THE ROLE OF FIBROBLAST GROWTH FACTOR-9 IN MALIGNANT MESOTHELIOMA · 1.4 Fibroblast Growth Factors...

THE ROLE OF FIBROBLAST GROWTH FACTOR-9 IN MALIGNANT MESOTHELIOMA

This thesis is presented for the degree of Doctor of Philosophy

from The University of Western Australia

Ai Ling Tan BSc. (Hons)

The University of Western Australia School of Medicine and Pharmacology

2012

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ABSTRACT

Background: Malignant mesothelioma (MM) is a cancer with no cure and its global

incidence continues to rise. Identifying the key molecules governing the pathogenesis

of MM is urgently needed. Such molecules can potentially provide better understanding

of the disease pathology, unveil therapeutic targets and may have diagnostic or

prognostic relevance.

Fibroblast growth factor-9 (FGF-9) was the leading candidate gene in a pilot global

gene profiling study of our laboratory using prospectively-collected human

thoracoscopic biopsies. The finding was validated in a second cohort. FGF-9

expression was 17- and 35-fold higher in MM over controls (metastatic pleural

carcinomas and benign pleuritis) in those studies. This thesis followed on the data to

explore the biological significance of FGF-9 in MM.

Hypothesis: I hypothesize that

• FGF-9 plays a vital role in MM development including proliferation and invasion;

• Antagonising FGF-9 activity retards MM growth;

• FGF-9 can aid diagnosis of MM;

• Mutations in the FGF-9 and/or its receptors cause aberrant FGF-9 signalling in

MM.

Results: I demonstrated the presence of FGF-9 protein in all 10 human and murine

MM cell lines tested. Using tissue-array of human fluid cells and pleural tissues, FGF-9

immunostaining was significantly stronger in MM (n=121) and metastatic

adenocarcinoma (n=29) over benign controls (n=35), chi-square 82.8, df=2, p<0.001.

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FGF-9 levels in pleural fluids were measured in two (Oxford and Perth) cohorts of 283

and 639 patients respectively. The median FGF-9 levels in MM were significantly

higher by 7.2- and 12.5-fold over metastatic carcinomas as well as 4.6- and 11.3-fold

over benign pleural fluids in the two cohorts respectively (p<0.05 MM vs other groups

in both populations). Pleural fluid FGF-9 can differentiate MM from metastatic cancers

(area under curve, AUC 0.8303) and from all non-MM fluids (benign and metastatic

cancers combined, AUC 0.8228). The AUC for combined use of FGF-9 and mesothelin

were 0.8848 (MM vs metastatic cancer) and 0.9002 (MM vs non-MM fluids). It was also

found that in 22 out of 25 samples that had detectable FGF-9 levels in the MM pleural

fluids, the median FGF-9 levels were 6-fold higher in pleural fluids compared to plasma

samples highly suggesting the pleural origin of FGF-9.

FGF-9 induces dose- and time-dependent proliferation of all six human and murine MM

cell lines tested. This proliferation could be inhibited by JNK and p38 inhibitors. ERK

inhibition reduced murine MM cell proliferation only. FGF-9 only induces a dose- and

time-dependent release of IL-8 (or MIP-2), VEGF and MCP-1 from all ten human and

murine MM cell lines tested. Treatment with p38, JNK and ERK inhibitors antagonised

the cytokine release by varying degree. FGF-9 also induces MM cell invasion/migration

using two separate methods (Matrigel assay and scratch assay) in vitro.

FGF-9 shRNA knockdown MM cells were used to assess the necessity of FGF-9 in MM

growth using validated murine models. MM growth was significantly retarded in Balb/c

mice inoculated with FGF-9 shRNA cells compared to the parent cells and control MM

cells transfected with scrambled vectors in both the subcutaneous tumour model

(p<0.001) and if tumours were injected intraperitoneally (p<0.05 in tumour nodules).

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Gene sequencing was performed on 50 human MM samples to examine for mutations

in the exons of FGF-9 and its two receptors, FGFR2 and FGFR3. No significant and

consistent mutations were found.

Summary: FGF-9 over-expression was confirmed at both RNA and protein levels in

human pleural tissue and fluids in five different cohorts. FGF-9 induces MM cell

proliferation, invasion and release of key cytokines known to promote MM

development. Knockdown of FGF-9 significantly retards MM growth in various animal

models. The role and potential application of FGF-9 as a therapeutic target and clinical

aid for diagnosis/prognosis for MM should be explored.

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CONTENTS

CHAPTER 1 1

1.0 GENERAL INTRODUCTION 2

1.1 The Structure of Mesothelium 2

1.2 The Functions of Mesothelium 3 1.2.1 Non-adhesive Surface and Protective Barrier 3 1.2.2 Transport of Fluids and Particulates 4 1.2.3 Inflammation 4 1.2.4 Tumour Cell Adhesion, Proliferation and Growth 5 1.2.5 Leukocyte Migration 5 1.2.6 Tissue Repair 6

1.3 Malignant Mesothelioma 9 1.3.1 Causes 9 1.3.2 Pathogenesis 10 1.3.3 Epidemiology 12 1.3.4 Histological Subtypes 12 1.3.5 Clinical Features 13 1.3.6 Diagnosis 13 1.3.7 Prognosis 19 1.3.8 Current Therapies 20 1.3.9 Animal Models 22

1.4 Fibroblast Growth Factors 23 1.4.1 Nomenclature of Fibroblast Growth Factors 23

1.5 Fibroblast Growth Factor-9 26 1.5.1 Fibroblast Growth Factor-9 Gene 27 1.5.2 Fibroblast Growth Factor-9 mRNA 29 1.5.3 Fibroblast Growth Factor-9 Protein Structure 30 1.5.4 Secretion of Fibroblast Growth Factor-9 33 1.5.5 Physical Interactions between Fibroblast Growth Factor-9 and Heparin 33 1.5.6 Biological Function of Fibroblast Growth Factor-9 34 1.5.7 Expression Modulation of Fibroblast Growth Factor-9 37 1.5.8 Mutations on Fibroblast Growth Factor-9 38 1.5.9 Fibroblast Growth Factor-9 in Cancer 39

1.6 Fibroblast Growth Factor Receptors 41 1.6.1 The Structure of Fibroblast Growth Factor Receptor 41 1.6.2 The Receptors for Fibroblast Growth Factor-9 45 1.6.3 Fibroblast Growth Factor-9 Signalling Pathway 45 1.6.4 Mutations of the Receptors for Fibroblast Growth Factor-9 50

1.7 Therapeutic Approaches 55

1.8 Summary 55

1.9 Preliminary Results 56

1.10 Hypothesis and Aims 59

CHAPTER 2 61

2.0 MATERIALS AND METHODS 62

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2.1 Maintenance of Malignant Mesothelioma Cell Lines 62 2.1.1 Cell Culture 62 2.1.2 Malignant Mesothelioma Cell Lines 62 2.1.3 Cryo-Freezing and Storage of Cells 63

2.2 Phenotypic Characterisation of Cells and Tissues 64 2.2.1 Immunofluorescence 64 2.2.2 Immunohistochemistry 65 2.2.3 Tissue Microarray Analysis 66

2.3 Western Immunoblotting 66 2.3.1 Protein Extraction 66 2.3.2 Determination of Protein Concentration 67 2.3.3 SDS-PAGE and Immunoblotting 67

2.4 Functional Assays 68 2.4.1 Cell Proliferation WST-1 Assay 68 2.4.2 Trypan Blue Cell Exclusion Assay 69 2.4.3 Matrigel – Invasion Assay 69 2.4.4 Scratch Assay 70 2.4.5 Cytokine and Chemokine Measurements 70

2.5 Molecular Characterisation of Cells 71 2.5.1 RNA Isolation 71 2.5.2 Determination of RNA Concentration 71 2.5.3 Reverse Transcription and cDNA Synthesis 71 2.5.4 Real-time Polymerase Chain Reaction 72

2.6 Sample Processing and Storage 72

2.7 Mutational Sequencing of Cells and Tissues 73 2.7.1 DNA Isolation 73 2.7.2 Determination of DNA Concentration 74 2.7.3 Polymerase Chain Reaction 74 2.7.4 Agarose Gel Electrophoresis 80 2.7.5 Unpurified PD+ Capillary Sequencing 80 2.7.6 DNA Sequencing Analysis 80

2.8 Molecular Knockdown In Vitro 80 2.8.1 Short Hairpin RNA Knockdown 80

2.9 In Vivo Inoculation of Short Hairpin Knockdown Cells 82 2.9.1 Heterotopic Model 82 2.9.2 Orthotopic Model 82 2.9.3 Athymic Model 83

2.10 Statistical analysis 83

CHAPTER 3 84

3.0 THE EXPRESSION OF FIBROBLAST GROWTH FACTOR-9 IN MALIGNANT MESOTHELIOMA 85

3.1 Introduction 85

3.2 Results 85 3.2.1 The Detection of FGF-9 in MM Samples 85 3.2.2 The Expression of FGF-9 in MM Cells and Tissues 94 3.2.3 The Expression of FGF-9 in Pleural Fluids 96

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3.3 Discussion 108

CHAPTER 4 112

4.0 THE BIOLOGICAL ROLE OF FIBROBLAST GROWTH FACTOR-9 IN MALIGNANT MESOTHELIOMA 113

4.1 Introduction 113

4.2 Results 113 4.2.1 MM Cells Proliferation In Vitro in Response to FGF-9 Stimulation 113 4.2.2 Cytokines and Chemokines Release in Response to FGF-9 Stimulation 120 4.2.3 The Effects of Antibody Neutralisation on Cytokine Release 129 4.2.4 The Effects of Pathway Inhibitors on FGF-9-Stimulated MM Cells 132 4.2.5 The Role of FGF-9 in MM Cell Invasion 138 4.2.6 The Involvement of FGF-9 in MM Cell Migration 139

4.3 Discussion 142

CHAPTER 5 147

5.0 THE NECESSITY OF FGF-9 IN MALIGNANT MESOTHELIOMA TUMOUR GROWTH IN VIVO 148


5.2 Results 148 5.2.1 Development of FGF-9 shRNA Knockdown Cells 148 5.2.2 FGF-9 shRNA Knockdown Cells in Heterotopic Model 151 5.2.3 FGF-9 shRNA Knockdown Cells in Orthotropic Model 154 5.2.4 FGF-9 shRNA Knockdown Cells in Athymic Model 157

5.3 Discussion 159

CHAPTER 6 163

6.0 MUTATIONS OF FGF-9 AND ITS RECEPTORS IN MALIGNANT MESOTHELIOMA PATHOBIOLOGY 164


6.2 Results 164 6.2.1 Mutations in FGF-9 164 6.2.2 Expression of FGF-9 Receptors in MM Cells 171 6.2.3 Mutations in FGFR2 and FGFR3 in MM Cell Lines and Tumour Biopsies 174

6.3 Discussion 184

CHAPTER 7 187

7.0 SUMMARY 188

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LIST OF FIGURES

1.1 The functions of mesothelial cells

1.2 The alignment of amino acid sequence of FGF-9 and other members of the FGF-9

family

1.3 A ribbon diagram of FGF-9

1.4 The fibroblast growth factor receptor structure

1.5 Signalling through fibroblast growth factor receptors

1.6 Mechanisms of pathogenic cancer cell FGF signalling

1.7 Global gene profiling on 22 human pleural tissue samples

1.8 Quantification of FGF-9 gene expression from global gene profiling

1.9 Validation of microarray gene expression results using RT-PCR

3.1 Optimisation of murine FGF-9 ELISA

3.2 The presence of FGF-9 in murine MM cells detected using ELISA

3.3 Expression and distribution of FGF-9 in the human JU77 and murine AB2 MM cell

lines

3.4 Expression and distribution of FGF-9 in the MM human tissue biopsy and murine

MM tumour

3.5 Expression of FGF-9 in cells and tissues on tissue microarray

3.6 The stability of FGF-9 in pleural fluids following freeze-thaw

3.7 Pleural fluids FGF-9 levels in the Oxford and Perth cohorts

3.8 FGF-9 levels in different MM histology

3.9 FGF-9 levels in matched pleural fluid and plasma of patients diagnosed with MM

3.10 The correlation between FGF-9 and mesothelin

3.11 The area under the ROC for FGF-9 and mesothelin to differentiate MM from non-

MM

4.1 Optimisation of cell density for MM cell proliferation

4.2 Dose-dependent MM cell proliferation

4.3 Dose-dependent MM cell proliferation using Trypan Blue

4.4 Time-dependent MM cell proliferation

4.5 IL-8 and MIP-2 release from human and murine MM cells

4.6 MCP-1 release from human and murine MM cells

4.7 VEGF release from human and murine MM cells

4.8 Time-dependent cytokine release from human and murine MM cells

4.9 Optimisation of neutralisation antibody concentration

4.10 Inhibition of cytokine release from murine MM cells using antibody neutralisation

4.11 FGF-9 mediated MM cell proliferation is inhibited by ERK, JNK and p38 pathway

inhibitors

4.12 Inhibition of cytokine release from human and murine MM cells

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4.13 Phosphorylation of proteins downstream of FGF-9 signalling pathway

4.14 FGF-9 stimulates MM cell invasion

4.15 FGF-9 stimulates MM cell migration

5.1 FGF-9 shRNA knockdown cells have lower levels of FGF-9 protein

5.2 FGF-9 shRNA knockdown cells have lower levels of FGF-9 mRNA

5.3 Knockdown of FGF-9 in MM cells significantly retards their tumour growth in

heterotopic model

5.4 shRNA knockdown of FGF-9 significantly reduced MM tumour growth in

intraperitoneal model of disease

5.5 shRNA knockdown of FGF-9 had similar MM tumour growth in athymic model of

disease

6.1 Agarose gel showing the band intensities for different conditions for a PCR reaction

6.2 Sequence alignment for FGF-9 exon 1

6.3 Sequence alignment and amino acid translation for FGF-9 exon 3

6.4 Expression and distribution of FGFR2 in the human NO36 and murine AB1 MM cell

lines

6.5 Expression and distribution of FGFR3 in the human NO36 and murine AB2 MM cell

lines

6.6 Amino acid substitution occurring in exon 6 of FGFR2

6.7 Amino acid substitution occurring in exon 11 of FGFR2

6.8 Amino acid substitution occurring in exon 6 of FGFR2 in tumour biopsy

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LIST OF TABLES

1.1 Structure and phylogeny of FGF-9 ligands

2.1 Primary antibodies

2.2 Secondary and tertiary antibodies

2.3 Primers for real-time PCR

2.4 Primers used for PCR for the mutational sequencing analysis in human samples

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ACKNOWLEDGEMENT

Conducting this PhD project and writing up this thesis would be totally

impossible if it is not for my supervisor, Winthrop Professor YC Gary Lee. I would like

to express my heartfelt thanks and appreciation to him for his invaluable guidance,

inspiration, help, support and advice provided throughout the entire years.

I also owe my deepest gratitude to Professor Jeanette Creaney for her technical

advice in the mutational sequencing studies and support in grant writing as well as

supplying pleural fluid samples, the tissue microarray slides and the tumour samples

required for my research work.

I would also like to thank the post-doctoral scientists, Dr Sally Lansley and Dr

Julius Varano for providing me with refreshing insights on this project and Dr Bahareh

Badrian, Dr Scott Fisher and Dr Connie Jackaman for their technical help. I would also

like to thank Prof Nick de Klerk for his help in statistical analysis and Dr Amanda Segal

for her advice in immunohistochemistry.

I am also greatly indebted to my colleagues from the Lung Institute of Western

Australia and Tumor Immunology group, for their encouragement and support. Special

thanks goes out to Miss Hui Min Cheah and Dr Rabab Rashwan for the friendship and

moral support given, Miss Justine Leon and Miss Sarah Wong for assisting with the

pleural fluid samples collection and Miss Samantha Woo for teaching me in vivo

techniques.

Last but not least, my heartfelt thanks to my family and my husband, Chin Fei

Low, for their continuous words of encouragement and unwavering love and for

believing in me that I can achieve a PhD.

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Financial support

I would like to acknowledge the financial support of the following organisations:

• The University of Western Australia for the Scholarship for International

Research Fees, University International Stipend

• The Lung Institute of Western Australia for the LIWA PhD Top-Up

Scholarship

Candidate’s contribution in the research work

I hereby declare that this submission is my own work and that, to the best of my

knowledge, it contains no material that to any substantial extent, has been accepted for

the award of a degree or a diploma from any university. I also declare that the

intellectual content of this thesis was the product of my own work. These studies were

performed at Lung Institute of Western Australia, University of Western Australia.

I would like to acknowledge the collaboration and assistance received during the

course of this project. In Chapter 3, the scoring of the tissue microarray was performed

blindly by Professor Jenette Creaney, National Centre for Asbestos Related Disease,

Perth, Australia. The FGF-9 levels quantitated in the pleural fluids from the Oxford

cohort were performed by our collaborators in the Oxford Pleural Unit, Oxford, UK. The

Matrigel cell invasion assay in Chapter 4 was assessed by our collaborator, Dr

Mulugeta Worku, University College London, UK. Development of FGF-9 transfected

clones in Chapter 5 was performed by our collaborators, Sophia Karabela and

Professor George Stathopoulos, University of Patras, Greece. The inoculation of

transfected cells into animal models was performed blindly by our group colleague, Dr

Sally Lansley and the number of tumour nodules in the intraperitoneal model was

counted blindly by Dr Sally Lansley and Dr Julius Varano, Pleural Disease Unit, Lung

Institute of Western Australia, Perth, Australia.

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PUBLICATIONS ARISING FROM THIS THESIS

Abstracts Published in Scientific Journals

1. A. L. Tan, M. Worku, H. E. Davies, E. Mishra, R. Sadler, J. Creaney, S. M

Lansley, J. Varano, S. Karabela, G. Stathopoulous, R. J. O. Davies, Y. C. G.

Lee. Fibroblast Growth Factor-9 is Up-regulated in Malignant Mesothelioma and

May Be Involved in the Disease Pathobiology. Am J Respir Crit Care Med 185;

2012: A6354



Lee. Fibroblast Growth Factor-9 is Upregulated and May Be Involved in

Mesothelioma Disease Pathobiology. Respirology 17 (S1); 2012: TO-097


Lansley, R. J. O. Davies, Y. C. G. Lee. The Potential Biological Role of

Fibroblast Growth Factor-9 in Malignant Mesothelioma. Journal of Thoracic

Oncology 6; 2011:P2.043


Lansley, R. J. O. Davies, Y. C. G. Lee. Fibroblast Growth Factor-9 and Its

Potential Biological Role in Malignant Mesothelioma. Am J Respir Crit Care

Med 183; 2011: A2361

5. A. L. Tan, M. Worku, H. E. Davies, E. Mishra, R. Sadler, S. M Lansley, R. J. O.

Davies, Y. C. G. Lee. The Potential Biological Role of Fibroblast Growth Factor-

9 in Malignant Mesothelioma. Respirology 16 (S1); 2011: TO-034


Lansley, R. J. O. Davies, Y. C. G. Lee. Malignant Pleural Mesothelioma:

Potential Biological Role of Fibroblast Growth Factor (FGF) -9. Am J Respir Crit

Care Med 181; 2010: A4347

7. A. L. Tan, M. Worku, H. E. Davies, E. Mishra, R. Sadler, S. M Lansley, R. J. O.

Davies, Y. C. G. Lee. Fibroblast Growth Factor (FGF) -9 is Upregulated in

Malignant Mesothelioma. Respirology 15 (S1); 2010: TP124

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Publication Peripheral to this Thesis

1. Varano Della Vergiliana JF, Lansley S, Tan AL, Creaney J, Lee YC, Stewart

GA. Mesothelial cells activate the plasma kallikrein-kinin system during pleural

inflammation. Biol Chem 392 (7); 2011:633-42

Publications in Preparation



Lee. Fibroblast Growth Factor-9 is Up-regulated in Malignant Mesothelioma and

Is Involved in the Disease Pathobiology.

2. A. L. Tan, J. Creaney, Y. C. G. Lee. The Fibroblast Growth Factor-9 and Its

Receptors: No Significant Mutations Detected in Patients with Malignant

Mesothelioma

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AWARDS AND SCHOLARSHIPS

2012

• UWA Graduate Research School Travel Funding, University of Western Australia

- to support my travel to the American Thoracic Society meeting in the USA 2012

• LIWA Travel Grant, Lung Institute of Western Australia

- to top-up the amount to support my travel to the TSANZ Annual Scientific Meeting

2012 in Canberra

• TSANZ Travel Award, The Thoracic Society of Australia & New Zealand

- to support my travel to the TSANZ Annual Scientific Meeting 2012 in Canberra

2011

• PhD project featured in Australian Society for Medical Research Media Release 2011

• School of Medicine and Pharmacology Research Symposium Oral Presentation Award,

School of Medicine and Pharmacology, University of Western Australia

- for the best oral presentation during the School of Medicine and Pharmacology

Research Symposium

• Telethon Institute for Child Health Research Award, Telethon Institute for Child Health

- for the best oral presentation in Australian Society for Medical Research Symposium

• The Thoracic Society of Australia & New Zealand Ann Woolcock Young Investigator

Award Finalist, The Thoracic Society of Australia & New Zealand

• Slater and Gordon International Travel Grant, Slater and Gordon

- to support my travel to the American Thoracic Society meeting in the USA in 2012


- to top-up the amount to support my travel to the 14th World Conference on Lung

Cancer 2011 in The Netherlands

• LIWA PhD Top-Up Scholarship (2011-2014), Lung Institute of Western Australia

- to support my postgraduate studies at the University of Western Australia

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2010

• UWA Convocation Postgraduate Research Travel Award, Graduate Research School

of The University of Western Australia

- to support my travel to the 14th World Conference on Lung Cancer 2011 in The

Netherlands

• The Thoracic Society of Australia & New Zealand WA meeting Young Investigator

Award Finalist

• TSANZ Travel Award, The Thoracic Society of Australia & New Zealand

- to support my travel to the TSANZ Annual Scientific Meeting 2010 in Brisbane


- to top-up the amount to support my travel to the TSANZ Annual Scientific Meeting

2010 in Brisbane

• Scholarship for International Research Fees (SIRF), Safety-Net Top-Up Scholarship

and University International Stipend (UIS) (2010-2013), University of Western Australia

- to support my postgraduate studies at the University of Western Australia

xvi

LIST OF ABBREVIATIONS

Chemicals and reagents

BSA Bovine serum albumin

DAPI 4’,6-Diamidino-2-phenylindole

DMEM Dulbecco’s modified eagle medium

DMSO Dimethyl sulfoxide

DTT Dithiothreitol

ECL Enhanced chemi-luminescenece

EDTA Ethylenediaminetetraacetic acid

ELISA Enzyme linked immunosorbent assay

FBS Fetal bovine serum

FITC Fluorescein isothiocyanate

HRP Horseradish peroxidase

PBS Phosphate buffered saline

PVDF Polyvinylidene difluoride

SDS Sodium dodecylsulphate

SDS-PAGE Sodium dodecylsulphate polyacrylamide gel electrophoresis

TBS Tris buffered saline

Tw Tween

WST-1 Water soluble tetrazolium – 1 salts

Units and measurements

°C Degree celcius

µg Microgram

µL Microlitre

bp Base pairs

Da Daltons

g Gram

kDa Kilodalton

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L Litre

mg Miligram

mins Minutes

mL Mililitre

MW Molecular weight

ng Nanogram

nM Nanomolar

r.p.m. Revolutions per minute

Others

ARE Adenylate/uridylate-rich element

CO2 Carbon dioxide

ddH2O Double distilled water

DNA Deoxyribonucleic acid

ECM Extracellular matrix

EGF Epidermal growth factor

EGFR Epidermal growth factor receptor

EMA Epithelial membrane antigen

EPP Extrapleural pneumonectomy

ERK Extracellular-signal regulated kinase

FGF Fibroblast growth factor

FGF-9 Fibroblast growth factor -9

FGFR Fibroblast growth factor receptor

FGFR-1 Fibroblast growth factor receptor -1




GAPDH Glyceraldehyde 3-phosphate dehydrogenase

H2O Water

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H2O2 Hydrogen peroxide

HER2 Human epithelial growth factor receptor 2

HSPG Heparan sulfate proteoglycan

ICAM-1 Intercellular adhesion molecule

IFN-γ Interferon gamma

Ig Immunoglobulin

IgG Immunoglobulin G

IL Interleukin

JNK c-Jun N-terminal kinase

MAPK Mitogen activated protein kinase

MCP-1 Monocyte chemotactic protein -1

MIP-2 Macrophage inflammatory protein-2

MKP3 Mitogen activated protein kinase phosphatase 3

MM Malignant mesothelioma

MMP Metalloproteinase

MPF Megakaryocyte potentiating factor

mRNA Messenger ribonucleic acid

NO Nitric oxide

PCR Polymerase chain reaction

P/D Pleurectomy/decortication

PDGF Platelet derived growth factor

PI3K Phosphatidyllinositol-3 kinase

ROC Receiver operating curve

RT-PCR Reverse transcriptase polymerase chain reaction

SFM Serum free media

SMRP Soluble mesothelin-related peptide

SNT-1/FRS2 Fibroblast growth factor receptor substrate 2

TGF-β Transforming growth factor beta

TIMP Tyrosine inhibitor of metalloproteinase

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TKI Tyrosine kinase inhibitor

TNF-α Tumour necrosis factor alpha

Tyr Tyrosine

UCC Urothelial cell carcinoma

VCAM-1 Vascular cellular adhesion molecule

VEGF Vascular endothelial growth factor

VEGFR Vascular endothelial growth factor receptor

WT Wild type

WT-1 Wilms’ tumour antigen 1

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GENERAL INTRODUCTION

CHAPTER 1

2

1.0 GENERAL INTRODUCTION

1.1 The Structure of Mesothelium

The mesothelium is an extensive monolayer of predominantly elongated, flattened,

squamous-like mesothelial cells. The mesothelium lines three serosal cavities; the

pleural, peritoneal and pericardial cavities, as well as the internal organs within

these cavities. Mesothelial cells can also be found in the lining that surrounds the

testes. With a few exceptions, this monolayer of cells is mostly always found at the

same anatomical site and is conserved between different species (Minot, 1890,

Whitaker et al., 1982, Odor, 1954).

Mesothelial cells are supported by connective tissue stroma on a thin basement

membrane. The diameter of a cell is approximately 25 µM and its cytoplasm is

elevated over a central round or oval nucleus (Mutsaers, 2004). Mesothelial cells

contain organelles such as vesicles and vacuoles, microtubules and

microfilaments, a few mitochondria, a poorly developed Golgi apparatus and a few

rough endoplasmic reticulum (Mutsaers, 2004). Microvilli are found on the luminal

surface of the mesothelial cells and they trap glycoproteins rich in hyaluronic acid

to reduce the friction and provide a slippery surface between two adjacent organs

(Andrews, 1973, Wang, 1974). There are also cell-to-cell junctions such as tight

junctions, adherens junctions, gap junctions and desmosomes in between the cells

which are vital for cell surface polarity and semi-permeable diffusion (Mutsaers,

2004).

Mesothelial cells are fragile and shedding of mesothelial cells is common in

humans. As a result, mesothelial cells can be found in pleural fluids (Peng et al.,

1994). These shed-cells are round or oval and are rich in organelles. They are

3

capable of transforming themselves into macrophages-like cells which can

phagocytose (Efrati and Nir, 1976) and so, they may have an immunological role

(Bakalos, 1974).

1.2 The Functions of Mesothelium

In the early years, as mesothelial cells secrete surfactant and lubricating

glycoproteins, it was thought that this monolayer could provide a protective barrier

as well as a slippery surface for frictionless movement of organs and tissues within

the cavity. However, in recent years, the role of the mesothelium has been

extended to the transportation of fluids and particulates, regulation of leukocyte

migration in response to inflammation and tissue repair (Figure 1.1).

1.2.1 Non-adhesive Surface and Protective Barrier

An ultrastructural analysis revealed that mesothelial cells produce and secrete a

lubricant-like substance, similar to the type II pneumocytes, which decreases the

friction and allows free movement of opposing organs (Dobbie J.W., 1988).

In addition to that, mesothelial cells secrete glycosaminoglycans, primarily

hyaluronan, on both the surface and within the pinocytic vesicles (Roth, 1973).

There is an association between the increased concentration of hyaluronan and

the existence of cuboidal mesothelial cells in pleural effusions (Wang and Lai-

Fook, 1998, Satoh K, 1987). In vitro studies have shown that mesothelial cells

synthesize hyaluronan to form “coats” (Castor C.W., 1969, Honda et al., 1986,

Ohashi Y., 1988, Breborowicz A., 1998, Yung et al., 2000, Heldin and Pertoft,

1993). The hyaluronan coats are up-regulated following injury (Yung et al., 2000,

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Baumann M.H., 1996), possibly to serve as a protective barrier against viral

infections and the cytotoxic effects of lymphocytes (Heldin and Pertoft, 1993).

1.2.2 Transport of Fluids and Particulates

Furthermore, mesothelial cells are involved in the transport and movement of fluids

and particulates across the serosal cavities. The presence of many microvilli on

the luminal surface of the mesothelial cell increases the surface area of the cell to

boost absorption (Odor, 1954). Moreover, the microvilli are covered with glycocalyx

which contains glycosaminoglycans that bind to fluids, further aiding adsorption

(Wang, 1974).

It has been shown that the transport of fluids through the mesothelium occurs via

intracellular junctions and stomata (Leak and Rahil, 1978, Whitaker et al., 1982)

while on the other hand, particulates and solutes are actively transported across

the mesothelium layer by pinocytic vesicles (Fedorko and Hirsch, 1971, Leak and

Rahil, 1978, Fukuta, 1963).

1.2.3 Inflammation

The mesothelium plays an active role in inflammation. In the presence of bacterial

endotoxins and cytokines (Antony et al., 1993), asbestos (Boylan et al., 1992) or

instilled agents (Antony et al., 1995), mesothelial cells secrete various pro- and

anti-inflammatory and immunomodulatory mediators such as prostaglandins,

chemokines, cytokines, nitric oxide, reactive oxygen and nitrogen species and

growth factors (Mutsaers, 2002). The secreted mediators help to restore the

normal serosal architecture and function.

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For instance, mesothelial cells produce nitric oxide (NO) and reactive nitrogen (NO.

radical) and oxygen (O2-. radical, hydrogen peroxide (H2O2) and OH. radical)

species in vitro in response to asbestos, cytokines and bacterial products (Chen et

al., 2000, Owens and Grisham, 1993, Tracey et al., 1995, Choe et al., 1998).

1.2.4 Tumour Cell Adhesion, Proliferation and Growth

The mesothelium layer can also act as a site for tumour adhesions following injury

or trauma to the mesothelium (Cunliffe and Sugarbaker, 1989). This can be

prevented when the tumour cells adhere to the hyaluronic acid coat secreted by

the mesothelial cells (Jones et al., 1995). During surgical resection, the removal of

hyaluronan and other glycosaminoglycans can cause the tumour cells to attach

and re-seed onto the serosal surface again (Hofer et al., 1998, Van Den Tol et al.,

1998). On the contrary, other studies have shown that adhesion of the tumour cells

to the hyaluronan coat of mesothelial cells can contribute to the metastasis of

ovarian and colorectal cancers. This is because the tumour cells adhering to the

hyaluronic acid on the mesothelium are capable of migrating through the

mesothelium to invade the organs at distal sites (Catterall et al., 1997, Catterall et

al., 1999, Cannistra, 1994).

1.2.5 Leukocyte Migration

Furthermore, mesothelial cells are involved in leukocyte migration. The influx of

leukocytes from the vascular compartment to the serosal cavity contributes to

inflammation (Light, 1990, Brauner A., 1993). Leukocyte migration to the site of

inflammation occurs when (Topley N., 1996):

1. There is a site of activation

6

2. The resident cells are activated to generate signals that initiate a response

3. There is a chemotactic gradient to direct the migration of leukocytes to the site

of inflammation

4. Adhesion molecules such as the intercellular adhesion molecule (ICAM-1),

vascular cellular adhesion molecule (VCAM-1), E-cadherin, N-cadherin are up-

regulated to allow the leukocyte transverse the mesothelial cell monolayer into

the serosal cavity (Zeillemaker et al., 1996, Pelin et al., 1994, Jonjić N., 1992,

Liberek, 1996, Cannistra, 1994).

1.2.6 Tissue Repair

Like epithelial cells, mesothelial cells are capable of secreting a variety of growth

factors and extracellular matrix (ECM) molecules that play a role in inflammation

and tissue repair. The secreted growth factors, such as transforming growth factor

beta (TGF-β), platelet-derived growth factor (PDGF), fibroblast growth factors

(FGFs) and vascular endothelial growth factor (VEGF) stimulate cell migration to

the wound site and promote cell proliferation while the repair cells migrate over

ECM molecules that are already exposed at the wound site to cover the injury and

allow the wound to heal (Mutsaers et al., 1997, Martin et al., 1992).

Mesothelial cells secrete metalloproteinases (MMP) and tissue inhibitors of

metalloproteinases (TIMP) to regulate ECM turnover so that the wounded tissue

can regenerate and re-establish its normal function (Marshall et al., 1993, Rougier

et al., 1997, Ma et al., 1999).

7

Figure 1.1: The functions of mesothelial cells.

The figure above summarises the functions of mesothelial cells. Mesothelial cells can act as a protective barrier, facilitate leukocyte

migration in response to inflammation, regulate particulate and fluid transport, produce surfactant that allows smooth movement

between internal organs, secrete inflammatory mediators, cytokines and growth factors to participate in inflammation and may be

involved in the prevention of tumour adhesion (Mutsaers, 2004).

9

1.3 Malignant Mesothelioma

Mesothelial cells can undergo neoplastic transformation and become malignant

mesothelioma (MM). The transformation effects are detrimental as the median

survival for this aggressive tumour is approximately 9 – 12 months (Bograd et al.,

2011). MM is highly resistant to conventional therapies such as chemotherapy,

surgical resection and thoracic radiation alone or in combination.

1.3.1 Causes

The neoplastic transformation of normal, healthy mesothelial cells to MM is

predominantly caused by the exposure to asbestos dust fibres (Yarborough, 2006),

with the duration and quantity of exposure and the type of asbestos fibres inhaled,

as the key determining factors for the development of this malignancy.

Asbestos is widely used as an insulating material due to its fire-resistant

properties. The fibres can be classified into two main subtypes; i) the amphiboles

which contain long and thin fibres and includes crocidolite (blue asbestos) and

amosite (brown asbestos) and ii) serpentine fibres which are curly and includes the

chrysotile or white asbestos (Churg, 1994, Luus, 2007). Approximately 95% of

asbestos globally mined were the latter form (Kamp and Weitzman, 1999).

Epidemiology evidence have suggested that amphiboles are much more potent

than the serpentine fibres in causing MM, with the ratio of quantitative risks being

1:100:500 for chrysotile, amosite and crocidolite (Hodgson and Darnton, 2000).

The reason being is that the half-life of the thin-walled sheets in the chrysotile

fibres is 0.3 – 11 days while the double-chained chemistry of amphibole fibres

have a half-life from 500 days to infinity (Bernstein and Hoskins, 2006). As a result,

10

the chrysotile fibres can be cleared from the lungs much more rapidly than the

amphiboles fibres, hence eliciting a lower carcinogenic potential (Rudd, 2010).

1.3.2 Pathogenesis

As MM has a long latency period of up to several decades between the time of

asbestos exposure and the development of the tumour, it was postulated that there

is a somatic genetic event occurring in the normal, healthy mesothelial cells to

transform them to MM cells (Zervos et al., 2008).

There are many processes by which the asbestos fibres can affect the pleura. The

shape of the fibres, in particular, the ratio of the length to the width of the fibres,

can influence how deep the asbestos fibres penetrate into the lung (Robinson and

Lake, 2005) to irritate and damage the pleura and induce MM (Sebastien P.,

1980). Besides, the asbestos fibres can damage the mitotic spindle in the

mesothelial cells, thereby disrupting the mitotic events, resulting in DNA damage

and hence causing cancer (Ault et al., 1995). DNA damage can also occur due to

the reaction with iron-related reactive oxygen species generated from the asbestos

fibres (Kamp et al., 1995). In addition, the asbestos fibres can activate the

mitogen-activated protein kinase (MAPK) and the extracellular signal-regulated

kinases (ERK) 1 and 2 downstream signalling pathways, leading to the expression

of proto-oncogenes that give rise to Fos-Jun and activator protein 1 families

(Zanella et al., 1996), causing MM.

The metastatic events of MM can be due to the response of MM cells to varying

growth factors such as TGF-β (Fitzpatrick D.R., 1994, Marzo A.L., 1997), PDGF-A

and -B (Versnel M.A., 1991, Garlepp Mj, 1993) and epidermal growth factor (EGF)

11

(Dazzi H., 1990). As mesothelial cells produce these growth factors to stimulate

tissue repair, the over-expression of these growth factors by mesothelial cells can

lead to aberrant autocrine signalling that promotes increased and uncontrolled cell

proliferation. Studies have shown that MM cells produce angiogenic factors such

as VEGF (Masood et al., 2003) and FGF-2 (Kumar-Singh et al., 1999) for the

formation of new blood vessels (Hanahan D., 2000) as a continuous supply of

nutrients is required for tumour growth. There is a correlation between increased

vascularity in MM biopsies with a poor prognosis (Edwards et al., 2003, Kumar-

Singh et al., 1999) and in vivo studies have shown that antagonising VEGF activity

(Merritt et al., 2004) and disrupting the FGF-2 signalling using alpha-Tocopheryl

succinate can impede MM growth (Neuzil et al., 2007).

Besides that, ninety percent of MMs express telomerase. Telomerase is an

enzyme which allows the cells to avoid telomere shortening and hence continue

cell division leading to uncontrolled cell proliferation (Dhaene et al., 2000).

In addition, the uncontrolled cell division in MM could also be a result of the

resistance of the cells to apoptosis due to the absence of tumour suppressor

genes that are involved in the p53 pathway that is implicated in MM. Under normal

circumstances, the presence of ligands activating death receptors or the absence

of growth factors leading to the activation of caspase death signalling pathway

(Riedl and Shi, 2004), causes cells to undergo apoptosis. However, in MM, there is

a possibility that the anti-apoptotic molecule, Bcl-xL, is elevated, causing cells to

evade apoptosis and continue proliferating.

12

1.3.3 Epidemiology

Between the 1940s and 1979, an estimated 27 million individuals were exposed to

asbestos fibres in the United States and Europe where asbestos was used in the

shipbuilding and construction industries. However, the association between MM

and asbestos was not described until 1960 when Wagner et al. first noticed this

disease in the South African miners (Wagner et al., 1960). In the 1970s, workplace

regulations were implemented in the United States to limit the exposure to

asbestos. However, because of the long latency period between asbestos

exposure and the development of MM (Carbone et al., 2002), the incidence rate of

MM in men who were exposed to asbestos dramatically increased only in the last

30 years of the 20th century, with 2000 cases diagnosed in 2000 in the United

States alone (Price and Ware, 2004). The incidence in women remained the same

at approximately 500 cases each year (Price and Ware, 2004). Unfortunately, the

workplace regulations were only implemented in the United Kingdom a decade

later. As a result, the incidence of MM continues to rise and is not expected to

peak until 2015 (Hodgson et al., 2005). As there is no strict regulations to ban the

use of asbestos in most developing countries, the incidence rate of MM and

asbestos-related disease will continue to increase dramatically (Joshi and Gupta,

2004, Le et al., 2011).

1.3.4 Histological Subtypes

There are three main histological subtypes of MM; the epitheloid subtype accounts

for over 60% of MM tumours, the sarcomatoid subtype, about 10% and the rest are

the biphasic (mixed) (Suzuki, 2001). The histology of the epitheloid subtype is very

similar to the other lung carcinomas, making the diagnosis and distinction between

the two challenging (Klebe et al., 2008, Rudd, 2010). This subtype is the least

aggressive of the cell types and hence offers the best prognosis. Under the

13

microscope, the epitheloid cell type displays several patterns, including

tubulopapillary and glandular structure (Rudd, 2010). Each individual cell is usually

cube-shaped and has an easily identifiable nucleus (Inai, 2008).

In contrast, sarcomatoid MM has the worst prognosis. Microscopic analysis

normally shows a spindle cell or storiform structure with elongated nuclei (Inai,

2008). The biphasic subtype has both epitheloid and sarcomatoid components in

the same tumour. The prognosis for the biphasic MM is intermediate between

those of the epitheloid and sarcomatoid MM (Inai, 2008).

1.3.5 Clinical Features

Patients diagnosed with MM usually present with pleural effusions, associated with

breathlessness and persistent, aching, dull and non-pleuritic chest pain (Lee et al.,

2000, Antman, 1981, Elmes and Simpson, 1976, Oels et al., 1971, Antman, 1980).

Other commonly associated symptoms include cough, hemoptysis and weight

loss. By the time these patients present with symptoms, the disease is usually

extensive within the serosal cavity.

1.3.6 Diagnosis

It is often hard to diagnose patients with MM both from a clinical and pathological

perspective because the symptoms they present with are usually non-specific.

Patients typically have to undergo several medical tests including repeated

cytological examinations, serial chest X-rays or computed tomography (CT) scans

and often no definitive diagnosis could be established despite these investigations.

It is not unusual that a definite diagnosis can only be established after a

considerable delay. Nevertheless, findings of a unilateral pleural effusion or

14

thickening together with a history of asbestos exposure should alert the clinician to

the possibility of MM but the definitive diagnosis cannot be made without a

pathological diagnosis.

The International Mesothelioma Interest Group (IMIG) reported that to diagnose

MM, a confirmatory evidence of pleural tissue analysis by immunohistochemistry is

necessary in patients with a cytologic diagnosis suspicious of MM. The evidence

must also be supported by both clinical and radiological data (Husain et al., 2009).

On the contrary, the British Thoracic Society (2007) guidelines accept a cytological

diagnosis if the clinical, radiological and cytological reports support the diagnosis

for MM. A biopsy is needed only if the diagnosis is not clear after tests on pleural

effusions and CT scans are conducted (British Thoracic Society Standards of Care

Committee, 2001).

There is a consensus noting that the observation of neoplastic invasion of

mesothelial cells can be used to differentiate between the benign and malignant

mesothelial proliferation (Kao et al., 2011a). For a pathological diagnosis, fine

needle aspirations have its own limitations and thoracoscopic biopsies including

adjacent and underlying adipose tissue are sometimes needed (Attanoos and

Gibbs, 2008, Kao et al., 2011b). Immunohistochemistry is then conducted on the

sample to test for the expression of cell surface markers to distinguish the

epithelial form of MM from the reactive mesothelial proliferations. It can also be

used to test the cells in pleural effusions (Whitaker, 2000). Markers such as

calretinin and Wilms' tumour 1 antigen (WT1) are used to confirm that the tissue

obtained is of mesothelial origin. A positive expression of epithelial membrane

antigen (EMA; also known as CA15-3 and mucin-1) in a thick peripheral

distribution suggests the malignancy of the tissue (Wolanski et al., 1998, Saad et

15

al., 2005) while a positive staining for cytokeratin can help distinguish MM from

sarcoma and melanoma. Besides that, the tissue should also be stained with two

markers with negative diagnostic value (anti-Ber-EP4, a membrane marker; anti-

thyroid transcription factor-1, a nuclear marker; or monoclonal anti-

carcinoembryonic antigen, anti-B72-3, anti-MOC-31, anti-oestrogen/progesterone,

anti-EMA, cytoplasmic staining) to validate the diagnosis (Scherpereel et al.,

2010). In addition to immunohistochemistry, electron microscopy can differentiate

MM from adenocarcinoma or to distinguish desmoplastic or sarcomatoid MM from

fibrous pleuritis (Segal A, 2002).

There are considerable debates on the role of screening for early diagnosis of MM.

On one hand, the prognosis of MM is very poor and the disease may be treated

more effectively if diagnosed earlier. On the other hand, as there is no cure for

MM, it can be argued that early detection would make no difference to outcome.

Any screening test must prove to have good sensitivity, specificity and positive

predictive values. In addition, the screening test should also be non-invasive or

minimally invasive and the benefits of screening to the patients outweigh the risks

of the screening test (Scherpereel et al., 2010). Biomarkers are useful screening

tools that can screen at-risk populations, establish earlier diagnosis as well as

monitor the treatment outcomes in MM (Ray and Kindler, 2009). Only a small

proportion of those exposed to asbestos will develop MM (Carbone et al., 2012). A

recent study conducted by Testa et al. uncovered mutations occurring in the gene

encoding for BRCA1 associated protein-1 (BAP1) that may predispose asbestos-

exposed individuals to MM (Testa et al., 2011). Germline mutations were found

occurring in the gene encoding for BAP-1 in cases of high incidence of MM. In

addition, somatic mutations were found in familial MM, suggesting that perhaps

16

individuals who are at high risk of developing MM can be screened for mutations

occurring in BAP-1 gene to allow early intervention.

There is currently a challenge to find a biomarker for MM as there is no single

biomarker that can accurately discern MM from the other malignancies with great

sensitivity and specificity. The expression levels of a panel of biomarkers which

include mesothelin, megakaryocyte potentiating factor (MPF) and osteopontin, has

been tested in pleural effusions, serum and urine with variable levels of success.

Mesothelin or soluble mesothelin-related peptide (SMRP) is a glycoprotein that

plays a role in cell adhesion. SMRP is expressed at high concentrations in patients

with MM, lung, ovarian and pancreatic cancers (Ray and Kindler, 2009, Creaney et

al., 2010). At the time of diagnosis, more than 60 percent of MM patients have

elevated levels of SMRP. In a cross-sectional study, the serum SMRP levels were

raised in 84 percent of MM patients but only in less than 2 percent of lung cancer

patients (Robinson et al., 2003). Moreover, the pleural effusions SMRP levels were

increased in MM patients compared to benign and other non-MM groups (Pass et

al., 2008, Creaney et al., 2007). A high SMRP level is correlated with a poor

prognosis (Wheatley-Price et al., 2010) and the levels increase with the

progression of MM and decrease with its regression or following the resection of

the tumour, proving that it can be used as a disease monitoring tool. It may have a

role as a screening tool as some previously healthy persons who had been

exposed to asbestos and have elevated levels of SMRP, were reported to develop

MM within one to six years after their initial blood tests (Robinson et al., 2003,

Creaney et al., 2010, Ray and Kindler, 2009). A high false-positive rate was

reported in a prospective-screening study of over 500 asbestos-exposed subjects

(Park et al., 2008), although the study was short-termed and no subjects actually

17

developed MM. In addition, SMRP levels are sensitive in detecting the epitheloid

but not the sarcomatoid subtypes (Campbell and Kindler, 2011).

MPF is a soluble protein produced by proteolytic cleavage of the mesothelin

precursor protein (Onda et al., 2006). Serum MPF levels were elevated in 51 of 56

patients with MM but the basal levels were maintained in 70 healthy control

subjects. Postsurgical MPF correlated well with the degree of surgical debulking,

suggesting that MPF could be used to monitor treatment effect (Onda et al., 2006).

In addition, a study conducted on 507 patients consisting of healthy control

subjects (n = 101), healthy asbestos-exposed subjects (n = 89), patients with

benign asbestos-related disease (n = 123), benign respiratory disease individuals

(n = 46), lung cancer (n = 63) and MM (n = 85), showed that the receiver operator

curve (ROC) for serum MPF (0.85) was similar to that of serum mesothelin (0.87)

in distinguishing patients with MM from non-MM (Hollevoet et al., 2010).

Osteopontin is also glycoprotein that mediates cell-matrix interactions, that is

expressed by certain cancers, including lung, breast, colorectal, gastric and

ovarian cancers. Unlike mesothelin or SMRP, osteopontin is also increased in both

epitheloid and sarcomatoid subtypes of MM. This glycoprotein is also involved in

the cell signalling cascades that are associated with asbestos-induced

carcinogenesis. Hence, it can distinguish MM patients from patients with asbestos-

related diseases that were not malignant (Pass et al., 2005). Unfortunately,

changes in osteopontin did not appear to parallel disease response to SMRP

(Wheatley-Price et al., 2010).

18

In a direct diagnostic comparison of the above three biomarkers based on a

specificity of 95%, the sensitivity for detecting MM was 73% for SMRP, 45% for

MPF and 47% for osteopontin. Unfortunately, combining the three biomarkers did

not improve the sensitivity (Creaney et al., 2008).

The interpretation of the results using a panel of markers still remains very

subjective (Hammar, 2006, Husain et al., 2009). Mesothelin levels are low in the

non-epitheloid MM and a recent meta-analysis study found that despite having a

good specificity, the poor sensitivity of mesothelin suggests a limited value as a

screening marker for the early diagnosis for MM (Hollevoet et al., 2012). In

addition, there is a high false positive for the use of osteopontin as a screening

marker (Grigoriu et al., 2007). As a result, it is prudent that a reliable assay is

developed or a novel biomarker that can discriminate MM from benign and non-

MM cancers is discovered to achieve an accurate and rapid diagnosis.

At the time of writing, a new study was also conducted to assess the sensitivity

and specificity of fibulin-3 as a biomarker for MM (Pass et al., 2012). It was found

that plasma fibulin-3 was significantly higher in patients with MM compared to

patients without MM but exposed to asbestos. In addition, the fibulin-3 levels in

pleural fluids from patients with MM were also significantly higher than in pleural

fluids from non-MM patients. The study concluded that plasma fibulin-3 can be

used to differentiate asymptomatic asbestos-exposed patients from patients with

MM. Both the pleural fluid and plasma fibulin-3 levels can also distinguish MM from

non-MM and benign fluids (Pass et al., 2012).

19

1.3.7 Prognosis

MM is an aggressive tumour (Scott B., 2000) which often leads to significant

symptoms and has a very poor prognosis of up to 9 – 12 months (Bograd et al.,

2011). The prognosis is worse in those who have a poor performance status, have

a sarcomatoid histology, are in the advance stage of the disease, are males, have

elevated white cell counts, anaemia, thrombocytosis, or high standardised uptake

value ratios on PET (Pass et al., 2005, O’byrne et al., 2004, Herndon et al., 1998).

The expression of cyclooxygenase-2 and VEGF and hence increased vascularity,

as well as hypermethylation of the P16INK4a gene and evidence of SV40 virus, a

cofactor in MM pathology, in the tumour had also been linked to a worse prognosis

(Pass et al., 2005, O’byrne et al., 2004, Herndon et al., 1998).

Grigoriu et al. showed that MM patients who recorded a high mesothelin level

(>3.5 nmol/L) only had a median survival of 7 months while those who had lower

levels of mesothelin had 19 months to live (Grigoriu et al., 2007). Similarly, patients

with high serum osteopontin levels had a significantly shorter prognosis with a

median of 5 months compared to those who had a lower level of osteopontin that

had a median survival of 15 months (Cappia et al., 2008, Grigoriu et al., 2007).

Recently, there have been a growing number of studies looking at the use of

VEGF as a prognostic factor for MM (Hirayama et al., 2011, Demirag et al., 2005,

Strizzi et al., 2001). It has been reported that MM patients had higher levels of

VEGF in pleural effusions when compared to patients diagnosed with non-

malignant pleuritis (Strizzi et al., 2001) or lung cancer (Hirayama et al., 2011).

There was a significant inverse correlation between VEGF and patient survival

(Demirag et al., 2005, Strizzi et al., 2001) and a positive correlation between VEGF

levels and tumour stage (Hirayama et al., 2011, Demirag et al., 2005).

20

1.3.8 Current Therapies

There is currently no cure for MM. Attempts of complete resection of the tumour

through surgery, either extrapleural pneumonectomy (EPP) or

pleurectomy/decortication (P/D) is ineffective as residual microscopic tumours

cannot be completely removed. In addition, surgical resection is often not

advisable for patients in their advanced age, have a medical comorbidity, a

sarcomatoid histology or are in an advanced stage of the disease. In a

Mesothelioma and Radical Surgery (MARS) feasibility study conducted to assess

the clinical outcomes of patients who were randomly assigned to EPP or no EPP, it

was found that the median survival and quality of life scores were considerably

lower in the EPP group compared to the no EPP group (Treasure et al., 2011). Out

of the 112 patients registered, 50 were randomly assigned to both the groups, with

24 to EPP and 26 to no EPP group. After taking into account the factors for not

proceeding to randomisation, it was found that the median survival for the EPP

group (n = 16) was 14.4 months (5.3 – 18.7) and 19.5 months (13.4 to time not yet

reached) for the no EPP group (n = 26). A lower median quality of life scores was

recorded in the EPP group compared to the no EPP group, although no significant

differences between the groups were reported. In fact, there were ten serious

adverse events reported in the EPP group and only two reported in the no EPP

group (Treasure et al., 2011). Despite that, controversies still exist on the road on

EPP (Weder W et al., 2011, Weder W and Opitz I, 2012).

Hence, an approach using chemotherapy drugs remains the mainstay of

treatment. In a phase III trial of pemetrexed in combination with cisplatin (n = 226)

versus cisplatin alone (n = 222) in MM patients, those who received pemetrexed

and cisplatin had a median survival time of 12.1 months compared to 9.3 months

in the cisplatin group (Vogelzang et al., 2003). The response rate in the drug

21

combination group was 41.3% versus 16.7% in the control group (Vogelzang et al.,

2003). Vitamin supplementation in the drug combination group reduced the

toxicities of the drug and did not adversely affect the survival time (Vogelzang et

al., 2003).

However, pemetrexed does not provide a cure and only <50% of patients respond.

Also, not all MM patients are fit to receive chemotherapy drugs. As a result, there

are currently novel molecular targets being studied as a therapy for MM. For

instance, VEGF and its receptors, VEGF receptors 1 – 3, are found to be over-

expressed in MM patients (Demirag et al., 2005). This growth factor promotes MM

cell proliferation in vitro in a dose-dependent manner and the mitogenic effects can

be antagonised by anti-VEGF antibodies (Strizzi et al., 2001). MM patients have

recorded the highest levels of VEGF compared to patients with any other solid

tumours and the levels correlate inversely with their survival (Linder et al., 1998,

Kumar-Singh et al., 1999, Strizzi et al., 2001, Demirag et al., 2005). As a result,

sorafenib, an inhibitor of the tyrosine kinases on VEGFR-2 and PDGFR-b (platelet-

derived growth factor receptor), has been developed. However, the phase II trials

conducted only reported a modest improvement in survival duration of patients

compared to the chemotherapy-naïve patients (Janne et al., 2007, Dubey et al.,

2010).

A double-blinded, placebo-controlled randomised Phase II study reported that the

anti-VEGF monoclonal antibody, bevacizumab, compared to gemcitabine and

cisplastin only slightly improved the progression-free survival to 6.9 months in the

drug group compared to 6.0 months in the placebo group, with the difference not

statistically significant (Ray and Kindler, 2009, Kindler et al., 2012). The median

survival times were 15.6 versus 14.7 months for bevacizumab and placebo

22

respectively but it was not statistically significant either (Ray and Kindler, 2009,

Kindler et al., 2012). An on-going trial by the French Intergroup aims to test the

effects of pemetrexed-cisplatin with bevacizumab in a randomized phase III trial

(Zalcman G. et al., 2012). Other multiple single-arm phase II trials using other

VEGF inhibitors such as SU416, thalidomide, vatalinib (Kindler, 2008), sunitinib

(Nowak et al., 2010) and cediranib (Garland et al., 2009) show modest single-

agent activity.

Although antibody-based therapies targeting molecules found to be over-

expressed in tumours have shown benefits in other types of cancers, no such

benefits of these therapies have been shown in MM in randomised studies to date.

Therefore, there is a prudent need to identify novel therapeutic targets critical for

growth and propagation in MM.

1.3.9 Animal Models

Animal models, in particular rats and mice, have been well established to assess

the carcinogenicity of the various asbestos fibres as well as the pathogenesis of

MM (Davis et al., 1992, Kane, 2006). Genetically engineered mice develop MM

when exposed to asbestos fibres (Kane, 2006). The tumours developed closely

resemble the MM tumours in human in their biological behaviour, histopathology

and molecular alterations, including the latency of the disease, the superficial

growth of tumour on the serosal surface, shedding of tumour cells and growth as

spheroids as well as the accumulation of serosanguinous ascites (Fleury-Feith et

al., 2003, Altomare et al., 2005, Craighead and Kane, 1994). In addition, murine

mesothelial cells respond to asbestos exposure in a very similar way as to the

human mesothelial cells (Davis et al., 1992). As a result, the murine models can be

used to investigate immunotherapy, gene therapy and combined modality

23

treatments. For instance, xenografts of human MM can be used to test

chemotherapeutic agents whereby the experimental data could be translated to the

patients quite easily.

1.4 Fibroblast Growth Factors

Fibroblast growth factors (FGFs) are heparin-binding polypeptides, involved in

various metabolic processes such as cell proliferation, migration, tissue repair, cell

differentiation and morphogenesis (Antoine et al., 2007, Maggie et al., 2009, Ornitz

and Itoh, 2001). There have also been numerous in vivo studies pointing out the

role of FGFs in early embryonic development in mammals (Martin, 1998,

Yamaguchi and Rossant, 1995, Heikinheimo et al., 1994, Lewandoski et al., 2000,

Moon and Capecchi, 2000, Sekine et al., 1999).

1.4.1 Nomenclature of Fibroblast Growth Factors

FGF-1 and FGF-2 that were the first two members identified in the FGF family,

were isolated from bovine pituitary extracts and brain tissue in the 1970s and

found to elicit mitogenic effects (Armelin, 1973, Gospodarowicz, 1974). There are

currently 23 related polypeptides identified in the family, all consisting of similar

structure; having 28 highly conserved and 6 identical amino acid residues (Ornitz,

2000). They also share 13 – 71% of sequence homology. Their molecular weights

range from 17 to 34 kDa (Ornitz et al., 1996). Out of the 23 homologous

polypeptides, FGF-11 to FGF-14 are incapable of activating the FGF signalling

pathway. Instead, they interact with the intracellular domains of voltage-gated

sodium channels (Goldfarb, 2005). Hence, they are called the fibroblast

homologous factors and are classified as the intracellular fibroblast growth factor

subfamily. This leaves 19 members in the FGF family which can be further divided

24

into two subfamilies: the hormone-like and the canonical subfamilies. The

members in the hormone-like subfamily are FGF-15 (or FGF-19 which is the

human orthologue in mouse), FGF-21 and FGF-23. They have a lower affinity to

heparin and act as endocrine factors to regulate metabolism. The members in the

canonical subfamily can be further divided into five groups whose members share

synteny, greater homology and similar binding specificities to receptor. The five

groups are the FGF-1 group (FGF-1 and FGF-2), FGF-4 group (FGF-4 to FGF-6),

FGF-7 group (FGF-3, FGF-7, FGF-10 and FGF-22), FGF-8 group (FGF-8, FGF-17

and FGF-18) and FGF-9 group (FGF-9, FGF-16 and FGF-20) (Itoh and Ornitz,

2008) (Table 1.1).

All of the FGFs are differentially expressed in many, if not all, tissues but the

patterns and timing of expression vary. Each subfamily of FGFs has a similar

pattern of expression and each member of the subfamily has unique sites of

expression. For example, FGF-3, FGF-4, FGF-8, FGF-15, FGF-17 and FGF-19 are

expressed exclusively during embryonic development where as FGF-1, FGF-2,

FGF-5 – 7, FGFs-9 – 14, FGF-16, FGF-18 and FGFs-20 – 23 are found in the

embryonic and adult tissues (Ornitz and Itoh, 2001).

25

Table 1.1: Structure and phylogeny of FGF ligands (Guillemot and Zimmer,

2011).

The 23 human and mouse FGF ligands can be subdivided in canonical,

intracellular and hormone-like FGFs subfamilies (Itoh and Ornitz, 2008). All FGFs

consist of a heparan sulphate proteoglycan binding domain and most have an N-

terminal signal peptide and are secreted via a classical secretory pathway. The

three members of the FGF-9 subfamily (FGF-9, FGF-16 and FGF-20) are

efficiently secreted but have uncleavable signal sequences (Itoh and Ornitz, 2008).

Scheme Family Members

FGF-3 FGF-4

FGF-4

FGF-6 FGF-1 FGF-2

FGF-5

FGF-5 FGF-8

FGF-17

FGF-8

FGF-18 FGF-9 FGF-16

FGF-9

FGF-20 FGF-7 FGF-10

Canonical FGFs

FGF-10

FGF-22 FGF-15/FGF-19

FGF-21 Hormone-like

FGFs FGF-15/FGF-19

FGF-23 FGF-11 FGF-12

FGF-13

Intracellular FGFs

FGF-11

FGF-14

Signal protein

Heparan sulphate proteoglycan binding domain

26

1.5 Fibroblast Growth Factor-9

Our understanding on most aspects of the biology of FGF-9 is limited. FGF-9 was

first identified as a secreted factor in human glioma cells, NMC-G1 (Miyamoto et

al., 1993, Naruo et al., 1993). This growth factor which can be found in abundance

in the rat central nervous system was originally recognised as a mitogen for

primary rat glial cells (Naruo et al., 1993). As a result, it was called the glial

activating factor. Soon after, it was discovered that the glial activating factor share

a sequence homology with the rest of the other FGFs in the family and it was then

termed FGF-9 (Miyamoto et al., 1993).

The earlier studies showed that FGF-9 acts in an autocrine and/or paracrine

fashion to elicit its neuroprotective effect in the central nervous system (Tagashira

et al., 1995). Since then, there is a growing number of studies on FGF-9

expressions in other organs, such as in the normal uterine endometrium (Tsai et

al., 2002) and in the prostate (Giri et al., 1999) where it also acts in the same

manner to elicit its effects as a potent mitogen.

Although FGF-9 has no proliferative effect on the medulloblastoma cell lines

(Duplan et al., 2002) and on human umbilical vein endothelial cells (Naruo et al.,

1993), it is a potent mitogen on many other cells. Hence, abnormal FGF-9

expression and its dysregulated activity is associated with various human

diseases, including brain tumours, prostate cancer, lung adenocarcinomas and

endometriosis (Todo et al., 1998, Wing et al., 2003, Chien-Kai et al., 2009, Giri et

al., 1999). A study conducted by Sumie et al. reported that the over-expression of

this gene in mouse embryonic fibroblast 3T3 cells and in nude mice caused

cellular transformation and tumour formation respectively (Sumie et al., 1997).

27

1.5.1 Fibroblast Growth Factor-9 Gene

The gene encoding human FGF-9 is located on chromosome 11q11-13 (Mattei et

al., 1995) whereas its position on the mouse DNA is on chromosome 14 (Mattei et

al., 1997). The FGF-9 gene has three exons and two large introns (Colvin et al.,

1999). FGF-9 has only a 30% sequence identity with all the other members of the

family (Hecht et al., 1995) (Figure 1.2). There is, however, a greater than 93%

sequence identity between the FGF-9 found in mice, rats and humans, indicating

that this gene is likely to be important for vital biological functions (Miyamoto et al.,

1993).

Figure 1.2: The alignment of amino acid sequence of FGF-9 and other

members of the FGF-9 family (Miyamoto et al., 1993).

The amino acid sequences of the human FGF family, including FGF-9, are aligned

and the well-conserved amino acid regions are shaded in grey. The figure shows

that FGF-9 is very different from the other FGF members in the family.

28

1.5.1.1 Polymorphisms on the Fibroblast Growth Factor-9 Gene

Studies have reported a single nucleotide variant existing on the FGF-9 gene. A

human gonadal dysgenesis study conducted on 21 XY females, 72 XX females

and XY males showed a microsatellite polymorphism event occurring on the 3’

untranslated region of the human FGF-9 gene, which plays a role in regulating

FGF-9 promoter activity and hence modulating the gene expression in human

embryonic kidney and neuroblastoma cells (Chen et al., 2007). The polymorphism

gave rise to four alleles, (TG)13-16, whereby the consequences were cell-type

specific at both the pre- and post-transcriptional levels. One of the alleles was the

(TG)14 allele that was associated with the risk for 46 XY male-to-female sex

reversal, suggesting that any genetic variation in the FGF-9 expression might have

an impact on sex development (Chen et al., 2007).

In addition, a recent report by Harada et al. described a polymorphism event

occurring on the FGF-9 gene in the Eks mutant mice (FGF-9Eks), whereby an

asparagine on position 142 on the chromosome 14 in the mouse DNA, is

substituted with threonine (Harada et al., 2009). Consequently, the FGF-9Eks is

unable to form dimers. Since FGF-9 homodimers have a higher affinity to heparin

as compared to the monomers, FGF-9Eks were unable to bind to heparin, which

has a pivotal role in facilitating the transport of FGF-9 through the extracellular

matrix to the other distant FGFRs (Ornitz and Itoh, 2001, Ornitz, 2000,

Flaumenhaft et al., 1990). Accordingly, the mitogenic effect for FGF-9Eks is

decreased compared to the wild type FGF-9 (Harada et al., 2009). While the wild

type FGF-9 gene activates the ‘b’ and ‘c’ isoforms of FGFR3, the FGF-9Eks protein

activates only the ‘c’ splice variant of FGFR3 which is expressed in the

cartilaginous condensations. As a result of this aberrant signalling, the joint and

suture development is repressed in these mutants and this gave rise to a new

29

gain-of-function phenotype similar to the elbow and knee joint synostosis (Harada

et al., 2009).

1.5.2 Fibroblast Growth Factor-9 mRNA

The stability of FGF-9 mRNA is crucial to understand its implications in diseases. It

was shown that the adenylate/uridylate-rich elements (AREs), located on the FGF-

9 3’-untranslated region, influence the stability of the FGF-9 mRNA. Hence, the

expression level of FGF-9 can be controlled through the rapid degradation of FGF-

9 mRNA (Chen et al., 2010, Xu et al., 1997, Wilson and Treisman, 1988). The

AREs are found in gene transcripts that need to be precisely controlled, such as in

genes that function as growth factors, proto-oncogenes and cytokines where they

play a crucial role in regulating post-transcription of the gene (Chen and Shyu,

1995, Wu et al., 2007, Chen et al., 1995). It was found that the p42 isoform of AU-

rich element binding protein 1 (AUF1) acts as a negative regulator for FGF-9

expression post-transcriptionally by binding to the AREs of FGF-9 and

destabilising the mRNA. Consequently, FGF-9 protein synthesis is impaired.

Subsequently, failure to control this process could result in a prolonged half-life of

FGF-9 mRNA which leads to the sustained expression levels of FGF-9 that can

contribute to disease progression (Chen et al., 2010).

Studies have shown that FGF-9 mRNA can be up-regulated when stimulated by a

variety of factors, such as prostaglandin E2 (Chuang et al., 2006), estrogen (Tsai et

al., 2002) and androgen (Giri et al., 1999), but the mRNA levels will rapidly return

to its basal levels. This implies that the FGF-9 expression is strictly controlled to

avoid excessive production of FGF-9.

30

In a study conducted on the rat retina, it was found that there were high levels of

FGF-9 mRNA at birth but the steady-state mRNA levels decreased thereafter

during periods where terminal differentiation occurs. However, once the terminal

differentiation process was completed, the FGF-9 mRNA levels increased to the

initial levels at birth and remained constant throughout adulthood (Cinaroglu,

2005). It was postulated that low levels of FGF-9 mRNA allowed cells to

differentiate and develop to their final phenotypic status whereas excess cells

underwent apoptosis. Once the differentiation was complete, FGF-9 no longer

functioned as a mitogen but a survival factor to cells (Cinaroglu, 2005).

1.5.3 Fibroblast Growth Factor-9 Protein Structure

The predicted molecular mass of FGF-9 protein, consisting of 208 amino acids, is

23, 532 Da (Santos-Ocampo et al., 1996). FGF-9 can undergo post-translational

modifications whereby the protein is glycosylated prior to secretion (Miyamoto et

al., 1993). Through Western blotting studies, Cinaroglu et al. showed that the

immunoreactive bands of FGF-9 in rat retinal tissue were at 30 and 55 kDa

(Cinaroglu, 2005). Some studies have also found three molecular species of this

protein at 30, 29 and 25 kDa, where it is cleaved at Leu-4, Val-13 and Ser-34

respectively. There are also smaller sized products as a result of proteolytic

digestion (Miyamoto et al., 1993).

The atomic model of FGF-9 consists of one FGF-9 molecule (residues 52-208),

two phosphate ions and 68 water molecules (Plotnikov et al., 2001). Unlike the

other FGF members in the family, FGF-9 forms dimers when in solution, with a Kd

of 680 nm (Plotnikov et al., 2001). The crystal structure of this protein revealed

three copies of four-stranded β-sheet, known as β-trefoil fold, which is similar to

the other FGFs. However, in contrast to FGF-1 and -2, the N- and C- terminals in

31

the FGF-9 regions outside this β-trefoil core are ordered to give a more regular

conformation of the protein (Plotnikov et al., 2001). It was discovered that the

interactions between the N- and C- terminals of each FGF-9 promoter drives the

formation of a dimer complex. There is a significant surface area (>2000A2) that is

buried inside the 2-fold dimer interface that obstructs the receptor binding site of

FGF-9. As a result, it was postulated that the sequences outside of the β-trefoil

core influences the auto-inhibitory mechanism for FGF-9 (Plotnikov et al., 2001)

(Figure 1.3).

32

Figure 1.3: A ribbon diagram of FGF-9 (Plotnikov et al., 2001).

The β strands of FGF9 are labelled according to the conventional strand nomenclature for FGF-1 and FGF-2. CT, C-terminal; NT, N-

terminal.

33

1.5.4 Secretion of Fibroblast Growth Factor-9

In general, most of the FGFs contain a signal sequence located in the amino-

terminal to facilitate its export from the cells. However, FGF-9 is very different from

the other FGF members in the family. Sequencing studies conducted on the FGF-9

protein structure revealed a mildly hydrophobic amino terminal that is atypical

characteristic of a signal peptide (Revest et al., 2000). The non-cleaved signal

sequence is located on the first 33 residues that exports the protein out for

secretion (Revest et al., 2000, Matsumoto-Yoshitomi et al., 1997).

Immunofluorescence studies conducted on FGF-9-transfected COS-1 cells by

Revest et al. illustrated a strong perinuclear staining but a weak reticular staining

over the cytoplasm for mouse FGF-9 (Revest et al., 2000). Further studies

conducted demonstrated that FGF-9 is associated with the Golgi complex and

enters the constitutive secretory pathway (Revest et al., 2000). An

immunohistochemistry study conducted on rat hepatic stellate cells revealed FGF-

9 staining in the intracellular as well as cell surface localisation of FGF-9 (Antoine

et al., 2007). Although FGF-9 is a secreted protein, there have been no studies

that have looked at the half-life of the protein. However, it is believed that the

endogenous heparan sulphate proteoglycan (HSPG) or exogenous heparin can

increase the stability and hence prolong the half-life of the molecule (Santos-

Ocampo et al., 1996).

1.5.5 Physical Interactions between Fibroblast Growth Factor-9 and Heparin

FGF-9 is a classical signalling molecule that is secreted in the extracellular space

where it has a high affinity to HSPGs and binds to it. As a result of this, the

diffusion radius of FGF-9 is limited and this sequesters the FGF-9 in the

extracellular matrix of the connective tissue. It can however be released from such

microenvironmental stores by proteolytic enzymes or by the action of a specific

34

FGF-binding protein (Heinzle et al., 2011). This is evident from a report depicting

that in the absence of exogenous heparin, FGF-9 was found to be present at the

cell surface of rat hepatic stellate cells and detected in the cell lysates but not in

the supernatants, suggesting that FGF-9 was binding to the HSPG located on the

cell surface (Antoine et al., 2007). However, in the presence of heparin, FGF-9 is

efficiently secreted into the supernatants but the immunoreactive bands for FGF-9

were not detected in the matched cell lysates (Antoine et al., 2007).

HSPG plays an important role in the interaction of FGF ligands to their receptors

(Moscatelli, 1987). It not only regulates the distribution of FGFs, but also enhances

the interaction and stability between the ligands and their receptors in the FGF-

FGFR complex, leading to the activation of the FGF receptors (Roghani et al.,

1994, Mansukhani, 1992). This is proven through evidence given by Rapraeger et

al. and Yayon et al. whereby they demonstrated the incapability of FGF-2 to

activate its receptor in the CHO or Swiss 3T3 cells that were genetically,

chemically or enzymatically engineered to lack the endogenous HSPG (Yayon et

al., 1991, Rapraeger et al., 1991).

1.5.6 Biological Function of Fibroblast Growth Factor-9

Although the full functions of FGF-9 have yet to be uncovered, studies to date

have shown that FGF-9 plays a major role in many biological aspects pertaining to

the growth of the cell such as angiogenesis, migration, cell proliferation and

survival.

35

1.5.6.1 Developmental

There are many studies examining the role of FGF-9 during embryonic

development, acting as crucial activating factors that stimulate growth and

migration.

FGF-9 is vital for fetal testicular development as mouse embryos that lack this

gene result in a male-to-female sex reversal (Colvin et al., 2001a). Besides that,

these mice develop a disproportionately shorten small intestine that is associated

with short bowel syndrome (Geske, 2008).

FGF-9 was also found to be involved in epithelial and mesenchymal cell signalling

in the embryonic lung development (Antoine et al., 2007). FGF-9 is expressed in

both the mesothelium and lung epithelium where it acts as a mitogen for sub-

mesothelial mesenchyme (White et al., 2006) and a regulator for FGF-10-mediated

branching morphogenesis during lung development (White et al., 2006). Once the

lung is developed, FGF-9 is no longer expressed in the epithelium but continue to

be expressed in the mesothelium (Colvin et al., 1999). A study on FGF-9 knockout

mice conducted by Colvin et al. described that the lungs was underdeveloped

which led to the death of the mice, further strengthening the role of FGF-9 in

embryonic lung development (Colvin et al., 2001b).

1.5.6.2 Survival

Besides playing a role in somatic cell development in the testis, FGF-9 also

functions as a survival factor for XY germ cell after 11.5 days post coitum in mice

(Dinapoli et al., 2006). FGF-9 also promoted the survival of rat motoneurons that

are located in the embryonic spinal cord (Garcès et al., 2000).

36

Furthermore, Kinkl et al. demonstrated that FGF-9 signalling promoted the survival

of adult pig retinal ganglion cells (Kinkl et al., 2003) and rat retina (Cinaroglu,

2005) which is important to treat retinal degenerative diseases such as glaucoma.

1.5.6.3 Wound Healing and Angiogenesis

FGF-9 also has a role in wound healing. In a study involving young mice, it was

found that FGF-9 mRNA levels were significantly up-regulated at day 2 after

wounding on skin (Komi-Kuramochi et al., 2005). It has not been studied as to how

FGF-9 promotes wound healing. It is believed that like FGFs-1, -2, -7 and -10,

FGF-9 is released from HSPGs in the extracellular matrix through the up-

regulation of FGF-binding protein or when the damaged cell is enzymatically

degraded by proteases (Braun et al., 2004, Podolsky, 1997). This may promote the

proliferation and migration of cells such as keratinocytes and epithelial cells to

close the wound (Abuharbeid et al., 2006). Besides that, FGF-9 is involved in

tissue repair. During acute liver insult, FGF-9 is over-expressed in human hepatic

stellate cells and acts on the primary hepatocytes to repair the injured liver in a

paracrine fashion (Antoine et al., 2007).

The role of FGF-9 in angiogenesis can be demonstrated in a recent study

conducted by Frontini and colleagues where they showed that FGF-9 acts as a

survival factor and mitogen to promote survival and proliferation as well as

migration of smooth muscle cells to nascent microvessels. This allows the new

microvessels to mature, making them long lasting and physiologically active in vivo

(Frontini et al., 2011). In addition, a study conducted by Behr et al. demonstrated

that FGF-9 treatment in FGF-9+/- mice promoted angiogenesis through VEGF-A

and successfully promoted osteogenesis for bone healing (Behr et al., 2010).

37

1.5.6.4 Immune Response

In addition to the above roles, FGF-9 has been shown to play a role in the immune

response in humans (Workalemahu et al., 2004). Workalemahu et al. showed in

their study that γδ T-lymphocytes that play a role in immune response on epithelial

cells to guard against foreign pathogens, had an up-regulated FGF-9 mRNA and

protein levels over their basal levels in response to a mycobacterial antigen

(Workalemahu et al., 2004).

1.5.7 Expression Modulation of Fibroblast Growth Factor-9

There are various in vitro studies conducted to modulate the expression levels of

FGF-9 in the biological system. For instance, it was found that FGF-9 mRNA

expression is up-regulated when endometrial stromal cells were treated with 17β-

estradial (Tsai et al., 2002). The effect was not seen when the cells were treated

with progesterone, giving further evidence of the mitogenic role of FGF-9 in

endometrium during the late proliferative phase (Tsai et al., 2002). FGF-9 mRNA

expression is also up-regulated in lung adenocarcinoma cells following

benzo[a]pyrene treatment, a carcinogen that is an agonist for aryl hydrocarbon

receptor found at high levels in lung adenocarcinoma (Chien-Kai et al., 2009).

On the other hand, it was observed that the FGF-9 mRNA and protein expression

was down-regulated in Parkinson’s disease, where elevated levels of MPP+, a

dopaminergic neurotoxin that can induce oxidative stress, were found. The down-

regulation of FGF-9 expression led to the death of the primary cortical neurons

(Jui-Yen et al., 2009). The effect of H2O2 treatment on the down-regulation of FGF-

9 mRNA expression was antagonised when melatonin, an antioxidant, was co-

administered with FGF-9 (Jui-Yen et al., 2009). It was proposed in that study that

38

oxidative stress could destabilise FGF-9 mRNA or repress the gene promoter

activity by lowering its affinity to transcription factors hence down-regulating its

expression.

The association between oxidative stress and FGF-9 may be organ-specific. What

was observed in the nervous system was not reproduced in the respiratory system.

In human lung adenocarcinoma cells, FGF-9 mRNA levels were increased when

aryl hydrocarbon receptors are activated. There is a positive correlation between

aryl hydrocarbon receptor and intracellular oxidative stress in lung

adenocarcinoma cells (Chien-Kai et al., 2009). However, when transfected BEAS-

2B bronchial epithelial cells over-expressing the receptor were treated with an

antioxidant, FGF-9 mRNA levels remained elevated (Chien-Kai et al., 2009).

Hence, it is proposed that FGF-9 expression in human lung cells is independent of

oxidative stress (Chien-Kai et al., 2009).

1.5.8 Mutations on Fibroblast Growth Factor-9

A recent study revealed six mutations occurring on the FGF-9 gene including one

frameshift, four missense and one nonsense mutation in 10 (six colorectal and four

endometrial) out of 203 tumours and cell lines (Abdel-Rahman et al., 2008). The

mutations were located at the distal part of exon 3, a “hotspot” area, in eight of the

10 samples, but were not detected in the matching normal tissues of the primary

tumours. This suggested that the mutations may be of somatic origins. The first

mutation (c.563delT) was a deletion of one nucleotide from a (T6) repeat tract in

exon 3 that causes a frameshift which creates a premature stop codon that deletes

the last four amino acids (p.L188fxX18 or FGF9∆205-208). The second mutation,

c.424G>T, was a nonsense mutation truncating the distal 67 amino acids (p.E142X

or FGF9∆142-208) whereas the third mutation was a missense mutation (p.R173K)

39

present in the KM12 colon cancer cell line. The last three missense mutations

(p.G84E, p.V192M and p.D203G) were, on the other hand, identified in

endometrial carcinomas. All of these six mutations can cause the following:

1) The FGF9V192M, FGF9D203G and worse, the FGF9∆205-208 mutations negatively

impact ligand-receptor interactions, leading to the decreased activation of the

downstream signalling pathway to phosphorylate MAPKs

2) The FGF9G84E and FGF9∆142-208 mutations interfere with protein folding

3) The FGF9R173K mutation impairs binding of FGF-9 to heparin or HSPG, a

necessary cofactor for FGF signalling

1.5.9 Fibroblast Growth Factor-9 in Cancer

As FGF-9 is a potent mitogen for human glial cells, the uncontrolled activity of

FGF-9 could elicit detrimental effects to the human brain. Using

immunohistochemistry, a moderate to strong immunoreactivity of FGF-9 was

observed in 40 of 49 (82%) cases of human brain tumours examined (Todo et al.,

1998). In vitro studies demonstrated a time-dependent cell proliferation in U87 MG

cells following FGF-9 stimulation after Day 4, with the effects observed in three of

four human meningiomas studies (Todo et al., 1998).

FGF-9 was also found to be up-regulated in prostate cancer (Murphy et al., 2010,

Kwabi-Addo et al., 2004, Li et al., 2008). Positive FGF-9 expression in prostate

cancer cells was observed through immunohistochemistry in 24 of 56 primary

tumours derived from human organ-confined prostate cancer. FGF-9 is also

involved in bone metastasis in prostate cancer in 25 of 25 bone metastasis cases

studied (Li et al., 2008). Furthermore, there was a positive correlation between the

40

presence of FGF-9-positive cancer cells with post-operative recurrence in prostate

cancer. This is backed up by the in vitro evidence that FGF-9 stimulation on

LNCaP cells demonstrated significant cell proliferation as assayed by MTT assay

and cell invasion by Matrigel invasion assay (Teishima et al., 2012).

FGF-9 is also an important mediator of development and progression of ovarian

endometrioid adenocarcinomas (Hendrix et al., 2006). It was found through

microarray and RT-PCR studies that FGF-9 mRNA and protein were up-regulated

in 30 primary ovarian endometrioid adenocarcinomas that had a defected Wnt

pathway, as well as in two ovarian endometrioid adenocarcinomas-derived cell

lines. In vitro studies confirmed that FGF-9 promoted the invasion of epithelial and

endothelial cells as well as the neoplastic transformation of epithelial cells through

a focus formation assay (Hendrix et al., 2006).

In the lung context, it was demonstrated through immunohistochemistry that 86 of

the 146 non-small cell lung cancer samples expressed high levels of FGF-9 and it

was more prevalent in adenocarcinomas compared to squamous cell carcinomas

(odds ratio, 3.81; 95% confidence interval, 1.275-1.509) (Chien-Kai et al., 2009).

Another study reported that FGF-9 mRNA and protein were frequently co-

expressed with FGF-2, FGFR1IIIc and FGFR2IIIc in non-small cell lung cancer cell

lines, in particular, those that have not responded well to gefitinib, an EGFR-

specific tyrosine kinase inhibitor (Marek, 2009). FGF-9 could potently activate adult

lung epithelial cells and drive a progressive oncogenic process. Also, cytological

examination on the ascites fluids collected from mice induced to over-express

FGF-9 for 3 months, gave results that were consistent with metastatic

adenocarcinoma (Betsuyaku et al., 2011).

41

There are no studies investigating the role of FGF-9 in MM. Given the potent

carcinogenic potential exhibited by FGF-9 in other malignancies, it is important that

its role in MM be explored.

1.6 Fibroblast Growth Factor Receptors

The fibroblast growth factor receptors (FGFRs) belong to the receptor tyrosine

kinase subfamily. Alternative splicing of the transcribed receptor genes can occur

and give rise to a variety of receptor isoforms, such as soluble, secreted FGFRs,

FGFRs with truncated COOH-terminal domain and FGFRs with either two or three

Ig-like domains (Haugsten et al., 2010, Rose-John and Heinrich, 1994).

There are four members in the FGFR family, FGFR1 – 4, which share a 64 – 74%

amino acid identity in the extracellular domain and 72 – 85% sequence identity in

the kinase domain region (Jaye et al., 1992, Powers et al., 2000). The genes

encoding these FGFR monomers each contain approximately 20 exons.

RT-PCR experiments on adult rat retinal mRNA demonstrated amplification

products for FGFR1, 2, 3 and 4 at 297-, 247-, 214- and 156- bp respectively

where as western blotting studies revealed the presence of FGFR1 – 4 as multiple

forms between ~80 – 200 kDa (Cinaroglu, 2005, Kirschbaum et al., 2009, Yiangou

et al., 1997).

1.6.1 The Structure of Fibroblast Growth Factor Receptor

A typical FGFR consists of a cleavable signal peptide, an acidic box, intracellular

tyrosine kinase domain, a single transmembrane domain and an extracellular

42

portion containing three immunoglobulin (Ig)-like domains, IgI, IgII and IgIII

(Mckeehan et al., 1998) (Figure 1.4).

The IgI domain is absent in certain isoforms and is thought to be involved in

receptor auto-inhibition while the IgII domain contains a heparin-binding domain

and is hence necessary for ligand binding (Wiesmann et al., 2000).

An alternative splicing event can occur on the second half of the IgIII domain, in

exons 8 and 9 of the receptor, but this event only occurs specifically in FGFR1, 2

and 3, generating either the IIIa, IIIb or the IIIc isoform of the receptor with different

ligand-binding specificities and affinities (Chellaiah et al., 1994, Werner et al.,

1992, Johnson, 1991, Zhang et al., 2006, Ornitz et al., 1996).

The IIIa isoform is a secreted FGF-binding protein whereas the IIIb and IIIc splice

variants are membrane-bound receptors. Studies have suggested that the IIIb

isoform is expressed in cells of epithelial lineages while the IIIc variant is found in

the mesenchyme (Avivi et al., 1993, Yan et al., 1993, Orr-Urtreger et al., 1993). In

contrast, the ligands for the IIIb variant are expressed in the mesenchymal cells

while the IIIc ligands are found in the epithelial cells, generating a paracrine cross-

talk interaction between the mesenchyme and epithelium that is critical for normal

development and homeostasis. It was also reported that activation of the 'c' splice

variant of FGFR2 and FGFR3 elicits a more potent mitogenic effect compared to

the activation of the ‘b’ splice variant (Santos-Ocampo et al., 1996, Ornitz et al.,

1996).

43

On the contrary, the soluble FGFR contains an extracellular ligand-binding domain

of the native FGFR but does not have a tyrosine kinase domain. As a result,

ligands can still bind to the receptor but are unable to activate it, thus 'mopping up'

ligands to prevent them from binding and activating the native FGFRs (Celli et al.,

1998).

44

Figure 1.4: The fibroblast growth factor receptor structure (Mason, 2007).

This figure illustrates the 3- immunoglobulin (Ig) isoforms of the four FGFRs. The extracellular domain contains the three Ig loops (IgI,

IgII and IgIII). The acidic box (AB) is located between IgI and IgII. In some splice variants, the acidic box is absent. The alternatively

splice events occurring in the IgIII domain give rise to the ‘a’ (not shown), ‘b’ and ‘c’ isoforms in FGFRs 1 – 3. There is also a

transmembrane domain (TM) and an intracellular domain consisting of two tyrosine kinase enzyme domain (TKI and TKII). The FGF

ligand-binding site is located at the C-terminal part of IgII and the N-terminal portion of IgIII.

45

1.6.2 The Receptors for Fibroblast Growth Factor-9

An affinity-labelling study conducted by Hetch et al. showed that FGF-9 binds

efficiently and activates the IIIc but not the IIIb isoforms of FGFR2 and FGFR3 and

its binding affinity was largely dependent on the presence of heparin (Hecht et al.,

1995). FGF-9 does not bind to FGFR 1 and FGFR4 (Hecht et al., 1995).

In addition, a radioligand binding assay followed by another binding assay utilising

the extracellular domains of the FGF receptors fused to alkaline phosphatase

conducted by Santos-Ocampo et al. also demonstrated that FGF-9 binds best to

FGFR3IIIc but not FGFR1IIIc. Furthermore, their study also demonstrated that

FGF-9 binds weakly to the IIIb isoforms of both FGFR2 and FGFR3 and was

incapable of activating the FGFR2IIIb isoform (Santos-Ocampo et al., 1996).

Interestingly, they also found that even though FGF-9 could not bind to cell surface

or soluble FGFR1IIIc, the mitogenic assay performed showed that FGF-9 could

partially activate that receptor isoform (Santos-Ocampo et al., 1996).

1.6.3 Fibroblast Growth Factor-9 Signalling Pathway

The FGF-9 molecule forms homodimers and binds to the IgII and IgIII regions of

the receptor. This interaction is stabilised by the HSPG. The binding of the FGF-9

ligand to the receptor, which exists as inactivated monomers, causes the receptor

to undergo homodimerisation (Schlessinger et al., 2000). Activation of the receptor

stimulates the downstream signalling pathway where several signalling proteins

are recruited to the tyrosine auto-phosphorylated sites on the activated FGFR to

transautophosphorylate several other tyrosine residues on the receptors (Klint and

Claesson-Welsh, 1999).

46

There is a critical docking protein called the SNT-1/FRS2 (fibroblast growth factor

receptor substrate 2) which serves as a platform for more tyrosine kinases to bind.

This leads to the phosphorylation of more tyrosine residues on the receptor to

induce the RAS/MAPK and PI3K (phosphatidyllinositol-3 kinase signalling

pathway) (Eswarakumar et al., 2005, Klint and Claesson-Welsh, 1999). As a result,

the phosphorylation state of ERK1/2 in the MAPK pathway can be assessed to

understand the FGF signalling pathway (Thisse and Thisse, 2005).

Activated FGFRs can also phosphorylate and activate PLCγ. The activated PLCγ

produces diacylglycerol and inositol 1,4,5-triphosphate, which in turn, releases the

intracellular calcium storages and activates calcium-dependent members of the

protein kinase C (Klint P. and Claesson-Welsh L., 1999).

The activation of the FGFR pathway causing a chemotactic response,

differentiation, apoptosis, migration and cell proliferation is context-dependent and

tissue-specific as the effects elicited is dependent on the location of the different

isoforms of the receptor in the tissue (Turner and Grose, 2010, Klint and Claesson-

Welsh, 1999).

FGFR signalling is regulated at multiple levels, resulting in a tight control of its

expression levels, its sites of expression and its duration of signalling. FGFR

signalling can be negatively regulated by several proteins such as the MAPK

phosphatase 3 (MKP3), the Sprouty proteins and Sef (similar expression to FGF)

family members (Turner and Grose, 2010). FGFRs are also endocytosed and

degraded in lysosymes to attenuate its signalling (Haugsten et al., 2008) (Figure

1.5).

47

In addition, it was postulated that the FGF-9 homodimer can lead to the obstruction

of critical binding sites on the receptors; a feedback mechanism to modulate the

signal transduction at another level. The signalling specificity of individual FGFR

types is further complicated by the fact that most of the cells express more than

one FGFR variant and FGFRs can also form active heterodimers (Bellot, 1991).

48

Figure 1.5: Signalling through fibroblast growth factor receptors (Mason, 2007).

This figure summarises the FGFR signalling as well as the endogenous agonists and antagonists acting on both the upstream and

downstream of the receptor signalling pathway. The ERK-MAPK pathway is widely studied in the FGFR signalling pathway and is

activated by the Ras downstream of FRS2-SOS-Grb2 complex while the calcium/protein kinase C pathway is activated by activation of

phospholipase C. The potential nuclear targets are those proteins that antagonize or potentiate FGFR signals and those that are

transcription factors. CAM, cell adhesion molecule; CREB, cyclic AMP response element binding protein; FLRT, fibronectin leucine-rich

transmembrane proteins; FRS, FGF receptor substrate; HSPG, heparan sulphate proteoglycan; Ig, immunoglobulin; IP3, inositol tris

phosphate; MAPK, mitogen-activated protein kinase; MKP, MAPK phosphatase; PI3K, phosphatidylinositol-3-kinase; PIP3,

phosphatidylinositol-3-phosphate; PIP4, phosphatidylinositol-4-phosphate; PKB, protein kinase B; PLC , phospholipase C ; SOS, son

of sevenless; TK, tyrosine kinase.

50

1.6.4 Mutations of the Receptors for Fibroblast Growth Factor-9

1.6.4.1 Activating Mutations

Mutations of fibroblast growth factor receptor 2 (FGFR2) have been described in

12% of endometrial cancers (Dutt et al., 2008). Mutants such as the N549K and

K659N are highly sensitive to FGFR tyrosine kinase inhibitors, suggesting that

FGFR2 can also be a potential therapeutic target in the treatment of endometrial

cancer (Ornitz and Marie, 2002). Studies have shown that the endometrial cell

lines that harbour these mutations have reduced cell proliferation and decreased

survival following treatment with an FGFR inhibitor, PD173704 or knockdown of

FGFR2 (Dutt et al., 2008, Byron, 2008).

There are many studies associating bladder cancer with FGFR mutations. It was

reported that somatic mutations in the FGFR3 coding sequence occurs in

approximately 50% of bladder cancers (Cappellen et al., 1999). The majority of the

mutations in FGFR3 occur at a single position in the extracellular domain. One of

them is the S249C where an intermolecular cysteine disulphide bridge is formed

causing the aberrant folding of the FGFR3 protein leading to the constitutive

dimerization and hence activation of the receptor (Naski et al., 1996, Di Martino et

al., 2009). Mutations are also commonly found in the transmembrane domain,

such as the Y373C and the G380R (Pandith et al., 2010) and less common in the

kinase domain, such as the K652E (Munro and Knowles, 2003). The effects of the

mutations in the transmembrane and the kinase domains impact less on the

constitutive activation of the receptor (Di Martino et al., 2009, Naski et al., 1996).

FGFR3 can be a useful potential therapeutic target for urothelial cell carcinoma

(UCC), the most common form of bladder cancer, (Pandith et al., 2010, Cappellen

51

et al., 1999, Hernández et al., 2006) as numerous studies have demonstrated the

oncogenic role of the mutationally-activated FGFR3 in UCC. This is evident from

the knockdown studies of mutated FGFR3 or the inhibition of FGFR3 using

monoclonal antibody targeting FGFR3 in mouse xenografts or specific FGFR

inhibitors such as SU5402 and PD173704 in UCC cell lines, which have shown

reduced tumour properties (Bernard-Pierrot et al., 2006, Qing et al., 2009, Miyake

et al., 2009, Tomlinson et al., 2007, Lamont et al., 2011).

Besides bladder cancer, FGFR3 mutations have also been identified in cervical

cancers (Rosty et al., 2005), multiple myeloma and prostate cancers (Hernandez

et al., 2009).

1.6.4.2 Chromosomal Translocations

Besides activating mutations, chromosomal translocations can also occur on the

receptor genes (Figure 1.6). 15% of multiple myelomas harbour a t(4;14)

translocation that links the FGFR3 at 4p16.3 to the immunoglobulin heavy chain of

immunoglobulin H (IgH) locus at 14q32 (Avet-Loiseau et al., 1998, Chesi et al.,

1997). As a result of this, FGFR3 is controlled by the highly active IgH promoter.

This leads to the over-expression of the receptor and hence increased sensitivity

to ligands. As a result, the negative feedback of the signalling and also the

receptor internalisation and hence receptor degradation are decreased leading to

aberrant signalling of FGFR3 (Otsuki T. et al., 1999). FGFR3 translocation in

multiple myeloma is associated with a poor prognosis and it promotes a rapid

conversion from the precursor condition to the full blown multiple myeloma (Avet-

Loiseau et al., 1999).

52

1.6.4.3 Gene Amplification

Another type of mutation is the gene amplification where it is more commonly

found in FGFR2 (Figure 1.6). In gastric cancer, an amplified FGFR2 gene results

in increased sensitivity to FGF-7-dependent stimulation of tumour cell growth

(Nakazawa et al., 2003, Takeda, 2007) and is associated with poor prognosis

(Kunii, 2008).

The amplification of FGFR2 has also been described in triple-negative breast

tumours, which are aggressive breast tumours negative for the oestrogen receptor,

progesterone receptor and HER2 (human EGFR2)/ErbB2 (Turner et al., 2010).

The cell lines derived from these tumours had constitutive activation of FGFR2 and

were sensitive to FGFR2 inhibition using a specific FGFR inhibitor, PD173074, and

to FGFR2 RNAi silencing (Turner et al., 2010). FGFR2 may be used as a novel

therapeutic target for these breast tumours that have FGFR2 gene amplification.

1.6.4.4 Germline Single Nucleotide Polymorphisms

Single nucleotide polymorphism (SNP) can also occur on the genes (Figure 1.6). A

recent genome-wide association study has identified the role of FGFR2 as a breast

cancer susceptibility gene (Easton et al., 2007, Hunter et al., 2007). There was a

correlation between a SNP occurring in the second intron of FGFR2 with an

increased risk of developing ER-positive breast cancer but with little or no effect on

ER-negative breast cancer (Garcia-Closas et al., 2008).

53

Figure 1.6: Mechanisms of pathogenic cancer cell FGF signalling (Turner and Grose, 2010).

FGFs and their receptors can be altered in several ways in malignant diseases. Genomic alteration of FGFR can occur through three

mechanisms, leading to ligand-independent signalling. Firstly, activating mutations can cause ligand-independent dimerization or

constitutive activation of the kinase (shown by the yellow lightning). Secondly, chromosomal translocations generate fusion proteins

leading to dimerization of the fusion protein and constitutive signalling. Thirdly, receptor amplification can contribute to an accumulation

of the receptors (Turner and Grose, 2010).

55

1.7 Therapeutic Approaches

Many FGFR tyrosine kinase inhibitors (TKIs) are now in early phases of clinical

trials. As the VEGFR and FGFR kinase domains are structurally similar, the TKIs

developed can dually inhibit both receptors, hence inhibiting angiogenesis and

tumour cell proliferation (Turner and Grose, 2010).

However, the dual inhibition increases the side effects of the TKIs. Consequently,

there are therapeutic antibodies being developed to specifically target individual

FGFRs. This can also reduce the potential toxicity of pan-FGFR inhibition.

Antibodies targeting FGFR3 have been shown to have an anti-proliferative effect

on bladder cancer cells (Martínez-Torrecuadrada et al., 2005, Qing et al., 2009)

and t(4;14) myeloma (Qing et al., 2009).

In addition, there are FGF ligand traps, such as the FP-1039, which are soluble

fusion proteins consisting of an extracellular FGFR1IIIc domain fused to the Fc

domain of IgG1. The ligand trap antagonises the activity of multiple FGF ligands

and receptors, exerting both anti-angiogenic and anti-proliferative effects (Zhang

H. et al., 2007).

1.8 Summary

MM is a universally fatal cancer, predominantly caused by exposure to asbestos.

MM has a long latency period of up to 50 years and many patients diagnosed with

MM have less than a year to survive as there is no effective cure. This fatal

disease is difficult to diagnose and patient prognosis is difficult to predict. There is

thus a desperate need to uncover novel molecules which play key biological roles

56

in MM. Such molecules can potentially be crucial therapeutic targets and their

expressions may also have diagnostic and prognostic values.

FGF-9 is a secreted growth factor, first identified in human glioma cells. FGF-9

activates FGFR2 and FGFR3 and is vital for lung and testicular development. The

over-expression of FGF-9 and its aberrant signalling have been recently described

in prostate, lung and endometrial cancers but its role in MM has not been

investigated.

1.9 Preliminary Results

To identify biologically important molecules that are differentially regulated in MM,

our group conducted global gene profiling experiments using human MM samples.

Uncovering key molecules governing the growth of MM may provide novel

therapeutic targets. These proteins may also serve as biomarkers to aid diagnosis

and/or prognosis prediction in MM, which may predict the treatment response.

Pleural biopsies were collected under direct vision from patients undergoing

thoracoscopy. Only samples that had enough RNA quantity (>5 µg) and RNA

quality as defined by Bioanalyzer, were profiled for the expression of more than

22000 genes using Affymetrix HG-U133A microarray chip. 22 samples (14 MM, 3

pleural metastatic adenocarcinoma and 5 benign pleuritis) were analysed.

Using a stringent cut-off of 4-fold increase over benign controls, 25 genes were

found to be statistically significant in the MM group (Figure 1.7). The global gene

profiling data identified FGF-9 as the leading candidate gene with an mRNA

expression of 17-fold higher in MM compared to benign pleural tissue and pleural

57

adenocarcinoma samples (Figure 1.8). FGF-9 was picked out of the 25 genes as it

was a novel molecule that has not been investigated in MM and its role in other

cancers were just only beginning to be discovered. FGF-9 over-expression was

validated in another second separate cohort of 24 human tissue biopsies using

quantitative real-time PCR. This confirmed once again that FGF-9 was over-

expressed in MM at 35-fold (median) increase over adenocarcinoma or benign

pleuritis samples (Figure 1.9).

The following thesis research project aimed to follow-up on these exciting

preliminary data and to examine the role of FGF-9 in MM using a wide range of

molecular and cellular experiments, in vivo studies, and analyses of several large

cohorts of human pleural fluid samples.

Figure 1.7: Global gene profiling on 22 human pleural tissue samples.

Unsupervised hierarchical clustering separated 13 of 14 MM samples into one

group and the others into adenocarcinoma and benign groups, indicating good

homology of the global gene expression within the samples for each group. Ad =

adenocarcinoma.

Benign Ad Mesothelioma

Expression levels

High Low

Medium Not expressed

Sample size nbenign pleuritis = 5

nmesothelioma = 14 nmetastatic adenocarcinoma = 3

58

Figure 1.8: Quantification of FGF-9 gene expression from global gene

profiling.

Quantification of FGF-9 gene expression determined by Affymetrix microarray data

of individual biopsy samples. Median expression of FGF-9 was 17-fold higher in

the MM group than in controls. *p<0.05 compared to benign and adenocarcinoma

controls using Student’s t-test.

Benign & Ad MM

0.01

0.1

1

10

100

*

FG

F-9

gen

e ex

pre

ssio

n

(Norm

alis

ed i

nte

nsi

ty)

n =8 n=14

59

Figure 1.9: Validation of microarray gene expression results using RT-PCR.

Quantification of candidate gene RNA expression in an independent sample set.

FGF-9 was significantly over-expressed in MM over benign controls by 35-fold,

markedly higher than all the other candidate genes examined.

Ben

ign

RA

LDH

CK

7

CX

AD

RH

GF

SK19

LAP

FGF9

0

10

20

30

40

50

Fo

ld i

ncr

ease

M/B

1.10 Hypothesis and Aims

The up-regulation of FGF-9 mRNA in MM over controls in our pilot data (of my

thesis) leads to the hypothesis that FGF-9 plays a vital role in MM pathobiology

including cell proliferation, invasion and metastasis. Therefore, inhibiting FGF-9

activity will retard MM growth. In addition, FGF-9 can serve as a useful diagnostic

and prognostic biomarker for MM patients. We hypothesised that mutations in the

FGF-9 molecule and/or its receptors may cause aberrant FGF signalling in MM.

The aims are:

1a) To characterise the biological role of FGF-9 in MM cells and tissues

b) To study the biological effects of FGF-9 on MM cells in vitro

c) To examine the effects of silencing FGF-9 in MM cells in vivo

60

2) To determine the diagnostic value of FGF-9 levels in pleural fluids and

plasma of MM patients as a stand-alone biomarker and in conjunction with

existing biomarkers

3) To assess MM tissues for mutations in FGF-9 and its receptors, FGFR2

and FGFR3

61

____________________________________________

MATERIALS AND METHODS

CHAPTER 2

62

2.0 MATERIALS AND METHODS

2.1 Maintenance of Malignant Mesothelioma Cell Lines

2.1.1 Cell Culture

MM cell lines were cultured in cell culture flasks using standard growth medium

containing Dulbecco’s Modified Eagle Medium (DMEM) with high glucose (4500

mg/L) (Invitrogen, Grand Island, NY, USA), penicillin (100 U/mL), streptomycin

(100 µg/mL), L-glutamine (4 mM) (Invitrogen, Waverley, Australia) and fetal bovine

serum (FBS) (10%) (Sigma-Aldrich, St Louis, MO, USA). The cells were incubated

in a 5% CO2-containing humidified atmosphere at 37°C. Once the cells reached

80% confluency, they were trypsinised with 0.25% trypsin-

ethylenediaminetetraacetic acid (EDTA) (2 mL) (Invitrogen, Waverley, Australia)

and passaged at a 1:10 dilution.

Prior to all cell culture experiments, cell number was assessed by Trypan Blue

exclusion method. Cells were seeded in standard growth medium for at least 5

hours for the cells to adhere to the plates before the media was changed to serum-

free media (SFM) the day before experiments were conducted.

2.1.2 Malignant Mesothelioma Cell Lines

Eight human MM cell lines were used in this study. Five of the human MM cell

lines (JU77, LO68, NO36, ONE58 and STY) derived from pleural effusions (Linda

et al., 1991) were obtained from Professor Bruce Robinson (University of Western

Australia). The other three human MM cell lines, CRL-2081, CRL-5820 and CRL-

5915, were obtained from American Type Culture Collection (Rockville, MD, USA).

In addition to the human MM cell lines, six murine MM cell lines; AB1, AB2 and

63

AB22, all derived from mice of Balb/C background, AC29, derived from CBA mice

background and AE5 and AE17, derived from C57/Bl6 mice background were

used. These cell lines were derived from MM developed in mice that were exposed

to asbestos (Davis et al., 1992, Jackaman et al., 2003). All of the above-mentioned

cells were maintained in the standard growth conditions mentioned in Section

2.1.1. The MM cells have been well-characterised by cytological and ultrastructural

(electron microscopy) analyses (Davis et al., 1992, Jackaman et al., 2003, Linda et

al., 1991) and have been used in many published studies (Nasreen et al., 2000,

Galffy et al., 1999b, Linda et al., 1991, Jackaman and Nelson, 2010, Kissick et al.,

2012, Crisanti et al., 2009, Greay et al., 2010, Bielefeldt-Ohmann et al., 1995,

Friedlander et al., 2003).

2.1.3 Cryo-Freezing and Storage of Cells

Cells were trypsinised and centrifuged at 1200 r.p.m. for 10 minutes at room

temperature. The cell pellets were resuspended in pre-chilled serum-free growth

medium containing 10% dimethyl sulfoxide (DMSO) (Sigma-Aldrich, St Louis, MO,

USA). 2 x 106 cells/mL was aliquoted into each cryovial and stored at -80°C

overnight before they were transferred to liquid nitrogen for long term storage.

Cells in cryovial were thawed in a 37°C water-bath before they were transferred to

cell culture flasks and maintained in conditions described in Section 2.1.1. The

growth medium was changed the next day to remove non-adherent cells and

passaged as in Section 2.1.1.

64

2.2 Phenotypic Characterisation of Cells and Tissues

2.2.1 Immunofluorescence

2 x 105 human and murine MM cells were seeded in 8-well Lab Tek chamber

slides (In Vitro Technologies). After overnight serum-starvation, the cells were

washed with phosphate buffered saline (PBS) (3x) before fixing and permeabilising

using ice-cold methanol (100%) for 10 seconds. The cells were then rinsed with

PBS and non-specific protein binding was blocked with 10% heat-inactivated FBS

in PBS for 30 minutes at room temperature. Following that, the blocking solution

was aspirated and the cells in the wells were incubated in one of the primary

antibodies (FGF-9, FGFR2 and FGFR3) and their appropriate dilutions (Table 2.1)

overnight at 4°C. Universal Negative Control for N-series Rabbit Primary

Antibodies (Dako Denmark A/S Glostrup, Denmark) (Table 2.1) was used as a

negative control. The following day, the cells were washed in PBS (3x) and then

incubated with a secondary antibody, Alexa Fluor 488 goat-anti rabbit IgG (H+L)

(Invitrogen, Grand Island, NY, USA) (Table 2.2) for 30 minutes in the dark. Then,

the cells were washed with PBS (3x) and incubated with Hoechst 33342 for 15

mins in the dark before they were rinsed with PBS and mounted on slides in

aqueous mount and dried in the dark at 4°C. Images were captured using

AxioSkop 2 Plus fluorescence microscope (Zeiss, Thornwood, NY).

Table 2.1: Primary antibodies

Antibody and catalogue number

Dilution Application Supplier

1:200 Immunofluorescence FGF-9 (sc-7876) 1:250 Immunohistochemistry

Santa Cruz Biotechnology

1:250 Immunofluorescence FGFR-2 (ab10648) 1:1000 Immunohistochemistry

Abcam

1:100 Immunofluorescence FGFR-3 (sc-9007) 1:500 Immunohistochemistry

Santa Cruz Biotechnology

β-actin (ab8226) 1:10 000 Western Blotting Abcam Universal Negative Control for N-series

Rabbit Primary

Depending on dilution of

other

Immunohistochemistry Dako

65

Antibodies (N169987)

primary antibody

used p-ERK (# 4377) 1:1000 Western Blotting Cell Signalling p-JNK (# 9251) 1:1000 Western Blotting Cell Signalling p-p38 (# 9215S) 1:1000 Western Blotting Cell Signalling

Total ERK (sc-154) 1:1000 Western Blotting Cell Signalling Total p38(# 9212) 1:1000 Western Blotting Cell Signalling

Table 2.2: Secondary and tertiary antibodies

Antibody and catalogue number

Dilution Application Supplier

Biotinylated goat anti-rabbit (sc-2040)

1:200 Immunohistochemistry Santa Cruz Biotechnology

Streptavidin-horseradish

peroxidise (554066)

1:200 Immunohistochemistry BD Pharmingen

Alexa Fluor 488 goat-anti rabbit IgG

(H+L) (A11034)

1:400 Immunofluorescence Invitrogen

Hoechst 33342 1:1000 Immunofluorescence Sigma-Aldrich Rabbit anti-mouse-

HRP (ab6728) 1:1000 Western blotting Abcam

Goat anti-rabbit HRP (sc-2004)

1:1000 Western blotting Santa Cruz Biotechnology

2.2.2 Immunohistochemistry

The immunohistochemical staining was performed on formalin-fixed, paraffin-

embedded tissue biopsies of human and mice. After de-paraffinised with xylene

and rehydrated with 100% and then 70% ethanol, the tissue sections were then

subjected to heat-induced epitope retrieval in EDTA/Tris buffer, pH 8.0, (Appendix

I) using a microwave oven at high power for 2 minutes and 30 seconds before the

power was lowered for 15 minutes. Following that, the tissue sections were cooled

to room temperature in the same buffer and then rinsed with distilled water. Excess

peroxidase activity was blocked with the addition of 3% hydrogen peroxide solution

(Dako Denmark A/S Glostrup, Denmark) for 5 minutes at room temperature. The

tissue sections were then washed in distilled water before they were incubated

with 10% FBS/PBS for 30 minutes at room temperature to block non-specific

66

protein binding. Primary antibody incubation was done overnight at 4°C for all the

antibodies (FGF-9, FGFR2 and FGFR3 (Table 2.1)). Immunodetection was

performed on PBS-washed immunoreacted sections using a secondary antibody,

biotinylated goat anti-rabbit (Santa Cruz) (Table 2.2) for one hour followed by

incubation with streptavidin-horseradish peroxidise (BD Pharmingen) (Table 2.2)

for 30 minutes, at room temperature. Sections were then incubated with

SIGMAFAST™ 3,3’-Diaminobenzidine tablets (DAB Peroxidase Substrate Tablet

Set) dissolved in distilled water (Sigma-Aldrich, St Louis, MO, USA) and

counterstained with Mayers Haematoxylin (Sigma-Aldrich, St Louis, MO, USA).

After rinsing with distilled water and then Scott’s tap water substitute (Appendix I),

the sections were dehydrated with increasing concentrations of ethanol (70%, 95%

and 100%) and then xylene. DEPEX was added to each section before mounting.

Images were taken using AxioSkop 2 Plus microscope (Zeiss, Thornwood, NY).

2.2.3 Tissue Microarray Analysis

The tissue microarray staining was performed as stated in Section 2.2.2 with the

exception that the heat-induced epitope retrieval was done in sodium citrate buffer,

pH 6.0 (Appendix I). The slides were scored semi-quantitatively for the intensity of

FGF-9 staining by two independent blinded investigators. The intensity was graded

as not present (0), weak (1) and moderate to strong (2).

2.3 Western Immunoblotting

2.3.1 Protein Extraction

1 x 106 human and mice MM cell lines were plated in 65 x 15 mm dish. Following

the appropriate stimulations, the cells were then scraped on ice using a cell

scraper and lysed with pre-chilled breaking buffer (Appendix I) with the addition of

67

1:10 Protease Inhibitor Cocktail (Sigma-Aldrich, St Louis, MO, USA) and

PhosSTOP Phosphatase Inhibitor Cocktail (Roche, Castle Hill, Australia). The

sample was vortexed, left on ice for 10 minutes and vortexed again before being

centrifuged at 13100 r.p.m. for 10 minutes at 4°C. The supernatants were stored in

-80°C until assayed.

2.3.2 Determination of Protein Concentration

Protein concentrations were determined with the use of BioRad DC Protein Assay

Kit 2 (BioRad Laboratories, Hercules, CA) as per the manufacturer’s protocol with

various concentrations of BSA solutions (2, 0.75, 0.5, 0.25, 0.125, 0.025 mg/mL)

prepared in breaking buffer as standards for this assay.

2.3.3 SDS-PAGE and Immunoblotting

Cell lysates (20 µg) was mixed with NuPage® LDS sample buffer (Invitrogen,

Waverley, Australia) and dithiothreitol (DTT) (Sigma-Aldrich, St Louis, MO, USA).

The samples were then heated at 96°C for 10 minutes to denature the protein. 1X

SDS running buffer (Appendix I) or 1X MOPS buffer (Invitrogen, Waverley,

Australia) was added to the reservoirs and the samples were electrophoresed in

Ready Gel 4 – 20 % Tris-HCl (BioRad Laboratories, Hercules, CA) or NuPAGE®

Novex 4 – 12% Bis-Tris Gel (Invitrogen, Waverley, Australia) at 40 V until the

samples resolved through the stacking gel. Following that, the voltage was

increased to 100 V until the samples reached the bottom of the separating gel.

Transfer buffer (Appendix I) was pre-chilled before use and the polyvinylidene

difluoride (PVDF) membranes (PerkinElmer Life Sciences, Inc, Boston, MA) were

incubated with methanol (100%) for 1 minute, rinsed with distilled water and then

soaked in pre-chilled transfer buffer prior to use. The gels were then electro-

68

transferred onto PVDF membranes at 100V for 1.5 hours. The membranes were

stained with Ponseau S (Sigma-Aldrich, St Louis, MO, USA) to visualise effective

transfer and then blocked in 5% milk in TBS/Tw (Tris-buffered saline/0.1% Tween-

20) (Appendix I) for 1 hour at room temperature. The membranes were then

washed with TBS/Tw and probed with specific primary antibodies directed against

p-ERK, p-JNK, p-p38, total ERK, total p38 (Table 2.1) overnight at 4°C with

continuous rocking. Following washing with TBS/Tw, the blots were incubated in

horseradish peroxidise-conjugated goat anti-mouse or goat anti-rabbit IgG

antibody (Table 2.2) at room temperature for 1 hour. After extensive washing of the

membranes with TBS/Tw, bands corresponding to the BenchMark Prestained

Protein Ladder (Invitrogen) were visualised with an enhanced chemiluminescence

detection kit (Chemiluminescent Peroxidase Substrate, Sigma-Aldrich, St Louis,

MO, USA or Enhanced Chemiluminescence, GE Healthcare) according to the

manufacturer’s instructions. Antibody against β-actin (Table 2.1) was used as a

loading control. Membranes were exposed to Hyperfilm (Amersham Biosciences)

and developed on Agfa 1000 film processor (Raynostix, Louisville, KY).

2.4 Functional Assays

2.4.1 Cell Proliferation WST-1 Assay

Cell proliferation was evaluated by a colorimetric assay, WST-1 (Roche, Castle

Hill, Australia). This assay assesses the cellular viability by measuring the

metabolic conversion of a water-soluble tetrazolium salt, WST-1, into formazan.

Due to the enzymatic activity of mitochondrial dehydrogenases in viable cells, a

soluble dark red product is formed. The amount of formazan formed is directly

proportional to the number of viable cells in the culture and can be quantitated

using a spectrophotometer. This method has been employed in many published

reports (Humar et al., 2002, Nasreen et al., 2006, Khodayari et al., 2011).

69

Cell proliferation assay was conducted using the optimal cell density, 3 x 103

cells/well for both human and murine MM cells. This optimal cell density was

established in our pilot studies. The cells were seeded in a 96-well flat bottom cell

culture plate. After overnight serum-starvation, cells were then stimulated with 10%

FBS media (as a positive control) and with human (R & D Systems, Minneapolis,

MN) or murine (PeproTech Inc., Rocky Hill, NJ) recombinant FGF-9 at 1 – 100

ng/mL in 100 µL with 0% - 0.4% FBS for 48 hours. 0% - 0.4% FBS media was

used as a negative control. Cells were then incubated with WST-1 (1:10) for 0.5 - 1

hour at 37°C as per manufacturer’s instructions before the plate was read by a

scanning multiwell spectrophotometer as above.

2.4.2 Trypan Blue Cell Exclusion Assay

To validate the WST-1 assay above in Section 2.4.1, trypan blue cell exclusion

assay was conducted. Briefly, 1 x 104 human MM cells were seeded into a 12-well

plate. After overnight serum-starvation, cells were then stimulated with 10% FBS

media as a positive control and with human recombinant FGF-9 at 20 ng/mL in a

final volume of 1000 µL in 1% FBS media. 1% FBS media was used as a negative

control. Cells were washed with PBS, trypsinised and counted using the trypan

blue cell exclusion assay method on a hemocytometer at Day 1, 3, 6, 10 and 14.

The media was changed every 3 days.

2.4.3 Matrigel – Invasion Assay

Cell invasion was measured using 24-well Matrigel-invasion chamber plates

(Sigma-Aldrich, St Louis, MO, USA). 1 x 104 human MM cells were seeded in the

upper compartment of the Matrigel-coated inserts in a final volume of 500 µL in

serum-free media. Serum-free media alone (negative control) or 100 ng/mL FGF-9

70

was added to the companion plates. After 16 and 24 hours, non-invasive cells on

the upper surface of the insert were removed with a cotton applicator. The

Matrigel-coated insert membranes were stained with Diff-Quick solution (Andwin

Scientific) and viewed under a microscope. Invading cells were counted under a

10X magnification.

2.4.4 Scratch Assay

1.5 x 105 human and murine MM cells were plated in 6-well plates. Once the cells

are 90% confluent and following overnight serum-starvation, a 1 mL pipette tip was

used to scratch the surface of the well in the middle of the confluent cell

monolayer. Cells were then stimulated with human or murine recombinant FGF-9

at 100 ng/mL in 3 mLs of serum-free media for 0, 6, 8, 24, 48 and 72 hours. Cell

migration was monitored and images were taken using a camera attached to a

microscope. Cell migration was assessed by measuring the width of the gap

between the cells using a ruler and calculated as below:

Percentage increase of cell migration over 0 hour

= Width of gap at n hour – Width of gap at 0 hour

Width of gap at 0 hour

2.4.5 Cytokine and Chemokine Measurements

5 x 104 human and murine MM cell lines were plated in 24-well plates. Following

overnight serum-starvation, cells were then stimulated with human or murine

recombinant FGF-9 at 1 – 1000 ng/mL in a final volume of 500 µL in serum-free

media for 24 hours. In another set of experiments, 2.5 x 104 cells were stimulated

with 100 ng/mL FGF-9, resuspended in serum-free media, for 0, 2, 8, 24, 48 and

72 hours. Supernatants were then harvested and stored in -80°C. The samples

were assayed using commercially available ELISA kits for IL-8 (BenderMed

X 100 %

71

Systems), MIP-2 and VEGF (both from R & D Systems, Minneapolis, MN), IL-10,

MCP-1, TNF-α and IFN-γ (all from eBioscience Inc., San Diego, CA) according to

manufacturer’s instructions.

2.5 Molecular Characterisation of Cells

2.5.1 RNA Isolation

6 x 105 cells per well were plated in 6-well plates. After overnight serum-starvation,

RNA from cells was extracted using RNeasy Mini Kit (Qiagen, Hilden, Germany)

according to the manufacturer’s instructions. RNA was stored at -80°C until

required.

2.5.2 Determination of RNA Concentration

RNA quality was calculated by taking the ratio of the absorbance values at 260 nm

and 280 nm as determined using NanoDrop 2000 (Thermo Scientific). A ratio of

1.8 – 2 is considered satisfactory.

2.5.3 Reverse Transcription and cDNA Synthesis

Up to 5 µg of total RNA was reverse transcribed to complimentary DNA with RT2

First Strand Kit (SABiosciences) according to the manufacturer’s instructions,

except that the final step of adding 91 µL of nuclease-free water was omitted in

order to keep the total volume of cDNA at 20 µL. The sample was kept on ice for

the next step or stored at -20°C until required.

72

2.5.4 Real-time Polymerase Chain Reaction

The primers for FGF-9 and the housekeeping gene, glyceraldehyde 3-phosphate

dehydrogenase (GAPDH) are listed in Table 2.3. FGF-9 and GAPDH mRNA levels

in untreated and treated cells were determined by real-time polymerase chain

reaction using RT2 qPCR Primer Assay protocol from SABiosciences on Applied

Biosystems StepOne Plus™ real-time PCR (Applied Biosystems, Scoresby,

Australia) using the following protocol:

Cycle 1 (Holding stage): 95°C, 10 minutes

Cycle 2 (Cycling stage): Step 1: 95°C, 15 seconds,

Step 2: 60°C, 1 minute

Cycle 3 (Melt curve stage): Step 1: 95°C, 15 seconds

Step 2: 60°C, 1 minute

Step 3: An increment of 0.3°C to 95°C, 15 seconds

The FGF-9 mRNA levels were normalised to GAPDH RNA.

Table 2.3: Primers for real-time PCR

Gene Name

Supplier Catalogue number

Amplicon Size

Reference Position

Mouse FGF-9

SABioscience PPM02979E-200 87 bp 1398

Mouse GAPDH

SABioscience PPM02946E-200 140 bp 309

2.6 Sample Processing and Storage

Pleural fluids or plasma samples collected from patients were spun at 2000 r.p.m.

for 10 minutes and the supernatants were stored in -80°C freezer until assayed.

40 cycles

73

Pleural fluids and plasma samples were collected from tertiary pleural referral

centers: the Oxford Pleural Unit, Oxford, UK, as previously described (Davies et

al., 2009), the Pleural Disease Unit, Sir Charles Gairdner Hospital and from the

National Centre for Asbestos Related Diseases (NCARD) biobank, Perth, Western

Australia.

The ethics committees of Sir Charles Gairdner Hospital and Hollywood Hospital

(Australia) and the Mid- and South-Buckinghamshire and Central Oxford (UK)

Research Ethic Committees approved the collection of the samples and all

participants provided written consent.

2.7 Mutational Sequencing of Cells and Tissues

2.7.1 DNA Isolation

DNA was isolated from up to a maximum of 5 x 106 cultured cell lines using

DNeasy Blood and Tissue Kit (Qiagen, Hilden, Germany) following the

manufacturer’s protocol.

The extraction of DNA from tumour samples was also performed similarly using

the DNeasy Blood and Tissue Kit (Qiagen, Hilden, Germany) following the

manufacturer’s protocol with the incubation of the cut pieces of biopsy samples

with Proteinase K done at 56 °C overnight on a shaker platform until the tissue was

completely lysed.

74

2.7.2 Determination of DNA Concentration

DNA concentration and quality was determined using NanoDrop 2000 (Thermo

Scientific) similar to as described in Section 2.5.2. DNA quality was calculated by

taking the ratio of the absorbances at 260 nm and 280 nm. A good quality and

uncontaminated DNA has a ratio of between 1.8 and 2. The concentration of DNA

in ng/µL is obtained by taking the absorbance value at 260 nm multiply by 50 (the

extinction coefficient of DNA).

2.7.3 Polymerase Chain Reaction

The primers for all the exons of FGF-9, FGFR2 and FGFR3 and the optimised

conditions for polymerase chain reaction (PCR) are summarised in Table 2.4. PCR

was performed using HotStar Taq DNA Polymerase (Qiagen, Hilden, Germany) in

a final volume of 25 µL using the following cycle:

Cycle 1: 95°C, 15 minutes

Cycle 2: Step 1: 95°C, 30 seconds

Step 2: T1°C, 30 seconds 35 cycles

Step 3: 72°C, 30 seconds

Cycle 3: 72°C, 5 minutes

Cycle 4: 4 – 10°C, eternity

75

Table 2.4: Primers used for PCR for the mutational sequencing analysis in human samples

Gene Primer name

Sequence 5’ to 3’ [MgCl2] (mM)

Presence of Q solution

T1 °C Size (bp)

Reference

Forward CCTGGGTTGACACCATCATT Exon 1

Reverse tttcaacatgtcatctcatggac

1.5 No 57.9 382

Forward gcttagtgtcctctccaaaacc Exon 2

Reverse acagactcagttgcatttctgg

1.5 Yes 62.3 300

Forward cctatcaatccatcccctaggta

FGF-9

Exon 3

Reverse CCGCGTGAAACCTTTATAGTG

1.5 Yes 62.3 388

(Abdel-Rahman et al., 2008)

Forward TCCCTGACTCGCCAATCTCTTTC Exon 2

Reverse TGCCCCCAGACAAATCCCAAAAC

2.5 No 62.3 341

Forward CACTGACCTTTGTTGGACGTTC Exon 3

Reverse GAGAAGAGAGAGCATAGTGCTGG

2.5 No 62.3 380

Forward TGGAGAAGGTCTCAGTTGTAGAT Exon 4

Reverse AGACAGGTGACAGGCAGAACT

2.5 Yes 62.3 232

Forward CAAAGCGAAATGATCTTACCTG Exon 5

Reverse AGAAATGTGATGTTCTGAAAGC

2.5 No 62.3 291

Forward GCTAGGATTGTTAAATAACCGCC

FGFR2

Exon 6

Reverse AAACGAGTCAAGCAAGAATGGG

1.5 No 57.9 226

(Kan et al., 2002)

76

Forward TGAGTTTGCCTCTCCTCGTGTG Exon 7 (5’)

Reverse CCTTCTACAGTTGCCCTGTTGG

2.5 Yes 62.3 390

Forward GATGTGCTGTAGCAGACCTTTGG Exon 7 (3’)

Reverse ATCATCACAGGCAAAACCTGGG

2.5 Yes 62.3 360

Forward GGTCTCTCATTCTCCCATCCC Exon 8 (IIIa)

Reverse CCAACAGGAAATCAAAGAACC

1.5 No 54.8 325

Forward AATGCTAAGACCTTCCTGGTTGG Exon 9 (IIIb)

Reverse CAGTCTCCCAAAGCACCAAGTC

1.5 No 62.3 284

Forward CCTCCACAATCATTCCTGTGTC Exon 10 (IIIc)

Reverse ATAGCAGTCAACCAAGAAAAGGG

1.5 No 62.3 257

Forward TGCGTCAGTCTGGTGTGCTAAC Exon 11

Reverse AGGACAAGATCCACAAGCTGGC

2.5 Yes 62.3 341

Forward TGACTTCCAGCCTTCTCAGATG Exon 12

Reverse AGTCTCCATCCTGGGACATGG

1.5 No 62.3 252

Forward CCCCATCACCAGATGCTATGTG Exon 13

Reverse TTGATAAGACTCTCCACCCAGCC

1.5 No 60.4 221

Forward TAGCTGCCCATGAGTTAGAGG Exon 14

Reverse ATCTGGAAGCCCAGCCATTTC

1.5 No 62.3 250

Exon 15 Forward TGTTTTGCTGAATTGCCCAAG 1.5 No 54.8 294

77

Reverse TCCACCCAGCCAAGTAGAATG

Forward CTGGCGGTGTTTTGAAATTAG Exon 16

Reverse CCTTTCTTCCTGGAACATTCTG

2.5 No 62.3 242

Forward AGCCCTATTGAGCCTGCTAAG Exon 17

Reverse CCAGGAAAAAGCCAGAGAAAAG

2.5 Yes 62.3 177

Forward GGTTTTGGCAACGTGGATGGG Exon 18

Reverse GGTATTACTGGTGTGGCAAGTCC

1.5 No 60.4 250

Forward ACACCACGTCCCCATATTGCC Exon 19

Reverse CTCACAAGACAACCAAGGACAAG

1.5 No 54.8 243

Forward TCTGCCAAAATTGTTGTTTCTAGT Exon 20

Reverse GGTCTGGAACTCCTGACCTCA

2.5 Yes 54.8 208

Forward TCCCACGTCCAATACCCACATC Exon 21

Reverse TACTGTTCGAGAGGTTGGCTGAG

1.5 No 62.3 196

Forward CGTCCAATACCCACATCTCAAG Exon 22

Reverse TTCCCAGTGCTGTCCTGTTTGG

1.5 No 54.8 363

Forward CGAGGGGGCGTGCCCTGCGCC Exon 1

Reverse AGCACCGTTGGACCCCTCCG

1.5 Yes 62.3 339

Forward AGGGGTCGGGACGCAGGAG

FGFR3

Exon 2

Reverse CCCAACGCCTCTGCCCGCAC

1.5 Yes 62.3 350

(Wüchner et al., 1997)

78

Forward GTCTGTAAACGGTGCCGG Exon 3

Reverse ACCAGAGAGACCCCCAGC

1.5 No 60.4 425

Forward ATCTGGGAGGGGCACCTGGG Exon 4

Reverse GTCCCTCAGCTGCCTGTGAAG

1.5 Yes 62.3 222

Forward GTTCAGAGGGGCCTCTGCTC Exon 5

Reverse AGTGAGCGGAGGCAGCAACC

1.5 Yes 54.8 290

Forward CAGGCGCGGTGGTTGCTGCC Exon 6

Reverse GCACGTCCAGCGTGTACGTCTG

1.5 No 60.4 177

Forward CGGCAGTGGCGGTGGTGGTG Exon 7

Reverse CCAGCCCAGGAGCCCCAGCG

1.5 Yes 54.8 299

Forward TCTCCCACATCCTGCGTC Exon 8

Reverse GGGCCTTGGAGCTGGAGCTC

1.5 Yes 54.8 277

Forward AGGGCGGTGCTGGCGCTCGC Exon 9

Reverse AGACAGTGCGGAGCAGCAGC

1.5 Yes 54.8 228

Forward CAGGCCAGGCCTCAACGCCC Exon 10

Reverse AGGCCTGGCGGGCAGGCAGC

2.5 Yes 60.4 271

Forward CTGTACCTCCACGCCCTGTCGC Exon 11

Reverse CTGTTTCACCCCCACCACC

1.5 Yes 57.9 264

Exon 12 Forward GAGTGGGCGAGTTTGCACATCT 1.5 No 60.4 211

79

Reverse GCCCCCAGCCCTGCTCTGCAC

Forward GTGCAGAGCAGGGCTGGGGGC Exon 13

Reverse GCTCCTCAGACGGGCTGCCAG

1.5 Yes 62.3 240

Forward CTGGCAGCCCGTCTGAGGAGC Exon 14

Reverse CTGCTCCCAGCATCTCAGGGCA

1.5 Yes 62.3 286

Forward GGTGGAGAGGCTTCAGCCCT Exon 15

Reverse GCCAGGCGTCCTACTGGCATGA

1.5 Yes 62.3 217

Forward TCATGCCAGTAGGACGCCTGGC Exon 16

Reverse GGTCCTGGCTCTGCCCAGTTC

1.5 No 54.8 184

Forward CAGCGCAGCCCTGGCCTATTC Exon 17

Reverse CCTGAAGGGCTGCCAGTCCCT

1.5 Yes 62.3 314

Forward GAAGCGGCGGGGCTCACTCCT Exon 18

Reverse ATAGGCGGGTGGCACCAGGC

1.5 Yes 57.9 180

Forward GCGAAGAGGGGCTCGGTGGCAC Exon 19

Reverse CACCAGCAGCAGGGTGGGCTGCTAG

1.5 No 57.9 254

80

2.7.4 Agarose Gel Electrophoresis

2% agarose gels were prepared by heating the agarose solution in a microwave

until the solution turns clear. Ethidium bromide was added to a final concentration

of 0.5 µg/mL. The gel was poured into a casting tray and left to polymerise at room

temperature before being transferred to an electrophoresis tank (BioRad,

Hercules, CA) containing 1X TAE Running Buffer (Appendix I). Samples and a 100

bp DNA ladder (Promega, Madison, WI, USA) were loaded and electrophoresed at

100V until the bands are completely separated. The gel was imaged on a Typhoon

scanner.

2.7.5 Unpurified PD+ Capillary Sequencing

Once the PCR reaction was completed and the samples are electrophoresed in

agarose gel as in Section 2.7.4 to verify the correct products, the DNA samples

were sent to Australian Genome Research Facility (AGRF) for further processing

using the unpurified PD+ capillary sequencing method.

2.7.6 DNA Sequencing Analysis

The results obtained were analysed and compared by alignment using AlignX from

the Vector NTI Advance 11 software package (Invitrogen, Grand Island, NY, USA).

2.8 Molecular Knockdown In Vitro

2.8.1 Short Hairpin RNA Knockdown

AB1 was seeded at a concentration of 1 x 105 cells/well in a 6 well plate for 24

hours and then washed with PBS and incubated with serum-free medium for

81

another 24 hours before transfection. The cells were then left at room temperature

for 20 minutes and the serum-free media was replaced with fresh growth media.

Transfection with the FGF-9 plasmid was carried out using jetPRIMETM (Polyplus-

Transfection) Reagent and jetPRIMETM Buffer with N/P = 8 ratio, followed by the

formula determining the ionic balance within the complexes, where N refers to the

number of nitrogen residues in the jetprime (N/P>3 required) per P (phosphate) of

DNA.

µl of jetPRIME™ to be used

= (µg of oligonucleotide x 3) x N/P ratio c

jetPRIME™ concentration in nitrogen residues x 7.5 mM

Three different shRNAs (sh273, sh496, sh588) and a scrambled vector

(pSUPER.retro.puro) were used to transfect the cells. Each plasmid was added to

a different well. From the formula above, 3.2 µL of jetPRIME was diluted to a final

volume of 100 µL jetPRIMETM Buffer for each shRNA and scrambled vector. 1 µg

of each shRNA and the scrambled vector was added separately into another tube

containing 100 µL of jetPRIMETM Buffer and mixed. Then, the diluted jetPRIMETM

was combined with the diluted plasmid and gently mixed to a final volume of 200

µL before they were added slowly to the cells in a drop-wise fashion. Cells cultured

without any plasmids acted as negative controls. The plates were then gently

agitated in the incubator for another 48 hours. The media was then removed, the

cells were washed with PBS and new medium was added together with 1 µg/mL of

puromycin-dihydrochloride (Applichem, Darmstadt, Germany). This selection

process was repeated every 24 hours. At a time when all of the cells in the

82

negative control wells have died, colonies were picked from the treated wells and

placed in new petri dishes and grown in media with the antibiotic. ELISA and RT-

PCR were performed to select clones with successful knockdown of FGF-9.

.

2.9 In Vivo Inoculation of Short Hairpin Knockdown Cells

2.9.1 Heterotopic Model

FGF-9 shRNA knocked down MM cell clones were tested in vivo. A single injection

of 5x105 cells from selected shRNA targeting FGF-9 (sh588), scrambled vector or

parent controls was administered to the subcutaneous right flank of at least 10

Balb/c mice. Tumour dimensions were measured daily. This was performed by one

blinded investigator. Animals were sacrificed after tumour size reached the

maximum limit of 10 mm x 10 mm. Tumour tissues were harvested for histology.

2.9.2 Orthotopic Model

For the orthotopic experiments, Balb/c mice received a single intraperitoneal

injection of 5x105 cells from selected shRNA targeting FGF-9 (sh588), scrambled

vector or parent controls. The mice were observed daily: their weight loss and

survival recorded. At day 13, the animals were sacrificed, their peritoneal cavities

opened and volume of fluids (if any) measured. Two blinded investigators graded

the tumour load i) by counting the number of tumour nodules; and ii) by removing

and weighing all macroscopic tumours.

FGF-9 expression in tumour tissue was determined by immunohistochemistry. The

histology of the tumour and neighbouring tissues were examined with an

experienced pathologist in MM (Dr Amanda Segal, Perth, WA) who was blinded to

the treatment groups.

83

2.9.3 Athymic Model

For the experiments conducted in athymic mice, a single injection of 5x105 cells

from selected shRNA targeting FGF-9 (sh588), scrambled vector or parent controls

was administered to the subcutaneous right flank of at least 5 nude mice. Tumour

dimensions were measured daily. This was performed by one blinded investigator.

Animals were sacrificed after tumour size reached the maximum limit of 10 mm x

10 mm.

2.10 Statistical analysis

Data are presented as mean ± standard error of the mean if normally distributed

and as median (range) if not. For parametric data, statistical comparisons between

groups were performed using either a Student’s or paired t-test. For multiple group

comparison, one-way analysis of variance (ANOVA) was used followed by a post-

hoc test if appropriate. For non-parametric data, comparison of groups were

performed using Mann-Whitney rank sum test and multiple of group comparisons

were performed using the Kruskal-Wallis ANOVA-on-Ranks. Student-Newman-

Keuls or Dunn’s test was used as the post-hoc test. p<0.05 was considered

significant. Statistics were performed using SigmaPlot version 11.0 (Systat

Software, San Jose, California, USA).

84

____________________________________________

THE EXPRESSION OF FIBROBLAST GROWTH

FACTOR-9 IN MALIGNANT MESOTHELIOMA

CHAPTER 3

85

3.0 THE EXPRESSION OF FIBROBLAST GROWTH FACTOR-9 IN

MALIGNANT MESOTHELIOMA

3.1 Introduction

MM is a fatal disease that has no effective treatment. As a result, there is an

urgent need to discover new molecules involved in MM disease pathobiology

where a potential to develop new therapeutic targets can be achieved. These

molecules may also have potential diagnostic and prognostic values.

The preliminary pilot experiments as discussed in Section 1.9 uncovered FGF-9

from 22000 genes in the global gene profiling data that was up-regulated in MM

but not in the metastatic adenocarcinoma and benign pleural diseases groups. The

gene over-expression was validated in another second cohort of patients. This

chapter explores the hypothesis that FGF-9 is over-expressed in MM tissues

compared to other non-MM cancers and benign pleural conditions. Human pleural

fluids from a range of diseases as well as human and murine MM tissues and cells

were used to test this hypothesis.

3.2 Results

3.2.1 The Detection of FGF-9 in MM Samples

The preliminary results showed that FGF-9 is over-expressed at the RNA level in

human MM thoracoscopic pleural biopsies using Affymetrix microarray and RT-

PCR. Prior to identifying if FGF-9 is over-expressed in human and murine MM cells

and tissues as well as in human pleural fluids, it is important to examine if FGF-9

can be detectable using other methods. As a result, ELISA to quantitate FGF-9 in

86

the cells and histology examinations using immunofluorescence and

immunohistochemistry were used to detect the presence of FGF-9.

The murine FGF-9 ELISA purchased was separate antibody pairs. Optimisation

was performed for the concentrations of the capture and detection antibodies (from

0.25, 0.5, 1 and 2 µg/mL) and for the best wavelength for reading the plates (at

405 nm and 450 nm). The condition that produces a 4-parameter logistic curve (1

µg/mL for both capture and detection antibodies and a wavelength at 450 nm) was

selected as the optimised condition for murine FGF-9 ELISA (Figures 3.1A and B).

87

Figure 3.1: Optimisation of murine FGF-9 ELISA.

The concentrations of capture and detection antibodies were varied accordingly from 0.25, 0.5, 1 and 2 µg/mL and absorbances were

read on the plate reader at (A) 405 nm and (B) 450 nm. The pair concentrations of capture and detection antibodies at 1 µg/mL read at

450 nm was selected as the optimised conditions for murine FGF-9 ELISA that produces a 4-parameter logistic curve (in red box).

88

3.1A

Capture

Detection

0.5 µg/mL 1 µg/mL 2 µg/mL

0.25 µg/mL

1000 2000 3000 4000 5000

-0.02

-0.01

0.00

0.01

0.02

0.03

[FGF-9 standards] (pg/mL)

Ab

sorb

ance

1000 2000 3000 4000 5000

-0.04

-0.03

-0.02

-0.01

0.00


Ab

sorb

ance

0 1000 2000 3000 4000 5000

0.00

0.01

0.02

0.03

0.04

0.05


Abso

rban

ce

0.5 µg/mL

1000 2000 3000 4000 5000

-0.04

-0.02

0.00

0.02

0.04

0.06


Ab

sorb

ance

1000 2000 3000 4000 5000

-0.07

-0.05

-0.03

-0.01

0.01


Ab

sorb

ance

0 1000 2000 3000 4000 5000

0.0

0.2

0.4

0.6

0.8


Ab

sorb

ance

1 µg/mL

0 1000 2000 3000 4000 5000

0.0

0.1

0.2

0.3

0.4

0.5


Ab

sorb

ance

0 1000 2000 3000 4000 5000

0.0

0.1

0.2

0.3

0.4


Ab

sorb

ance

0 1000 2000 3000 4000 5000

0.0

0.2

0.4

0.6

0.8


Ab

sorb

ance

89

3.1B

Capture

Detection

0.5 µg/mL 1 µg/mL 2 µg/mL

0.25 µg/mL

1000 2000 3000 4000 5000

-0.050

-0.025

0.000

0.025

0.050

0.075

0.100


Ab

sorb

ance

0 1000 2000 3000 4000 5000

-0.13

-0.11

-0.09

-0.07

-0.05

-0.03

-0.01

0.01


Abso

rban

ce

0 1000 2000 3000 4000 5000

0.000

0.025

0.050

0.075

0.100

0.125

0.150

0.175


Ab

sorb

ance

0.5 µg/mL

1000 2000 3000 4000 5000

-0.15

-0.10

-0.05

-0.00

0.05

0.10

0.15

0.20


Abso

rban

ce

1000 2000 3000 4000 5000

-0.25

-0.20

-0.15

-0.10

-0.05

-0.00

0.05


Ab

sorb

ance

0 1000 2000 3000 4000 5000

0.0

0.1

0.2

0.3

0.4

0.5

0.6


Ab

sorb

ance

1 µg/mL

0 1000 2000 3000 4000 5000

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75


Abso

rban

ce

0 1000 2000 3000 4000 5000

0.0

0.2

0.4

0.6

0.8

1.0

1.2


Ab

sorb

ance

0 1000 2000 3000 4000 5000

0.0

0.5

1.0

1.5

2.0

2.5

3.0


Ab

sorb

ance

90

Using the optimised FGF-9 ELISA (1 µg/mL for both capture and detection

antibodies), murine cell lysates and culture media supernatants were quantitated

for murine FGF-9. Murine FGF-9 can be detected in both the cell lysates and the

supernatants in all the six murine MM cell lines tested (Figure 3.2). The FGF-9

concentration was significantly higher in cell lysates than in the culture media

supernatants, in keeping with the reported observations in other cell types (see

Section 1.5.5). This confirms the presence of FGF-9 in murine MM cells.

Figure 3.2: The presence of FGF-9 in murine MM cells detected using ELISA.

Cells from different murine MM cell lines were lysed with breaking buffer. Cell

lysates and supernatants were tested and quantitated for murine FGF-9 using

ELISA. Values are expressed as mean ± SEM of five replicates from a

representative experiment conducted twice.

AB1 AB2 AB22 AC29 AE5 AE17

0

10

20

30

40

50

Lysates

Supernatants

Cells

Fold

in

crea

se o

f F

GF

-9 l

evel

s in

cel

ls

* *

*

** **

**

n = 5 per group

*p=0.008, **p<0.001 compared to supernatants of the same cell line, t-test

91

The presence and localisation of FGF-9 in murine and human MM cells was also

confirmed using immunofluorescence using a different antibody from that of the

ELISA (Figure 3.3). In all eight human cell lines (JU77, LO68, NO36, ONE58, STY,

CRL-2081, CRL-5820 and CRL-5915) and three murine cell lines (AB1, AB2 and

AE5) tested, immunofluorescence confirmed the presence of FGF-9 in the nuclei

and cytoplasm of the cells. A stronger fluorescent intensity for FGF-9 in the nuclei

of the cells was detected however the significance of its localisation in the nucleus

is unknown. This is the first evidence of the presence of FGF-9 in human and

murine MM cell lines.

92

Figure 3.3: Expression and distribution of FGF-9 in the human JU77 and murine AB2 MM cell lines.

(A) The expression of FGF-9 in a human MM cell line, JU77, as depicted by the green fluorescence intensity from the FITC-conjugated

antibody. (B) The nuclei of the cells as shown by the blue intensity of DAPI staining. (C) A merge of images A and B illustrates the

distribution of FGF-9 in both the nuclei and cytoplasm of the cells. (D-F) The expression of FGF-9 detected in a murine MM cell line,

AB2. These images are a representative image of all of the eight human and three murine MM cell lines tested. In the negative isotype

control (not shown), the only fluorescence observed is the DAPI staining.

FGF-9-FITC DAPI Merge

JU77

AB2

3.3A

3.3D 3.3F

3.3B 3.3C

3.3E

93

In addition, the presence of FGF-9 was detected by immunohistochemistry on MM

tumour tissues from human pleural biopsies and mice implanted with MM. A

greater brown intensity was present in the tumour tissues but lesser in the stroma,

indicating the abundance of FGF-9 in MM tumour tissues where FGF-9 is the key

protein. The presence of FGF-9 in the surrounding stroma demonstrates that

normal tissues also secrete FGF-9 that may be important in homeostasis of the

tissue.

Figure 3.4: Expression and distribution of FGF-9 in the MM human tissue

biopsy and murine MM tumour.

The expression of FGF-9 in MM tissues was observed by immunohistochemistry

using FGF-9 antibody. The brown staining intensity in (A) human MM tissue biopsy

and (C) murine MM tissue observed under a 20X magnification depicts the

presence of FGF-9 protein in tissues. Images B and D show the negative IgG

isotype control for the FGF-9 staining.

3.4A 3.4B

3.4C 3.4D

94

3.2.2 The Expression of FGF-9 in MM Cells and Tissues

Having established the presence of FGF-9 in MM cells and tissues, FGF-9

expression was further characterised in cells obtained from pleural fluids and

tissues from patients who were diagnosed with metastatic adenocarcinoma (n=29)

and MM (n=121). Samples obtained from patients who had benign diseases

(n=35) served as controls. The specificity of the FGF-9 antibody to FGF-9 is

demonstrated from the negative staining of FGF-9 in the IgG isotype control

(Figures 3.5B and D). Figure 3.5E illustrates that FGF-9 is highly expressed in

metastatic adenocarcinoma and MM, with approximately 76% and 65%

respectively being in the higher intensity (score 2-3) category. This is not the case

for benign pleural diseases whereby only in 37% of patients was FGF-9 highly

expressed. Although the results obtained from this immunohistochemistry study is

only semi-quantitative, the proportions of observations in the different patient

groups and the intensity of FGF-9 staining showed significant differences among

the groups (χ2 = 82.8, df = 2, p<0.001) and confirms the abundance of FGF-9 in

malignant cells and tissues but not in the non-malignant samples.

Figure 3.5: Expression of FGF-9 in cells and tissues on tissue microarray.

Tissue microarray for (A) benign mesothelial cells from pleural fluid given a score

of 1 (low intensity) where as adenocarcinoma tissue (C) were given a score of 3

(high intensity). The scoring of staining intensity was performed by two blinded

investigators. (B & D) The negative isotype controls for the figures A and C

respectively illustrates the specificity of FGF-9 antibody. (E) The bar graph shows

the percentage of scoring intensities for the different diagnoses; benign diseases,

metastatic adenocarcinoma and MM.

95

3.5E

Benign diseases Metastatic adenocarcinoma MM

0

10

20

30

40

50

60

70

80

90

100

2-30-1

Scores

n = 35 n = 29 n = 121

Scores

Per

cen

tage

of

score

s

χ2 = 82.8, df = 2, p<0.001

3.5A

3.5D

3.5B

3.5C

96

3.2.3 The Expression of FGF-9 in Pleural Fluids

To measure and quantitate the levels of FGF-9 in patient fluid samples, it is

prudent to investigate if FGF-9 is stable after repeated freeze-thaw cycles. Figure

3.6 shows that FGF-9 is stable in pleural fluid samples even after seven repeated

freeze-thaw cycles. This indicates that FGF-9 could still be detected and the levels

have not changed from the time of the first pleural fluid collection to the seventh

time that it has been thawed out for experiments. This is the first study that has

demonstrated the stability of FGF-9 after repeated freeze-thaw cycles. However,

as this has only been tested in pleural fluids, it is unknown if FGF-9 is stable in

other bodily fluids.

Figure 3.6: The stability of FGF-9 in pleural fluids following freeze-thaw.

Each of the twelve pleural fluid samples (represented as each line) were aliquoted

into eight different microfuge tubes, labelled A to H (represented as each symbol).

Each following tube is subjected to an additional freeze-thaw cycle, such that tube

A was not thawed, tube B was subjected to one thawing stage, C underwent two

stages of thawing process and tube H had seven repeated freeze-thaw cycles. The

FGF-9 levels were measured using human FGF-9 ELISA. FGF-9 is stable after

seven repeated freeze-thaw cycles in the pleural fluid samples tested.

0 1 2 3 4 5 6 7

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

Freeze-thaw cycles

[FG

F-9

] (p

g/m

L)

97

To compare the FGF-9 levels in pleural fluids, two separate patient cohorts were

tested. 283 prospectively collected, undiagnosed pleural fluids were obtained from

the Oxford Pleural Unit biobank cohort. The median FGF-9 levels in 43 pleural

fluids from MM patients (median 1.66 ng/mL; interquartile range 0.23 - 3.66 ng/mL)

were 7.2-fold higher than 137 patients with metastatic carcinomas (median 0.23

ng/mL, interquartile range 0.08 - 1.78 ng/mL, p<0.05 vs MM) and 4.6-fold higher

than 103 patients with benign pleural diseases (median 0.35 ng/mL, interquartile

range 0.09 - 1.82 ng/mL, p<0.05 vs MM) (Figure 3.7A).

This result was extended to a larger cohort of 639 pleural fluids from Perth,

Western Australia where a strikingly similar pattern was observed (Figure 3.7B). In

this cohort, the median levels of FGF-9 measured blindly in 205 pleural fluids

obtained from MM patients (median 1.58 ng/mL, interquartile range 0.56 – 0.31

ng/mL) were 12.5-fold higher than that of 210 patients with metastatic carcinomas

(median 0.13 ng/mL, interquartile range 0.0 – 0.39 ng/mL, p<0.05 vs MM) and

11.3-fold higher than 224 patients with benign pleural diseases (median 0.14

ng/mL, interquartile range 0.0 – 0.39 ng/mL, p<0.05 vs MM). The data confirms the

over-expression of FGF-9 protein in MM pleural fluid samples compared to

adenocarcinoma and benign pleural diseases and is consistent with the FGF-9

mRNA over-expression reported in the global gene profiling data. The results show

significant promise of FGF-9 as a biomarker that can discern MM from other

cancers and benign pleural diseases effectively.

The patient demographics from the Oxford cohort have been previously published

(Davies et al., 2009, Rahman et al., 2008) while the patient demographics from the

Perth cohort are tabulated in Figure 3.7C. The majority of pleural fluids obtained

from MM patients were of epitheloid subtype (n=80) while there were only 16 and

98

19 patients diagnosed with biphasic and sarcomatoid subtypes respectively. In the

remaining 90 pleural fluids, the diagnosis of MM was made on cytology and not

clarified for its histologies subgroups.

Figure 3.7: Pleural fluids FGF-9 levels in the Oxford and Perth cohorts.

(A) Pleural fluid FGF-9 levels in the Oxford cohort in 43 patients with MM were 7.2-

fold higher than in 137 patients with metastatic carcinomas and 4.6-fold higher

than 103 patients with benign pleural diseases (*p<0.05). (B) Pleural fluid FGF-9 in

the Perth cohort in 205 patients with MM were 12.5-fold higher than 210 patients

with metastatic carcinomas and 11.3-fold higher than 224 patients with benign

pleural diseases (*p<0.05). (C) Pleural fluids obtained from the Perth cohort is

categorised into MM, metastatic carcinomas and benign pleural diseases, which

are further subdivided into smaller groups.

99

3.7A 3.7B

*p<0.05 ANOVA-on-rank, Dunn’s test

Pleural fluid FGF-9 levels in Oxford cohort

[FGF-9] (ng/mL)

0 5 10 15 20

Mesothelioman=43

Carcinomasn=137

Benignn=103

*

*

Pleural fluid FGF-9 levels in Perth cohort

[FGF-9] (ng/mL)

0 2 4 6 8

Mesothelioman=205

Carcinomasn=210

Benignn=224

*

*

100

3.7C

Patient characteristics n Age

(median) % females

Mesothelioma Epitheloid 80 68 18.6 Biphasic 16 67 15.8 Sarcomatoid 19 74.5 9.1 Unknown 90 71 16.2 Total 205

Carcinomas Lung 80 68 45.3 Breast 35 64 100.0 Others 95 71 43.4 Total 210

Benign Asbestos exposure 1 79 0 Cardiac diseases 45 77 44.4 Haemothorax 2 79.5 0 Hepatic causes 13 59 15.4 Idiopathic 58 71 39.7 Idiopathoc pleuropericarditis 4 58 0 Infection 71 65 35.2 Pancreatic diseases 1 60 100 Pneumothorax 3 71 33.3 Post-cardiac surgery 3 73 33.3 Post-operative 3 68 33.3 Renal causes 8 52.5 37.5 Rhematological causes 3 64 33.3 Secondary to abdominal causes 5 39 40 TB pleural effusion 4 67.5 25

Total 224

101

3.2.3.1 The Expression of FGF-9 in the Different MM Histological Subtypes

To elucidate the differential expression levels of FGF-9 in the different histological

subtypes, MM pleural fluids in the Perth cohort were further subdivided into the

three main histological subtypes; the epitheloid, biphasic and sarcomatoid. It was

found that the epitheloid subtype (n=80, median 2130.95 pg/mL, interquartile

range 743.03 - 3804.76 pg/mL) had the highest FGF-9 levels of all three subtypes,

with a median level of 8.6-fold higher than in the sarcomatoid subtype (n=19,

median 254.56 pg/mL, interquartile range 63.94 - 612.31 pg/mL, p<0.05). The

median level of FGF-9 in the biphasic subtype (n=16, median 1711.91 pg/mL,

interquartile range 880.74 - 2648.88 pg/mL) was 7.1-fold higher than in the

sarcomatoid subtype (p<0.05). There were 90 pleural fluid samples whose

subtypes could not be characterised (median 1877.64 pg/mL, interquartile range

714.73 - 3173.90 pg/mL) (Figure 3.8). This data shows that like mesothelin, FGF-9

can only be used to diagnose epitheloid MM but not sarcomatoid MM.

102

Figure 3.8: FGF-9 levels in different MM histology.

FGF-9 levels in the epitheloid subtype was 8.6-fold higher than in the sarcomatoid

subtypes where as FGF-9 levels in the biphasic subtype was 7.1-fold higher than

in the sarcomatoid patients (*p<0.05). FGF-9 expression is significantly lower in

the patients with the sarcomatoid subtype.

Epitheloid Biphasic Sarcomatoid Not specified

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

20000

22000

*

*

n = 80 n = 19n =16 n = 90

MM histology

FG

F-9

lev

els

(pg

/mL

)

*p<0.05 ANOVA-on rank, Dunn’s test

103

3.2.3.2 The Expression of FGF-9 in MM Pleural Fluids and Matched Plasma

The over-expression of FGF-9 protein in MM pleural fluids demonstrates that it

may be used as a diagnostic marker to differentiate MM from other cancers and

benign pleural diseases. However, to serve as an early diagnostic biomarker, it

would have to be detected and also up-regulated in the blood so that a simple

minimally-invasive blood test is suffice to screen and diagnose MM from the early

stage. So, paired pleural fluids and serum samples from 35 patients with MM were

selected randomly from a biobank collected from patients from the Pleural Disease

Unit, Sir Charles Gairdner Hospital to compare the relative abundance of FGF-9 in

the pleural cavity and the systemic circulation. Figure 3.9 shows that in 22 out of

25 samples that had detectable FGF-9 in the pleural fluids, the median FGF-9

levels were 6-fold higher in pleural fluids than in plasma samples. Only 3 MM

patients had higher FGF-9 levels in their plasma samples than in their

corresponding pleural fluids. There were 10 patients who had no detectable levels

of FGF-9 in both their pleural fluids and plasma samples. Only 5 out of 35 plasma

samples tested had a positive FGF-9 level reading implying that FGF-9 is

undetectable in the majority of the plasma samples and hence cannot be used as

an early diagnostic marker nor can it be used as a simple screening test to monitor

the disease as treatment commences. In addition, the higher FGF-9 levels

detected in the pleural fluids compared to the matched plasma samples highly

imply the pleural origin of FGF-9.

It is worth to note that the FGF-9 levels in the pleural fluids from the same patient

measured by ELISA separately for two assays; the freeze-thaw assay (Figure 3.6)

and matched pleural fluids-plasma assay (Figure 3.9); were similar, indicating that

the inter-variable assay is very small.

104

Figure 3.9: FGF-9 levels in matched pleural fluid and plasma of patients

diagnosed with MM.

FGF-9 levels were measured using ELISA in matched pleural fluids and plasma

samples from 35 MM patients. Data was plotted as a log ratio of FGF-9 levels in

pleural fluids to plasma as the y-axis, whereby a log ratio of greater than zero

indicates a higher level of FGF-9 in the pleural fluids than in the corresponding

plasma sample and a log ratio of less than zero indicates otherwise. A log ratio of

zero implies that the FGF-9 levels in the pleural fluids and plasma samples are

equal. FGF-9 is detected in abundance in 22 out of 25 pleural fluids than in plasma

samples. Only three patients had a higher level of FGF-9 in plasma instead of their

pleural fluids. Ten patients had no detectable levels of FGF-9 in both their pleural

fluids and plasma samples.

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

Log r

ati

o o

f F

GF

-9 l

evel

s in

ple

ural

flu

id t

o p

lasm

a

n = 35

105

3.2.3.3 The Correlation between FGF-9 and Mesothelin

To determine if FGF-9 in pleural fluids added diagnostic value to mesothelin,

pleural fluid FGF-9 levels from the Perth cohort were compared with the

mesothelin levels previously measured by Creaney et al. (Creaney et al., 2007).

Figure 3.10 illustrates only a weak correlation between FGF-9 and mesothelin (n =

537, rs = 0.511, 95% CI 0.128 to 0.289, p<0.0001). This implies that FGF-9 and

mesothelin are totally different proteins and that measuring FGF-9 and mesothelin

pleural fluid levels separately will give different magnitudes although they are both

up-regulated in MM.

Figure 3.10: The correlation between FGF-9 and mesothelin.

Each dot represents the FGF-9 levels (pg/mL) in each of the pleural fluid samples

that were correlated with the mesothelin levels (nM), previously measured by

Creaney et al. (Creaney et al., 2007). FGF-9 correlates very weakly with a

Spearman rs value of 0.511 (p<0.0001).

0.1 1 10 100 1000

100

1000

10000

Sample size 537Spearman rs 0.511

95% confidence interval 0.127 to 0.289

p value (two-tailed) p<0.0001

Mesothelin (nM)

FG

F-9

(p

g/m

L)

106

3.2.3.4 The Value of a Diagnostic Marker When Combining FGF-9 and Mesothelin

Since FGF-9 correlates weakly with mesothelin, the area under the receiver

operating characteristic curve (ROC) was measured for FGF-9 and compared with

that for mesothelin. A perfect diagnostic marker will have a ROC value of one.

Figure 3.11A shows that the ROC for FGF-9 to differentiate MM (n=205) from

benign pleural diseases (n=224) is 0.816, while the ROC value for mesothelin is

0.9078. To distinguish MM from other cancers (n=210), FGF-9 was comparable to

mesothelin with a ROC value of 0.8303 and 0.8438 respectively (Figure 3.11B).

Furthermore, FGF-9 was as good as mesothelin in teasing out MM versus a

combined of benign pleural diseases and other cancers with a ROC value of

0.8228 and 0.8775 respectively (Figure 3.11C). Interestingly, combining FGF-9

and mesothelin as a panel of biomarkers increases the diagnostic validity to

differentiate MM versus benign pleural diseases to 0.9175 (Figure 3.11A), MM

versus other cancers to 0.8848 and MM versus non-MM to 0.9002 (Figure 3.11C).

The results are summarised in Figure 3.11D. The data demonstrates the quality of

FGF-9 in combination with mesothelin as a panel of biomarkers to diagnose and

differentiate MM from non-MM.

107

Figure 3.11: The area under the ROC for FGF-9 and mesothelin to differentiate MM from non-MM.

The area under the ROC for FGF-9 and mesothelin to predict MM (n=205) versus (A) benign pleural diseases (n=224) were 0.816 and

0.9078 respectively. Combining the two molecules increases the ROC to 0.9175 (B) other cancers (n=210) were 0.8303 and 0.8438

respectively and combining the two increases the ROC to 0.8848 (C) non-MM were 0.8228 and 0.8775 respectively while combining

the two molecules increases the diagnostic validity to 0.9002 (D) The results are summarised in the table.

3.11A 3.11B

3.11C 3.11D

MM vs Benign Cancer Benign &

Cancer

FGF-9 0.816 0.8303 0.8228

Mesothelin 0.9078 0.8438 0.8775

FGF-9 + Mesothelin 0.9175 0.8848 0.9002

0.0

00.

250.

50

0.7

51.

00S

ens

itivi

ty

0.00 0.25 0.50 0.75 1.001-Specificity

0.0

00.

250.

50

0.7

51.

00S

ens

itivi

ty

0.00 0.25 0.50 0.75 1.001-Specificity

0.0

00.

250.

50

0.7

51.

00S

ens

itivi

ty

0.00 0.25 0.50 0.75 1.001-Specificity

FGF-9

Mesothelin

FGF-9 + Mesothelin

FGF-9

Mesothelin

FGF-9 + Mesothelin

FGF-9

Mesothelin

FGF-9 + Mesothelin

108

3.3 Discussion

This is the first study demonstrating the presence of FGF-9 in MM using three

different methods; ELISA, immunofluorescence and immunohistochemistry. The

detection of FGF-9 was confirmed in two different species, human and murine, and

include all three common histological subtypes of MM: the epitheloid (human CRL-

5820 (Nutt et al., 2010)), sarcomatoid (human JU77 (Delage B. et al., 2011)) and

biphasic subtypes (human CRL-2081 (Delage B. et al., 2011)).

FGF-9 protein is also significantly higher in both cohorts of MM pleural fluids

compared to the other groups totalling to more than 900 samples, further

strengthening our observations from the preliminary pilot experiments using pleural

tissue biopsies.

FGF-9 may aid in differentiating between MM from benign pleural diseases and

metastatic carcinomas when it is measured using ELISA on the pleural fluid

samples, as shown in two different cohorts. FGF-9 was significantly up-regulated

in the MM pleural fluids compared to the metastatic carcinomas and benign

groups. Although the peak concentration of FGF-9 in MM pleural fluids differs

between the cohorts, the overall pattern and fold changes between MM and the

control groups are similar.

Interestingly, FGF-9 correlates very weakly with mesothelin, the current best

biomarker for MM, but its area under the receiver operating curve is still

comparable to that of the mesothelin. FGF-9 may therefore be capturing different

information, separate from mesothelin. Combining both the markers increases the

diagnostic validity to differentiate MM from non-MM. The capability of detecting

109

FGF-9 in pleural fluids presents a minimally invasive method of diagnosing MM

from other groups. Furthermore, FGF-9 is stable in pleural fluids after repeated

freeze-thaw cycles implying that the pleural fluids can be stored for later

assessments or further experiments.

Whether FGF-9 increases with the advancing stages of MM is unknown. There are

some MM patients who have undetectable FGF-9 levels in their pleural fluids and

this may represent early stages of the disease. In future, this may be assessed by

measuring FGF-9 in pleural fluid samples during the disease course longitudinally

in patients with indwelling pleural catheters. The role of FGF-9 as a prognostic

mediator should be assessed as well as its role as a disease monitoring tool for

MM especially in evaluating response to treatment. Future studies should also

explore the correlation between FGF-9 levels and survival.

Like mesothelin (Campbell and Kindler, 2011), FGF-9 is raised predominantly in

epitheloid but not in the sarcomatoid subtypes of MM. This may pose as a

limitation for the diagnostic value for FGF-9 although only 10% of the MM cases

are of sarcomatoid subtypes (Suzuki, 2001). Nonetheless, a positive FGF-9 in

pleural fluid still has a strong positive predictive value for diagnosis of MM. Finding

a separate biomarker sensitive to sarcomatoid MM in the future may allow its

combination with FGF-9 to improve the diagnosis for MM.

The immunohistochemistry findings recorded a high percentage of positively-

stained cells in both MM and other cancers groups. Hence the use of this FGF-9

antibody is sensitive to confirm the presence of FGF-9 but not necessarily specific

enough to discern (by intensity of staining) between MM from other cancers.

110

The source of FGF-9 in pleural fluids has not been defined. The many cell types

present in the pleural cavity can all contribute to the overall FGF-9 accumulation.

However, elevated levels of FGF-9 were only observed in the MM pleural fluids but

not in the metastatic carcinomas and benign pleural fluids highly suggest that MM

cells are the key source of pleural fluid FGF-9. These observations also argue

against other infiltrating cells (for example the inflammatory cells) in the pleural

cavity as the main source of FGF-9 as these cells are present in relative

abundance in metastatic pleural cancers and benign pleuritis. Also, these

inflammatory cells such as macrophages (which were stained positive in

immunohistochemistry) are present in highest quantity in peripheral blood. Yet,

FGF-9 levels in plasma are very low, further arguing against these cells as

principal source of FGF-9. The finding that FGF-9 is significantly higher in pleural

fluid over corresponding plasma is consistent with the hypothesis that FGF-9 was

produced by pleural MM cells and that a fraction of it is absorbed systemically. As

currently FGF-9 cannot be detected in the plasma, it cannot be used as an early

diagnostic test nor can it be used as a minimally invasive method to monitor the

disease. Also, FGF-9 is unable to be used as a screening marker in the 5 – 10% of

MM cases that do not develop pleural fluids.

It is interesting that in MM cell culture, FGF-9 is not secreted into the cell

supernatants but FGF-9 is readily secreted into the pleural fluids in patients. This

implies additional mechanisms present in vivo that causes FGF-9 to be released

out from the cells into the pleural fluids. The exact value of this mechanism is

beyond the scope of this thesis. This result however does present a potential

regulatory step of FGF-9 release which may contribute to its total activity in tissues

or tumours.

111

How confident are we that we are detecting FGF-9 and not other FGFs? Based

from the datasheets provided by the manufacturing companies, the antibody for

FGF-9 used in immunohistochemistry and ELISA is specific to human, rat and

mouse FGF-9. The epitope of the human FGF-9 antibody purchased for

immunohistochemistry corresponds to the amino acids 1 – 208 representing the

full length of human FGF-9. FGF-9 has only a 30% sequence identity with all the

other members of the family (Hecht et al., 1995) and the datasheet provided stated

clearly that the antibody does not cross-react with the other FGFs (FGFs-1, 2, 4 –

7) and even the FGF-16 which is in the same subfamily as FGF-9. Besides, the

primers used in RT-PCR are specific to FGF-9. Information on the Refseq

accession number and reference position provided by the manufacturing company

(Qiagen) was checked using the NCBI database. Products obtained from real-time

experiments were electrophoresed through an agarose gel to confirm that the band

size corresponds to the size information provided in the datasheet. All of these

make us confident in knowing that we are detecting the correct molecule and that

FGF-9 is truly over-expressed in MM.

Colvin et al. have illustrated the presence of FGF-9 in the mesothelium even after

embryonic development (Colvin et al., 1999). Aberrant FGF-9 activity has been

implicated recently in brain tumours, prostate cancers and lung adenocarcinomas

(Todo et al., 1998, Chien-Kai et al., 2009, Giri et al., 1999). Since MM cells in the

pleura are exposed to high concentrations of FGF-9 in the pleural fluids, it is likely

that FGF-9 may play a role in the pathobiology of MM.

In the following chapters, we followed up the above observations to study if FGF-9

contributes to the pathogenesis of MM, using in vitro and in vivo models.

112

____________________________________________

THE BIOLOGICAL ROLE OF FIBROBLAST GROWTH

FACTOR-9 IN MALIGNANT MESOTHELIOMA

CHAPTER 4

113

4.0 THE BIOLOGICAL ROLE OF FIBROBLAST GROWTH FACTOR-9 IN

MALIGNANT MESOTHELIOMA

4.1 Introduction

Since FGF-9 expression is elevated in MM at the RNA and protein levels in five

different cohorts, this molecule may have important biological role in the MM

disease pathobiology. As FGF-9 is secreted by MM cells into the pleural fluids and

since MM cells in the pleura are surrounded with elevated levels of FGF-9 in the

pleural fluids, it is probable that FGF-9 elicits an effect on the MM cells. Hence, the

role of FGF-9 in MM warrants investigation.

This chapter explores the hypothesis that FGF-9 plays a vital role in MM

pathobiology including cell proliferation, invasion and metastasis. Human and

murine MM cells were used to test this hypothesis.

4.2 Results

4.2.1 MM Cells Proliferation In Vitro in Response to FGF-9 Stimulation

FGF-9 is known to promote growth in some cancers such as glioma (Todo et al.,

1998) and lung adenocarcinoma (Chien-Kai et al., 2009). Hence, the mitogenic

role of FGF-9 in MM was examined using a commercially available WST-1 assay.

An optimisation experiment was first performed to select the best cell density for

WST-1 assay. Human NO36 and murine AB1 cell lines were selected for this

optimisation study as they were available at that time and they adhere to plastic

the quickest. Figure 4.1 shows a relatively linear relationship between cell density

and absorbance value for both the human NO36 and murine AB1 cell lines, until

50 x 103 cells/well when the absorbance values increased dramatically and

reached a plateau. 3 x 103 cells/well was then selected as the sub-optimal cell

114

Human NO36

1 3 5 7 9 10 30 50 70 90 100

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

Cell density (x103 cells per well)

Ab

sorb

ance

(A

450nm

- A

650nm

)

Murine AB1

1 3 5 7 9 10 30 50 70 90 100

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75

2.00

Cell density (x103 cells per well)

Ab

sorb

ance

(A

450nm

- A

650nm

)

density for WST-1 assay to allow for a dramatic increase in cell proliferation that is

still within the detection limit of the plate reader for this assay.

Figure 4.1: Optimisation of cell density for MM cell proliferation.

MM cells (A) human NO36 (B) murine AB1 were plated at a range from 1 to 100 x

103 cells/well in 96-well microtiter plates and incubated for at least 7 hours for cells

to adhere to plastic. Cell proliferation was assessed using WST-1 reagent as

described in the Materials and Methods section. Values are expressed as mean ±

SEM of six replicates from a representative experiment conducted twice.

4.1A 4.1B

n = 6 per group

115

The proliferative effects of FGF-9 on MM cells were then examined on three

human (NO36, ONE58 and STY) and three murine (AB22, AE5 and AE17) MM

cells. Figure 4.2 demonstrates that increasing concentrations of FGF-9 increases

MM cell proliferation in the human and murine MM cell lines, showing that FGF-9 is

an important mitogen factor for MM cells.

Figure 4.2: Dose-dependent MM cell proliferation.

MM cells, three human (A) NO36 (B) ONE58 (C) STY and three murine (D) AB22

(E) AE5 (F) AE17, were stimulated with human or murine recombinant FGF-9 in

increasing log concentrations for 48 hours and cell proliferation was assessed

using WST-1 reagent as described in the Materials and Methods section. Values

are expressed as mean ± SEM of nine replicates from a representative experiment

conducted four times.

4.2A

Human NO36

0 1 10 100 10% FBS

0.0

0.5

1.0

1.5

2.0

2.5

3.0

** ***

***

[FGF-9] (ng/mL)

Fo

ld i

ncr

ease

ov

er s

erum

-fre

e co

ntr

ol

4.2B

Human ONE58

0 1 10 100 10% FBS

0.80

0.85

0.90

0.95

1.00

1.05

1.10

1.15

1.20

*

***

[FGF-9] (ng/mL)

Fo

ld i

ncr

ease

ov

er s

erum

-fre

e co

ntr

ol

116

4.2C

Human STY

0 1 10 100 10% FBS

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75

2.00

* *

***

[FGF-9] (ng/mL)

Fo

ld i

ncr

ease

over

ser

um

-fre

e co

ntr

ol

4.2D

Murine AB22

0 1 10 100 10% FBS

0.0

0.5

1.0

1.5

2.0

2.5

***

*** ***

[FGF-9] (ng/mL)

Fold

incr

eas

e over

ser

um

-fre

e contr

ol

4.2E

Murine AE5

0 1 10 100 10% FBS

0.0

0.5

1.0

1.5

2.0

2.5

3.0

******

***

[FGF-9] (ng/mL)

Fo

ld i

ncr

ease

ov

er s

eru

m-f

ree

con

tro

l

4.2F

Murine AE17

0 1 10 100 10% FBS

0

1

2

3

4

5

6

***

***

***

[FGF-9] (ng/mL)

Fo

ld i

ncr

ease

ov

er s

eru

m-f

ree

con

tro

l

n = 9 per group

*p<0.05, **p=0.001, ***p<0.001 compared to non-stimulated cells, ANOVA

followed by Student-Newman-Keuls post-hoc test

117

The human and murine MM cell proliferation stimulated by exogenous recombinant

FGF-9 protein was validated using Trypan Blue cell exclusion assay. Figure 4.3

shows the dose-dependent MM cell proliferation of human JU77 in response to

exogenous human recombinant FGF-9 stimulation over two weeks, validating the

mitotic effect of FGF-9 on MM cells as assessed by WST-1.

Figure 4.3: Dose-dependent MM cell proliferation using Trypan Blue.

MM cells, human JU77, were plated at 1 x 104 cells/well in 12-well plates, serum-

starved overnight prior to stimulation with human recombinant FGF-9 resuspended

at 20 ng/mL in a final volume of 1000 µL in 1% FBS media. Cell proliferation was

assessed using trypan blue as described in the Materials and Methods section at

1, 3, 6, 10 and 14 days. Values are expressed as mean ± SEM of six replicates

from a representative experiment conducted twice.

n = 6 per group

*p<0.05, ***p<0.001 compared to non-stimulated cells, ANOVA followed by

Student-Newman-Keuls post-hoc test

0.E+00

2.E+05

4.E+05

6.E+05

8.E+05

1.E+06

1.E+06

1.E+06

1 3 6 10 14

Days

To

tal

nu

mb

er o

f cell

s

Control

20ng/ml FGF9

10% serum

***p = 0.0001

*p = 0.001

118

Following from the dose-dependent cell proliferation, the same cell lines were used

to examine the mitotic effects of exogenous recombinant FGF-9 in a time-course

experiment. Figure 4.4 shows the time-dependent cell proliferation of these cell

lines in response to FGF-9 stimulation.

Figure 4.4: Time-dependent MM cell proliferation.

MM cells, human (A) NO36 (B) ONE58 (C) STY and murine (D) AB22 (E) AE5 (F)

AE17, were stimulated with human or murine recombinant FGF-9 at a

concentration of 100 ng/mL for 0, 24, 48 and 72 hours and cell proliferation was

assessed using WST-1 reagent as described in the Materials and Methods

section. Unstimulated cells served as a negative control. Values are expressed as

mean ± SEM of nine replicates from a representative experiment conducted four

times.

4.4A

Human NO36

0 24 48 72

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

*

******

Duration of stimulation (hours)

Fo

ld i

ncre

ase

ov

er

seru

m-f

ree

co

ntr

ol

4.4B

Human ONE58

0 24 48 72

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

**

******


Fo

ld i

ncr

ease

ov

er s

eru

m-f

ree

con

tro

l

119

4.4C

Human STY

0 24 48 72

0.8

0.9

1.0

1.1

1.2

1.3

* *


Fo

ld i

ncre

ase

ov

er

seru

m-f

ree

co

ntr

ol

4.4D

Murine AB22

0 24 48 72

0

1

2

3

4

***

***


Fo

ld i

ncre

ase

over

seru

m-f

ree

co

ntr

ol

4.4E

Murine AE5

0 24 48 72

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

******

***


Fo

ld i

ncre

ase

ov

er s

eru

m-f

ree c

on

tro

l

4.4F

Murine AE17

0 24 48 72

0.0

0.5

1.0

1.5

2.0

2.5

∗

∗

******


Fold

in

cre

ase

over

seru

m-f

ree c

on

tro

l

n = 9 per group



120

4.2.2 Cytokines and Chemokines Release in Response to FGF-9 Stimulation

The release of important cytokines and chemokines known to be playing a role in

the MM pathobiology was also examined using commercially available ELISA kits.

Increasing concentrations of FGF-9 stimulates the release of IL-8 or MIP-2 (murine

homolog of IL-8) (Figure 4.5), MCP-1 (Figure 4.6) and VEGF (Figure 4.7) in MM

cells in both the two species. In addition to that, exogenous FGF-9 stimulated time-

dependent release of the above-mentioned cytokines and chemokines in the same

cell lines tested (Figure 4.8). FGF-9 mediated the release of other cytokines

involved in MM pathobiology represents another means by which FGF-9 regulates

MM proliferation.

Figure 4.5: IL-8 and MIP-2 release from human and murine MM cells.

Five human (A) LO68 (B) NO36 (C) STY (D) CRL-2081 (E) CRL-5820 and three

murine MM cells (F) AB1 (G) AB2 (H) AB22 were stimulated with increasing log

concentrations of human or murine recombinant FGF-9 for 24 hours. IL-8 or MIP-2

present in the supernatants was quantitated using ELISA. Values are expressed

as mean ± SEM of three to eight replicates from a representative experiment

conducted thrice.

4.5A

Human LO68

0 1 10 100 1000

0

20

40

60

80

100

120

140

160

[FGF-9] (ng/mL)

[IL

-8]

(pg/m

L)

***

******

4.5B

Human NO36

0 1 10 100 1000

0

25

50

75

100

125

150

175

∗

∗

∗

[FGF-9] (ng/mL)

[IL

-8]

(pg

/mL

)

121

4.5C

Human STY

0 1 10 100 1000

0

50

100

150

200

250

300

[FGF-9] (ng/mL)

[IL

-8]

(pg/m

L)

***

*** ***

4.5D

Human CRL-2081

0 1 10 100 1000

0

100

200

300

400

500

600

700

800

[FGF-9] (ng/mL)

[IL

-8]

(pg/m

L)

*

*

4.5E

Human CRL-5820

0 1 10 100 1000

0

100

200

300

400

500

600 ∗∗

[FGF-9] (ng/mL)

[IL

-8]

(pg

/mL

)

4.5F

Murine AB1

0 1 10 100 1000

0

20

40

60

80

100

[FGF-9] (ng/mL)

[MIP

-2]

(pg/m

L)*** ***

*

4.5G

Murine AB2

0 1 10 100 1000

0

5

10

15

20

25

30

[FGF-9] (ng/mL)

[MIP

-2]

(pg/m

L)

***

***

***

4.5H

Murine AB22

0 1 10 100 1000

0

20

40

60

80

100

120

140

∗

∗

[FGF-9] (ng/mL)

[MIP

-2]

(pg

/mL

)

n = 3 – 8



122

Figure 4.6: MCP-1 release from human and murine MM cells.

Human MM cells (A) LO68 (B) NO36 (C) STY (D) CRL-5820 and murine MM cells

(E) AB22 (F) AC29 (G) AE5 (H) AE17 were stimulated with increasing log

concentrations of human or murine recombinant FGF-9 for 24 hours. MCP-1

present in the supernatants was quantitated using ELISA. Values are expressed

as mean ± SEM of three to eight replicates from a representative experiment

conducted thrice.

4.6A

Human LO68

0 1 10 100 1000

0

250

500

750

1000

1250

1500

∗

∗

[FGF-9] (ng/mL)

[MC

P-1

] (p

g/m

L)

4.6B

Human NO36

0 1 10 100 1000

0

2000

4000

6000

8000

∗∗

∗

[FGF-9] (ng/mL)

[MC

P-1

] (p

g/m

L)

4.6C

Human STY

0 1 10 100 1000

0

200

400

600

800

1000

1200

1400

∗

∗

[FGF-9] (ng/mL)

[MC

P-1

] (p

g/m

L)

4.6D

Human CRL-5820

0 1 10 100 1000

0

50

100

150

200

250

300

[FGF-9] (ng/mL)

[MC

P-1

] (p

g/m

L) ***

*

123

4.6E

Murine AB22

0 1 10 100 1000

0

2000

4000

6000

8000

10000

∗

∗

∗

∗

[FGF-9] (ng/mL)

[MC

P-1

] (p

g/m

L)

4.6F

Murine AC29

0 1 10 100 1000

0

500

1000

1500

2000

2500

3000

3500

[FGF-9] (ng/mL)

[MC

P-1

] (p

g/m

L)

*** ***

***

4.6G

Murine AE5

0 1 10 100 1000

0

500

1000

1500

2000

2500

∗

∗

∗

[FGF-9] (ng/mL)

[MC

P-1

] (p

g/m

L)

4.6H

Murine AE17

0 1 10 100 1000

0

500

1000

1500

2000

[FGF-9] (ng/mL)

[MC

P-1

] (p

g/m

L)

***

******

.

n = 3 – 8



124

Figure 4.7: VEGF release from human and murine MM cells.

Human MM cells (A) LO68 (B) NO36 (C) STY (D) CRL-2081 (E) CRL-5820 and

murine MM cells (F) AB1 (G) AB2 (H) AB22 (I) AE5 (J) AE17 were stimulated with

increasing log concentrations of human or murine recombinant FGF-9 for 24

hours. VEGF present in the supernatants was quantitated using ELISA. Values are

expressed as mean ± SEM of three to eight replicates from a representative

experiment conducted thrice.

4.7A

Human LO68

0 1 10 100 1000

0

20

40

60

80

∗ ∗

[FGF-9] (ng/mL)

[VE

GF

] (p

g/m

L)

4.7B

Human NO36

0 1 10 100 1000

0

25

50

75

100

125

150

∗ ∗∗

[FGF-9] (ng/mL)

[VE

GF

] (p

g/m

L)

4.7C

Human STY

0 1 10 100 1000

0

20

40

60

80

∗

∗

[FGF-9] (ng/mL)

[VE

GF

] (p

g/m

L)

4.7D

Human CRL-2081

0 1 10 100 1000

0

200

400

600

800

1000

1200

∗ ∗

[FGF-9] (ng/mL)

[VE

GF

] (p

g/m

L)

125

4.7E

Human CRL-5820

0 1 10 100 1000

0

500

1000

1500

2000

2500

∗

∗

[FGF-9] (ng/mL)

[VE

GF

] (p

g/m

L)

4.7F

Murine AB1

0 1 10 100 1000

0

500

1000

1500

2000

2500

3000

∗

∗

∗ ∗

[FGF-9] (ng/mL)

[VE

GF

] (p

g/m

L)

4.7G

Murine AB2

0 1 10 100 1000

0

400

800

1200

1600

∗

∗

∗ ∗

[FGF-9] (ng/mL)

[VE

GF

] (p

g/m

L)

4.7H

Murine AB22

0 1 10 100 1000

0

400

800

1200

1600

∗

∗

∗ ∗

[FGF-9] (ng/mL)

[VE

GF

] (p

g/m

L)

4.7I

Murine AE5

0 1 10 100 1000

0

200

400

600

800

1000

∗∗

∗

∗

[FGF-9] (ng/mL)

[VE

GF

] (p

g/m

L)

4.7J

Murine AE17

0 1 10 100 1000

0

20

40

60

80

100

120

140

∗

∗

[FGF-9] (ng/mL)

[VE

GF

] (p

g/m

L)

n = 3 – 8

*p<0.05 compared to non-stimulated cells, ANOVA followed by Student-Newman-

Keuls post-hoc test

126

Figure 4.8: Time-dependent cytokine release from human and murine MM

cells.

Human MM cells, CRL-2081, CRL-5820, LO68 and NO36 and murine MM cells,

AB1 and AB22 were stimulated with 100 ng/mL human or murine recombinant

FGF-9 for for 0, 2, 8, 24, 48 and 72 hours. (A, B) IL-8, (C, D, I, J) MCP-1, (E, F, K,

L) VEGF and (G, H) MIP-2 present in the supernatants were quantitated using

ELISA. Values are expressed as mean ± SEM of three to eight replicates from a

representative experiment conducted thrice.

4.8A

Human CRL-2081

0 2 8 24 48 72

0

200

400

600

800

1000

∗ ∗

∗

∗

∗


[IL

-8]

(pg/m

L)

4.8B

Human CRL-5820

0 2 8 24 48 72

0

200

400

600

800

1000

∗∗

∗

∗

∗


[IL

-8]

(pg/m

L)

4.8C

Human LO68

0 2 8 24 48 72

0

400

800

1200

1600

∗

∗∗

∗

∗

∗


[MC

P-1

] (p

g/m

L)

4.8D

Human NO36

0 2 8 24 48 72

0

2000

4000

6000

8000

∗ ∗ ∗∗

∗


[MC

P-1

] (p

g/m

L)

127

4.8E

Human CRL-2081

0 2 8 24 48 72

0

200

400

600

800

1000

1200

1400

1600

∗∗

∗

∗


[VE

GF

] (p

g/m

L)

4.8F

Human CRL-5820

0 2 8 24 48 72

0

150

300

450

600

750

900

1050

1200

∗ ∗

∗

∗

∗


[VE

GF

] (p

g/m

L)

4.8G

Murine AB1

0 2 8 24 48 72

0.0

2.5

5.0

7.5

10.0

12.5

15.0

17.5

20.0 ∗


[MIP

-2]

(pg/m

L)

4.8H

Murine AB22

0 2 8 24 48 72

0

10

20

30

40

50

60

70

∗

∗

∗


[MIP

-2]

(pg/m

L)

4.8I

Murine AB1

0 2 8 24 48 72

0

200

400

600

800

1000

∗

∗

∗


[MC

P-1

] (p

g/m

L)

4.8J

Murine AB22

0 2 8 24 48 72

0

500

1000

1500

2000

2500

3000

∗

∗

∗ ∗

∗


[MC

P-1

] (p

g/m

L)

128

4.8K

Murine AB1

0 2 8 24 48 72

0

200

400

600

800

∗

∗

∗

∗ ∗


[VE

GF

] (p

g/m

L)

4.8L

Murine AB22

0 2 8 24 48 72

0

200

400

600

800

1000

1200

1400

∗

∗

∗

∗ ∗


[VE

GF

] (p

g/m

L)

n = 3 – 8


Keuls post-hoc test

129

4.2.3 The Effects of Antibody Neutralisation on Cytokine Release

To clarify the contribution of FGF-9 in cytokine release by MM cells, MM cells were

pre-treated with a monoclonal anti-human FGF-9 antibody prior to FGF-9

stimulation. Prior to that, the IC50 for the FGF-9 antibody to inhibit FGF-9 activity

was determined. The monoclonal anti-human FGF-9 antibody is not only specific

to human, as there have been published studies using this antibody in murine (Li

et al., 2008), rat (Jui-Yen et al., 2009) and pig cells (Kinkl et al., 2003). Murine

AB22 cells were chosen for this optimisation study as this cell line released a high

level of VEGF in response to FGF-9. Figure 4.9 shows that the suboptimal

concentration of FGF-9 antibody against VEGF release was 10 µg/mL.

Figure 4.9: Optimisation of neutralising antibody concentration.

5 x 104 murine AB22 cells were pretreated with 0.1 – 100 µg/mL monoclonal anti-

human FGF-9 antibody or 100 µg/mL mouse IgG2A isotype control resuspended in

serum-free media for 30 minutes before they were stimulated with 100 ng/mL

murine recombinant FGF-9 for 24 hours. Untreated cells served as a negative

control whereas cells treated with 100 ng/mL FGF-9 alone serve as a positive

control. The supernatants were harvested and assayed for VEGF release. Values

are expressed as mean ± SEM of two replicates from an experiment.

Murine AB22

SFM FGF-9 +0.1 +1 +10 +100 +IgG2A

0

200

400

600

800

[FGF-9 Ab] (µg/mL)

Treatment

[VE

GF

] (p

g/m

L)

n = 2 per group

130

Following the pilot optimisation study, murine MM AB22 cells were pretreated with

the suboptimal concentration of FGF-9 antibody or mouse IgG2A isotype control at

10 µg/mL prior to stimulation with 100 ng/mL murine recombinant FGF-9 for 24

hours. Figure 4.10 shows that the FGF-9 antibody significantly reduced the levels

of MIP-2, MCP-1 and VEGF in the AB22 cells. The negative IgG2A isotype control

had only little attenuation effect on the FGF-9 stimulated cytokine release,

demonstrating that the release of cytokine is a result of FGF-9 stimulation. This is

consistent with other reports demonstrating the role of FGF-9 using neutralizing

antibody, in prostate cancer cells (Li et al., 2008, Teishima et al., 2012) and lung

adenocarcinomas (Ueng et al., 2010).

131

Figure 4.10: Inhibition of cytokine release from murine MM cells using

antibody neutralisation.

Murine MM AB22 were pretreated with monoclonal anti-human FGF-9 antibody or

mouse IgG2A isotype control, at a final concentration of 10 µg/mL, for 30 minutes

before stimulated with 100 ng/mL murine recombinant FGF-9 for 24 hours. (A)

MIP-2 (B) MCP-1 and (C) VEGF present in the supernatants were quantitated

using ELISA. Values are expressed as mean ± SEM of six replicates from a


4.10A

MIP-2 (pg/mL)

SFM FGF9 +αFGF9+IgG2A

0

50

100

150

200

250

∗

∗

***

Treatment

4.10B

[MCP-1] (pg/mL)

SFM FGF-9 +αFGF9 +IgG2A

0

4000

8000

12000

16000

***

***

***

Treatment

4.10C

[VEGF] (pg/mL)

SFM FGF9 +αFGF9+IgG2A

0

200

400

600

800

∗

∗

∗

Treatment

n = 6 per group

*p<0.05, ***p<0.001 compared FGF-9-stimulated treatment, ANOVA followed by

132

4.2.4 The Effects of Pathway Inhibitors on FGF-9-Stimulated MM Cells

There have been several studies demonstrating that FGF-9 acts through the ERK

pathway (Antoine et al., 2007, Wing et al., 2005). We were also interested to

examine if FGF-9 could elicit its effects through the JNK and p38 pathways too.

Hence, inhibition studies were conducted in the presence or absence of 3

pharmacological inhibitors of different signalling pathways, PD98059 (ERK

inhibitor), SP600125 (JNK inhibitor II) and SB203580 (p38 inhibitor) (all from Merck

Pty Limited, Kilsyth, Victoria, Australia). FGF-9-stimulated proliferation was

moderately inhibited by the ERK inhibitor in the human cells (Figure 4.11A and B),

but so significantly in the murine cells (Figures 4.11C and D). Both the JNK and

p38 inhibitors significantly inhibited cell proliferation in the two cell lines.

On the other hand, Figures 4.12A and B depicts that the p38 inhibitor was unable

to inhibit IL-8 release in the human MM cell (Figures 4.12A and B), but significantly

reduced MCP-1 and VEGF levels in the human and murine MM cells (Figures

4.12C – F). The ERK and the JNK inhibitors are potent in inhibiting all three

cytokine release caused by FGF-9 stimulation in the human and murine MM cells,

suggesting that FGF-9 could be mediating its effects in cytokine release through

the ERK and JNK pathways.

133

Figure 4.11: FGF-9 mediated MM cell proliferation is inhibited by ERK, JNK

and p38 pathway inhibitors.

MM cells, human (A) NO36 (B) ONE58 and murine (C) AB22 (D) AE17 were

pretreated for 30 minutes with ERK inhibitor, PD98059, JNK inhibitor, SP600125 or

p38 inhibitor, SB203580, at final concentrations of 50 µM, 10 µM and 10 µM

respectively. A vehicle control for the inhibitors, DMSO at the final concentration of

0.1%, was also conducted. The cells were then stimulated with 100 ng/mL human

or murine recombinant FGF-9 for 48 hours and inhibition of cell proliferation was

assessed using WST-1 reagent. Values are expressed as mean ± SEM of nine

replicates from a representative experiment.

4.11A

Human NO36

0

20

40

60

80

100

∗∗

Cel

l pro

life

rati

on

(% o

f F

GF

-9 s

tim

ula

ted r

esp

onse

)

FGF-9 + + + + + DMSO - + - - - PD98059 - - + - - SP600125 - - - + - SB203580 - - - - +

4.11B

Human ONE58

0

20

40

60

80

100

∗

∗

Cel

l pro

life

rati

on

(% o

f F

GF

-9 s

tim

ula

ted r

esponse

)

FGF-9 + + + + + DMSO - + - - - PD98059 - - + - - SP600125 - - - + - SB203580 - - - - +

134

4.11C

Murine AB22

0

20

40

60

80

100

∗

∗

∗

∗

Cell

pro

life

rati

on

(% o

f F

GF

-9 s

tim

ula

ted r

esp

onse

)

FGF-9 + + + + + DMSO - + - - - PD98059 - - + - - SP600125 - - - + - SB203580 - - - - +

4.11D

Murine AE17

0

20

40

60

80

100∗

∗

∗

∗

Cel

l p

roli

fera

tio

n

(% o

f F

GF

-9 s

tim

ula

ted r

esp

on

se)

FGF-9 + + + + + DMSO - + - - - PD98059 - - + - - SP600125 - - - + - SB203580 - - - - +

n = 9 per group

*p<0.05 compared to FGF-9-stimulated cells, ANOVA followed by Student-

Newman-Keuls post-hoc test

135

Figure 4.12: Inhibition of cytokine release from human and murine MM cells.

Human CRL-2081, CRL-5820, LO68, NO36 and murine AE17, AB1, AB22 MM

cells were pretreated with MAPK inhibitors, ERK inhibitor (ERK i), JNK inhibitor

(JNK i) and p38 inhibitor (p38 i), at final concentrations of 50 µM, 10 µM and 10 µM

respectively, for 30 minutes. DMSO was used as a vehicle control. 100 ng/mL

human or murine recombinant FGF-9 was added for 24 hours. (A, B) IL-8, (C, D,

G, H) MCP-1 and (E, F, I, J) VEGF present in the supernatants were quantitated

using ELISA. Values are expressed as mean ± SEM of six replicates from a

representative experiment.

4.12A

Human CRL-2081

FGF-9 +DMSO+ERK i+ JNK i +p38 i

0

20

40

60

80

100 ∗

∗ ∗

Treatment

% I

L-8

rel

eas

e over

FG

F-9

contr

ol

4.12B

Human CRL-5820


0

20

40

60

80

100

120

∗∗

Treatment

% I

L-8

rele

ase

over

FG

F-9

contr

ol

4.12C

Human LO68


0

20

40

60

80

100

∗

∗

∗

Treatment

% M

CP

-1 r

ele

ase

over

FG

F-9

contr

ol

4.12D

Human NO36


0

20

40

60

80

100

∗

∗∗

∗

Treatment

% M

CP

-1 r

eleas

e over

FG

F-9

contr

ol

136

4.12E

Human CRL-2081


0

20

40

60

80

100

∗

∗

∗

∗

∗

Treatment

% V

EG

F r

ele

ase

over

FG

F-9

contr

ol

4.12F

Human CRL-5820


0

20

40

60

80

100

∗

∗

∗ ∗

Treatment

% V

EG

F r

eleas

e over

FG

F-9

contr

ol

4.12G

Murine AE17

FGF-9 +DMSO+ERK i + JNK i +p38 i

0

20

40

60

80

100∗

∗

∗

∗

Treatment

%

MC

P-1

rel

ease

over

FG

F-9

con

trol

4.12H

Murine AB22


0

20

40

60

80

100

∗

∗

∗

∗

Treatment

% M

CP

-1 r

elease

ov

er

FG

F-9

co

ntr

ol

4.12I

Murine AB1


0

20

40

60

80

100

∗ ∗

∗

Treatment

% V

EG

F r

ele

ase o

ver

FG

F-9

contr

ol

4.12J

Murine AB22


0

20

40

60

80

100

∗

∗ ∗

∗

Treatment

% V

EG

F r

elease

ov

er

FG

F-9

co

ntr

ol

n = 6 per group

*p<0.05 compared to FGF-9-stimulated cells, ANOVA followed by Student-

Newman-Keuls post-hoc test

137

To validate if the pharmacological inhibitors were specific in inhibiting their target

pathways, Western Blot was conducted to visualise the phosphorylation of the

target proteins, ERK, JNK and p38. Figure 4.13 depicts that in the human CRL-

2081 MM cells and murine AB22, FGF-9 stimulation causes an increase in ERK

phosphorylation and this phosphorylation was reduced by the ERK inhibitor,

demonstrating the specificity of the ERK inhibitor to the target ERK protein. A

similar image was also seen in the JNK phosphorylation in the human MM cells

and in the p38 phosphorylation in the murine MM cells. Surprisingly, JNK protein

phosphorylation was increased in response to the JNK inhibitor in the murine MM

cells. This was also the case for the p38 protein in the human MM cells.

Figure 4.13: Phosphorylation of proteins downstream of FGF-9 signalling

pathway.

Phosphorylation of proteins involved in the ERK, JNK and p38 pathway were

studied using Western blotting assays. The images are a representative image

from experiments conducted thrice. i = inhibitor.

Human CRL-2081 Murine AB22 p-ERK +ERKi +DMSO FGF-9 SFM

+ERKi +DMSO FGF-9 SFM

p-JNK +JNKi +DMSO FGF-9 SFM

+JNKi +DMSO FGF-9 SFM

p-p38 +p38i +DMSO FGF-9 SFM

+p38i +DMSO FGF-9 SFM

Beta actin

138

4.2.5 The Role of FGF-9 in MM Cell Invasion

The role of FGF-9 in MM pathobiology in the context of tumour cell invasion was

also studied using Matrigel transwell assay. It has been shown that FGF-9

promotes invasion in prostate cancer cell (Teishima et al., 2012) as well as

epithelial and endothelial cells (Hendrix et al., 2006). Figure 4.14 shows that FGF-

9 at 100 ng/mL also stimulates MM cell invasion by 24 hours.

Figure 4.14: FGF-9 stimulates MM cell invasion.

Human MM CRL-2081 cells were seeded at a concentration of 1 x 104 cells in the

upper compartment of the Matrigel-coated inserts. 100 ng/mL FGF-9 (or serum-

free media (SFM) as negative control) was added to the companion plates. Cell

invasion was measured 16 and 24 hours post-stimulation. The Matrigel-coated

insert membranes were stained with Diff-Quick solution and invading cells were

counted. Values are expressed as a mean ± SEM of three replicates from a


CRL-2081 invasion in response to

FGF-9 (100 ng/mL) for 16 and 24 hours

0

100

200

300

400

500

600*

Cel

l n

um

ber

(co

un

ted a

cross

the

slid

e

at 1

0X

mag

nif

icati

on

)

n = 3 per group


Keuls post-hoc test

SFM FGF-9 FGF-9

24 hours 16 hours 24 hours

139

4.2.6 The Involvement of FGF-9 in MM Cell Migration

MM is also potent factor that stimulates cell migration of endothelial and ovarian

cancer cells (Hendrix and Cho, 2005). Treatment with FGF-9 potently stimulated

cell migration in all human and murine MM cells tested. Representative scratch

assay results are shown in Figure 4.15A. The scratch gap was almost closed by 48

hours in the FGF-9 stimulated cells, which is similar to the positive control cells

that were incubated in 10% FBS media. Figure 4.15B-E shows the percentage

increase of cell migration over 0 hour quantitated on two human and two murine

cell lines, using the formula stated in Section 2.4.4.

Figure 4.15: FGF-9 stimulates MM cell migration.

(A) Representative images of MM cell migration following FGF-9 stimulation over

time. Human (B) ONE58 and (C) STY and (D) murine AB22 and (E) AE17 were

seeded in a tissue culture dish until confluent. A 1000 mL pipette tip was used to

scratch the surface of the culture dish. The cells were stimulated with human or

murine recombinant FGF-9 resuspended at 100 ng/mL and cell migration was

analysed under the microscope. Values are expressed as a mean ± SEM of three

replicates from a representative experiment conducted thrice.

140

0 hr 24 hrs 48 hrs 72 hrs SFM

FGF-9

10% FBS

4.15A

141

4.15B

Human ONE58

24 48 72

0

25

50

75

100

SFMFGF-9FBS***

***

******

***

***


Per

cen

tag

e in

crea

se o

f

cell

mig

rati

on

ov

er 0

ho

ur

4.15C

Human STY

24 48 72

0

25

50

75

100SFMFGF-9FBS

***

******

******


Per

cen

tag

e in

crea

se o

f

cell

mig

rati

on

ov

er 0

ho

ur

4.15D

Murine AB22

6 8 24

0

25

50

75

100

FGF-9SFM

FBS

***

***

Duration (hours)

Per

cen

tag

e in

crea

se o

f

cell

mig

rati

on

ov

er 0

ho

ur

4.15E

Murine AE17

24 48 72

0

25

50

75

100FGF-9SFM

FBS***

*** ***

*

Duration (hours)

Per

cen

tag

e in

crea

se o

f

cell

mig

rati

on

ov

er 0

ho

ur

n = 3 per group



142

4.3 Discussion

Our data shows that exogenous FGF-9 not only promotes dose- and time-

dependent cell proliferation but also stimulates migration and invasion in human

and murine MM cell lines tested. Furthermore, increasing concentrations of FGF-9

increase the release of IL-8, MIP-2, VEGF and MCP-1 in these cell lines.

It has been previously reported that FGF-9 does not induce cell proliferation on

endometrial epithelial cells (Tsai et al., 2002) and human umbilical vein endothelial

cells (Hendrix et al., 2006, Miyamoto et al., 1993). Our studies show that FGF-9 is

a potent mitogen factor for MM cells, consistent with other reports on other cell

lines such as in the human oesophageal epithelial cells (Mulder et al., 2009),

human lung fibroblasts (Chien-Kai et al., 2009), human prostate cancer cells

(Teishima et al., 2012) and rat kidney epithelial cells (Hendrix et al., 2006). Our cell

proliferation assay recorded a higher fold change in the murine cell lines compared

to the human cell lines possibly due to the higher growth rate in the murine cell

lines observed during the routine expansion of cell cultures. Like its role in prostate

cancer cells (Teishima et al., 2012), FGF-9 is involved in MM cell invasion

suggesting that this growth factor may be playing a role in tumour spread and

invasion.

MM cells secrete important cytokines known to be playing a role in the MM

pathobiology in response to FGF-9. IL-8 is a known autocrine growth factor for MM

(Galffy et al., 1999a), and would contribute to the potent mitogen effect of FGF-9 in

MM. In addition, FGF-9 may also promote angiogenesis via VEGF stimulation

(Masood et al., 2003). This is consistent with other data illustrating the decreased

VEGF signalling and hence delayed vascularisation in Fgf -/- mice (Hung et al.,

2007). Besides that, FGF-9 may also contribute to the increased vascular

143

permeability and pleural fluid formation by inducing MCP-1 (Stathopoulos et al.,

2008), seen in MM. To our knowledge, there are no studies that have reported the

association between FGF-9 and IL-8, and FGF-9 and MCP-1.

Although MM tumour development is a complex process that is regulated by

signals from numerous growth factors, cytokines and chemokines, which are

influenced by the tumour cell itself and/or the tumour microenvironment, our results

show that FGF-9 may play a part in all of the key processes underpinning MM

tumour growth. The signals generated from the release of IL-8, VEGF and MCP-1

in response to FGF-9 stimulation may be inter-related to each other. IL-8 has been

shown to be involved in angiogenesis and metastasis (Li et al., 2003) while MCP-1

is involved in recruiting immune cells, such as monocytes, to the site of

inflammation, a crucial step in promoting post-ischemic angiogenesis (Li et al.,

1997). Besides, VEGF has been postulated to be an important mediator for pleural

fluid formation and accumulation (Cheng et al., 1999, Kraft et al., 1999, Thickett et

al., 1999). We are not certain if the release of the above-mentioned cytokines were

a direct result of FGF-9 stimulation or if FGF-9 was promoting the release of the

cytokines indirectly via a secondary mediator. This will be a subject of interest in

future studies. Although we cannot detect the release of the other vital mediators in

MM including TNF-α (Stathopoulos et al., 2007), IFN-γ and IL-10 by ELISA in

response to FGF-9 stimulation, we cannot conclude that FGF-9 does not signal to

those cytokines or other mediators that are important in MM such as IL-6 (Monti et

al., 1994), cyclooxygenase-2 (Edwards et al., 2002), transforming growth factor

beta (Fujii et al., 2012) and matrix metalloproteases (Servais et al., 2012).

Our time-dependent cytokine release data demonstrates that FGF-9-induced cells

sustained release of cytokines up to 72 hours indicating an increased production

144

(rather than release of intracellular stores) of the cytokines. Cytokine release was

inhibited by FGF-9 neutralizing antibody demonstrating the specificity of the role of

FGF-9 in the MM pathobiology. This is consistent with the previous studies

showing the potential therapeutic use of FGF-9 neutralizing antibody to abolish

signals generated by FGF-9 (Cinaroglu, 2005, Tsai et al., 2002, Chien-Kai et al.,

2009). Our data further support the need to evaluate the efficacy of FGF-9

neutralizing antibody against MM.

A concentration of 1000 ng/mL of FGF-9 was used in our in vitro studies as the

concentration of FGF-9 at the tumour microenvironment is not known. Despite that,

biological effects were still seen from MM cells at least up to 1000 ng/mL of FGF-9

which shows that the MM cells have a significant ability to respond to FGF-9 at a

concentration 50 times higher than the highest FGF-9 concentration found in our

cohorts of fluids, with no observation signs of necrosis or apoptosis.

The mitogen-activated protein kinase (MAPK) pathways such JNK and ERK

pathways, integrate signals from receptor tyrosine kinases, in this case, FGFRs, to

control cell proliferation and other cellular functions (Mckay and Morrison, 2007).

Hence, we are interested to examine the signal transduction pathways that FGF-9

is involved in, to elicit its effects in MM cells. The present study demonstrates that

whilst FGF-9 could potentially be acting as a mitogen for MM through all three

pathways, the p38 pathway may not be important for cytokine release. This is in

contrast to a previous study reporting that p38 inhibitor does not affect proliferation

in the Muller cell primary cultures (Bugra-Bilge and Cinaroglu, 2005). The disparity

could also be due to the different cell lines used. While inhibiting JNK activity in the

human MM cell line using SP600125 decreased JNK phosphorylation, the same

inhibitor paradoxically increased the phosphorylation of JNK in the murine MM

145

cells. This was also seen when a p38 inhibitor (SB203580) decreased p38

phosphorylation in murine MM cells but not in the human MM cell line tested. This

could be due to the induction of other signalling pathways in response to the

blockade of the JNK and p38 pathways. It was shown that the inhibition of p38 with

SB203580 compound increased the phosphorylation status of p38 in a model of

colitis (Ten Hove et al., 2002). In addition, Kumar et al. reported that the SB203580

compound specifically inhibited the activity of p38 MAPK but not its activation by

upstream map kinase kinase (MAPKK) (Kumar et al., 1999). Further evaluation on

other MM cell lines using different inhibitors that target JNK and p38 proteins and

the other proteins involved in the JNK and p38 signalling cascades is therefore

required.

The FGF family also activates the PI3K as well as the PLCγ signalling cascades

(Eswarakumar et al., 2005, Klint and Claesson-Welsh, 1999). A previous report

has demonstrated that FGF-9 also signals through the PI3K pathway in human

uterine endometrial stromal cells (Wing et al., 2005). To our knowledge, there have

been no studies that have investigated if FGF-9 signals through PLCγ. Evaluation

of these signalling pathways in MM through the examination of downstream

signalling proteins involved and the increase of Ca2+ is warranted in future studies.

There have been studies looking at FGF-9 and sonic hedgehog signalling in lung

development (White et al., 2006, White et al., 2007, Del Moral et al., 2006). As the

role of sonic hedgehog signalling in MM has recently been revealed (Shi et al.,

2012), it will be important to examine if FGF-9 is involved in this signalling pathway

during MM progression. Likewise, interactions between FGF-9 signalling and Wnt

signalling have been shown in lung (Yin et al., 2008) and gonadal development

(Kim et al., 2006) and in the pathology of ovarian endometrioid cancer (Hendrix et

al., 2006). Exploring the interactions between FGF-9 and Wnt signalling in MM is

146

outside the scope of my thesis, but may enhance our understanding of the

complex role of FGF-9 in MM tumour development.

It is unclear how FGF-9 is up-regulated in MM. We speculate that FGF-9 is

produced and secreted in abundance as a result of the malignant transformation of

the benign mesothelial cells to MM cells. Very little is known about the upstream

pathway of FGF-9 in cancers as most studies to date have explored its role during

normal embryogenesis. Scattered studies have emerged recently linking the up-

regulation of FGF-9 mRNA expression in endometrial stromal cells to 17β-estradial

(Tsai et al., 2002) and in lung adenocarcinoma cells to benzo[a]pyrene treatment,

a carcinogen found in cigarette smoke (Chien-Kai et al., 2009). Although asbestos

is the main cause of MM, it is unknown if this mineral can drive up-regulation of

FGF-9 in MM. Searching for stimulation of FGF-9 in the setting of pleural MM

should be explored in future studies.

There are limitations of the experiments presented. The experiments performed

using cell lines bear their intrinsic shortcomings. However, the consistency of

response to FGF-9 among all eight human and six murine cell lines argue strongly

that it is a genuine observation. We have shown for the first time that FGF-9 is

expressed at significant levels in MM tissues and pleural fluids (Chapter 3). In this

study, we mimicked the over-expression of FGF-9 by adding recombinant FGF-9

to MM cells in vitro and have demonstrated that MM cells exhibits a response to

exogenous FGF-9. However, endogenous FGF-9 released by MM cells in vivo

cannot be compared to the exogenous recombinant FGF-9 that we used in our in

vitro studies. Hence, the next chapter explores MM tumour growth in vivo using

MM cells lacking endogenous FGF-9.

147

____________________________________________

THE NECESSITY OF FGF-9 IN MALIGNANT

MESOTHELIOMA TUMOUR GROWTH IN VIVO

CHAPTER 5

148

5.0 THE NECESSITY OF FGF-9 IN MALIGNANT MESOTHELIOMA TUMOUR

GROWTH IN VIVO

5.1 Introduction

In the previous chapter, it was shown that exogenous FGF-9 stimulates MM cell

proliferation, migration, invasion as well as the release of important cytokines that

are crucial for this disease. However, whether FGF-9 has an essential role in MM

development requires exploration. FGF-9 is important during embryonic

development and knockout of FGF-9 is embryonically lethal. As such FGF-9

knockout mice are not available. Hence, a knockdown of FGF-9 in MM cells was

employed to explore the necessity of FGF-9 in MM pathobiology.

5.2 Results

5.2.1 Development of FGF-9 shRNA Knockdown Cells

FGF-9 shRNA knockdown studies were performed on murine AB1 MM cells as

these cells are robust to transfection studies. Four clones were selected from each

shRNA plasmid (sh273, sh496, sh588) and a scrambled vector, making it to a total

of 16 clones that were tested by ELISA for FGF-9 levels. The shRNA clone that

recorded the lowest FGF-9 protein level (sh588) and the scrambled vector that

recorded the highest FGF-9 protein level were selected for further validation by

quantitative real-time PCR. Figure 5.1 shows that FGF-9 protein levels was

successfully reduced by approximately 50% in the FGF-9 shRNA knockdown cells

compared with the scrambled vector controls. Figure 5.2 shows that FGF-9 was

knocked down at the RNA level in the shRNA knockdown cells compared to the

parent and the scrambled vector cell lines control. The data confirms that FGF-9

was successfully knocked-down in the shRNA murine AB1 cell line.

149

Figure 5.1: FGF-9 shRNA knockdown cells have lower levels of FGF-9

protein.

FGF-9 protein levels in cell lysates of FGF-9 shRNA and scrambled control murine

MM cells were determined using ELISA. FGF-9 protein levels in FGF-9 shRNA

knockdown cells were reduced by two fold compared to controls. Values are

expressed as a mean ± SEM of three replicates from a representative experiment

conducted twice.

FGF-9 shRNA Vector

0

1

2

3

4

5

6

7

∗∗∗

Cell lines

FG

F-9

/Tota

l ce

lls

(x10

-5)

(pg/m

L/c

ells

)

n = 3

***p<0.001, t-test

150

Figure 5.2: FGF-9 shRNA knockdown cells have lower levels of FGF-9 mRNA.

FGF-9 mRNA levels in parent, FGF-9 shRNA and scrambled murine MM cell lines

were determined using RT-PCR. FGF-9 mRNA levels in FGF-9 shRNA knockdown

cells were reduced compared to controls. Values are expressed as a mean ± SEM

of six replicates from a representative experiment conducted thrice.

Parent FGF-9 shRNA Vector

0.0

0.5

1.0

1.5

2.0

2.5

*

***

Cell lines

mF

GF

-9 m

RN

A e

xpre

ssio

n

n = 6

*p<0.05, ***p<0.001, ANOVA followed by Student-Newman-Keuls post-hoc test

151

5.2.2 FGF-9 shRNA Knockdown Cells in Heterotopic Model

The successfully transfected cells as well as the parent cell line were then

inoculated into Balb/c mice subcutaneously in an established murine model

(Section 2.9.1). Figure 5.3A shows that there was no adverse effects on the

animals inoculated with the transfected cell lines compared to the parent cell lines.

The animals inoculated with the parent and the vector cell lines developed

significant-sized tumours by Day 17. Mice injected with FGF-9 shRNA knockdown

MM cells had significantly smaller tumours (Figure 5.3B). Figure 5.3C depicts the

representative images of the animals from each group. The parent and vector

groups developed large subcutaneous tumours. On the other hand, there were no

macroscopic tumours seen in the shRNA knockdown group. The data

demonstrates the necessity of FGF-9 in MM tumour development.

Figure 5.3: Knockdown of FGF-9 in MM cells significantly retards their

tumour growth in heterotopic model.

Balb/c mice (n = 10 each group) were injected with 5 x 105 parent MM cell line,

shRNA knockdown MM cells or scrambled vector MM cells. (A) No weight loss

was recorded in mice in all three groups. (B) Tumour dimensions were measured

and animals were sacrificed once tumour size reached the limit of 10 mm x 10 mm

maximum as allowed by the animal ethics committee. Tumour development in

shRNA group was significantly suppressed compared to control groups. (C)

Animals in the parent and vector groups developed large macroscopic tumours

that were not seen in the shRNA knockdown groups.

152

5.3A

0 5 7 10 12 14 17 18

21

22

23

24

25

26

27

28ParentFGF-9 shRNAVector

Days post tumour inoculation

Anim

al W

eight

(g)

n = 10 per group

5.3B

0 5 7 10 12 14 17 18

0102030405060708090

100110

ParentFGF-9 shRNAVector


Tum

our

Siz

e (m

m2)

***

***

n = 10 per group

***p<0.001, ANOVA followed by Student-Newman-Keuls post-hoc test

153

5.3C

Parent

FGF-9 shRNA

Vector

154

5.2.3 FGF-9 shRNA Knockdown Cells in Orthotropic Model

To further confirm these findings, an orthotopic model was employed whereby the

Balb/c mice received a single intraperitoneal injection (Section 2.9.2). As

preliminary pilot experiments conducted showed that tumours developed much

quicker in the intraperitoneal model compared to the subcutaneous model (not

shown), the animals were sacrificed at Day 13. Figure 5.4A again shows that the

animal weights were not affected by the intraperitoneal injection of the transfected

cell lines. The number of tumour nodules in the FGF-9 shRNA knockdown group

was significantly lower compared to the parent and the vector groups (Figure

5.4B). Figure 5.4C depicts the representative images of the numerous and larger

tumours in the parent and the vector groups compared to the fewer and smaller

tumour nodules in the shRNA knockdown group. This confirms the finding of the

subcutaneous flank model and strengthens the finding that FGF-9 is a key factor in

the development of MM tumour.

155

Figure 5.4: shRNA knockdown of FGF-9 significantly reduced MM tumour

growth in intraperitoneal model of disease.

Balb/c mice (n = 10 each group) were injected with 5 x 105 parent MM cell line,


was recorded in the animals as a result of inoculation of transfected cell lines. (B)

Mice in the shRNA knockdown group have fewer tumour nodules compared to the

parent and the vector groups. (C) Animals in the parent and vector groups

developed large macroscopic tumours that were not seen in the shRNA

knockdown groups.

5.4A

0 2 6 9 12 13

19

21

23

25

27

29

FGF9 shRNA

Parent

Vector


Anim

al

Wei

ght

(g)

n = 10 per group

156

5.4B

Parent FGF9 shRNA Vector

0

10

20

30

40

50

Num

ber

of

Tu

mou

r N

odule

s **

n = 10 per group

*p<0.05, ANOVA followed by Student-Newman-Keuls post-hoc test

5.4C

Parent FGF-9 shRNA Vector

157

5.2.4 FGF-9 shRNA Knockdown Cells in Athymic Model

To examine if the immune response in the host system is involved in tumour

growth suppression in the FGF-9 shRNA knockdown group, we inoculated the

transfected and parent cell lines subcutaneously into nude mice that lack a thymus

and hence an inhibited immune system. Figure 5.5A shows that the animal weights

were not affected by the subcutaneous injection of the transfected cell lines while

Figure 5.5B depicts that the tumours developed in the FGF-9 shRNA knockdown

group were as large as the scrambled vector and the parent groups when

measured at the same time point. The data could possibly answer the role of the

immune system on FGF-9 signalling in MM development.

Figure 5.5: shRNA knockdown of FGF-9 had similar MM tumour growth in

athymic model of disease.

Nude mice (n = 7 each group) were injected with 5 x 105 parent MM cell line,


was recorded in the animals as a result of inoculation of transfected cell lines. (B)

Tumour dimensions were measured and animals were sacrificed once tumour size

reached the limit of 10 mm x 10 mm maximum as allowed by the animal ethics

committee. Tumour development in shRNA group was similar compared to control

groups.

158

5.5A

0 4 6 8 11 13 18

15

16

17

18

19

20

21 ParentFGF-9 shRNAVector


Anim

al

Weig

ht

(g)

n = 7 per group

5.5B

0 4 6 8 11 13 18

0

20

40

60

80

100

120

140

ParentFGF-9 shRNAVector


Tum

our

Siz

e (m

m2)

n = 7 per group

159

5.3 Discussion

Our results show that the FGF-9 shRNA knockdown cells had significantly retarded

growth compared to the parent and scrambled vector groups in vivo. Tumours

developed in the FGF-9 shRNA knockdown group in both the subcutaneous and

intraperitoneal models were significantly smaller compared to the controls. On the

other hand, in the nude mice model, the tumours developed in the FGF-9 shRNA

knockdown group were as large as the scrambled vectors and the parent groups

when measured at the same time point, thus implying that the retardation of MM

growth seen in FGF-9 knockdown cells is mediated by immune response.

FGF-9 induces significant biological responses in MM cells (Chapter 4). In this

chapter, we tested the necessity of FGF-9 in the pathobiology of MM using shRNA

to inhibit FGF-9 expression in MM cells. The clones were selected through

puromycin selection and the success of the transfection assay was confirmed by

ELISA and quantitative RT-PCR. While there is no obvious phenotypic difference

in the cells in vitro, the results were dramatic when the cells were inoculated into

mice in our in vivo studies.

Knockdown of FGF-9 expression impacts significantly on its growth in vivo but not

in vitro. The fact that FGF-9 shRNA-treated cells grew significantly slower in both

the subcutaneous and the intraperitoneal models suggests that it is unlikely that

the retardation of tumour growth can be explained by local factors related to the

mesothelial environment or blood and nutrient supply in the host system. This

raised the possibility that FGF-9 allows MM cells to escape immune surveillance

and the knockdown of FGF-9 therefore results in immune clearance of the tumour

cells. Indeed the retardation of tumour growth in FGF-9 shRNA cells no longer

160

exist when athymic mice were used. This strongly implies that FGF-9 inhibits the

cell-mediated immunity and its ability to clear MM cells. Further studies are

currently in progress in our lab to tease out the immune mechanisms involved.

The observed effects from FGF-9 shRNA cells should be specific to the down-

regulation of FGF-9. The sequences were confirmed on the NCBI database and

the real-time PCR and ELISA data show a significant reduction in FGF-9 mRNA

and protein in the shRNA knockdown cells. Care was taken to titrate and use the

lowest shRNA concentration that still gave the desirable effects in knocking down

FGF-9 to reduce the potential off-target effects. Our findings that shRNA

knockdown cells caused slower tumour growth in vivo are in keeping with our data

in previous chapters showing that FGF-9 is a key factor for MM tumour

development. We plan to validate our results with other shRNA clones generated

from different shRNA sequences to the non-overlapping regions of FGF-9. In

addition, we are attempting to reconstitute the levels of FGF-9 in the FGF-9 shRNA

knockdown cells by knocking in FGF-9 into the FGF-9 shRNA cells for further

revalidation.

If FGF-9 is essential during MM development, then antagonising FGF-9 should

attenuate MM growth. However, as FGF-9 is crucial to lung development, knockout

of FGF-9 is lethal due to lung hypoplasia and hence intrauterine death of the mice

(Colvin et al., 2001b). In theory, FGF-9 may be knocked out specifically from the

mesothelium in vivo to generate conditional knockout mice which can be subjected

to asbestos inhalation to generate MM (Yin et al., 2011, Lin et al., 2006). Showing

that condition knockout mice had reduced tumour development will help strengthen

our observations.

161

The use of shRNA knockdown of FGF-9 MM cells allows us to provide proof-of-

principle data confirming the essential function of FGF-9 in MM pathogenesis. To

target FGF-9 theoretically, several potential strategies can be attempted. FGF-9

monoclonal antibodies are available although their efficacies in vivo have not been

well established. The pharmacokinetics of these antibodies have not been

thoroughly studied even for common laboratory animals. Future studies will need

to establish the optimal route and dose of delivery, particularly to the pleural

tissues, if these antibodies are tested against MM. Another approach will be to

employ FGF-9 receptor antagonist or small inhibitors to the downstream signalling

of FGF-9. FGF-9 binds to FGFR2 and FGFR3 (Hecht et al., 1995) and activates

the IIIc isoform of the two receptors best (Santos-Ocampo et al., 1996). Hence,

any therapeutic attempts directing at FGFRs must target this isoform. Other FGF

family members can also bind to this isoform (Guillemot and Zimmer, 2011), thus

demonstrating the limitations of using FGFR antagonists to antagonise FGF-9

activity.

It would be interesting in future to examine the effects of FGF-9 over-expression in

normal murine mesothelial cells and assess for malignant transformation via

anchorage-independent growth assay in soft agar (Combes, 1999). Since FGF-9 is

a potent mitogen factor (as shown in Chapter 4), it is hypothesized that over-

expressing the levels of FGF-9 in the normal mesothelial cells would cause the

cells to transform into malignant cells causing them to form colonies in soft agar: a

feature that non-transformed cells are unable to. The malignant potential of the

FGF-9 over-expressed cells can then be tested using murine models.

It is also important to be cautious that our results in knocking down FGF-9,

although impressive in murine studies, still require validation in human MM. Our

162

group will attempt to knock down FGF-9 in human MM cells and test their biology

in vitro and in vivo.

In conclusion, our in vitro findings demonstrating the role of FGF-9 in MM

pathobiology is backed up with this in vivo study, confirming that FGF-9 is a key

factor in MM. Like other cancers caused by genetic mutations, there is a possibility

that there may be mutations occurring in the FGF-9 gene as well as in its receptors

that may lead to MM development. This is explored in the next chapter.

163

____________________________________________

MUTATIONS OF FGF-9 AND ITS RECEPTORS IN

MALIGNANT MESOTHELIOMA PATHOBIOLOGY

CHAPTER 6

164

6.0 MUTATIONS OF FGF-9 AND ITS RECEPTORS IN MALIGNANT

MESOTHELIOMA PATHOBIOLOGY

6.1 Introduction

As FGF-9 plays an important role in MM, it is prudent to investigate if there are any

mutations occurring in FGF-9 and its receptors that may impact on its signalling,

which lead to the development of this disease. One study on 203 tumours and cell

lines have reported six somatic mutations occurring on the FGF-9 gene; one

frameshift, four missense and one nonsense mutation in 10 (six colorectal and four

endometrial) tumour samples (Abdel-Rahman et al., 2008). Mutations of FGF-9 in

MM tumours have not been investigated before.

In addition, mutations in FGFR2 have also been described in 12% of endometrial

cancers (Dutt et al., 2008) while somatic mutations in the FGFR3 coding sequence

have been reported in 50% of bladder cancers (Cappellen et al., 1999), leading to

aberrant protein folding and hence constitutive activation of the receptor (Naski et

al., 1996, Di Martino et al., 2009). All of these lead to the next question whether

there are any mutations occurring in FGF-9 and its receptors, FGFR2 and FGFR3,

which are important in MM and is discussed in this chapter.

6.2 Results

6.2.1 Mutations in FGF-9

To examine if there are any mutations occurring in FGF-9, the conditions for the

PCR reaction using the primers to amplify the three exons in FGF-9 had to be first

optimised for the concentrations of Mg2+, the presence or absence of Q solution

and the melting temperature, T1 °C. Figure 6.1 shows a representative image of a

165

PCR optimisation study conducted by varying the conditions stated above. Each

column represents a different condition. DNA in RNAse-free water was used as a

negative control for the PCR reaction. The condition that gives the best band

intensity, with no smear was selected for later PCR reactions conducted on eight

human MM cell lines (Section 2.7.3). The sequences obtained from each sample

following the unpurified PD+ capillary sequencing method was compared against

each other and the consensus sequence from the NCBI database using Vector

NTI Advance 11 software package. Figure 6.2 shows the representative diagram

from AlignX demonstrating that all the sequences from the 8 MM samples align

with a 100% similarity for FGF-9 exons 1 and 2. Figure 6.3A shows the single point

mutation from A to G in the FGF-9 exon 3 for all the human MM cell lines tested

except for the NO36 cell line. Translation of the DNA sequence gave the same

amino acid sequence demonstrating that the single point mutation was a silent

mutation for FGF-9 (Figure 6.3B). The pilot study did not find any significant FGF-9

mutations in the MM human samples studied.

166

Figure 6.1: Agarose gel showing the band intensities for different conditions for a PCR reaction.

Each column represents a different condition for the PCR reaction. The top half of the gel shows the PCR products for FGF-9 exon 2

while the bottom half is for exon 3. The second column at the conditions of 62°C, 1.5 mM Mg2+ and the presence of Q solution was

selected for the FGF-9 exons 2 and 3 PCR reaction conditions.

Conditions: 62°C 1.5 mM Mg2+ Presence of Q solution

FGF-9 Exon 2

FGF-9 Exon 3

167

Figure 6.2: Sequence alignment for FGF-9 exon 1.

The representative image of a 100% sequence alignment for FGF-9 exons 1 and 2. All eight sequences for the eight human MM cell

lines tested were aligned with the sequence obtained from NCBI database using the AlignX program from the Vector NTI Advance 11

software package. The figure shows a 100% sequence alignment of all the sequences as depicted from the highlighted sequences in

yellow.

168

Figure 6.3: Sequence alignment and amino acid translation for FGF-9 exon 3.

(A) The image of a 98.6% sequence alignment for FGF-9 exon 3. All eight sequences for the eight human MM cell lines tested were

aligned with the sequence obtained from NCBI database using the AlignX program from the Vector NTI Advance 11 software package.

The figure shows one column highlighted in turquoise while the rest of the sequences were highlighted in yellow, demonstrating the

mutation occurring in that point of sequence (in turquoise), hence giving a 98.6% sequence alignment. (B) The amino acid translation

for one of the DNA sequences that were mutated. The amino acid sequence is exactly the same as the one for the wild type,

demonstrating the point mutation is a silent DNA mutation.

169

6.3A

170

6.3B

171

6.2.2 Expression of FGF-9 Receptors in MM Cells

To investigate if there are any mutations occurring in the FGF-9 receptors, it is

important to first determine if the receptors are present in MM cells. The presence

of the FGFR2 and FGFR3, which are the receptors for FGF-9, were identified

using immunofluorescence studies. Figures 6.4A – F demonstrates the strong

fluorescence observed in both the human (NO36) and murine (AB1) MM cell lines

tested for the presence of FGFR2 while Figures 6.5A – F showed the presence of

FGFR3 in both the human (NO36) and murine (AB2) MM cell lines. Although there

is only one paper to date that has reported the basal expression levels of FGFR2

in MM cells using real-time PCR (Stapelberg et al., 2005), the cell lines used were

different from this study. Hence, to our knowledge, this is the first study which

confirms the presence of FGFR2 and FGFR3 in both the human and murine MM

cells using immunofluorescence.

172

Figure 6.4: Expression and distribution of FGFR2 in the human NO36 and murine AB1 MM cell lines.

The expression of FGFR2 in human NO36 and murine AB1 MM cell lines is observed from the green fluorescent intensity in A & D.

The nuclei of the cells are shown by the blue intensity of the DAPI staining in images B & E. Images C & F show the distribution of

FGFR2 in the nuclei and cytoplasm of the cells from the merged images of the FITC and DAPI staining. The images are

representatives from the immunofluorescence studies conducted on eight human and three murine MM cell lines tested.

FGFR2-FITC DAPI Merge

NO36

AB1

6.4D 6.4F 6.4E

6.4A 6.4B 6.4C

173

Figure 6.5: Expression and distribution of FGFR3 in the human NO36 and murine AB2 MM cell lines.

The expression of FGFR3 in human NO36 and murine AB2 MM cell lines is observed from the green fluorescent intensity in A & D.

The nuclei of the cells are shown by the blue intensity of the DAPI staining in images B & E. Images C & F show the distribution of

FGFR2 in the nuclei and cytoplasm of the cells from the merged images of the FITC and DAPI staining. The images are

representatives from the immunofluorescence studies conducted on eight human and three murine MM cell lines tested.

FGFR3-FITC DAPI Merge

NO36

AB2

6.5A

6.5D 6.5F

6.5B 6.5C

6.5E

174

6.2.3 Mutations in FGFR2 and FGFR3 in MM Cell Lines and Tumour Biopsies

After confirming that FGFR2 and FGFR3 are present in MM, mutational

sequencing were carried out to determine if mutations occurred on FGFR2 and

FGFR3 were important in MM disease. An optimisation study was conducted to

decide on the best condition for each primer for the PCR reaction. In the early pilot

experiment conducted on 8 human MM cell lines on all the exons in FGFR2 and

FGFR3, two mutations were found in FGFR2. Figure 6.6A shows an image from

AlignX demonstrating that all but one sequence from the ONE58 human MM cell

line, align with a 100% similarity for FGFR2 exon 6, which codes for the IgII

domain of the receptor. Figure 6.6B shows the DNA mutation identified after

comparing with the consensus sequence obtained from the NCBI database and

Figure 6.6C depicts the amino acid substitution from glycine to serine occurring at

the point of mutation. The second mutation identified, occurred at Exon 11, which

codes for the juxta-membrane region in FGFR2. Figure 6.7A shows the image

obtained from AlignX demonstrating the point mutation from C to T in CRL-2081

and CRL-5820 cell lines. Figure 6.7B depicts the image obtained from ABI

sequence scanner while Figure 6.7C demonstrates the amino acid translation

showing a deletion of arginine amino acid in the two cell lines. There were no

mutations found in the other exons of FGFR2 and FGFR3 (image not shown).

As there were two mutations identified in FGFR2, a further mutational sequencing

analysis was performed on MM tumour biopsies. A total of 50 frozen MM tumour

biopsy samples were obtained from Professor Jenette Creaney, National Centre

for Asbestos Related Diseases, Perth, Western Australia of which 31 of them were

of the epitheloid subtype. There were eight biphasic and four sarcomatoid

subtypes while the histology for the remaining seven was unspecified. Figure 6.8

shows the image from AlignX demonstrating that out of the 50 tumour samples

175

tested, only one tumour (epitheloid subtype) sample showed the same DNA

mutation (G substituted by A) seen in ONE58 MM cell line. No mutations were

found in Exon 11 in the 50 tumour samples tested (image not shown). The data

obtained showed mutations that were not occurring in the hotspots area of the

receptors in other cancers.

176

Figure 6.6 : Amino acid substitution occurring in exon 6 of FGFR2.

(A) A diagram from AlignX software showing the single point mutation occurring in exon 6 of ONE58 MM cell line. All eight sequences

for the eight human MM cell lines tested were aligned with the sequence obtained from NCBI database using the AlignX program from

the Vector NTI Advance 11 software package. The figure shows one column highlighted in turquoise while the rest of the sequences

were highlighted in yellow, demonstrating the mutation occurring in that cell line (ONE58) at that point of sequence (in turquoise). (B)

The DNA mutation and the histogram as shown from ABI sequence scanner software. (C) The amino acid translation and the amino

acid substitution obtained from Vector NTI Advance 11 software package.

177

6.6A

178

6.6B

ONE58 Exon 6 (IgII domain): 72G→A

Mutation: G T G T A G T G G

Wild type: G

6.6C

Type of mutation: amino acid substitution

>rf 1 FGFR2 exon 6

ALEPHYGKCGPI*QGKLYLCGGE*IRVHQSHVPPGCC

>rf 1 ONE58 exon 6

ALEPHYGKCGPI*QGKLYLCSGE*IRVHQSHVPPGCC

179

Figure 6.7 : Amino acid substitution occurring in exon 11 of FGFR2.

(A) A diagram from AlignX software showing the single point mutation occurring in CRL-2081 and CRL-5820 MM cell lines. All eight

sequences for the eight human MM cell lines tested were aligned with the sequence obtained from NCBI database using the AlignX

program from the Vector NTI Advance 11 software package. The figure shows one column highlighted in turquoise while the rest of the

sequences were highlighted in yellow, demonstrating the mutation occurring in those cell lines (CRL-2081 and CRL-5820) at that point of

sequence (in turquoise). (B) The DNA mutation and the histogram as shown from ABI sequence scanner software. (C) The amino acid

translation and the amino acid substitution obtained from Vector NTI software.

180

6.7A

181

6.7B

CRL-2081 and CRL-5820 Exon 11 (Juxta-membrane domain): 124C→T

Mutation: A A C A T G A C C A A

Wild type: C

6.7C

Type of mutation: deletion

>rf 1 FGFR2 exon 11

RLEEKRRLQLPQTTWR*PFTA*GSS*SPVWW*QSSCAE*RTRPRSQTSAASRLCT

S*PNVSPCGD

>rf 1 ONE58 exon 11

RLEEKRRLQLPQTTWR*PFTA*GSS*SPVWW*QSSCAE*RT*PRSQTSAASRLCT

S*PNVSPCGD

182

Figure 6.8: Amino acid substitution occurring in exon 6 of FGFR2 in tumour biopsy.

A diagram from AlignX software showing the single point mutation occurring in one tumour biopsy sample (2005006) that had the

same mutation (G substituted by A) as in ONE58 MM cell line (Figure 6.6). All 50 sequences for the 50 human MM tumour biopsies

tested were aligned with the sequence obtained from NCBI database using the AlignX program from the Vector NTI Advance 11

software package. The figure shows one column highlighted in turquoise while the rest of the sequences were highlighted in yellow,

demonstrating the mutation occurring in the tumour biopsy (2005006) at that point of sequence (in turquoise).

184

6.3 Discussion

Based on our mutational analyses data, we report that there are no consistent or

frequent mutations occurring in all the three exons of FGF-9 and in all 19 exons of

FGFR3 in the MM samples that we tested. There are only two distinct mutations

occurring in two separate FGFR2 exon regions in two out of the 58 MM samples

tested. This is the first study carried out to analyse mutations on FGF-9 and both

its receptors in MM. DNA sequencing was carried out in both directions (on both

strands of the DNA) for verification.

Since FGF-9 is important in MM development (Chapters 4 and 5) and because

there have been no studies examining the mutational status of FGF-9 and its

receptors in MM, investigating if there are any mutations occurring in these genes

in MM samples is useful to understand if the mutations are implicated in this

cancer. Had mutations been recognised, it would be interesting to correlate the

mutational status of FGF-9/FGFR with the patient’s prognosis.

In our study, the frequency of the two FGFR2 mutations in the MM samples that

we tested is very low (3.4%) but comparable to the frequencies detected in

endometroid (1 in 46 samples, 2.2%) and serous (1 in 41 samples, 2.4%) ovarian

cancer (Byron et al., 2010) and slightly lower in melanoma (15 of 116 melanoma

cell lines and 8 of 100 uncultured metastases and primary tumours, 10.6%)

(Gartside et al., 2009). While we cannot exclude that a larger cohort may find

mutations, the chances of missing any mutations in our samples are very unlikely.

The low mutational frequency in FGFR2 exons and the lack of mutations in the

FGFR3 exons in our study depicts that the mutations in the exons of FGF-9

receptors are unlikely to be important in MM tumour development. Even the

mutation detected in FGF-9 exon 3 resulted in the same amino acid sequence

185

demonstrating that mutations in FGF-9 exons are very rare. This shows that the

DNA sequence of FGF-9 is conserved, a feature that is very important for a

molecule that has a key role in driving cancer progression. One paper recently

reported six distinct FGF-9 mutations in colorectal and endometrial samples

(Abdel-Rahman et al., 2008). All six mutations were loss-of-function mutations,

demonstrating the tumour-suppressor properties of FGF-9 in these cancers

(Abdel-Rahman et al., 2008). As FGF-9 has a key role in MM tumour development,

it is less likely that any loss-of-function mutations would occur. Mutations however

can result in the gain-of-function, leading to aberrant activity of the growth factor

although no such mutations have been identified in FGF-9 to date. Our data,

together with our results from earlier chapters, further strengthens the importance

of FGF-9 in MM. This allows the possibility of FGF-9 and/or its receptors as

therapeutic targets for MM.

The mutations that we detected are not the common mutations occurring in the

hotspot regions of FGFR2. Previous studies have reported mutations in FGFR2

within the IIIa and IIIc exons hotspots in other diseases (Kan et al., 2002, Kan et

al., 2004, Meyers et al., 1996, Jang et al., 2001). Here we identified only one

mutation (G substituted by A) at exon 6 in FGFR2 in one of eight MM cell lines and

2% of the 50 MM tumour samples tested. Exon 6 codes for IgII domain in FGFR2

which is necessary to induce receptor dimerization following ligand binding

(Wiesmann et al., 2000). The mutation we found causes glycine (wild type) to be

replaced by serine. The second mutation identified occurred at exon 11, which

codes for the juxta-membrane region in FGFR2, resulting in a deletion of arginine

amino acid in two out of eight MM cell lines. However, this mutation was not found

in the 50 MM tumour samples tested. The juxta-membrane region in FGFR is

required and sufficient for the interaction and phosphorylation of FRS2 (Xu et al.,

186

1998, Lin et al., 1998, Ong et al., 2000, Dhalluin et al., 2000). FRS2 is an adapter

protein that links FGFRs to the MAPK signalling pathway (Eswarakumar et al.,

2005, Klint and Claesson-Welsh, 1999). It is not known if the mutations that we

detected in exons 6 and 11 of FGFR2 are germline mutations or a mutation as a

result of MM. This can be verified by examining if the same exons in FGFR2 are

mutated in benign tissues obtained from the same patient. However, this is outside

the scope of my thesis. Nonetheless, the mutations we detected are infrequent in

MM and have not been previously reported in other diseases, suggesting that the

two mutations in the exon regions of the gene may not be important.

This technique proves to be robust. Although the sensitivity of the capillary

electrophoresis method used in this study to sequence DNA has not been

assessed, this method has long been established and used in many previous

studies (Bai et al., 2010, Dragileva et al., 2009, Novak-Weekley et al., 2012).

This mutation study only focused on all the exons of FGF-9 and its receptors.

Future work will need to examine the promoter and the regulatory regions which

may account for increased FGF-9 expression in MM. We will examine for any

methylation status occurring in the promoter region of FGF-9 that could lead to

increase copy numbers and hence the amplification of the molecule. These

experiments to sequence the promoter region of FGF-9 are necessary to unravel

as to why FGF-9 is increased or how the downstream signalling is affected in MM.

Yet, the mutations may not be the only cause for its over-expression in MM. We

cannot rule out the possibility of the up-stream effect of other molecules on FGF-9

signalling that may also implicate on FGF-9 signalling in MM.

187

____________________________________________

SUMMARY

CHAPTER 7

188

7.0 SUMMARY

Given the rising incidence of MM and the lack of effective therapy, there is a

desperate need to identify the key molecules. Such molecules would have a role

as therapeutic, diagnostic and prognostic markers for MM. Understanding the

molecular drivers of MM development may help establish new treatments. Prompt

diagnosis and reliable predictors of survival will significantly benefit patient care.

Our preliminary pilot experiments uncovered that FGF-9 mRNA was significantly

up-regulated in MM compared to metastatic adenocarcinoma and benign pleural

tissues. This thesis tested the general hypothesis that FGF-9 plays a vital role in

MM pathobiology and that its inhibition retards MM growth. FGF-9 is a secreted

growth factor, first identified in human glioma cells (Miyamoto et al., 1993, Naruo et

al., 1993). This growth factor activates FGFR2 and FGFR3 (Hecht et al., 1995) and

is vital for lung development (Colvin et al., 2001b).

Using a wide array of techniques, we have demonstrated, in Chapter 3, the

significant up-regulation of FGF-9 mRNA and protein in MM cells, tissues and

pleural fluids compared to metastatic adenocarcinomas and benign pleural

diseases. Our results are robust and consistent in a large cohort of more than

1000 samples in total. Previous studies have examined the role of FGF-9 in

embryonic development (Colvin et al., 2001a, Geske, 2008, Antoine et al., 2007,

White et al., 2006, Colvin et al., 1999) and in other cancers such as prostate

(Murphy et al., 2010, Kwabi-Addo et al., 2004, Li et al., 2008), lung (Chien-Kai et

al., 2009, Betsuyaku et al., 2011) and endometrial cancers (Hendrix et al., 2006).

We are the first to report its up-regulation in MM.

189

FGF-9 is a member of the FGF family which are heparin-binding polypeptides,

involved in various metabolic processes such as cell proliferation, migration, tissue

repair, cell differentiation and morphogenesis (Antoine et al., 2007, Maggie et al.,

2009, Ornitz and Itoh, 2001). We showed that recombinant FGF-9 stimulated

dose- and time-dependent cell proliferation in the human and murine MM cell lines

tested. In addition, FGF-9 is involved in MM cell migration and invasion.

Stimulation of human and murine MM cells with FGF-9 caused the release of

cytokines important in MM pathobiology (IL-8, MIP-2, VEGF and MCP-1) (Galffy et

al., 1999b, Masood et al., 2003, Hung et al., 2007, Stathopoulos et al., 2008).

FGF-9-induced cell proliferation in MM was mediated via ERK, JNK and p38

pathways.

FGF-9 knockdown MM cells have retarded growth in vivo using a heterotopic

(subcutaneous) model and an orthotopic (intraperitoneal) model. The growth

inhibition was abolished when experiments were conducted in athymic nude mice,

suggesting that FGF-9 induction of MM growth in vivo is partly mediated by

avoidance of immune clearance.

We also examined for mutations in FGF-9 and both its receptors, FGFR2 and

FGFR3 and found no consistent or significant mutations in the exons of these

genes. The highly conserved sequencing results among all samples examined

may indirectly demonstrate the importance of these proteins in MM.

Our results, collectively as a whole, support the idea that FGF-9 plays a vital role in

MM tumour development. Hence, strategies that antagonise FGF-9 activity may be

a valuable approach to treat MM.

190

Our data shows that FGF-9, in pleural fluids, is higher in MM than in non-MM

cases. The clinical utility, if any, of FGF-9 warrants examination. This would

include its diagnostic accuracy and how it can add value to existing diagnostic

tools.

Strategies to target FGF-9 including using an antisense (Morrison, 1991), a soluble

FGFR (Li et al., 1994), neutralising anti-FGF-9 antibody (Hori et al., 1991, Stan et

al., 1995, Murai et al., 1996, Takahashi et al., 1991) and FGF-9 peptides or small

molecule inhibitors should be tested. Their efficacies in vivo, pharmacokinetics in

the pleura, toxicities and many other issues need evaluation.

The possible prognostic role as well as disease monitoring tool of FGF-9 can also

be studied in MM in future. Whether FGF-9 increases with the advancing stages of

MM has not been studied yet. Measurement of FGF-9 in pleural fluids during the

course of the disease is feasible using longitudinal pleural fluid samples collected

through indwelling pleural catheters. We will also examine if FGF-9 can be used to

monitor treatment outcomes. FGF-9 expression in pleural fluids in response to

chemotherapy agents will be investigated.

Although we have demonstrated the role of FGF-9 in MM using exogenous

recombinant FGF-9, we are interested to examine if the FGF-9 present in the

pleural fluids are all active in rendering a response. Hence, we will investigate if

the endogenous FGF-9 present in the pleural fluids is able to elicit similar

responses as the recombinant FGF-9 used in our in vitro assays.

191

It will also be interesting to further define the signalling pathways involved in FGF-

9-FGFR pathway in MM. The cell signalling is a complex network but a further

understanding on the actions of FGF-9 on MM will no doubt provide a greater

insight on the development of MM and may lead to effective interventions for the

treatment of MM. We are interested in examining the interactions of FGF-9

signalling with other signalling pathways involved in MM cancer, such as the Sonic

Hedgehog, Wnt and TGF-β signalling pathways.

In addition, studies are in progress to establish the therapeutic effect of the

different methods in inhibiting FGF-9 in MM in in vivo models. FGF-9 neutralizing

antibody and the receptor antagonists are now commercially available to allow

assessment of the efficacy of the reagents in antagonising FGF-9 activity.

Knocking down FGF-9 in human MM cells and confirming the effects in a xenograft

murine model are warranted.

We will also examine if methylation or genetic defects in the promoter or regulatory

regions of FGF-9 is one of the causes for the abundance of FGF-9 in MM. Studies

will be conducted to investigate if the asbestos mineral can up-regulate FGF-9

mRNA and protein.

While the results on the role of FGF-9 in MM are exciting, the role of FGF-9

receptors needs to be studied. Investigating the expression profile and the

signalling of the different receptor isoforms in MM cells will no doubt provide an

insight on strategies to treat MM.

192

Our findings are new and only represent the tip of the iceberg of a very highly

complex signalling network of FGF-9 in MM involving numerous other signalling

pathways that we have yet to unravel. Despite that, our results are very promising

and may provide the key to understanding the pathogenesis of MM.

i

APPENDIX

ii

GENERAL BUFFERS AND SOLUTIONS

Scott’s tap water substitute

3.5 g sodium bicarbonate

20 g magnesium sulphate

1 L distilled water

Sodium citrate buffer (10 mM sodium citrate, 0.05% Tween-20, pH 6.0)

2.4 g Tri-sodium citrate (dehydrate)

1 L distilled water

Adjust pH to 6.0 with 1 M HCl and then add 0.5 mL of Tween-20.

10X EDTA/Tris buffer

6.25 g Tris HCl

12.5 g EDTA

8.0 g sodium citrate

1 L H2O

Adjust pH to 8.0 and make it up to a final volume of 2 L

Breaking buffer

50 mM Tris pH 7.5

0.5 mM EGTA

150 mM NaCl

1% v/v Triton X 100

50 mL ddH2O

10% v/v Protease inhibitor cocktail

1 tablet of PhosSTOP phosphatase inhibitor cocktail in 10 mL extraction solution

Protease inhibitor cocktail and PhosSTOP Phosphatase inhibitor cocktail added

immediately prior to use.

iii

Transfer buffer (store at 4°C)

39 mM Glycine

48 mM Tris base

10% Methanol

SDS running buffer

25 mM Tris

250 mM Glycine (electrophoresis grade) (pH 8.3)

0.5% w/v SDS

Tris buffered saline (TBS)

10 mM Tris pH 7.6

500 mM NaCl

1% Tween-20

50X TAE running buffer

242 g Tris base

57.10 mL Glacial acetic acid

5 mM EDTA (pH 8.0)

1 L ddH2O

iv

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