The effect of molecular targeted agents used in combination with ...€¦ · targeted cytostatic agents to inhibit repopulation, and to determine the optimal scheduling of chemotherapy

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).

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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

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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.

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15

20

25

30

35

0 20 40 60 80 100 120 140

Distance to nearest blood vessel (μm)

Mea

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i67)

UntreatedDay 3 PaclitaxelDay 5 Paclitaxel

B.

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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.

0

10

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30

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50

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70

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Control Day 3 Day 5

% F

unct

iona

l Blo

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esse

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C.

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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.

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A.

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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

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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.

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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.

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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.

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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.

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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

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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

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30

40

50

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Control Paclitaxel Gefitinib Sequential Concurrent

% g

ated

pop

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G1SG2

B.

0

5

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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

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8

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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

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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

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i67)

UntreatedDay 3 SequentialDay 5 Sequential

B.

0

5

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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

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0 20 40 60 80 100 120 140

Distance to nearest blood vessel (μm)

Mea

n In

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aspa

se-3

)UntreatedDay 3 SequentialDay 5 Sequential

B.

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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.

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% F

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ControlDay 3Day 5

B.

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400

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800

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1200

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Control Paclitaxel Gefitinib Sequential Concurrent

Blo

od V

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ls /

tum

our a

rea Control

Day 3Day 5

C.

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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

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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.

3.7 REFERENCES

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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.

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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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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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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.

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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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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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2. Davis AJ, Tannock IF. Repopulation of tumour cells between cycles of chemotherapy: a neglected factor. Lancet Oncol 2000;1:86-93

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.

5. Trédan O, Galmarini CM, Patel K, Tannock IF. Drug resistance and the solid tumor microenvironment. Journal of the National Cancer Institute 2007; 99: 1441-54

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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