolimus was highly effective at delaying the growth of PTEN negative human
prostate PC-3 xenografts when administered alone or in combination with docetaxel
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(209). The work in chapter 4 stemmed from these studies and aimed to determine the
capacity of temsirolimus to inhibit growth of other PTEN negative/mutant cells and
xenografts (i.e. human prostate cancer, LnCaP, or human breast cancer, MDA-468) when
used alone or in combination with chemotherapy, as well as to establish an optimal
treatment schedule for combined therapy. As in chapter 3, I hypothesized that
temsirolimus might inhibit repopulation when used in sequence with chemotherapy.
I observed marked inhibition of prostate cancer cell growth, and cell cycle arrest,
as indicated by an increase in the G0/G1 population in flow cytometry studies, following
temsirolimus treatment. However, there was no effect of temsirolimus to improve the
cytotoxicity of docetaxel when used in combination in prostate cancer cells, as measured
by clonogenic assays; in addition, there was no difference between the efficacy of
sequential or concurrent treatment schedules in vitro. Temsirolimus showed limited
efficacy in MDA-468 cells and xenografts.
My in vivo studies showed greater delay of PC-3 xenograft growth with combined
docetaxel and temsirolimus treatment when compared to either agent alone. Furthermore,
there was a greater effect to delay PC-3 and LnCaP tumour growth with the concurrent
administration of docetaxel and temsirolimus compared to sequential treatment. My data
did not support the hypothesis that temsirolimus might be more effective at inhibiting
repopulation when administered in sequence with chemotherapy, as I found better delay
of xenograft growth with concurrent treatment. It is likely that the effect of combined
treatment was due more to tumour microenviromental factors, or the predominant effects
of temsirolimus, which might have up-regulated cell death mechanisms, rather than to
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inhibition of repopulation of cells surviving docetaxel, which has smaller effects than
temsirolimus to inhibit growth of PC-3 xenografts.
5.2.5 Implications of the Study
Few studies have examined the effect of temsirolimus used in combination with
chemotherapy in prostate cancer; in addition, this study is the first to our knowledge that
compares concurrent and sequential scheduling of temsirolimus and chemotherapy. Our
study highlights the possible efficacy of combined therapy against prostate cancer when
administered concomitantly; however, optimal dosing for patients should be evaluated in
clinical trials. Importantly, our data suggest that combined docetaxel and temsirolimus
treatment might be an effective treatment for men with prostate cancer.
5.2.6 Limitations and Future Directions
Given the approval of temsirolimus for use in patients with kidney cancer, and the
observed effects of docetaxel and temsirolimus treatment in prostate cancer cells and
xenografts in our study, it will be important to examine the efficacy of chemotherapy and
temsirolimus in other cancer types that posses a PTEN mutant or deficient phenotype,
including patients with prostate cancer. A limitation of the current study is the lack of
mechanistic data regarding the effect of temsirolimus, docetaxel, or combined therapy on
repopulation (i.e. changes in cell proliferation) or the tumour microenvironment over
time. Future studies should address these issues to determine the mechanisms leading to
the efficacy of concurrent temsirolimus and docetaxel treatment in prostate cancer
xenografts.
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Similar to data obtained with gefitinib treatment, temsirolimus seemed to be more
effective at inhibiting prostate xenograft growth in mice than chemotherapy (i.e.
docetaxel), which is opposite to what is often observed in clinic. This is a potential
limitation of our study, and caution should be used when translating pre-clinical results
into clinical studies.
In addition, we found minimal effects of temsirolimus used alone or in
combination in PTEN negative MDA-468 cells and xenografts; this might have been due
to a feedback mechanism associated with PI3K dependent activation of the downstream
Akt and eIF4E proteins following temsirolimus treatment (230). Further characterization
of these signalling changes in MDA-468 cells and xenografts might be beneficial in
determining possible mechanisms of resistance to temsirolimus treatment.
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5.3 Concluding Remarks
In summary, work completed in this thesis has added knowledge to the field of
cancer biology by characterizing the distribution of repopulating cells within tumours and
determining the effect of the tumour microenvironment on repopulation. I have identified
the ability of chemotherapy and molecular targeted agents, such as gefitinib, to decrease
the number and function of tumour blood vessels. Notably, the antiangiogenic effect of
anticancer agents on tumour vasculature has important implications in terms of
antitumour effects and treatment efficacy of combined therapy. Lastly, I have studied the
efficacy of cytostatic agents, such as gefitinib and temsirolimus, to inhibit repopulation
between courses of chemotherapy, and highlighted the importance of tumour
microenvironmental factors, such as functional vasculature, when determining optimal
scheduling of combined therapy.
Future studies should continue to evaluate repopulation in various tumour models
following different anticancer treatments. Characterizing the spatial distribution of
repopulation in solid tumours can be beneficial for:
1) Providing information to aid in determining which targeted agents can be used
to inhibit repopulation. The present study demonstrated the ability of targeted therapies,
such as gefitinib and temsirolimus, to inhibit repopulation between courses of
chemotherapy. Future studies should evaluate other targeted agents for use as inhibitors
of repopulation. For example, we and others have provided evidence that repopulation
occurs in hypoxic regions; therefore, hypoxia-activated agents might be useful as
inhibitors of repopulation.
175
2) Evaluating methods of tracking repopulation in human tumours. Due to the
observed association between tumour cell repopulation and changes in functional tumour
vasculature, there might be potential for monitoring vascular changes in tumours as a
surrogate for detecting repopulation of surviving tumour cells. It might be possible to
study changes in tumour vasculature in the clinic through the use of imaging modalities
such as MRI or PET, as a marker of tumour response and repopulation following
treatment.
3) Developing treatment strategies aimed at targeting the source of repopulation.
For example, if stem cells or hypoxic cells are the source of repopulation, then anticancer
treatments that target these cell populations could be used to try to prevent repopulation
from occurring. Presently, a significant area of research is focused on identifying and
characterizing putative cancer stem cells (CSCs) in solid tumours. As previously
mentioned, CSCs may contribute to repopulation; however, studying this cell population
has been difficult to date due to the lack of definitive cancer stem cell markers.
Understanding the role of CSCs in repopulation is imperative in order to better treat solid
tumours. Furthermore, if CSCs are involved in repopulating a tumour between courses of
chemotherapy, then it will be important to evaluate anticancer agents that can target these
cell populations with minimal toxicity to patients.
The work in this thesis highlights the complexity of the solid tumour
microenvironment, and illustrates the importance of optimizing treatment schedules for
combined chemotherapy and molecular targeted treatment due to the influence of the
tumour microenvironment on treatment efficacy. The distribution of anticancer drugs
following treatment, as well as the changes in nutrient and oxygen concentrations (i.e.
176
hypoxia) in response to alterations in tumour vasculature, can influence how tumour cells
survive drug treatment and repopulate a tumour. It is difficult to predict the translation of
pre-clinical observations to clinical outcomes. However, by broadening our
understanding of the process of repopulation, and determining factors that affect
repopulation of surviving tumour cells (e.g. changes in functional vasculature, hypoxia,
and drug distribution), we can better evaluate optimal treatment strategies for patients.
177
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APPENDIX I Image Quantification: Future Considerations
Some of the current image analysis software programs (e.g. ImagePro Plus,
ImageJ) can be used to quantify positively stained nuclei within an area of interest or
user-specified regions (i.e. concentric circles surrounding an object such as a blood
vessel) in a tissue section; however, they are not able to measure corresponding distances
from the positively-stained nuclei to a specified object such as a blood vessel. Due to our
interest in determining changes in the spatial distribution of proliferating and apoptotic
cells in relation to functional blood vessels or regions of hypoxia, the distance
measurements are essential for our studies. Therefore, in order to include the distance
parameter, a customized algorithm was used, which measures the pixel intensity for each
pixel in an area of interest (AOI) and the corresponding distance to the nearest functional
blood vessel (or region of hypoxia). There are limitations with the current quantification
protocol used in the studies conducted in chapters 2 and 3, arising largely because a pixel
does not correspond to an object of interest such as a cell nucleus. Rather the pixels (of
size 0.4 μm2) are distributed between nuclear, cytoplasmic and extracellular areas. The
effect of averaging pixels at a given distance from blood vessels may therefore lead to an
underestimate of quantitative changes in the parameters measured (e.g. Ki67 nuclear
staining). Other problems may arise due to use of continuous scale analog measurements
for binary objects (e.g. Ki67 and cleaved caspase-3), and the conversion of variable
hypoxia staining to binary units.
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Additional factors leading to a probable underestimate of parameters shown in the
mean intensity curves plotted in chapters 2 and 3 include the following:
Quantifying mean intensity changes in relation to functional blood vessels: The
data were plotted as a function of the distance to the nearest functional blood
vessel. Since there was a marked decrease in the number of functional vessels
present in tumours following drug treatment, changes in the level of cell
proliferation are greater than those shown in the graphs because the customized
algorithm did not normalize for the overall decrease in functional vessels.
Averaging of data: For each tumour section, numerous areas of interest (AOIs)
were quantified in order to be representative of the whole tumour area. The
variations within each AOI, and between AOIs taken from different tumour
sections, likely results in an underestimate of the data (i.e. a shallower gradient of
change in the plotted intensity values) due to averaging across numerous data sets.
Blood vessels out of plane of view: Signal from blood vessels that are out of the
two-dimensional plane of view will contribute to the mean intensity values plotted
and will likely make the gradients of intensity less steep. Therefore, mean
intensity values at greater distances from the nearest functional blood vessel are
less representative of the raw data that would be obtained if there was no noise
(i.e. additional signal) from blood vessels out of the plane of view.
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Future quantification protocols/programs should take the changes in total functional
blood vessels present within tumours into consideration when measuring the changes in
cell proliferation and apoptosis in relation to the nearest functional vessel. Currently, the
distance to the nearest blood vessel is measured for each pixel in an image by averaging
the number pixels with a specific intensity and distance (i.e. frequency) within an area of
interest to obtain the mean intensity value at each distance. Through this method,
gradients of intensity are not determined for each specific vessel within an area of
interest, but are calculated as an average across numerous vessels in the AOI. An
alternative method might be to analyze the changes in cell proliferation/apoptosis around
each individual vessel in a tumour section and average the distributions obtained from
individual vessels in a tumour. It will be difficult to avoid noise from blood vessels out of
the plane of view since this is an unavoidable limitation of two-dimensional analyses.
Another potential limitation is the quantification of gradients of change in cell
proliferation and apoptosis rather than considering these parameters as binary
measurements. For instance, Ki67 staining was plotted as a gradient of intensity values
representative of Ki67 positivity, whereas, changes in Ki67 staining (cell proliferation) is
likely better represented as a binary measurement (i.e. Ki67-positive or Ki67-negative);
this also applies to changes in apoptosis as measured by cleaved caspase-3 staining.
Future quantification protocols should measure Ki67 or cleaved caspase-3 positive cells
as a function of distance to the nearest functional blood vessel or hypoxic region. A
preliminary re-analysis of a subset of the data presented in chapter 2 (Figures 2.2 and 2.3)
was carried out to measure changes in cell proliferation when Ki67 staining was
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considered a binary parameter. Using the ImagePro Plus analysis software, the upper and
lower threshold values for Ki67-positive nuclear staining were determined for each
tumour section and used to binarize the Ki67 images for quantification. The number of
Ki67-positive pixels was calculated as a percentage of the total number of pixels at a
specific distance from the nearest functional blood vessel (Figure A1.1). There is a
steeper gradient of decrease in the percentage of Ki67-positive pixels with increasing
distance from nearest functional vessel in untreated tumours. Furthermore, analysis with
Ki67 as a binary unit allowed for more sensitive detection of changes in cell proliferation
at early time points (i.e. Day 4) following paclitaxel treatment. However, using this
analysis we were not able to detect the changes in proliferation that are observed at later
time points (i.e. Day 12 tumours). The method of quantification needs to be further
refined in order to detect changes at later time points, and also to take the changes in
functional vasculature into consideration.
Additionally, in Figure A1.1 we plotted the percentage of Ki67-positive pixels;
however, many pixels will make up a nucleus of a cell so it would be more informative to
measure Ki67-positive cells/nuclei rather than Ki67-positive pixels in future
quantification programs. It is possible to use the ImagePro Plus software to mask the
Ki67 image, thereby assigning all positively-stained nuclei a specific intensity value. A
customized algorithm could be written to detect all objects of a certain size (the average
pixel area of a cell nucleus could be calculated using ImagePro Plus) with a specific
intensity value, and measure the corresponding distance to the nearest functional blood
vessel (denoted by the pixel intensity value 255) in each area of interest.
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Finally, in our characterization of the changes in the distribution of cell
proliferation (Ki67 staining) in relation to regions of hypoxia, the current analysis
considered EF5 staining (hypoxia) as a binary measurement. However, various studies
have shown that there are gradients of EF5 staining that correspond with a range of
hypoxia or pO2 levels in tumours (231, 232). Therefore, future analysis should quantify
changes in cell proliferation in relation to the gradients of hypoxia in tumours.
We will continue to refine our current quantification protocol in order to better
represent the data we have obtained. Moreover, by addressing the potential limitations of
our current methodology, we will be better able to incorporate the complexities of tumour
microenvironmental changes, in conjunction with the observed changes in cell
proliferation and apoptosis, to determine the effects on repopulation in solid tumours.
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0
5
10
15
20
25
30
35
0 20 40 60 80 100 120 140
Distance to nearest blood vessel (um)
% K
i67-
posi
tive
pixe
lsDay 0Day 4Day 8Day 12
Figure A1.1. The effect of a single dose of paclitaxel (25mg/kg) on cell proliferation in A431 xenografts, as measured by the percentage of Ki67-positive staining in relation to distance from the nearest functional blood vessel. Lines, mean of 3-4 tumors per treatment group; error bars represent SE.
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