Pancreatic Stellate Cells in Chronic Pancreatitis

Lu Yang

September 2011

Thesis submitted for a degree of Master by Research

Faculty of Medicine

The University of New South Wales,

Sydney, NSW, Australia

Certificate of Originality

‘I hereby declare that this submission is my own work and to the best of my knowledge it contains no materials previously published or written by another person, nor material which to a substantial extent has been accepted for the award of any other degree or diploma at UNSW or any other educational institution, except where due acknowledgement is made in the thesis. Any contribution made to the research by others, with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in the thesis. I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project’s design and conception or in style, presentation and linguistic expression is acknowledged.’

Signed………………………………………………………………

Acknowledgements

I would like to express my gratitude to my masters’ supervisors Professor Minoti Apte,

Dr Phoebe Phillips and Professor Jeremy Wilson, for the opportunity to undertake a master project in the field of alcoholic pancreatitis and for their assistance, guidance and support throughout my candidature. Professor Minoti Apte is not only a scientist of superior quality but also a wonderful person who was always positive, patient and possesses great leadership qualities. Dr Phoebe Phillips has been a constant source of inspiration and provided me with precious intellectual and technical advice. Professor

Jeremy Wilson, Head of South Western Sydney Clinical School, despite his many commitments, provided invaluable assistance, encourage, advice and support throughout my studies and during the preparation of this thesis.

I thank all past and present research staff of the Pancreatic Research Group (A/Professor

Ron Pirola, Zhihong Xu, Xuguo Zhang, Eva Fiala-Beer, Jie Liu, Janet Youkhana and

Narada Kiriella) for their support and their help with the isolation of pancreatic stellate cells.

Thank you to Dr Alain Vonlaufen for his assistance and advice during my masters candidate and his patience in training me with several lab techniques.

I would like to thank my parents for all their understanding, encouragement and patience through out my studies.

Finally, I would like to offer my husband Jin a special thankyou for his love, understanding and unconditional support during my studies. iii

Publications ______

Publications in peer reviewed journals

1. Phillips PA, Yang L, Shulkes A, Vonlaufen A, Poljak A, Bustamante S, Warren A, Xu Z, Guilhaus M, Pirola R, Apte MV, Wilson JS. Pancreatic Stellate Cells Synthesize and Secrete Acetylcholine: A potential role in exocrine pancreatic secretion, Proc Natl Acad Sci U S A. 2010 Oct 5; 107(40):17397-402.

2. Vonlaufen A, Phillips PA, Yang L, Xu Z, Fiala-Beer E, Zhang X, Pirola RC, Wilson JS, Apte MV. Isolation of quiescent normal human pancreatic stellate cells (NhPSCs): a promising in vitro tool for studies of hPSC biology, Pancreatology. 2010; 10(4):434-43.

3. Xu Z, Vonlaufen A, Phillips PA, Fiala-Beer E, Zhang X, Yang L, Biankin AV, Goldstein D, Pirola RC, Wilson JS, Apte MV. Role of pancreatic stellate cells in pancreatic cancer metastasis, Am J Pathol. 2010 Nov; 177(5):2585-96.

4. Vonlaufen A, Phillips PA, Xu Z, Zhang X, Yang L, Pirola RC, Wilson JS, Apte MV. Withdrawal of alcohol promotes regression while continued alcohol intake promotes persistence of LPS-induced pancreatic injury in alcohol-fed rats, Gut. 2011 Feb; 60(2):238-46.

Abstracts

1. Yang L*, Phillips PA*, Vonlaufen A, Kaplan W, Cowley M, Pirola R, Wilson JS and Apte MV. Collagen-I Increases the Expression of Transgelin and Lumican (regulators of cell migration) by Activated Pancreatic Stellate Cells. *These authors contributed equally to the study. Awarded Best Poster Prize at the the Joint Conference of the International Association of Pancreatology and the Indian Pancreas Club, Cochin, 2011

2. Fiala-Beer E, Xu Z, Phillips PA, Yang L, Goldstein D, Pirola R, Wilson JS and Apte M. Role of pancreatic stellate cells in pancreatic cancer: the urokinase plasminogen activator system. Role of pancreatic stellate cells in pancreatic cancer: the urokinase plasminogen activator system. Oral presentation in the plenary session at the Joint Conference of the International Association of Pancreatology and the Indian Pancreas Club, Cochin, 2011.

3. Yang L*, Phillips PA*, Vonlaufen A, Kaplan W, Cowley M, Pirola R, Wilson JS and Apte MV. Collagen-I Increases the Expression of Transgelin and Lumican (regulators of cell migration) by Activated Pancreatic Stellate Cells. *These authors contributed equally to the study. Awarded in the Poster of Merit competition and won postgraduate student travel award in the annual scientific meeting of Australia Gastroenterology Week Oct. 2010 4. Yang L*, Phillips PA*, Vonlaufen A, Kaplan W, Cowley M, Pirola R, Wilson JS and Apte MV. Collagen-I Increases the Expression of Transgelin and Lumican (regulators of cell migration) by Activated Pancreatic Stellate Cells. *These authors contributed equally to the study. Oral presentation at 5th Australian Health and Medical Research Congress (AH&MRC) Nov.2010

5. Yang L*, Phillips PA*, Vonlaufen A, Kaplan W, Cowley M, Pirola R, Wilson JS, and Apte MV. *These authors contributed equally to the study. Collagen-1 increases the expression of transgelin and lumican (regulators of cell migration) by activated pancreatic stellate cells. Pancreas, 2010; 39(8):p1358. Poster presentation at the annual American Pancreatic Association meeting, 2010.

6. Yang L*, Phillips PA*, Vonlaufen A, Kaplan W, Cowley M, Pirola R, Wilson JS and Apte MV. Collagen-I Increases the Expression of Transgelin and Lumican (regulators of cell migration) by Activated Pancreatic Stellate Cells. v

*These authors contributed equally to the study. Poster presentation at European Pancreatic Club Meeting Jun, Sweden, 2010 7. Yang L*, Phillips PA*, Vonlaufen A, Kaplan W, Cowley M, Pirola R, Wilson JS, and Apte MV. *These authors contributed equally to the study. Collagen-1 increases the expression of transgelin and lumican (regulators of cell migration) by activated pancreatic stellate cells. Oral presentation at the annual Ingham’s Research Showcase, 2010

8. Fiala-Beer E, Xu Z, Phillips PA, Yang L, Goldstein D, Pirola R, Wilson JS and Apte M. Role of pancreatic stellate cells in pancreatic cancer: the urokinase plasminogen activator system. Oral presentation at the annual Australasian Pancreatic Club meeting, 2010.

9. Xu Z, Phillips PA, Vonlaufen A, Fiala-beer E, Yang L, Zhang X, Biankin AV, Goldstein D, Pirola RC, Wilson JS, Apte MV. Normal pancreatic stellate cells facilitate pancreatic cancer progression, exhibit transendothelial migration and accompany cancer cells to distant metastatic sites. Oral presentation at the annual Ingham’s Research Showcase, 2010.

10. Fiala-Beer E, Xu Z, Phillips PA, Yang L, Goldstein D, Pirola R, Wilson JS and Apte M. Role of pancreatic stellate cells in pancreatic cancer: the urokinase plasminogen activator system. Oral presentation at the annual Ingham’s Research Showcase, 2010. 11. Yang L*, Phillips PA*, Vonlaufen A, Kaplan W, Cowley M, Pirola R, Wilson JS and Apte MV. Gene expression profiling of rat pancreatic stellate cells. *These authors contributed equally to the study. Poster presentation at American Pancreatic Association and Japan Pancreas Society, November 2009, Hawaii, USA. 12. Yang L*, Phillips PA*, Vonlaufen A, Kaplan W, Cowley M, Pirola R, Wilson JS and Apte MV. Gene expression profiling of rat pancreatic stellate cells. *These authors contributed equally to the study. Oral presentation at Australia Pancreatic Club, August 2009, Australia. 13. Yang L, Phillips PA, Vonlaufen A, Xu Z, Zhang X, Fiala-Beer E, Pirola RC, Wilson JS. Apte MV. Alcohol and cytokines stimulate pancreatic stellate cell activation. Poster presentation at 4th Australian Health & Medical Research vi

Congress, 16-21 November 2008, Brisbane Convention & Exhibition Centre, Queensland, Australia. Won Travel Award. 14. Phillips PA, Yang L, Poljak A, Bustamante S, Shulkes A, Vonlaufen A, Xu Z, Guilhaus M, Pirola R, Apte MV, J. Wilson. Pancreatic stellate cells synthesise and secret acetylcholine: a potential role in enzyme secretion. Oral presentation (P.A. Phillips) European Pancreatic Club Meeting in Szeged July 2009 15. Phillips PA, Yang L, Vonlaufen A, Xu Z, Biankin A, Goldstein D, Pirola R, Wilson JS, Apte MV. Heat shock proteins are induced during pancreatic stellate cell activation in pancreatic cancer. European Pancreatic Club Meeting in Szeged July 2009 16. Phillips PA, Chow E, Kaplan W, Cowley M, Vonlaufen A, Yang L, Xu Z, Biankin A, Goldstein D, Pirola R, Wilson JS, Apte MV. Gene expression profiling of human pancreatic stellate cells and their roles in pancreatic cancer progression. European Pancreatic Club Meeting in Szeged July 2009 17. Phillips PA, Yang L, Vonlaufen A, Xu Z, Biankin A, Goldstein D, Pirola R, Wilson JS and Apte MV. Heat shock proteins are induced during pancreatic stellate cell activation in pancreatic cancer. Poster presentation at American Association for Cancer Research Annual Meeting in Denver, Apr. 2009 18. Phillips PA, Chow E, Vonlaufen A, Xu Z, Yang L, Biankin A, Goldstein D, Pirola R, Wilson JS, and Apte MV. Gene Expression Profiling of Human Pancreatic Stellate Cells and their Roles in Pancreatic Cancer Progression. Poster presentation at American Association for Cancer Research Annual Meeting in Denver, Apr. 2009 19. Phillips PA, Yang L, Vonlaufen A, Xu Z, Pirola R, Wilson JS and Apte MV. Heat shock proteins are differentially regulated during pancreatic stellate cell activation. Oral presentation (Phillips PA) at the annual meeting of American Pancreatic Association, 6-7 November 2008, Chicago IL, USA. (Pancreas, November 2008, Volume 37, Number 4, Page 459-505.) 20. Phillips PA, Yang L, Vonlaufen A, Xu Z, Pirola R, Wilson JSS and Apte MV. Heat shock proteins are differentially regulated during pancreatic stellate cell activation. Oral presentation (Phillips PA) at the annual Australian Gastroenterology Week, 22-25 October 2008, Brisbane, Australia. 21. Vonlaufen A, Xu Z, Yang L, Phillips PA, Zhang X, Pirola C, Wilson J, Apte M. Abstinence Promotes Regression While Continued Alcohol Intake Promotes vii

Persistence of LPS-Induced Pancreatic Injury in Alcohol-Fed Rats. Digestive Disease Week, 20 May 2008, Washington, D.C. USA 22. Vonlaufen A, Xu Z, Yang L, Biankin A, Parker N, Pirola C, Wilson JS, Apte M. Isolation of quiescent (normal) human pancreatic stellate cells (HPSCS): A useful in vitro tool for studies of HPSC biology. APA Meeting 8-9 November 2007 Chicago, USA 23. Xu Z, Vonlaufen A, Phillips PA, Fiala-Beer E, Yang L, Biankin A, Goldstein D, Pirola R, Wilson JS, Apte MV. Pancreatic stellate cells stimulate angiogenesis in pancreatic cancer and accompany pancreatic cancer cells to distant metastatic sites. Oral presentation (Xu Z) at the annual meeting of American Pancreatic Association, 6-7 November 2008, Chicago IL, USA. (Pancreas, November 2008, Volume 37, Number 4, Page 459-505.) 24. Vonlaufen A, Xu Z, Phillips PA, Yang L, Zhang X, Pirola PC, Wilson JS, Apte MV. Abstinence promotes regression while continued alcohol intake promotes persistence of LPS-induced pancreatic injury in alcohol-fed rats. Poster presentation at the annual meeting of American Pancreatic Association, 6-7 November 2008, Chicago IL, USA. (Pancreas, November 2008, Volume 37, Number 4, Page 459-505.) 25. Phillips PA, Chow MW, Vonlaufen A, Xu Z, Yang L, Pirola R, Wilson JS, Goldstein D and Apte MV. Gene Expression Profiling of Human Pancreatic Stellate Cells and their Roles in Pancreatic Cancer Progression. Abstract accepted by American Association of Cancer Research/ Digestive Disease Week 26. Xu Z, Vonlaufen A, Phillips PA, Fiala-Beer E, Yang L, Biankin A, Goldstein D, Pirola R, Wilson JS and Apte MV. The desmoplastic reaction in pancreatic cancer: Role of pancreatic stellate cells in cancer progression. Invited national speaker at the 4th Australian Health and Medical Research Congress (AH&MRC), 16-21 November 2008, Brisbane Convention & Exhibition Centre, Queensland, Australia. (Abstract ID: 211.) viii

Abstract

The overall hypothesis for the studies described in this thesis was that alcohol induced pancreatic fibrosis is a result of excessive extracellular matrix (ECM) synthesis by pancreatic stellate cells (PSCs) activated synergistically by alcohol and cytokines and that the composition of ECM, in turn, influence gene expression patterns of PSCs during the activation process.

Three specific aims for this study were addressed:

1) The synergistic effect of low concentrations of ethanol and cytokines on PSC

activation;

2) The influence of extracellular matrix (collagen I, MatrigelTM and plastic) on PSC

gene expression patterns;

3) The influence of the most highly dysregulated gene transgelin on PSC function.

Background to work:

x Pancreatic fibrosis is a characteristic histological feature of two major

pancreatic diseases - chronic pancreatitis and pancreatic cancer. PSCs play a

major role in pancreatic fibrogenesis.

x During pancreatic injury, PSCs undergo activation. This is accompanied by

the following changes: loss of cytoplasmic vitamin A containing lipid

droplets, transformation into a myofibroblast-like phenotype, increased

proliferation, increased expression of the cytoskeletal protein alpha-smooth

muscle actin (αSMA) and increased synthesis and secretion of ECM

proteins that comprise fibrous tissue.

x Factors known to activate PSCs in vitro include alcohol and its oxidative

metabolite acetaldehyde, oxidant stress and cytokines and growth factors ix

that are synthesised and secreted at increased levels during pancreatic

injury. However, during pancreatic injuries in vivo, PSCs are likely to be

exposed to several factors at the same time. Whether factors such as ethanol

and cytokines may exert synergistic effects on PSC activation has not been

fully studied.

x ECM plays a central role in the maintenance of normal tissue architecture

and regulates cell function. In health, PSC are surrounded by normal

basement membrane comprising collagen IV, laminin, fibronectin,

proteoglycans and growth factors. However, during pancreatic injury, PSCs

are activated and secrete excessive amount of ECM proteins such as

collagen I that comprise fibrous tissue. However, the influence of ECM

components on PSC gene expression profiles has not been previously

studied.

Specific aims:

A) Synergistic effect of ethanol and cytokines on PSC activation

In vitro studies designed to address this aim involved i) treatment of rat PSCs alone or in combination with ethanol and cytokines (TNFα and IL-1); ii) and assessment of PSC activation (αSMA expression and collagen expression). These studies demonstrated that

i) at very low doses, ethanol (5mM, a dose seen with social drinking) and

cytokines individually had negligible effects on PSC activation.

ii) however, the combination of ethanol with IL-1 or TNFα activated PSCs

by significantly increasing αSMA expression and/or collagen expression.

B) The influence of ECM on PSC gene expression patterns

These experiments involved the assessment of gene expression patterns in PSCs

cultured on MatrigelTM (mimicking normal basement membrane) and collagen I

(mimicking fibrotic pancreas) by a microarray experiment. These studies

demonstrated that gene expression patterns of PSCs are influenced by ECM

composition.

C) Characterisation of specific genes involved in PSC activation

These experiments involved i) analysis of microarray results and selection of

genes (transgelin, lumican, Fos, and IL-1α) that are highly dysregulated in cells

cultured on different matrices; ii) further validation of these genes at mRNA and

protein levels; iii) functional studies of one of the genes, namely transgelin, by

assessing the effect of modulating transgelin expression on PSC function.

Transfection of PSCs with small interfering RNA (siRNA) for transgelin resulted

in decreased PSCs proliferation.

The potential value of this work lies in the possibility of determining the molecular mechanisms responsible for mediating PSC activation. This could lead to the development of therapies that target PSC activation, in order to retard or reverse pancreatic fibrosis.

Contents

Certificate of Originality ...... i Acknowledgements ...... ii Publications ...... iii Abstract ...... viii Abbreviations ...... xv Chapter 1 - Pancreas and Alcoholic Pancreatitis ...... 1 1.1 The Anatomy and Function of Pancreas ...... 1 1.2 Pancreatitis ...... 3 1.3 Alcoholic Pancreatitis ...... 4 1.3.1 Natural History ...... 4 1.3.2 Clinical Manifestations ...... 7 1.3.3 Alcohol- Induced Pancreatic Injury ...... 8 1.4 Metabolism of Alcohol by Pancreatic Acinar Cells ...... 8 1.4.1 Oxidative Pathway of Ethanol Metabolism ...... 9 1.4.2 Non-Oxidative Pathway of Ethanol Metabolism...... 9 1.4.3 Oxidant Stress ...... 10 1.4.4 Susceptibility Factors ...... 10 1.5 Pancreatic Fibrosis ...... 11 Chapter 2 - Pancreatic Stellate Cells ...... 14 2.1 Introduction ...... 14 2.2 Historical Perspective of Stellate Cells ...... 14 2.3 Hepatic Stellate Cells ...... 15 2.4 Pancreatic Stellate Cells ...... 17 2.4.1 Characterisation of PSCs ...... 17 2.4.2 The Role of PSCs in Pancreatic Fibrosis ...... 21 2.4.3 Signalling Pathways in PSCs...... 23 2.4.4 Inhibition of PSC Activation ...... 24 2.5 Summary ...... 26 Chapter 3 - Synergistic Effect of Cytokines and Ethanol on PSC Activation ...... 27 3.1 Introduction ...... 27 3.2 Cytokines Relevant to Pancreatitis ...... 28 3.2.1 Interleukin-1 (IL-1) ...... 30 3.2.2 Tumour Necrosis Factor alpha (TNFα) ...... 32

xii

3.3 Methods ...... 33 3.3.1 Isolation of Rat PSCs ...... 33 3.3.2 Passaging of Rat PSCs ...... 36 3.3.3 Collection of Cell Lysates from Ethanol ± IL-1 Treated Rat PSCs ...... 37 3.3.4 Collection of Cell Lysates from Ethanol ± TNFα Treated Rat PSCs ...... 39 3.3.5 Assessment of Ethanol ± IL-1 or Ethanol ± TNFα on αSMA Expression by Rat PSCs…...... 40 3.3.6 Assessment of the Effects of Ethanol ± IL-1 or Ethanol ± TNFα on Collagen I Expression by Rat PSCs ...... 44 3.3.7 Assessment of the Combination of Ethanol, IL-1 and TNFα on Fibronectin Expression by Rat PSCs ...... 45 3.3.8 RNA Extraction from Treated Rat PSCs ...... 46 3.3.9 Preparation of cDNA for Real-Time PCR Analysis ...... 48 3.3.10 Real-time PCR for Collagen I mRNA Expression ...... 49 3.3.11 Statistical Analysis ...... 51 3.4 Results ...... 51 3.4.1 Rat PSC Isolation and Culture ...... 51 3.4.2 Effect of Ethanol ± IL-1 and Ethanol ± TNFα on αSMA Expression by rat PSCs ... 52 3.4.3 Effect of Ethanol ± IL-1 and Ethanol ± TNFα on Collagen I Expression - mRNA and Protein ...... 56 3.4.4 Effect of Ethanol, TNFα and IL-1 on Fibronectin Expression ...... 61 3.5 Discussion ...... 64 Chapter 4 - Effect of Extracellular Matrix Composition on Pancreatic Stellate Cell Gene Expression Pattern ...... 69 4.1 Extracellular Matrix ...... 69 4.1.1 Introduction ...... 69 4.1.2 ECM Degradation ...... 70 4.1.3 Stellate Cells and Extracellular Matrix Turnover ...... 72 4.1.4 ECM Regulates Stellate Cell Functions ...... 74 4.2 Methods ...... 76 4.2.1 Preparation of MatrigelTM Coated Petri Dishes and Cell Recovery ...... 76 4.2.2 Preparation of Collagen I Coated Petri Dishes and Cell Recovery ...... 78 4.2.3 Culture and Recovery of Rat PSCs from Uncoated Petri Dishes ...... 79 4.2.4 RNA Extraction for Microarray Analysis ...... 79 4.2.5 Assessment of RNA Quality ...... 80 4.2.6 Microarray (Affymetrix Rat Gene 1.0 ST Array) ...... 80 4.2.7 Microarray Data Analysis...... 81 xiii

4.3 Results ...... 82 4.3.1 Rat PSCs cultured on MatrigelTM, Collagen I and Plastic ...... 82 4.3.2 RNA Quality ...... 82 4.3.3 Microarray Result ...... 84 4.3.4 Biological Functions of Differentially Expressed Genes ...... 87 4.4 Discussion ...... 94 4.5 Summary ...... 98 Chapter 5 - Validation and Functional Studies for Selected Genes ...... 99 5.1 Introduction ...... 99 5.1.1 Transgelin ...... 99 5.1.2 Lumican ...... 102 5.1.3 Fos ...... 104 5.1.4 IL-1α ...... 105 5.2 Methods ...... 105 5.2.1 Validation of Transgelin, Lumican, Fos and IL-1α mRNA Expression in Rat PSCs105 5.2.2 Validation of Transgelin Protein Expression by Western Blotting ...... 106 5.2.3 Validation of Lumican Protein Expression by Immunoprecipitation and Western Blotting ...... 107 5.2.4 Assessment of Transgelin and Lumican Expression in Rat PSCs by Immunocytochemistry ...... 109 5.2.5 Assessment of Transgelin and Lumican Expression in Quiescent vs Activated Rat PSCs ...... 110 5.2.6 Inhibition of Transgelin Expression in Rat PSCs Using Small Interfering RNA (siRNA)...... 111 5.2.7 Effect of Transgelin Inhibition on αSMA Expression in Rat PSCs ...... 113 5.2.8 Effect of Transgelin Inhibition on Rat PSC Proliferation ...... 113 5.2.9 Effect of Transgelin Inhibition on Proliferation of Rat PSCs Cultured on Different Matrices ...... 114 5.2.10 Transgelin and Lumican Expression in Human Chronic Pancreatitis Tissue Sections…… ...... …114 5.2.11 Statistical Analysis ...... 117 5.3 Results ...... 117 5.3.1 Validation of Transgelin, Lumican, Fos and IL-1α mRNA of Rat PSCs Cultured on Collagen I vs MatrigelTM ...... 117 5.3.2 Validation of Transgelin and Lumican Protein Expression in PSCs Cultured on MatrigelTM vs Collagen I ...... 122 5.3.3 Immunocytochemistry of Transgelin and Lumican ...... 122 xiv

5.3.4 Transgelin and Lumican Expression in Quiescent vs Activated Rat PSCs ...... 127 5.3.5 Inhibition of Transgelin Expression by Transgelin siRNA ...... 131 5.3.6 Effect of Transgelin Inhibition on Rat PSCs Activation (Cultured on Plastic, MatrigelTM and Collagen I) ...... 134 5.3.7 Transgelin Expression in Human Chronic Pancreatitis Tissue Sections ...... 137 5.3.8 Lumican Expression in Human Chronic Pancreatitis Tissue Sections ...... 137 5.4 Discussion ...... 142 5.5 Summary ...... 146 Chapter 6 - Summary and Conclusion ...... 148 6.1 Background ...... 148 6.2 Summary of Present Work ...... 148 6.3 Conclusion ...... 150 6.4 Future Studies ...... 150 References ...... 153 Supplementary Data ...... 180

Abbreviations

ABC Avidin-biotin-peroxidase complex

ANOVA Analysis of variance bp Base pairs

BSA Bovine serum albumin

CaCl2 Calcium chloride

CaCO3 Calcium carbonate

CFTR Cystic fibrosis transmembrane regulator

CO2 Carbon dioxide cDNA Complementary DNA

CCl4 Carbon tetrachloride

CYP2E Cytochrome P450 (subfamily 2E)

DAB Diaminobenzidine

DMEM Dulbecco’s modified eagles medium

DNA Deoxyribonucleic acid

ECL Enhanced chemiluminescence

ECM Extracellular matrix

EDTA Ethylene diamine tetra acetic acid

ERK1/2 Extracellular signal regulated kinase

FAEE Fatty acid ethyl esters

FBS Fetal bovine serum

FGF Fibroblast growth factor

GAPDH Glyceraldehyde phosphate dehydrogenase

GBSS Gey’s balanced salt solution xvi

GFAP Glial fibrillary acidic protein

HBSS Hank’s balanced salt solution

HCl Hydrochloric acid

HRP Horseradish peroxidase

HSC Hepatic stellate cell

ICAM Intercellular adhesion molecule

IL Interleukin

IMDM Iscove’s modified Dulbecco’s medium

IP3 Inositol triphosphate

JAM Junctional adhesion molecule

KCl Potassium chloride

KDa Kilo daltons

KH2PO4 Potassium dihydrogen orthophosphate

L Lysosomes

MAPK Mitogen-activated protein kinase

MgCl2 Magnesium chloride

MgSO4 Magnesium sulfate

MiaPaCa-2 Pancreatic cancer cell line

MMPs Matrix metalloproteinases mRNA Messenger RNA

Na2CO3 Sodium carbonate

Na2HPO4 Disodium hydrogen phosphate

NaCl Sodium chloride

NaHCO3 Sodium bicarbonate

NaOH Sodium hydroxide xvii

NCAM Neural cell adhesion molecule

NGF Nerve growth factor

PBS Phosphate buffered saline

PCR Polymerase chain reaction

PPAR Peroxisome proliferator-activated receptor

PCR Polymerase chain reaction

PDGF Platelet derived growth factor

PI3-kinase Phosphatidylinositol 3-kinase

PMSF Phenylmethylsulfonyl fluoride

PSC Pancreatic stellate cell

RER Rough endoplasmic reticulum

RNA Ribonucleic acid

RT-PCR Real time-polymerase chain reaction

SDS Sodium dodecyl sulphate

SEM Standard error of the mean

SMA Smooth muscle actin

TBS Tris buffered saline

TGF Transforming growth factor

TNF Tumour necrosis factor 1

Chapter 1 - Pancreas and Alcoholic Pancreatitis

1.1 The Anatomy and Function of Pancreas

The pancreas is located in the upper abdomen and is intimately related to many blood vessels and viscera such as the duodenum, stomach and spleen. To the naked eye, the pancreas appears to be a pinkish-tan organ with a lobulated structure. The adult gland is 14 to 18 cm long, 2 to 9 cm wide and 2 to 3 cm thick. It comprises four regions: head, neck, body and tail (Figure 1.1).

The exocrine pancreas is composed of lobules each made up of numerous acini comprising acinar cells surrounding a central lumen [1]. Acinar cells contain numerous zymogen granules which store digestive enzymes including proteases, amylases, lipases and nucleases [2]. During the ingestion of food, neural (cholinergic) and hormonal

(predominantly CCK, released from the duodenum) stimulate acinar cells to release enzymes into the lumen of the acinus; subsequently, digestive juice tracks through intralobular and interlobular ducts and then into the main pancreatic duct which drains into the duodenum. Within acinar cells, digestive enzymes are produced as inactive precursors which are packed into zymogen granules and are thus segregated from lysosomal enzymes to avoid premature activation. In the duodenal lumen, enteropeptidase cleaves the pancreatic protease trypsinogen into active trypsin which in turn catalyses the activation of all other pancreatic proteases [2].

The endocrine cells in the pancreas are grouped into regions called Islets of

Langerhans. The adult pancreas contains about one million islets distributed throughout the organ. Endocrine cells are responsible for the synthesis of pancreatic hormones including insulin, glucagon and somatostatin which maintain glucose homeostasis.

Figure 1.1

The Anatomy of Pancreas

The Pancreas is intimately related with many abdominal organs and blood vessels. It is anatomically divided into a head, body and tail (adapted from AGA Teaching Slide Set

2005). a. =artery, R. =right, inf. =inferior, S. =superior, v. =vein

1.2 Pancreatitis

Pancreatitis (inflammation of the pancreas) has both acute and chronic forms.

While acute pancreatitis (AP) due to gallstones is a reversible condition (upon treatment of gallstones), recurrent attacks of acute inflammation have the potential to evolve into chronic pancreatitis. Severe forms of both acute and chronic pancreatitis can lead to impaired pancreatic exocrine and endocrine function.

Patients with acute pancreatitis typically present with abdominal pain and elevated pancreatic enzyme levels in the serum. In 80% of acute pancreatitis cases, pancreatic injury is mild and patients recover without complications. However, in a minority of patients, the disease is severe, with local and systemic complications [3].

Chronic pancreatitis (CP) is characterised by acinar atrophy and fibrosis with progressive deterioration of pancreatic structure and function. Patients typically have chronic abdominal pain, exocrine insufficiency (steatorrhea, maldigestion, vitamin deficiency and weight loss) and diabetes [4].

The major causes of acute pancreatitis are alcohol abuse and gallstones [5].

Other less frequent causes include genetic factors, drugs, hypercalcaemia, hyperlipidaemia, viruses and venoms [3]. In about 20% of the cases with acute pancreatitis, no cause is found (idiopathic pancreatitis). With regard to chronic pancreatitis, alcohol abuse is the major cause in Western countries [6], but other factors such as genetic mutations, pancreatic duct obstruction (caused by strictures), hypertriglyceridemia, hypercalcemia and autoimmunity also have been implicated [7-9], again, in a proportion of 25% cases [10], no cause can be found (idiopathic chronic pancreatitis).

1.3 Alcoholic Pancreatitis

It has been recognised for over 100 years that alcohol consumption is associated with pancreatitis. The earliest recorded link between pancreatic disease and alcoholism was described in 1878 by a German pathologist Friedreich who wrote “I am inclined to believe that a general chronic interstitial pancreatitis may result from excessive alcoholism (drunkard’s pancreas)” [11]. Since then, many studies have confirmed that excessive alcohol consumption is associated with pancreatic damage. The morbidity, mortality and economic costs of this disease are considerable so that it is important to develop strategies to prevent its onset or progression of the disease [12].

1.3.1 Natural History

Several decades ago, it was generally accepted that alcoholic pancreatitis was a chronic disease from the beginning punctuated during its course by acute exacerbations.

This notion was based on histological (atrophy, fibrosis) and radiological (calcification) evidence of chronic pancreatitis in patients at the time of their first attack of pancreatitis

[13, 14]. Furthermore, autopsy studies had demonstrated pancreatic fibrosis in alcoholics with no history of clinical pancreatitis [15].

More recently, the concept that alcoholic pancreatitis is a chronic disease from the beginning has been challenged by the “necrosis-fibrosis” concept [16-21]. It is postulated that chronic pancreatitis begins as an acute episode of pancreatic necroinflammation and with recurrent acute attacks, there is increasing residual damage to the gland, eventually resulting in chronic, irreversible changes (Figure 1.2).

There are several clinical studies which support the necrosis-fibrosis concept [16,

22, 23]. One of the largest prospective studies has reported that clinical manifestations of CP were more likely to occur in alcoholics with more frequent clinical recurrent 5

acute attacks [24]. A post-mortem study of patients dying from acute alcoholic pancreatitis showed that 53% have no evidence of chronic changes in the pancreas [25].

Experimental studies also support this concept by showing that repeated episodes of acute pancreatitis in rats produce chronic changes (fatty infiltration of the gland, atrophy and fibrosis) in the pancreas [16, 25-29].

Figure 1.2

Necrosis-Fibrosis Sequence of Pancreatitis

ChronicChronic pancreatitis pancreatitis

Acute episodes

Pancreatic damage

TimeTime (Years) (Years)

The diagram illustrates the necrosis-fibrosis sequence for the development of chronic pancreatitis. It is postulated that chronic pancreatitis begins as an acute episode of pancreatic necroinflammation and with recurrent acute attacks there is increasing residual damage of the gland, eventually resulting in chronic, irreversible changes such as acinar atrophy and fibrosis [30-32].

1.3.2 Clinical Manifestations

The onset of alcoholic pancreatitis usually occurs in men between the ages of 35 and 40 [24]. The initial attack is usually preceded by prolonged (5-15 years) of heavy alcohol consumption. Attacks of acute pancreatitis after a single alcoholic binge are rare.

The symptoms of acute pancreatitis are upper abdominal pain, nausea, vomiting, and loss of appetite. Radiologically, there is usually evidence pancreatic and peri- pancreatic oedema. Normally, in 80% of cases, acute pancreatitis is mild and will resolve within a week or two. However, in severe cases, acute pancreatitis can result in multiple organ dysfunction, sepsis and local complications (such as pseudocysts, abscesses and aneurysms) and is associated with a high mortality [3].

With continuation of heavy alcohol consumption after the onset of pancreatitis, chronic pancreatitis may develop five or ten years later [33]. Patients typically develop persistent abdominal pain, maldigestion and diabetes due to failure of exocrine and endocrine functions of the gland. Ammann et al [22] reported a study on 73 patients who progressed from clinically acute to chronic pancreatitis. Surgical specimens were obtained at a mean of 4.1 years and postmortem specimens at a mean of 12 years after the onset of acute pancreatitis. These pancreata often showed severe perilobular and intralobular fibrosis (85%) and calcifications (74%), but rarely necrosis (4%). Fibrosis correlated with progressive pancreatic dysfunction. Another study has classified patients according to their long term course into calcific, non-calcific and non-progressive chronic pancreatitis groups and found that the progression of acute to chronic pancreatitis is closely related to the incidence and severity of acute attacks [16].

1.3.3 Alcohol - Induced Pancreatic Injury

The mechanisms of alcohol induced pancreatic injury have been increasingly studied over the past 30 years, with the researchers focusing on the acinar cell as the possible site of initial injury. This is understandable, given that acinar cells produce large amounts of digestive enzymes which have the potential to cause considerable tissue damage (i.e. premature activation within the cell). Normally, acinar cells are protected from autodigestion by i) synthesising most digestive enzymes as inactive precursors, ii) the segregation of digestive enzymes into membrane-bound organelles and iii) the presence of protease inhibitors in the acinar cell. However, sometimes these protective mechanisms are overwhelmed and premature intracellular activation of digestive enzymes occurs leading to the initiation of acinar injury. Several studies have shown that chronic ethanol intake increases the synthesis of digestive enzymes in the pancreas [34, 35] and decreases the stability of zymogen granule and lysosomal membranes [36], thus, increasing the potential for contact between digestive and lysosomal enzymes. Trypsinogen can be activated by the lysosmal cathepsin B [37].

Active trypsin, in turn, can activate trypsinogen and other pro-enzymes and trigger a digestive enzyme activation cascade within the cell, resulting in autodigestive injury to the cell causing, in turn, an acute inflammatory response in the gland.

1.4 Metabolism of Alcohol by Pancreatic Acinar Cells

It is now well established that the pancreas is capable of metabolising ethanol

[38]. Acinar cells are capable of metabolising ethanol via both oxidative and nonoxidative pathways, though the rate of oxidative metabolism is higher than that of the non-oxidative pathway [38]. The metabolites of both pathways may act as mediators of alcohol induced damage to the pancreas. 9

1.4.1 Oxidative Pathway of Ethanol Metabolism

The oxidative pathway is comprised of several enzymes that convert ethanol to acetaldehyde and then acetic acid. The enzymes responsible for this reaction are alcohol dehydrogenase (ADH) and acetaldehyde dehydrogenase (ALDH) with modest contributions from cytochrome P450 2E1 and possibly catalase [39].

The main isoform of ADH in rat acinar cell is ADH III, a non-saturable form with a low affinity and a high Km (the substrate concentration required for an enzyme to reach one-half its maximum velocity) [39]. In contrast to rat acinar cells, the ADH isoforms in human pancreatic acinar cell is mainly ADH I [40].

Acetaldehyde is more toxic than ethanol and can cause distinct morphological and biochemical changes in the exocrine pancreas [41]. It has been shown to inhibit cholecystokinin (CCK)-induced secretion from isolated rat pancreatic acini [41]. This effect is thought to be a result of acetaldehyde interfering with the binding of CCK to its cellular receptors and to disruption of microtubules responsible for transporting intracellular compartments [42]. In addition, hydrogen ions (reducing equivalents) are released during the oxidation of ethanol to acetaldehyde and subsequently acetate [43].

This alters the redox state of the cell by a reduced NAD/NADH ratio and increased lactate/pyruvate ratio, leading to a number of metabolic alterations that could contribute to pancreatic injury.

1.4.2 Non-Oxidative Pathway of Ethanol Metabolism

The non-oxidative pathway yields fatty acid ethyl esters (FAEE) and is catalysed by enzymes known as FAEE synthases. Compared to the liver, FAEE synthase activity in the pancreas is greater, whereas that of ADH is much less [44]. FAEEs have been 10

shown to damage the pancreas and its subcellular organelles [45]. Infusion of FAEEs into rats leads to oedema, acinar vacuolisation, trypsinogen activation and increased extracellular matrix protein levels in the pancreas [46]. FAEEs are thought to exert toxicity by several mechanisms: i) direct interaction of the compounds with cellular membranes [47]; ii) acting as a shuttle for free fatty acid and iii) stimulation of cholesteryl ester synthesis by transesterification [48]. They have been shown to cause mitochondrial dysfunction, intracellular calcium accumulation, ATP depletion and cell death.

1.4.3 Oxidant Stress

One of the consequences of ethanol oxidation is the generation of reactive oxygen species (ROS) leading to oxidant stress in the cells. The generation of ROS occurs by a number of mechanisms. ROS are highly reactive substances, which can damage cell components such as proteins, lipids and DNA. Oxidant stress may contribute to the destabilisation of zymogen granule and lysosomal membranes observed in ethanol-fed rats (see review by [49]). Oxidant stress has also been reported in the pancreas of patients with alcoholic chronic pancreatitis and in experimental animals after acute and chronic ethanol exposure [50-52].

1.4.4 Susceptibility Factors

Only a minority of alcoholics develop pancreatitis, indicating that some individuals have an increased susceptibility to the disease. Possible susceptibility factors include diet [53], smoking [54-56], type and amount of alcohol consumed [53, 57], the pattern of drinking [53] and lipid intolerance [58]. 11

A range of hereditary factors have also been analysed. These include human leukocyte antigen (HLA) serotypes [59], blood group antigens, α1-antitrypsin phenotypes [60] and cystic fibrosis transmembrane regulator (CFTR) genotypes [61-64], cytokine (TNFα, TGFβ, IL-10 and interferon-γ [62]), alcohol metabolising enzyme such as ADH, ALDH and CYP2E1 [65] and detoxifying enzyme such as UDP glucuronosyltransferase (UGT1A7) [66] and glutathione S-transferase [67]. However, most of these studies have failed to show an association with alcoholic pancreatitis.

In addition to clinical studies, researchers have used experimental animal models to investigate possible trigger factors of alcohol induced pancreatic injury. Previous studies have employed alcohol administration with additional factors such as pancreatic duct ligation [68], super physiological doses of caerulein [a cholecystokinin (CCK) analogue] [28, 69], a chemical toxin such as trinitrobenzene sulfonic acid [70] or a drug such as cyclosporine [71]. However, the clinical relevance of this model is questioned due to the lack of the physiological basis in human. Vonlaufen et al [29] have recently reported that innocuous doses of endotoxin initiate overt pancreatic injury (acinar cell vacuolization and necrosis, inflammatory infiltrate and hemorrhage) in alcohol-fed rats, and importantly, repeated endotoxin injections result in the progressive pancreatic damage (acinar atrophy and fibrosis). The effect of alcohol and LPS on pancreatic fibrosis in this model suggests a synergistic effect of the two compounds on the activation of pancreatic stellate cells (PSCs, now established as the key effecter cells in the pancreatic fibrogenesis - detailed in Chapter 2).

1.5 Pancreatic Fibrosis

Fibrosis is a characteristic pathological feature of chronic pancreatitis and pancreatic cancer, and is characterised by an increase in the collagenous and non- 12

collagenous components of the extracellular matrix (ECM) and an altered composition of the fibrotic matrix [72]. The architecture of normal pancreas is maintained by a fine balance between ECM synthesis and degradation. Alteration of this balance leads to the deposition of excessive amounts of ECM protein and the development of fibrosis [73].

ECM is mainly modulated by PSCs in the pancreas; therefore, the identification, isolation and characterisation of PSCs has allowed significant advances in understanding pancreatic fibrosis [30, 74].

The fibrogenic process is thought to be initiated by injury to the various cell types within the pancreas, resulting in cell apoptosis and/or necrosis [73]. The consequent release of cytokines and growth factors by the resident cells attract inflammatory cells such as polymorphonuclear neutrophils, monocyte/macrophages and lymphocytes to the injured site. These cells then phagocytose cell debris and release cytokines which activate PSCs, the major effector cells of pancreatic fibrogenesis [73].

In addition, recent studies have shown that PSCs may also be directly activated by toxic factors such as alcohol and its metabolites leading to the initiation of fibrosis even in the absence of concurrent inflammation of pancreas [75] (Figure 1.3). The pathophysiological mechanisms underlying pancreatic fibrosis are discussed in detail in

Chapter 2.

Figure 1.3

Hypothesis for the Pathogenesis of Alcoholic Pancreatitis

The diagram depicts an overall hypothesis for the pathogenesis of alcoholic pancreatitis. It is postulated that ethanol, its metabolites (including acetaldehyde, Ac) and oxidant stress exert a number of toxic effects on pancreatic acinar cells which predispose the gland to autodigestive injury, acute necroinflammation and cell death. These include:

(1) increased digestive and lysosomal enzyme content due to increased synthesis (increased mRNA) and impaired secretion; (2) destabilisation of lysosomes and zymogen granules mediated by (3) oxidant stress, cholesteryl esters (CE) known to accumulate in the pancreas during ethanol consumption and fatty acid ethyl esters (FAEE). These changes sensitise the cell such that in the presence of an appropriate trigger/cofactor, overt injury is initiated. (4) cytokines released during alcohol-induced necroinflammation activate pancreatic stellate cells (PSCs). In addition, PSCs are activated directly by ethanol and subsequent generation of oxidant stress. Activated PSCs then synthesise excess amounts of extracellular matrix proteins leading to pancreatic fibrosis [76]. 14

Chapter 2 - Pancreatic Stellate Cells

2.1 Introduction

Fibrosis is a characteristic histological feature of two major diseases of pancreas, chronic pancreatitis and pancreatic cancer. For a long time, pancreatic fibrosis was considered to be a mere epiphenomenon of injury; however, the mechanisms responsible for the development of fibrosis have received increasing attention in recent years and now it is clear that pancreatic fibrosis is not a passive response to injury, but an active process with the potential to be reversible, at least in the early stages [77]. The development of methods to isolate and characterise PSCs from rat and human pancreas

[30, 74, 78] has provided researchers with a much needed in vitro tool to examine PSC biology in health as well as in disease states.

2.2 Historical Perspective of Stellate Cells

Stellate cells were first described and isolated from the liver. Hepatic stellate cells were first identified as “sternzellen” by Karl Wilhelm Von Kupffer in 1876. He described these cells around the hepatic sinusoidal capillaries in the human liver [79].

However, because of the similar distribution of gold-reactive stellate cells and phagocytic cells in human liver, Von Kupffer classified these cells as phagocytes [79].

In the first half of the 20th century, there was considerable controversy about the identification, function and the name of these cells. In 1951, Toshio Ito [80] described lipid-containing cells in the human liver. These cells were surrounded by reticular fibers and were termed as fat-storing cells or Ito cells for several decades. In 1971, Wake [81] showed that “sternzellen” of Kupffer and lipid-containing cells of Ito were the same cells using light and electron microscopy, gold chloride staining as well as vitamin A 15

autofluorescence methods. In 1996, an agreement was made by the investigators in the field to use a standard name “hepatic stellate cells” to refer to the resting form of this cell type found in normal liver [82].

The counterpart of HSCs in the pancreas, namely pancreatic stellate cells (PSCs) were first reported by Watari [83] in 1982. Using fluorescence, he discovered the presence of vitamin A storing cells in the pancreas which emitted a rapidly fading blue- green fluorescence when exposed to UV light at 328nm. Subsequently, Ikejiri et al [84] demonstrated the presence of vitamin A-storing cells in human and rat pancreas using electron microscopy in 1990.

However, major advances in our understanding of stellate cell biology and the role of stellate cells in fibrosis have only been made since the development of techniques to isolate and culture these cells from both human and rat tissues. The first successful isolation of hepatic stellate cells in rodents and humans was performed in the early 1980s [85, 86]. Thirteen years later, rat and human pancreatic stellate cells were successfully isolated and cultured [30, 74, 78]. The availability of this in vitro tool has given significant impetus to studies on the molecular mechanisms of pancreatic fibrogenesis.

2.3 Hepatic Stellate Cells

Hepatic stellate cells (HSCs) account for approximately 5-8% of total cells in the liver [87]. They are located in the perisinusoidal space, between the basolateral surface of hepatocytes and the ante-luminal side of sinusoidal endothelial cells. HSCs are also located directly adjacent to nerve endings [88]. In normal liver, HSCs are spindle- shaped cells and the most characteristic feature is the storage of vitamin A (retinoid) lipid droplets in their cytoplasm. Vitamin A content is visible after excitation with UV 16

light at a wavelength of 328nm. The number of droplets varies with the species and the amount of vitamin A stores of the organism [89]. Other than storage of vitamin A, some intermediate filament proteins are also useful to identify stellate cells, such as desmin and glial fibrillary acidic protein (GFAP) [90, 91]. The cells also express nestin, nerve growth factor (NGF) and neural cell adhesion molecule (NCAM). Desmin expression in human HSC appears to be activation dependent [92] since it appears in cells cultured for longer periods (>7 days) instead of early culture (i.e., 2 to 3 days).

Numerous biological functions of HSCs have been described in normal liver.

These include: 1) a key role in the storage and transport of vitamin A; under physiological conditions, 50-80% of total retinoid of the body is stored in the liver [93];

2) synthesis of cytokines and growth factors in the liver [94] [95]; and, 3) maintainance of normal basement membrane-type matrix.

In response to liver injury, the fine structure of stellate cells changes considerably. They lose their characteristic lipid droplets and become “activated”. Once activated, HSCs transform from a quiescent vitamin A storage form into a myofibroblast-like phenotype and exhibit increased proliferation [96], migration, fibrogenesis [97], contractility and increased production of collagen I and other matrix constituents [98, 99]. These features are now used as the parameters to characterise activated HSCs. Activation of HSCs is initiated by cytokines and growth factors, oxidant stress and products of ethanol metabolism [100, 101]. Importantly, activated

HSCs can produce cytokines and growth factors which can exert autocrine effects leading to the perpetuation of the activated state as well as paracrine effects, promoting development and growth of other liver cell types such as hepatocytes [102] and cholangiocytes [103].

2.4 Pancreatic Stellate Cells

2.4.1 Characterisation of PSCs

In charactererising PSCs, researchers have often taken their clues from knowledge regarding the biology of HSCs. PSCs are resident cells and represent 4-7% of all parenchymal cells in the normal pancreas [30, 74]. In health, PSCs are star-shaped, lipid-containing cells (quiescent phenotype) with a central body and long elongated cytoplasmic processes encircling the basolateral aspect of adjacent acinar cells (Figure

2.1).

Both human and rat PSCs can be isolated from normal pancreas by density gradient centrifugation [30, 78]. This method takes advantage of the fact that PSCs contain vitamin A lipid droplets in their cytoplasm which significantly decreases cell density thereby allowing them to be separated from other pancreatic cells. In early culture, PSCs assume a flattened polygonal shape with abundant vitamin A containing lipid droplets surrounding a central nucleus (Figure 2.2) and stain positive for GFAP and desmin [30, 74]. Upon exposure to UV light at 328nm, PSCs display the transient blue green fluorescence characteristic of vitamin A. When cultured on plastic over 48 hours or when exposed to extracellular stimuli, PSCs become activated resulting in an increase in cell proliferation and transformation into myofibroblast-like cells that stain positive for α-smooth muscle actin (α-SMA), synthesise and secrete increased amounts of ECM proteins (e.g. collagens I and III, fibronectin and laminin) and matrix metalloproteinases and possess the ability to migrate and produce endogenous cytokines

[104] (Figure 2.3).

Figure 2.1

Frozen Section of Rat Pancreas Stained for Desmin

A frozen section of rat pancreas immunostained for desmin and corresponding line diagram. The brown stained cells are desmin positive pancreatic stellate cells (PSCs).

Demonstrated are the small body and fibrillar extensions, giving a star-like (stellate) shape (u40 objective) and in a basalateral position surrounding the acinus (A) [30].

Figure 2.2

Phase Contrast Micrograph of PSCs

Vitamin A droplets

Phase contrast micrograph of cultured PSCs at 24 hours after isolation depicting PSCs exhibiting a flattened polygonal shape with abundant lipid droplets surrounding a central nucleus (u400 magnification) [30, 78] .

Figure 2.3

ECM Protein Expression in PSCs

Pancreatic stellate cells immunostained for some of the ECM proteins that

comprise fibrous tissue [104].

2.4.2 The Role of PSCs in Pancreatic Fibrosis

Evidence for a central role of PSCs in pancreatic fibrogenesis comes from both in vivo and in vitro studies.

In vivo studies

In vivo studies using pancreatic tissue sections from patients with chronic pancreatitis have shown that i) collagen is the predominant ECM protein in the fibrotic areas; ii) areas that stain positive for collagen also exhibit positive immunostaining for

α-SMA, suggesting the presence of activated PSCs in fibrotic areas [105]; iii) αSMA positive cells in fibrotic areas are the only cells that exhibit positive staining for collagen messenger RNA, indicating that activated PSCs are the principal source of collagen deposition in the fibrotic pancreas [105]; and, iv) proinflammatory cytokines and growth factors are present in areas of fibrosis raising the possibility that these factors play a role in mediating PSC activation [73]. Thus the above human studies have supported the concept that activated PSCs may play a role in pancreatic fibrosis [105].

However, these studies are limited by their point-in-time nature. Therefore, to study the early changes in PSCs during the development of pancreatic injury, researchers have turned to experimental models of pancreatic fibrosis.

Several rat models have been described in the literature. However, only some have focused on the specific role of PSCs in fibrogenesis. These include: i) infusion of trinitrobenzene sulfonic acid (TNBS) into the pancreatic duct [105, 106]; ii) a spontaneously occurring WBN/Kob rats model of chronic pancreatitis [107]; iii) severe hyperstimulation obstructive pancreatitis (SHOP) [108]; iv) repeated IP injections of a superoxide dismutase inhibitor [109]; v) continuous intragastric infusion of ethanol plus a high fat liquid diet [110, 111]; and, vi) chronic alcohol feeding with repeated endotoxin (LPS) injection [29]. 22

Mouse models of pancreatitis fibrosis that have examined the role of PSCs include: i) transgenic mice that overexpress TGFβ1 [112] and heparin-binding EGF-like growth factor [113] and ii) repetitive injury induced by repeated injections of caerulein

[114].

The animal models have examined the effect of PSCs in injury at different time points, establishing that PSCs are activated early during the course of pancreatic injury and confirmed the findings of human studies that PSCs are the primary source of collagen in pancreatic fibrosis [105].

In vitro studies

In vitro studies have used knowledge obtained from in vivo events during pancreatic injury to select putative PSC activating factors for examination in vitro.

These include growth factors and cytokines such as transforming growth factor beta

(TGFβ), platelet derived growth factor (PDGF) and tumour necrosis factor alpha (TNFα) as well as hormones. PSC activation in response to the above potential stimulators has been assessed by at least one or more parameters such as cell proliferation, αSMA expression, ECM protein synthesis and degradation, cell migration, loss of vitamin A stores and cytokine production. Using cultured PSCs, it has been established that i)

PDGF is a potent mitogenic and chemotactic factor for PSCs [104, 115, 116]; ii) PSCs respond to the proinflammatory cytokines, TNFα, IL-1 and 6 (known to be upregulated during pancreatic injury) [104, 117]; iii) the profibrogenic cytokine TGFE activates

PSCs as evidenced by increased αSMA expression as well as increased collagen and fibronectin synthesis [74, 104]; iv) upon activation, PSCs release endogenous cytokines

(IL-1, IL-8 and TGFβ) and proinflammatory molecules (monocyte chemoattractant protein (MCP)-1, and RANTES (regulated on activation normal T cell expressed and 23

secreted) [118, 119] that perpetuate PSC activation via autocrine loops; v) hormones such as angiotensin II also play a role in PSC activation in culture [120-122].

Given that alcohol is a major cause of both acute and chronic pancreatitis in the western world and that alcohol is known to be metabolised by the pancreas, the effects of ethanol and its toxic metabolites as well as oxidant stress on PSC activation in vitro have been examined. It has been shown that both ethanol (50mM - seen with heavy alcohol consumption) and acetaldehyde (200μM - liver tissue concentration reported in alcohol-fed rats) increase αSMA expression and synthesis of extracellular matrix proteins by PSCs [75, 123]. With regard to oxidant stress, PSCs have been shown to respond to pro-oxidant compounds which generate reactive oxygen species (ROS) within the cells [75, 124], which in turn, mediate PSC activation. In fact, the effects of alcohol and acetaldehyde can be abrogated by anti-oxidants suggesting that the effects are mediated by oxidant stress [75].

2.4.3 Signalling Pathways in PSCs

In recent years, given that PSCs responded to numerous exogenous and endogenous stimuli, researchers have focused on the identification of the intracellular signalling pathways that ultimately mediate PSC activation.

One of the major pathways that regulate cell functions (protein synthesis, cell differentiation and cell division) is the mitogen activated protein kinase (MAPK) pathway [125]. It is now established that both ethanol and its metabolites induce the activation of all 3 classes of the MAPK pathway in PSCs, namely extracellular signal regulated kinase (ERK1/2), p38 kinase and c-jun amino terminal kinase (JNK) as well as the nuclear transcription factor activator protein-1 (AP-1) [126]. Ethanol and 24

acetaldehyde also activate two upstream signaling molecules phosphatidylinositol-3- kinase (PI3K) and protein kinase C (PKC) in PSCs [127, 128].

Both MAPK and PI3K have been identified to be important regulators of cytokine-related PSC activation [129-131]. It has been shown that PDGF-induced PSC proliferation is mediated via the ERK pathways [132], while PDGF-induced PSC migration is regulated by the PI3K pathway [130].

2.4.4 Inhibition of PSC Activation

Given that activated PSCs play a major role in pancreatic fibrosis, there is an increased interest in the study of reversion/inhibition of PSC activation as a means of treating pancreatic fibrosis in chronic pancreatitis and pancreatic cancer. Several studies have tested the efficacy of antifibrotic strategies in vivo using experimental models as well as in vitro using cultured PSCs.

i) Vitamin A

A constant feature of PSC activation is the loss of vitamin A (retinol) containing lipid droplets in the cytoplasm. However, whether loss of vitamin A is a cause or an effect of PSC activation remains to be clearly elucidated. Retinol and its metabolites all- trans retinoic acid (ATRA) and 9-cis retinoic acid (9-RA) have been shown to induce quiescence in culture activated PSCs [133, 134]. Of relevance to the current study is the knowledge that alcohol and retinol metabolism occur through similar pathways, with alcohol being converted to acetaldehyde and acetate by ADH and ALDH respectively and retinol being converted to retinaldehyde and retinoic acid via retinol dehydrogenase

(RDH) and retinaldehyde dehydrogenase (RALDH) respectively. Competitive inhibition has been reported of retinol metabolism in the presence of ethanol. In fact, in vitro studies have been shown that retinol can partially inhibit ethanol induced activation of 25

PSCs [134], most likely due to competitive inhibition of ethanol oxidation by retinol, leading to decreased oxidant stress.

ii) Vitamin E

Vitamin E [include tocotrienol stereoisomers (α, β, γ, δ) and tocopherol steroisomers (α, β, γ, δ) subclasses] has been shown to reduce pancreatic fibrosis in a rat model of chronic pancreatitis [135]. α-Tocopherol can prevent PSC activation induced by oxidant stress in vitro [75]. Tocotrienols induce death of activated PSCs via increased cell apoptosis and autophagy. Importantly, this effect was not seen in quiescent PSCs or in acinar cells [136].

iii) Peroxisome proliferator-activated receptor γ ligand (PPARγ)

PPARγ is a member of the nuclear hormone receptor superfamily [137]. Its ligand troglitazone is reported to prevent the progression of chronic pancreatitis in a rodent model by inhibiting ECM production [138, 139]. Overexpression of PPARγ strongly inhibited PSC proliferation and ECM production and increased the rate of apoptosis [140].

iv) Cytokine Inhibition

TGFβ neutralizing antibody reduced ECM formation during the regeneration of the pancreas in a caerulein induced rat experimental acute pancreatitis model [141].

Simultaneous inhibition of TNFα production and xanthine oxidase activity reduced the local and systemic inflammatory response in sodium taurocholate induced pancreatitis

[142]. TNFα antibody, has been shown also to reduce the morbidity and mortality of bile induced acute pancreatitis model [143].

v) Anti-inflammatory agents

Protease inhibitors such as camostat mesilate inhibited MCP-1 production and proliferation by PSCs in DBTC induced chronic pancreatitis [144]. Carboxamide 26

derivative IS-741 inhibited pancreatic fibrosis (induced by dibutyltin dichloride in rats) and decreased PSC activation in vitro and in vivo [145].

Following repeated injuries, the pancreas undergoes a complex remodelling process, significantly altering the microenvironment of stellate cells. Although, the majority of anti-fibrotic therapies have focused on limiting the activation and proliferation of stellate cells, understanding the influence of all microenvironmental components on stellate cell activation is of critical importance. A detailed discussion of microenvironment and its influence on PSC functions is presented in Chapter 4 of this thesis.

2.5 Summary

Over the past decade, morphological and functional changes that occur in pancreatic stellate cells during the activation process have been increasingly delineated.

Several activating factors have now been identified including ethanol, its metabolite acetaldehyde, oxidant stress, proinflammatory cytokines and growth factors. However, the molecular mechanisms (mediating signalling pathways, transcriptional factors and genetic changes) remain to be fully elucidated with respect to the transformation of

PSCs from a quiescent to an activated state. Elucidation of these mechanisms is essential for the identification of molecular targets that may be amenable to therapeutic modulation.

Chapter 3 - Synergistic Effect of Cytokines and

Ethanol on PSC Activation

3.1 Introduction

Inflammation, the response of tissue to injury, is characterised in its acute phase by increased blood flow, and vascular permeability along with the accumulation of fluid, leukocytes and cytokines in tissues. In the chronic phase, it is characterised by the development of specific cellular immune responses to the pathogen present at the site of tissue injury.

Cytokines, which act as mediators of inflammation, are small secreted proteins, polypeptides and glycopeptides that are produced as a means of intercellular communication [146]. They exert their effect by binding to specific membrane receptors, resulting in the activation of intracellular second messengers [including cyclic adenosine monophosphate (cAMP), inositol triphosphate/diacylglycerol (IP3/DAG) and protein kinases] to alter cell behaviour. Cytokines exhibit redundancy, in that many cytokines appear to share similar functions. On the other hand, the effect of particular cytokines on a given cell could vary depending on cell type. Like hormones, cytokines are extremely potent and are active in the femtomolar–picomolar concentration range.

One important difference between cytokines and hormones is that cytokine concentrations can increase up to 1000 fold during infection while hormones usually vary by less than one order of magnitude. Cytokines are involved in extensive networks that involve synergistic as well as antagonistic interactions and exhibit both negative and positive regulatory effects on various target cells.

3.2 Cytokines Relevant to Pancreatitis

A number of inflammatory mediators are produced locally and systemically during acute pancreatitis (Figure 3.1). After the initial injury to the acinar cells, the cytokine cascades develop quickly with a rapid amplification of various mediators.

Interleukin-1 (IL-1) and tumour necrosis factor-alpha (TNFα) have the ability to induce nearly all of the other mediators while feeding back to produce a direct noxious effect within the pancreas itself [146].

A number of studies have reported a correlation between the severity of an episode of acute pancreatitis and serum cytokine levels [147-149]. In particular, interleukin-6 (IL-6) and interleukin-8 (IL-8) are now generally accepted as useful markers in the early assessment of severity of acute pancreatitis [150, 151]. Increased serum levels of TNFα and IL-1 have also been reported in patients with acute pancreatitis [146, 152, 153].

Cytokines may also be involved in the progression of chronic pancreatitis.

Serum IL-1 levels are elevated in chronic pancreatitis patients and serum IL-6 levels are correlated with C-reactive protein (CRP) in patients with chronic pancreatitis [154].

Increased expression of transforming growth factor beta (TGFE) has been described in human chronic pancreatitis [155, 156]. Combined determination of both s-fractalkine (a member of the chemokine superfamily) and TGFβ in human serum is also correlated with the severity of chronic pancreatitis [157]. Using a transgenic mouse model, in vivo studies have shown that overexpression of IL-1 and TGFβ1 induces chronic pancreatitis

[112, 158].

Figure 3.1

Inflammatory Mediators of Acute Pancreatitis

Inflammatory mediators of acute pancreatitis (adapted from Norman et al [146] with permission). After the initial injury to the acinar cells, the cytokine cascades develop quickly with rapid amplification of various mediators. Interleukin-1 (IL-1) and tumor necrosis factor alpha (TNFα) have the ability to induce nearly all of the other mediators while feeding back to produce a direct noxious effect within the pancreas itself.

Essentially all of these mediators are produced under the influence of inflammatory cytokines, or play an activate role in initiating or amplifying the cytokine cascade [146].

N.O.=nitric oxide; INF=interferon; PAF=platelet activating factor.

Further support for a role of cytokines in pancreatitis comes from evidence that

IL-1, IL-6 and TNFα are all produced during experimental pancreatitis induced by various methods such as caerulein hyperstimulation, intraductal taurocholate infusion and microvascular ischaemia [159, 160]. Increased TNFα expression at both mRNA and protein levels has been demonstrated in pancreatic acinar cells in the caerulein hyperstimulation model of pancreatitis in the rat [161]. IL-10 also increases at the initiation of acute pancreatitis and returns to basal levels thereafter [162] .

Many of the cytokines released during inflammation of the pancreas have also been established as activators of PSCs. In vitro studies of rat and human PSCs have identified IL-1, IL-6, TNFα, PDGF and TGFβ as regulators of PSC activation [104,

115-117]. Potential sources of these activating factors are activated macrophages, platelets, pancreatic acinar cells, ductal cells and endothelial cells. Notably, it has been shown that PSCs can synthesise cytokines themselves, suggesting that an autocrine loop could perpetuate PSC activation even in the absence of the initial triggers [104, 116,

117]. In the clinical situation, during alcohol-induced necroinflammation, PSCs are likely to be exposed not only to alcohol itself but also to cytokines. However, whether ethanol and cytokines exert synergistic effects on PSC activation has not yet been elucidated. Since IL-1 and TNFα are released early in pancreatitis and are capable of inducing nearly all of the other mediators, these two cytokines were chosen for this study.

3.2.1 Interleukin-1 (IL-1)

IL-1 is an important mediator of the inflammation response in the body.

Increased level of IL-1 expression and synthesis has been reported in patients with various viral, bacterial, fungal, and parasitic infections; intravascular coagulation; solid 31

tumours; leukemias; asthma; pancreatitis; transplant rejection etc. [163]. IL-1 is the prototypic multifunctional cytokines and affects nearly every cell type and often in concert with other cytokines or small mediator molecules.

The main members of the IL-1 family are IL-1α and IL-1β. IL-1 activity involves two receptors: IL-1R-I and IL-1R-II. IL-1 is secreted in its precursor form which is activated by IL-1 converting enzyme (ICE). IL-1α and IL-1β are involved in immune defense against infection; IL-1 receptor antagonist (IL-1RA) competitively inhibits receptor binding and prevents signal transduction thereby blocking the role of

IL-1 in immune activation.

Many cell types are known to produce IL-1 and IL-1 converting enzyme (ICE), including macrophages, monocytes, fibroblasts and dendritic cells. The main sources of

IL-1 in the pancreas are inflammatory leukocytes [164]. Some studies have suggested acinar cells may also produce IL-1 during pancreatic injury [165]. As noted earlier, upon activation, PSCs also produce cytokines such as IL-1 [166] (including a newly identified IL-1 family member IL-33 [167]), IL-8 [118], and TGFβ [168].

IL-1 has also been shown to play a role in the inflammatory cascade of pancreatitis. Experimental studies report increased production of IL-1 in the early phases of pancreatitis. Immunostaining of tissues from experimental caerulein-induced acute pancreatitis has shown that IL-1 is detected within the pancreas early in the course of pancreatitis [169]. Furthermore, rat with pancreatitis induced by retrograde injection of deoxycholate into the pancreatic duct exhibited reduced mortality when administrated

IL-1RA intravenously [170]. In addition, another study demonstrated attenuation of pancreatic injury and decreased mortality in mice with experimental acute pancreatitis following administration of IL-1RA or the use of IL-1 receptor knockout animals [171-

173]. 32

It is now believed that in addition to its role in AP, IL-1 also contributes to the development of CP. Mews et al [117] showed that IL-1 activates PSCs. A recent in vivo study using a transgenic IL-1 overexpression mouse model has shown typical features of chronic pancreatitis (acinar atrophy and fibrosis), along with prominent expression of

TNFα and TGFβ as well as MMPs 2, 7 and 9 [158]. Importantly, the severity of chronic pancreatitis changes correlated well with the level of IL-1 expression [158].

3.2.2 Tumour Necrosis Factor alpha (TNFα)

TNFα is secreted as a 26KD transmembrane protein. The extracellular domain of this protein is cleaved off by TNFα converting enzyme (TACE) to release the active soluble form [174]. Two receptors have been identified for TNFα and both receptors act to increase nuclear translocation of NFκB, which increases the expression of a variety of genes by binding to their promoter regions.

It appears that TNFα is one of the driving forces for the initiation and propagation of the systemic inflammatory response. TNFα is produced in the pancreas in the early stages of AP and is detected in high amounts in both blood and tissue.

Serum levels of TNFα are related to the severity of AP [153]. Another study has shown that the level of TNF receptors acts as a marker of TNF activity and is also elevated in chronic pancreatitis patients [175]. TNFα has also been reported to be elevated in the early stages of CP in a study of chronic alcoholic pancreatitis patients [176].

The main source of TNFα in vivo is activated macrophages, although TNFα is known to be produced by other cell types, such as NK cells, T-lymphocytes and mast cells. In the pancreas, its expression has been observed in acinar cells and inflammatory cells [177]. 33

The effect of TNFα on PSC activation has been studied in cultured PSCs. It was found that TNFα stimulates total collagen protein synthesis but does not affect type I collagen mRNA [117], suggesting that TNFα induced collagen protein expression is regulated at a post transcriptional level.

This Chapter describes studies related to the effect of cytokines (IL-1 and TNFα) in the presence and absence of ethanol on PSC activation. The aim of these studies was to determine whether these cytokines and ethanol exert a synergistic effect on PSC activation as assessed by αSMA, collagen I and fibronectin expression.

3.3 Methods

3.3.1 Isolation of Rat PSCs

Pancreatic stellate cells were isolated using the method of Apte et al [30]. a) Reagents

Except where otherwise mentioned throughout this thesis, all chemicals were of analytical reagent grade and were purchased from the Sigma Chemical Company (St

Louis, MO, USA).

1. Gey’s Balanced Salt Solution [GBSS; prepared with sodium chloride (GBSS +

NaCl) and without sodium chloride (GBSS – NaCl) sodium chloride]

Magnesium chloride (MgCl2.6H2O) 0.21g/L

Magnesium sulfate (MgSO4; anhydrous) 0.0342g/L

Potassium chloride (KCl) 0.37g/L

Potassium dihydrogen phosphate (KH2PO4; anhydrous) 0.03g/L

Sodium bicarbonate (NaHCO3) 2.27g/L

Sodium chloride (NaCl) 7.00g/L

Sodium hydrogen phosphate (Na2HPO4; anhydrous) 0.112g/L 34

Calcium chloride (CaCl2) 0.225g/L

2. Enzyme solution in GBSS + NaCl

Collagenase P (Roche, Sydney, Australia) 1.3mg/ml

Pronase (Sigma) 1.0mg/ml

Deoxyribonuclease (Roche, Sydney, Australia) 0.01mg/ml

3. Culture Medium (Gibco BRL, Grand Island, NY, USA)

Iscove’s modified Dulbecco’s medium (IMDM), containing:

Foetal bovine serum 10%

Glutamine 4mM

Penicillin 100U/ml

Streptomycin 100Pg/ml

4. Hanks Balanced Salt Solution (HBSS)

Potassium chloride (KCl) 0.4g/L

Potassium dihydrogen phosphate monobasic (KH2PO4, anhydrous) 0.06g/L

Sodium chloride 8.0g/L

Sodium hydrogen phosphate dibasic (Na2HPO4, anhydrous) 0.0447g/L

D-glucose 1.0g/L

Phenol red 0.01g/L

Sodium bicarbonate (NaHCO3) 0.35g/L

5. 0.3% Bovine serum albumin (BSA; Trace Electron Pty Ltd, Australia)

0.15g BSA / 50ml GBSS + NaCl

6. Nycodenz (Nycomed Pharma, Oslo, Norway)

2.87g Nycodenz / 10ml GBSS – NaCl

b) Method 35

One male Sprague-Dawley rat (150-200g) was sacrificed by decapitation for each preparation of pancreatic stellate cells. The pancreas was dissected, removed and placed into a 50mL glass beaker containing ice-cold saline (0.9% NaCl solution), trimmed of adipose and connective tissue as well as blood vessels and transferred to a

60mm plastic Petri dish. Using an insulin syringe, the pancreas was injected with 10mL of the enzyme solution (protease, DNase and collagenase) until all pancreatic lobules were well separated. The pancreas was then transfered to aconical (Erlenmeyer) flask and incubated in 20mL of enzyme solution at 37RC for 4 minutes in a shaking water bath at high speed (240 cycles/minutes) followed by 3 minutes at low speed (120 cycles/minutes). Following incubation, the pancreas was finely minced with scissors and any remaining adipose, connective tissue or blood vessels removed before the second incubation at 37RC in the shaking water bath (7 minutes at low speed). At the end of this incubation, digested pancreatic tissue was transferred into a 50mL Falcon tube and pipetted through successively narrower orifices using 5mL and 1mL Gilson pipette tips and filtered through a 250Pm nylon mesh. Cells were then centrifuged at

450g for 10 minutes at 4RC, using a Beckman J2-21 centrifuge (Beckman, Palo Alto,

CA, USA). The cell pellet was washed by resuspension in GBSS + NaCl containing 0.3% bovine serum albumin (BSA) and then recentrifuged as above. The washed pellet was then resuspended in 9.5mL GBSS + NaCl with BSA, to which 8mL of a 28.7% solution of Nycodenz in GBSS NaCl (final Nycodenz concentration 11.4%) was added. 6mL of GBSS + NaCl with BSA were placed into a polycarbonate centrifuge tube and the cell suspension in Nycodenz gently layered underneath using a length of polyvinyl tubing attached to a 25mL syringe, taking care not to disrupt the interface (good separation of stellate cells was dependent on an undisturbed interface). The sample was then centrifuged at 1400g for 20 minutes at 4RC. Stellate cells separated into a hazy 36

(fuzzy) band just above the interface. This band was harvested using a glass transfer pipette and the cells were washed and resuspended in culture medium (as described above). The above technique yielded a preparation of stellate cells devoid of contamination by acinar cells, endothelial cells or macrophages, as evidenced by negative staining for the markers factor VIII and ED1 respectively [30].

Cells were plated into 25 cm2 culture flasks and grown to confluence in a

R humidified atmosphere of 5% CO2/95% air at 37 C. Culture medium was changed the following day and from then on twice weekly. Cells were passaged and replated at equal seeding densities for use in individual experiments.

3.3.2 Passaging of Rat PSCs a) Reagents

These were as outlined in Section 3.3.1 with the following addition:

1. Trypsin (0.05%) EDTA (0.1%) (Gibco BRL, Grand Island, NY, USA)

b) Method

Cells were washed twice with sterile PBS warmed to 37RC. Cells were then incubated at 37RC with 1.0mL 0.05% trypsin-0.1% EDTA per 25 cm2 monolayer for 1-2 minutes, until the cells were detached from the culture surface. The reaction was terminated by the addition of 2mL culture medium containing 10% fetal bovine serum.

Cells were harvested and placed into centrifuge tubes and then centrifuged at 450g for

10 minutes at 4RC. The pellet was resuspended in 1mL of culture medium and mixed well, and a 20μL cell suspension was removed and mixed with an equal volume of

Trypan blue. An aliquot of 10μL was removed for cell counting using a haemocytometer. Following estimation of total cell number, cells were plated at equal 37

seeding densities ranging from 4x104 to 15x104 into 6-well culture plates, 1x105 and 3x

105 into 60mm Petri dishes or 100mm Petri dishes as required for use in individual experiments. Cells from each individual experiment were not used beyond the first passage.

3.3.3 Collection of Cell Lysates from Ethanol ± IL-1 Treated Rat PSCs a) Reagents

1. Culture Medium (Invitrogen, Carlsbad, CA, USA)

Iscove’s modified Dulbecco’s medium (IMDM), containing:

Fetal bovine serum 0.1%

Glutamine 4mM

2. Recombinant rat IL-1α (PeproTech Asia, Rehovot, Israel)

Serum reduced medium (0.1% FBS) was used for all in vitro experiments

involving ethanol with the exception of experiments where PSCs in early culture

were used.

3. Cell lysis buffer (Cell Signalling, Beverly, MA, USA)

4. Phenylmethanesulphonyl fluoride (PMSF)

100mM stock solution in absolute ethanol

5. Bovine serum albumin (BSA) standards were diluted in double deionised water

and stored at -20°C. The concentration of the BSA stock solution was 2mg/ml

(Pierce, Rockford, IL, USA).

6. Bicinchoninic acid (BCA): working reagent (Pierce, Rockford, IL, USA) was

prepared as follows:

50 parts of Reagent A was added to 1 part of Reagent B. 200μL mixed reagents

was then added to each well of a 96 well plate. 38

b) Method i) Treatment of rat PSCs in early culture with ethanol r IL-1

In order to assess the potential synergistic effects of alcohol and IL-1, we chose to study PSCs in early culture, since the cells are known to become activated (as assessed by DSMA activation) within 48 hours of isolation and plating on uncoated plastic culture well plates. It was thus postulated that subtle differences in PSC activation parameters were best studied within 24 hours of isolation of PSCs.

For this study, PSCs were treated with ethanol at a concentration of 5mM which corresponds to a blood alcohol concentration of 0.02g/100mL (0.02%) and is below the legal limit (0.05%) for driving in Australia. Higher concentrations of ethanol (10 and

50mM) have previously been shown to induce PSC activation [75].

IL-1 concentration used for the following studies was 0.5pg/mL. Mews et al

[117] has reported that IL-1 at concentrations higher than 1pg/mL significantly stimulates αSMA expression. To ensure that any synergistic effect of alcohol and IL-1 on PSC activation was not obscured by the known activation effect of the individual factors, lower concentration of both ethanol and IL-1 were chosen for this study.

In addition, to ensure adequate yield of protein for further analyses, PSC preparations from two rats were pooled and then evenly distributed into a 6 well dish.

R Cells were cultured for 6 hours at 37 C in 95% air / 5% CO2. Cells were then serum starved in IMDM with 0.1% FBS for an additional 3 hours. At this time, 1.8mL IMDM with 10% FBS was replaced with the same volume of serum free medium thereby avoiding loss of partially attached cells. Cells were incubated in this serum reduced

(FBS 0.1%) medium for 3h followed by culture in serum reduced IMDM in sealed air- tight 6-well plates with the following treatment regimens for 12h: i) culture medium 39

alone, ii) ethanol 5mM, iii) IL-1 0.5 pg/mL, iv) ethanol 5mM + IL-1 0.5 pg/mL. Cells were then harvested and lysed as described below. ii) Collection of cell lysates and protein estimation

Cells were detached following the cell passage procedure described in Section

3.3.2. After harvest and centrifugation, cell pellets were washed twice with PBS and resuspended in 60μL lysis buffer containing 1% of the PMSF stock solution (1mM final concentration) and gently mixed by pipetting. Samples were gently agitated on a tilting stage at 4°C for one hour, and then centrifuged at 14000g for 10 minutes. The supernatants were stored at -80°C until use.

Protein concentration in cell lysates was measured using the Pierce bicinchoninic acid (BCA) protein assay kit as per the manufacturer’s instructions.

Briefly, a standard curve was established by the addition of 10μL BSA standard (25,

125, 250, 500, 750, 1000, 1500 and 2000μg/ml) into the wells of a 96 well plate. 10μl of sample were added into the appropriate well. 200μL of the working reagent from the

BCA kit were then added to each well and contents were mixed by pipetting. The plate was wrapped in aluminium foil and incubated at 37°C for 30 minutes. Absorbance was measured at 562nm using the Bio Tek ELLX800 microplate reader (Bio Tek

Instruments Inc, Winooski, VT, USA).

3.3.4 Collection of Cell Lysates from Ethanol ± TNFα Treated Rat

PSCs a) Reagents

These were as outlined in Section 3.3.3 with the following modification / addition:

1. Rat recombinant TNFα (PeproTech Asia, Rehovot, Israel)

b) Method

This was as described in Section 3.3.3 with the following modification/addition:

Mews et al [117] have reported that TNFα at concentrations of 10U/mL significantly stimulates αSMA expression. To ensure that any synergistic effect of alcohol and TNFα on PSC activation was not obscured by the known activation effect of individual factors, the initial concentration of TNFα selected for the study was 5U/mL. However, at this concentration of TNFα (alone or in combination with ethanol), PSCs didn’t exhibit any features of activation. Therefore, TNFα concentration was then increased to 10U/mL.

Although this concentration has been previously shown to increase αSMA expression by PSCs, it was determined that it would be of interest to examine whether 10U/mL of

TNFα in the presence of low concentrations of ethanol, could activate PSCs over and above that seen with TNFα alone.

3.3.5 Assessment of Ethanol ± IL-1 or Ethanol ± TNFα on αSMA

Expression by Rat PSCs a) Reagents

1. Monoclonal mouse αSMA antibody (Sigma)

2. Polyclonal rabbit α-tubulin antibody (Cell Signalling, Beverly, MA, USA)

3. Horseradish peroxidase (HRP)-labelled goat anti-mouse antibody (DAKO,

Botany, Australia)

4. Horseradish peroxidase (HRP)-labelled goat anti-rabbit antibody (DAKO,

Botany, Australia)

5. Phosphate buffered saline solution (PBS) pH 7.4

Sodium chloride (NaCl) 8g/L

Potassium chloride (KCl) 0.2g/L 41

Disodium orthophosphate (Na2HPO4) 1.4g/L

Potassium dihydrogen phosphate (KH2PO4) 0.24g/L

6. 1.5M Tris base (pH 8.8)

18.15g/100mL double deionised H2O

7. 0.5M Tris base (pH 6.8)

6g/100mL double deionised H2O

8. 10% (w/v) Sodium dodecyl sulphate (SDS)

9. 30% (w/v) Acrylamide/bis-acrylamide

10. 10% (w/v) Ammonium persulfate (APS)

11. 0.05% (w/v) N, N, N’, N’-tetramethylethylenediamine (TEMED)

12. 1% (w/v) Bromophenol blue

13. Electrophoresis sample buffer

Double deionised water 47.5%

Glycerol 10%

0.5M Tris-HCl (pH 6.8) 12.5%

2-mercaptoethanol 5%

Bromophenol blue (1% w/v) 5%

SDS (10% w/v) 20%

14. Protein molecular weight standards (Pre-stained Broad Range; Biorad

Laboratories, Richmond, CA, USA)

15. 10x Electrophoresis running buffer (pH 8.3)

Tris base 30g/L

Glycine 144g/L

SDS 10g/L

16. Skim milk powder 42

17. Polyoxyethylene sorbitan monolaurate (Tween-20)

18. 5% Bovine serum albumin (BSA; Pierce, Rockford, IL, USA)

0.5g/10ml 0.1% Tween-20 in Phosphate buffered saline (PBS)

20. Restore western blot stripping buffer (Pierce Biotechnology, Rockford, IL,

USA)

21. Ponceau S staining solution (0.5%)

22. PBS + 0.1% Tween-20 (TPBS)

1mL Tween-20/1L PBS

23. Amersham Enhanced Chemiluminescence (ECL) detection kit (Amersham,

Little Chalfort Buckinghamshire, UK)

b) Method

i) Gel electrophoresis and western blotting

A 10% (wt/vol) sodium dodecyl sulfate (SDS) polyacrylamide gel was used to separate sample proteins by electrophoresis. Protein standards of known molecular weight were run alongside the samples. Separated proteins were transferred onto nitrocellulose membranes using a commercial blotting apparatus (BioRad, Richmond,

CA, USA).

Each nitrocellulose membrane was incubated for 1-2 minutes with 5mL Ponceau

S staining solution (the stain binds to positively charged amino groups on immobilised proteins) to ensure equal protein loading and transfer. The detection limit of this staining is 250ng [178]. The membranes were then washed twice with double deionised

H2O. This was followed by a further 2 washes in PBS to remove any remaining staining solution. Membranes were then incubated for 1 hour at room temperature in blocking buffer [PBS (pH 7.4), skim milk 5%, Tween-20 0.1%] in order to prevent non-specific 43

binding of the antibody. This was followed by incubation for 1 hour at room temperature with the monoclonal mouse αSMA antibody (1:15000 in 0.1% TPBS containing 5% skim milk). The membranes were then washed 3 times for 5 minutes in

0.1% TPBS (pH 7.5) and incubated with the secondary antibody (HRP-labeled goat anti-mouse IgG, 1:2000 in 0.1% TPBS containing 5% skim milk) for 45 minutes at room temperature. The membranes were then washed 3 times as described above.

Relevant bands were detected using the Amersham Enhanced Chemiluminescence kit.

For quantitation, scanned autoradiographs were subjected to densitometry and analysed using Quantity One Software, Version 4.2.2 (BioRad). Densitometry readings were expressed as integrated optical density units (arbitrary densitometer units calculated from the density as well as the size of each band).

ii) Loading control for western blotting

Equal protein loading on the SDS gel was assessed using α-tubulin as a loading control. After completing the western blotting procedure for αSMA, the membrane was stripped to remove bound αSMA antibody using Pierce Restore western blot stripping buffer as per the manufacturer’s instructions. Briefly, the membrane was incubated with

5mL of the stripping buffer for 10 minutes at 37°C. This was followed by washing the membrane three times for 10 minutes each in 0.05% TPBS and the stripped membrane was incubated with a rabbit polyclonal anti-α-tubulin (1:1000) in 0.1% TPBS containing

5% skim milk antibody overnight at 4°C. The membranes were then washed 3 times for

5 minutes in 0.1% TPBS and incubated with the secondary antibody (HRP-labeled goat anti-rabbit IgG, 1:2000 in 0.1% TPBS containing 5% skim milk) for 1 hour at room temperature. The membranes were then washed 3 times as described above. Relevant bands were detected using the Amersham Enhanced Chemiluminescence kit. For 44

quantitation, scanned autoradiographs were subjected to densitometry and analysed using Quantity One Software, Version 4.2.2 (BioRad). Densitometry readings were expressed as integrated optical density units (as described above).

3.3.6 Assessment of the Effects of Ethanol ± IL-1 or Ethanol ± TNFα on Collagen I Expression by Rat PSCs a) Reagents

These were as outlined in Section 3.3.5 with the following modifications/ additions:

1. Polyclonal pro-collagen I

2. Qentix Western Blot Signal Enhancement Kit (Pierce, Rockford, CA, USA)

b) Method

This was as described in Section 3.3.5 with the following modifications: A 8%

(wt/vol) sodium dodecyl sulfate (SDS) polyacrylamide gel was used to separate sample proteins by electrophoresis. Membranes were then enhanced using the Qentix Western

Blot Signal Enhancement Kit according to the manufacturer’s instructions and subsequently incubated for two hours at room temperature in blocking buffer [PBS (pH

7.4), skim milk 5%, Tween-20 0.1%]. This was followed by an overnight incubation at

4°C with the polyclonal goat anti-rabbit collagen I antibody (1:1000 in 0.1% TPBS containing 5% skim milk). HRP-labeled goat anti-rabbit IgG (1:2000 in 0.1%TPBS containing 5% skim milk) were applied as a secondary reagent for 1 hour at room temperature. Equal loading was assessed by α-tubulin expression as described above.

3.3.7 Assessment of the Combination of Ethanol, IL-1 and TNFα on

Fibronectin Expression by Rat PSCs a) Reagents

These were as outlined in Section 3.3.5 with the following modifications/ additions:

1. Mouse monoclonal [IST-9] anti- Fibronectin antibody (Abcam, Cambridge, UK)

2. Mouse monoclonal anti-GAPDH antibody (Abcam, Cambridge, UK)

b) Method

i) Fibronectin western blotting

This was as described in Section 3.3.5 with the following modifications: A 8%

(wt/vol) sodium dodecyl sulfate (SDS) polyacrylamide gel was used to separate sample proteins by electrophoresis. Membranes were then incubated for one hour at room temperature in blocking buffer [PBS (pH 7.4), skim milk 5%, Tween-20 0.1%]. This was followed by an overnight incubation at 4°C with the monoclonal anti-mouse fibronectin antibody (1:1000 in 0.1% TPBS containing 5% skim milk). HRP-labeled goat anti-mouse IgG (1:2000 in 0.1% TPBS containing 5% skim milk) was applied as a secondary reagent for 1 hour at room temperature.

ii) Loading control for fibronectin western blotting

Equal protein loading for SDS gel was assessed using the house keeping protein

GAPDH. Although α-tubulin have been used as a loading control in previous experiment, the antibody used to detect α-tubulin was a polyclonal antibody which can be prone to non-specific binding. GAPDH can be highly specific detected using a monoclonal antibody, therefore was used as the loading control in all experiments from here to end. 46

After completing westerns blotting procedure for fibronectin, the membrane was stripped to remove bound fibronectin antibody using Pierce Restore western blot stripping buffer as described in Section 3.3.5. After stripping, the membrane was incubated with a mouse monoclonal anti-GAPDH (1:15000) in 0.1% TPBS containing antibody overnight at 4°C. The membranes were then washed 3 times for 5 minutes in

0.1% TPBS (pH 7.5) and incubated with the secondary antibody (HRP-labeled goat anti-mouse IgG, 1:2000 in 0.1% TPBS containing 5% skim milk) for 1 hour at room temperature. The membranes were then washed 3 times as described above. Relevant bands were detected using the Amersham Enhanced Chemiluminescence kit. For quantitation, scanned autoradiographs were subjected to densitometry and analysed using Quantity One Software, Version 4.2.2 (BioRad). Densitometry readings were expressed as integrated optical density units.

3.3.8 RNA Extraction from Treated Rat PSCs a) Reagents

1. RNeasy Plus Mini Kit – Qiagen (Doncaster, Victoria, Australia)

Genomic DNA (gDNA) Eliminator Mini Spin Columns

RNeasy Mini Spin Columns

Collection tubes (1.5 and 2ml)

Buffer RLT Plus

Working solution: 10Pl E-mercaptoethanol 14.3M

per 1ml buffer RLT plus (Note: this solution is

stable for 1 month at room temperature).

Buffer RPE (concentrate) 47

Working solution: 4 volumes absolute ethanol per

1 volume Buffer RPE concentrate.

RNase-free water

2. 14.3M E-mercaptoethanol

3. Absolute ethanol

4. Ethanol 70%

5. QiA shredder spin column – Qiagen, Doncaster, Victoria, Australia

b) Method

The following steps were all performed at room temperature. Cells were treated as described in Section 3.3.3. Cells were detached from the plate as described in Section

3.3.2. After washing twice with warmed PBS, supernatant was completely removed, the cell pellet was loosened by gently flicking the tube and cells were disrupted by adding

350Pl of Buffer RLT Plus. The lysates were then loaded onto QiA shredder spin columns placed into 2ml collection tubes and centrifuged at t10000g for 2 minutes. The homogenised lysates were then transferred to a gDNA eliminator spin column placed on top of a 2 ml collection tube and centrifuged at t10000g for 30 seconds. 350Pl of ethanol 70% were then added to the flow through in each collection tube and the content mixed well by pipetting. Up to 700Pl of this sample was then transferred to an RNeasy

Spin Column placed into a collection tube, centrifuged at t 10000g for 15 seconds and the flow-through was then discarded. The remainder of the sample was then transferred into the same RNeasy Spin Column, centrifuged at t 10000g for 15 seconds and the flow through discarded. In order to wash the Spin Column membrane, 700Pl Buffer

RW1 were added to the RNeasy Spin Column (placed on a collection tube) followed by centrifugation at t10000g for 15 seconds. Particular care was taken to avoid any contact 48

between the membrane and the flow-through which was again discarded. 500Pl Buffer

RPE were then added to the RNeasy Spin Column (fitted on a collection tube), centrifuged at t 10000g for 15 seconds and the flow-through discarded. 500Pl Buffer

RPE were loaded again into the RNeasy Spin Column followed by centrifugation at t10000g for 2 minutes (this longer centrifugation step was undertaken in order to ensure complete evaporation of ethanol and avoid any interference with subsequent experimental steps). The RNeasy Spin Column was then carefully removed from the collection tube (in order to avoid any contact of the column with ethanol). The column was then placed into a fresh collection tube and centrifuged at full speed for 1 minute in order to eliminate any remaining RPE buffer. The RNeasy Spin Column was then placed onto a new collection tube. 30Pl RNase-free water were directly added onto the

Spin Column Membrane followed by centrifugation at t10000g for 1 minute in order to elute the RNA. RNA content was determined using a full spectrum UV spectrophotometer (NanoDrop, Thermo Fisher Scientific, MA, USA) and samples were stored at -80°C until use.

3.3.9 Preparation of cDNA for Real-Time PCR Analysis a) Reagents

1. High Capacity cDNA Reverse Transcription Kit (Invitrogen, Carlsbad,

CA, USA) containing the following components:

10X Reverse Transcription buffer

25X dNTP mix (100mM)

10X random primers

MultiScribe reverse transcriptase

2. Molecular grade water (Invitrogen, Carlsbad, CA, USA) 49

b) Method

0.25Pg of RNA was placed into PCR tubes on ice and the volume made up to

10Pl with molecular grade water. The 2X master mix (total reaction volume: 20Pl) was prepared on ice as follows:

Component Volume per reaction (μl) 10X RT buffer 2.0 25X dNTP Mix (100mM) 0.8 10X RT Random Primers 2.0 MultiScribe Reverse Transcriptase 1.0 Nuclease Free Water 4.2 Total per Reaction 10.0

A negative control reaction (containing all components of the kit with the exception of the MultiScribe reverse transcriptase) was also prepared. The master mix was mixed thoroughly, centrifuged and mixed again. 10Pl of 2X master mix were then added to each tube containing the diluted RNA and the solution mixed using a pipette.

Reverse transcription was then performed as follows:

Step 1 Step 2 Step 3 Step 4 Temperature (qC) 25 37 85 4 Time 10 min 120 min 5 sec f

Samples were stored at -20°C until use.

3.3.10 Real-time PCR for Collagen I mRNA Expression a) Reagents

1. Quantifast SYBR Green PCR kit (Qiagen, Doncaster, Victoria, Australia)

containing the following components: 50

HotStartTaq Plus DNA Polymerase

QuantiFast SYBR Green PCR Buffer

dNTP mix

2. Primer sets for rat collagen I (Quantitect Primers, Qiagen Doncaster, Victoria,

Australia)

3. Primer sets for rat 18S ribosomal RNA (Quantitect Primers, Qiagen Doncaster,

Victoria, Australia)

4. Molecular grade water (Invitrogen, Carlsbad, CA, USA)

b) Method

The standards were prepared as follows:

1 0.5 0.25 0.125 0.0625

30Pl undiluted 30Pl (1) + 30Pl (0.5) + 30Pl (0.25) + 30Pl (0.125) +

cDNA 30Pl water 30Pl water 30Pl water 30Pl water

The RT-PCR reaction mix was prepared for the target gene and the 18S housekeeping gene (final reaction volume 25Pl) as follows:

The reaction solution was mixed thoroughly and centrifuged. 2.5Pl cDNA were then added to the corresponding wells of a 96-well opaque PCR plate. 22.5Pl of the

PCR reaction mix were added to each well. Two controls were run alongside the standards and the sample: i) water (non transcription control) in order to exclude any contamination or primer dimer formation and ii) a no-RT negative control (i.e. non reverse-transcribed RNA, in order to exclude any contamination with genomic DNA).

The 96-well plate was then sealed and centrifuged at 800rpm for 3 minutes. The plate 51

was then placed into the real-time PCR machine (Light Cycler 480, Roche Diagnostics

Australia, Pty Ltd, Castle Hill, NSW).

After completion of the reaction, data were analysed using the Roche Light

Cycler software. The relative value of each sample was normalised to the relative value of the housekeeping gene 18S rRNA. The relative values of the treated samples were then normalised to control values.

3.3.11 Statistical Analysis

Data are expressed as meanrSEM and analysed as appropriate by the Kruskal-

Wallis test followed by Dunn’s post-hoc test, one-way ANOVA followed by Tukey’s post-hoc test or Student’s t test (for paired data). The analyses were performed using the

GraphPad Prism Software.

3.4 Results

3.4.1 Rat PSC Isolation and Culture

The yield of rat PSCs was between 1 and 5x106 per whole rat pancreas preparation. The variability in the yield might be explained by the age of the rat. [Note: in the experience of Pancreatic Research Group, PSC yield from rats aged between 5-6 weeks are higher than the yield for older rats]. Using uncoated plastic cell culture flasks, it was observed that the majority of cells settled between 6 and 24 hours after isolation.

Cells displayed a polygonal shape and contained lipid droplets in their cytoplasm. 80-90% of PSCs retained their vitamin A droplets up until the first passage.

3.4.2 Effect of Ethanol ± IL-1 and Ethanol ± TNFα on αSMA

Expression by rat PSCs

3.4.2.1 Ethanol ± IL-1

The expression of αSMA by cells exposed to ethanol or IL-1 alone was higher than control but this difference did not reach statistical significance. The lack of PSC activation by ethanol or IL-1 alone may be due to the very low concentrations of ethanol

(5mM) and IL-1 (0.5pg/mL) used in these studies. However, αSMA expression in cells treated with ethanol+IL-1 was significantly higher than that in control cells or cells treated with ethanol and IL-1 alone (p<0.05, EtOH+IL-1 vs EtOH, vs IL-1 and vs CTRL; n=6 separate rat PSC preparations) (Figure 3.2).

3.4.2.2 Ethanol ± TNFα

Two concentrations of TNFα (5U/mL and 10U/mL) were used for this study. At lower concentrations (5U/mL), TNFα alone or in combination with ethanol has no effect on αSMA expression by PSCs (Figure 3.3). At higher concentrations (10U/mL), TNFα alone also had no effect on αSMA expression. However, the combination of 10U/mL

TNFα with ethanol significantly increased αSMA expression by PSCs (p<0.01,

EtOH+TNFα vs CTRL, p<0.05, EtOH+TNFα vs EtOH and vs TNFα; n=4 separate rat

PSC preparations (Figure 3.4).

Figure 3.2

Effect of Ethanol ± IL-1 on Rat Pancreatic Stellate Cell Activation in Vitro

αSMA

α-tubulin

CTRL EtOH IL-1 EtOH+IL-1

Densitometry units (% of CTRL)

Synergistic effect of IL-1 and ethanol on rat PSC activation in vitro. A representative western blot and densitometry analysis of αSMA expression by rat PSCs exposed to serum reduced medium alone (CTRL), ethanol 5mM (EtOH), IL-1 0.5pg/mL or ethanol

5mM + IL-1 0.5pg/mL. A significant increase of αSMA expression was observed with cells exposed to ethanol+IL-1 (*p<0.05; EtOH+IL-1 vs EtOH, vs IL-1 and vs CTRL, n=6 separate rat PSC preparations). α-tubulin was used as a loading control. 54

Figure 3.3

Effect of Ethanol ± TNFα (5U/mL) on Rat Pancreatic Stellate Cell Activation in Vitro

αSMA

α-tubulin

CTRL EtOH TNFα EtOH+TNFα

Densitometry

units (% of CTRL)

CTRL EtOH TNFα EtOH+TNFα

Effect of ethanol in the combination of low concentration of TNFα (5U/mL) on rat PSC

αSMA expression. A representative western blot and densitometry analysis of αSMA expression by PSCs exposed to serum reduced medium alone (CTRL), ethanol 5mM

(EtOH), TNFα 5U/mL or ethanol 5mM + TNFα 5U/mL. There is no effect of ethanol and TNFα alone or in combination on αSMA expression by PSCs (n=4 separate rat

PSC preparations). α-tubulin was used as a loading control. 55

Figure 3.4

Effect of Ethanol ± TNFα (10U/mL) on Rat Pancreatic Stellate Cell Activation in Vitro

αSMA

α-tubulin

CTRL EtOH TNFα EtOH+TNFα

# *

Densitometry units (% of CTRL)

CTRL EtOH TNFα EtOH+TNFα

Synergistic effect of TNFα and ethanol on rat PSC activation in vitro. A representative western blot and densitometry analysis of αSMA expression by rat PSCs exposed to serum reduced medium alone (CTRL), ethanol 5mM (EtOH), TNFα 10U/mL or ethanol

5mM + TNFα 10U/mL. A significant increase of αSMA expression was observed with

PSCs exposed to ethanol+TNFα (#p<0.01, EtOH+TNFα vs CTRL, *p<0.05,

EtOH+TNFα vs EtOH and vs TNFα; n= 4 separate rat PSC preparations). a-tubulin was used as a loading control. 56

3.4.3 Effect of Ethanol ± IL-1 and Ethanol ± TNFα on Collagen I

Expression (mRNA and Protein)

3.4.3.1 Ethanol ± IL-1 mRNA

The combination of ethanol and IL-1 had no effect on collagen I mRNA level compared to control cells or cells treated with each compound alone (Figure 3.5).

Protein

Ethanol and IL-1 alone had no effect on collagen protein expression. However, collagen I protein expression was significantly higher in cells treated with ethanol+IL-1 than control cells or cells treated with ethanol or IL-1 alone (p<0.05, EtOH+IL-1 vs E5, vs IL-1 and vs CTRL; n=4 separate rat PSC preparations) (Figure 3.6), suggesting that

IL-1 and ethanol may have a post transcriptional effect on collagen I expression by

PSCs.

3.4.3.2 Ethanol ± TNFα mRNA and Protein

Similar to the results with ethanol and IL-1, a combination of ethanol and TNFα had no effect on collagen I mRNA in PSCs (Figure 3.7). However, in contrast to the observation of ethanol with IL-1 (where a post-transcriptional effect was observed on collagen I protein expression), ethanol ± TNFα did not affect collagen protein levels in

PSCs (Figure 3.8).

Figure 3.5

Effect of Ethanol ± IL-1 on Rat Pancreatic Stellate Cell Collagen I mRNA Expression

Relative normalised collagen I mRNA (% of CTRL)

CTRL EtOH IL-1 EtOH+IL-1

Effect of ethanol and IL-1 on collagen I mRNA expression by rat PSCs. PSCs were incubated for 24 hours at 37°C as follows: i) serum reduced medium alone (CTRL); ii) ethanol 5mM (EtOH); iii) IL-1 0.5pg/mL or iv) ethanol 5mM + IL-1 0.5pg/mL.

Exposure of PSCs to ethanol±IL-1 had no effect on collagen I mRNA expression by

PSCs (n=3 separate rat PSC preparations). Collagen I mRNA levels were normalised against house keeping gene 18S levels.

Figure 3.6

Effect of Ethanol ± IL-1 on Rat Pancreatic Stellate Cell Collagen I Protein Expression

collagen I

α-tubulin CTRL EtOH IL-1 EtOH+IL-1

Densitometry units (% of CTRL)

CTRL EtOH IL-1 EtOH+IL-1

Synergistic effect of IL-1 and ethanol on rat PSC activation in vitro. A representative western blot and densitometry analysis of collagen I expression by rat PSCs exposed to serum reduced medium alone (CTRL), ethanol 5mM (EtOH), IL-1 0.5pg/mL or ethanol

5mM + IL-1 0.5pg/mL. A significant increase of collagen I was observed with cells exposed to ethanol+IL-1 (*p<0.05, EtOH+IL-1 vs CTRL and vs EtOH; n= 4 separate rat PSC preparations). a-tubulin was used as a loading control.

Figure 3.7

Effect of Ethanol ± TNFα on Rat Pancreatic Stellate Cell Collagen I mRNA Expression

Relative normalised

collagen I mRNA (% of CTRL)

CTRL EtOH TNFα EtOH+TNFα

Effect of ethanol and TNFα on collagen I mRNA expression by rat PSCs. PSCs were incubated for 24 hours at 37°C as follows: i) serum reduced medium alone (CTRL); ii) ethanol 5mM (EtOH); iii) TNFα 10U/mL or iv) ethanol 5mM + TNFα 10U/mL.

Exposure of PSCs to ethanol ± TNFα had no effect on collagen I mRNA expression

(n=3 separate rat PSC preparations). Collagen I mRNA levels were normalised against house keeping gene 18S levels.

Figure 3.8

Effect of Ethanol ± TNFα on Rat Pancreatic Stellate Cell Collagen I Protein Expression

collagen I

α-tubulin CTRL EtOH TNFα EtOH+TNFα

Densitometry units (% of CTRL)

CTRL EtOH TNFα EtOH+TNFα

Effect of TNFα and ethanol on collagen I protein expression by rat PSCs. A representative western blot and densitometry by rat PSCs exposed to serum reduced medium alone (CTRL), ethanol 5mM (EtOH), TNFα 10U/mL or ethanol 5mM + TNFα

10U/mL. Exposure of PSCs to ethanol ± TNFα had no effect on collagen I protein expression compared to individual treatments (n=4 separate rat PSC preparations). α- tubulin was used as a loading control.

3.4.4 Effect of Ethanol, TNFα and IL-1 on Fibronectin Expression

Since production of ECM is an important characteristic feature of PSC activation, fibronectin expression was assessed in rat PSCs exposed to ethanol ± IL-1, and ethanol ± TNFα. In addition, because no study on PSC fibronectin production has used such low concentrations of each compound and to better mimic the in vivo situation, I also assessed the combination of all three compounds i.e. ethanol+IL-

1+TNFα on PSC fibronectin expression. Ethanol+IL-1 or ethanol+TNFα had no effect on fibronectin expression compared to cells treated with each compound alone. In addition, the combination of ethanol, IL-1 and TNFα had no effect on cells treated with the individual compounds (Figure 3.9).

Note: Table 1 (page 63) summerises the findings described in this Chapter (the effect of ethanol, IL-1 and TNFα on PSC activation).

Figure 3.9

Effect of Ethanol, IL-1 and TNFα on Fibronectin Protein Expression by Rat PSCs

Fibronectin

GAPDH CTRLL EtOH IL-1I 1 TNFα EtOHE OH EtOH IL-1I 1 EtOH +IL-1-1 +TNFα ++TNFT Fα +IL-1 +TNFα

Densitometry units (% of CTRL)

Effect of ethanol, IL-1 and TNFα on fibronectin protein expression by rat PSCs. A representative western blot and densitometry by rat PSCs exposed to serum reduced medium alone (CTRL), ethanol 5mM (EtOH), IL-1 0.5pg/mL, TNFα 10U/mL or the combinations for 24 hours. Exposure of PSCs to either individual or combination of each compound had no effect on fibronectin protein expression (n=4 separate rat PSC preparations). GAPDH was used as a loading control. 63

Table 1

Effect of Ethanol and Cytokines Individual or in

Combination on PSC Activation

αSMA Collagen I Collagen I protein mRNA protein

Ethanol (5mM) - - -

IL-1 (0.5pg/mL) - - -

TNFα (5U/mL) - - -

TNFα (10U/mL) - - -

Ethanol (5mM)+ ↑ - ↑ IL-1 (0.5pg/mL) Ethanol (5mM)+ - - - TNFα (5U/mL) Ethanol (5mM)+ ↑ - - TNFα (10U/mL)

(- No effect, ↑ Increase)

3.5 Discussion

As discussed in Chapter 2 of this thesis, a direct effect of ethanol alone and individual cytokines on PSC activation has been demonstrated in previous in vitro studies [75, 104, 117]. During alcohol-induced pancreatitis, PSCs in vivo are exposed not only to ethanol but also to cytokines produced during pancreatic necro-inflammation.

In this regard, it has previously been shown that TGFβ, PDGF, TNFα, IL-1 and IL-6 activate PSCs. Interestingly, as mentioned earlier in this Chapter, PSCs have also been reported to secrete cytokines themselves. Thus, in the in vivo situation, PSCs would be expected to be exposed to several activating factors at the same time. The experimental protocol described in this Chapter was designed to simulate the in vivo situation to some extent by exposing cultured PSCs to ethanol as well as two different cytokines - IL-1 and TNFα. Given that IL-1 and TNFα are upregulated in the early stages of pancreatic inflammation, it is possible that PSCs are activated early in acute pancreatitis by these cytokines.

A synergistic effect on αSMA expression was apparent between alcohol (at a dose as low as 5mM) and IL-1 (at a dose as low as 0.5pg/mL) as well as between alcohol (5mM) and TNFα (at a dose of 10U/mL). Ethanol and IL-1 also showed a synergistic effect on collagen I protein expression. These findings indicate that a combination of two major toxic influences (ethanol and cytokines) has a significant effect on PSC function.

In terms of the relevance of the concentration of ethanol and cytokines used in this studies, i) concentrations of 10mM and 50mM ethanol have previously been shown to induce PSC activation [75]. 50mM of ethanol corresponds to blood alcohol concentrations of 0.2g/100mL and are frequently seen with moderate to heavy alcohol intake; this concentration is equivalent to four times the legal limit for driving (0.05%) 65

in Australia; ii) a study of IL-1 concentrations in pancreatic tissue and serum using the caerulein induced model of acute pancreatitis has shown that within 48 hours, IL-1 concentrations [179] are elevated to 100pg/mL-200pg/mL in both pancreatic tissues and serum; iii) with regard to TNFα, in serum concentration of this cytokines are reported to be around 55IU/mL after 24 hours pancreatic injury in an acute pancreatitis animal model [180]. The concentrations of ethanol, IL-1 and TNFα used in this study were all well below the concentrations reported in tissue and serum during pancreatic injury.

As noted earlier, αSMA expression by PSCs is known to steadily increase with duration of culture, with passaged cells having higher expression than freshly isolated cells [30, 181]. In addition, ethanol and individual cytokines have previously been reported to activate PSCs by increasing αSMA expression [117]. Therefore, the reason for selecting low doses of individual factors for the combination studies was to maximise the likelihood of observing an activating effect on PSCs over and above that of individual factors. With low concentrations of individual compounds, even though the factors alone had no effect on PSC activation, a synergistic effect of the combined treatment (ethanol + cytokines) was found on PSC activation as evidenced by increased

αSMA. As mentioned previously, it is a well-established clinical fact that not all alcoholics develop pancreatitis, suggesting that factor in addition to ethanol may be required to elicit clinical disease [182]. The notion that individual cytokines and ethanol at very low concentration have a synergistic effect on PSC activation may represent an important mechanism mediating disease progression in alcoholic pancreatitis.

TNFα alone in this study showed no significant effect on expression of αSMA which is consistent with a previous report [117]. However, the lack of effect on αSMA expression in PSCs exposed to IL-1 alone does not concur with previous studies [117]. 66

This lack of an effect is most likely due to the significantly lower concentration of IL-1 used in this study compared to that used by Mews and colleagues [117].

The predominant collagen isotope in normal healthy tissue is collagen type IV whereas in fibrosis there is an accumulation of fibrillar collagens, particularly type I collagen. Each specific collagen type is encoded by a specific gene. As the messenger

RNA for each collagen type is transcribed from the gene, it undergoes many processing steps to produce a final code for that specific collagen type [183]. Initially, a precursor form of collagen – procollagen, is produced which contains additional peptides at both end. As the procollagen is secreted from the cell, it is cleaved by the enzymes procollagen proteinases that remove both of the extension peptides from the ends of the molecule, converting of procollagen into collagen. An overall increase in collagen synthesis can result from increases in the rate of transcription, increases in the stability of the mRNA, alterations in processing, or decreases in collagen degradation. Collagen protein levels can be detected using hydroxyproline as a marker. Hydroxyproline is abundance and found in few proteins besides collagen.

Mews et al [117] previously showed that newly synthesised collagen expressed per ng DNA in PSCs (measured by assessing the incorporation of 14C proline into collagen) was increased by exposure to TNFα at a concentration of 10U/mL. In the current study, it was found that TNFα alone or in combination with ethanol had no effect on both protein and mRNA levels for procollagen α1 of PSCs. Compared to

Mews’ method which measured the newly synthesised collagen upon treatment, the method used in this thesis measured collagen content of PSCs. It is possible that an effect of ethanol and TNFα on collagen may have been missed because measuring collagen by western blotting is a significantly less sensitive method than measurement of 14C proline incorporation into collagen. Therefore, to better understand the effect of 67

ethanol and TNFα on PSCs, further studies requires to measure the newly synthesised collagen instead of total collagen.

IL-1 alone had no effect on collagen I mRNA expression level. This finding concurs with the lack of an effect of IL-1 on collagen protein synthesis by PSCs reported by Mews et al [117]. Notably, in the current study, ethanol and IL-1 together showed a significant increase in collagen I protein expression, suggesting that these compounds may regulate collagen I protein synthesis at a post-transcriptional level.

Table 3.1 summarised the synergistic effect of ethanol and cytokines found in this study.

Since production of ECM proteins is an important characteristic of PSC activation, we assessed the expression of fibronectin in rat PSCs exposed to a combination of ethanol (5mM), IL-1 (0.5pg/mL) and TNFα (10U/mL) for 24 hours.

However, there was no effect of these compounds alone or in combination on fibronectin expression by PSCs. One possible reason could be that the concentration of ethanol used in this study was very low compared to previous reports where PSCs incubated with 50mM ethanol showed a significant induction of fibronectin expression

[134]. The other reason could be that fibronectin is a secreted ECM protein, therefore is best studied in cell secretions. Further studies using ELISA to measuring fibronectin in the cell supernatant rather than western blotting of cell lysates may clarify this issue.

PSC proliferation, as a measure of cell activation, was not assessed in this study because: i) IL-1 (0.001, 0.01, 0.1, 1 and 10ng/mL) has been shown to have no effect on

PSC proliferation [117] and ii) ethanol at the concentrations of both 10mM and 50mM had no effect on proliferation of cultured PSC [75]; in fact, ethanol at both concentrations showed a trend (albeit not significant) to decrease PSC proliferation [75].

In conclusion, the studies described in this Chapter provide evidence that ethanol and cytokines may have synergistic effects on pancreatic stellate cell activation as 68

assessed by αSMA expression and/or ECM protein expression. The findings indicate that in the presence of low, otherwise innocuous, low concentration of cytokines, exposure of PSCs to low levels of ethanol (such as those observed in social drinking) can induce a profibrogenic state in the gland.

Chapter 4 - Effect of Extracellular Matrix

Composition on PSC Gene Expression Pattern

4.1 Extracellular Matrix

4.1.1 Introduction

The extracellular matrix (ECM) is a complex meshwork of fibrous proteins and polysaccharides that contributes to the maintenance of normal tissue architecture. Three types of molecules are abundant in the ECM of all tissues: collagen fibers, soluble multi-adhesive matrix proteins and highly viscous proteoglycans [184]. Collagen fibers strengthen and organise the matrix. Proteins such as fibronectin, laminin, and tenascin serve less of a structural role and more of an adhesive or integral role within the ECM matrix; these proteins allow for cell attachment and form crosslinks within the matrix gel. Finally, numerous proteoglycans and heparan sulfate containing proteins form the highly hydrated gel-like mixture that helps stabilise the matrix within its aqueous environment.

ECM provides a physical scaffold for cells to move, which is important in embryonic development during which tissues, organs and body parts are formed by cell movements and rearrangement. In addition to being a framework or mesh to support cells, ECM also coordinates cellular functions by activating intracellular signalling pathways that control cell growth, proliferation and gene expression. Changes in ECM components can modulate the interactions of a cell with its microenvironment. In addition, the matrix also serves as a reservoir for many extracellular signalling molecules that control cell functions.

ECM contributes considerably to the onset and progression of a wide range of diseases. Among these are all fibrotic diseases of the skin, liver, lung and kidney, some 70

skeletal, muscular and neuron diseases as well as respiratory, cardiac and ophthalmic diseases [185, 186]. Some other cell functions which have previously not been related to

ECM are now been increasingly acknowledged as being crucially dependent on the composition of the ECM and the stromal cells, such as stem cell self-renewal and differentiation, cancer cell progression and angiogenesis [186-188].

Cell – ECM adhesion is regulated by specific cell surface cellular adhesion molecules which bind directly to ECM components and also interact with the cell cytoskeleton. The largest cell surface receptor family is the integrin family [189, 190].

Integrins mediate the adhesion of cells to ECM proteins and endothelial surface. They are transmembrane alpha-beta heterodimers and at least 18 alpha and 8 beta subunits are known in humans, which form at least 24 α/β heterodimers [191]. Different integrin combinations may recognise a single ligand or bind to several different ECM proteins.

4.1.2 ECM Degradation

It is now evident that ECM turnover (synthesis, secretion, and degradation) is a critical step in the tissue remodelling that accompanies physiological as well as pathological processes. The major enzymes involved in ECM protein degradation are matrix metalloproteinases (MMPs), the ADAM (a disintegrin and metalloproteinase)

[192] and ADAM with thrombospondin domains (ADAMTS) metalloproteinases [193].

These enzymes are members of the metzincins superfamily of zinc-based proteinases and are capable of digesting ECM macromolecules and non-ECM molecules including receptors, growth factors, cytokines and chemokines (factors which are important components of the tissue microenvironment). These enzymes can be produced by a variety of cell types including epithelial cells, fibroblasts, tumour cells and inflammatory cells. 71

In humans, MMPs are a family of 23 enzymes. According to their substrate specificity, structural features and cellular location, these enzymes have been subdivided into gelatinases (MMP2, MMP9), stromelysins (MMP3, MMP10, MMP11), elastases (MMP7, MMP12), collagenases (MMP1, MMP8, MMP13, MMP18) and membrane-type matrix metalloproteinases (MT1-MMP, MT2-MMP, MT3-MMP, MT4-

MMP, MT5-MMP) [194]. MMPs are generally secreted in their latent form consisting of a signal peptide, a propeptide (which is cleaved during activation), a catalytic domain containing a highly conserved zinc-binding site, and a hemopexin-like domain, which is linked to the catalytic domain by a hinge region [195]. Activation of MMPs results from dissociation of the propeptide from the catalytic domain [196].

The human genome contains 25 ADAM [192] and 19 ADAMTS genes [197].

Most ADAMs are transmembrane proteins that contain disintegrin and metalloprotease domains and are able to carry out both cell adhesion and protease activities. Soluble isoforms of ADAMs have also been discovered and characterised.

The activities of these metalloproteinases in vivo are precisely controlled at three steps: 1) gene expression; 2) proenzyme processing and 3) inhibition of enzymatic activity [198]. Tissue inhibitors of metalloproteinases (TIMPs) are endogenous inhibitors of MMPs, ADAMs and ADAMTSs and are consequently important regulators of ECM turnover, tissue remodelling and cellular behaviour. TIMPs are disulfide-bonded proteins of 20-30 kDa. Four subtypes of TIMPs (TIMP1-TIMP4) have been identified [199-201]; TIMPs differ in their affinities for specific MMPs. TIMP1 inhibits the activity of MMPs 1, 3, 8, 9, 10, 11, 13 and 18. TIMP2 and 3 are weaker inhibitors than TIMP1 for MMP3 and MMP7, contrasting with their affinities for other

MMPs [202]. Among the TIMPs, TIMP3 is unique in inhibiting a broader array of

MMPs including several members of ADAM and ADAMTS families [203, 204]. 72

However, it is not known whether other types of ADAM inhibitors exist in addition to

TIMP3. TIMP4 displays tight tissue specificity, predominantly in the brain, heart, ovary, and skeletal muscle [205]. Besides MMP inhibition, TIMPs have other important biological functions such as modulation of cell proliferation, migration, invasion, apoptosis and angiogenesis [206].

Regulation of ECM synthesis and degradation by metalloproteinases and their inhibitors (TIMPs) is a complex process. In general, TIMPs inhibit MMP activity by binding to the active site of MMPs with a 1:1 stoichiometry in a reversible and non- covalent manner [207]. However, TIMPs have also been shown to exert an opposite effect i.e. activation of MMPs. For example, TIMP2, at low concentrations is known to facilitate the activation of MMP2 by acting as a bridging molecule linking the C- terminal of pro-MMP2 to the N-terminal of MT1-MMP (the MMP that activates pro-

MMP2) [207]. On the other hand, at high concentrations, TIMP2 binds to pro-MMP2 and inhibits its activation by MT1-MMP [207].

RECK (the reversion-inducing cysteine - rich protein with Kazal motif) is a newly found membrane-anchored regulator of MMPs. RECK can regulate MMP2,

MMP9 and MT1-MMP. Oh et al [208] found disrupted tissue and reduced collagen IV, laminin and fibronectin in RECK deficient mouse embryos due to increased MMP-2 activity [208].

4.1.3 Stellate Cells and Extracellular Matrix Turnover

As discussed in Chapter 1, fibrogenesis is a complex process resulting from an overall imbalance between ECM synthesis and ECM degradation [207]. Studies with liver have shown that normal liver contains 12 different types of collagen, with type I and III accounting for 70% of total liver collagen [209]. The ratio of type I to III 73

collagen in normal liver is 1:1. In liver fibrosis, the synthesis of collagen is increased and its degradation is decreased; most of the increased collagen is type I and the ratio of type I to III is increased to 4:1 [210]. It has been established that when hepatic stellate cells (HSCs) are activated, they synthesise increased ECM proteins particularly fibrillar collagen, but reduce the expression of proteases such as MMP13 (which degrades fibrillar collagen) [196, 211]. A recent study showed that ADAM28 is overexpressed by

HSCs in the liver tissue from patients with chronic liver diseases and its expression levels correlate with the degree of liver fibrosis [212].

With regard to the pancreas, the mean collagen content in pancreatic carcinoma and chronic pancreatitis is reported to be 3 fold higher than in normal pancreas with the dense fibroblastic stroma consisting primarily of collagen type I, III and fibronectin

[213]. As noted earlier, PSCs are the main source of ECM in the pancreas. In health,

PSCs maintain a balance between the ECM synthesis and degradation. It has been shown that PSCs have the capacity to synthesise a number of MMPs, including MMP2,

MMP3, MMP9, and MMP13 and also their inhibitors TIMP1, TIMP2 [123] and RECK

[214]. It has been shown that MMP3 and MMP9 are suppressed by TGFβ [119]. MMP2 secretion is significantly increased on exposure to the proinflammatory cytokines

TGFβ1 and IL-6 [123]. Importantly, both ethanol and its metabolite acetaldehyde increase MMP2 as well as TIMP2 secretion by PSCs [123]. MMP2 is known to digest basement membrane and facilitate deposition of fibrillar collagen [215]. Ethanol and acetaldehyde also induce expression of TIMP2 [123]. TGFβ prevents proteolytic degradation of RECK when PSCs are activated, resulting in the expression of a fully active form of RECK, which preserves its MMP inhibitory activity leading to ECM accumulation [214]. Together, the progression and regression of fibrosis is regulated by the balance between ECM production and degradation. 74

4.1.4 ECM Regulates Stellate Cell Functions

While evidence is accumulating regarding the capacity of PSCs to regulate ECM protein synthesis and degradation, little is known about the ability of the fibrotic microenvironment to influence the functions of these cells.

In an attempt to investigate the specific genes that are changed due to altered microenvironment in vivo, researchers have performed gene expression profiling of microdissected pancreatic tissue from chronic inflammation or cancer patients. Several specific genes were identified, such as MMP2 [216, 217], PDGF-α [217], collagen type

Iα1 and type IIIα1[217, 218], interleukin-8 [216, 219] and connective tissue growth factor [216]. These studies have identified specific genes which may play a role in the development of fibrosis and which are potential diagnostic and therapeutic targets.

However, these studies have the following limitations:

1) Lack of purity of the cell population under study: the microenvironment of fibrotic pancreas consists of proliferating fibroblasts and PSCs (which produce and deposit fibronectin and collagens), inflammatory cells and macrophages, nerve fibers, endothelial cells and marrow derived stem cells. Therefore, microdissected specimens contain not only PSCs but also other cell populations, making it difficult to identify cell- specific sources of differentially expressed genes.

In addition to containing several other cell types, the microenvironment also serves as a reservoir for numerous proteins, cytokines, chemokines and growth factors from PSCs and inflammatory cells. As noted earlier, all of these factors can contribute to PSCs activation and make it difficult to investigate the influence of ECM per se on

PSC function.

2) Lack of identification of early changes of PSCs. Research regarding PSC biology has almost exclusively focused on the activated phenotype, using 75

microdissected specimens and thus might miss the early changes in gene expression that are responsible for PSC activation.

In order to investigate the influence of specific diseases (e.g. chronic pancreatitis and pancreatic cancer) on PSC gene expression, researchers have isolated PSC populations from heterogeneous tissues and performed molecular analysis of cultured cells in vitro. This approach successfully reduces tissue complexity to a single-cell type propagated in vitro. Thus, CELSR3 (cadherin EGF LAG seven-pass G-type receptor 3) and SYT13 (synaptotagmin XIII) are identified as specific tumour related PSC genes while PTPRC (protein tyrosine phosphatase receptor type C) and DHODH

(dihydroorotate dehydrogenase) are shown to be inflammation related PSC specific genes [220].

It is to be noted however that culture on plastic (a traditional culture surface) itself induces PSC activation [30, 74]. In view of the known role of ECM in organising and maintaining normal cell function, a lack of native-tissue microenvironment (as in the case of culture on plastic) may dramatically change the pattern of gene expression compared to that of PSCs in situ within the pancreas. Therefore, PSCs grown on tissue culture plastic may not fully represent their counterparts in vivo.

MatrigelTM is a solubilised basement membrane preparation extracted from the

Engelbreth-Holm-Swarm (EHS) mouse sarcoma, a tumour rich in ECM proteins. Its major components are laminin, collagen IV, heparan sulfate proteoglycans and entactin/nidogen. It also contains TGFβ, epidermal growth factor, insulin-like growth factor, fibroblast growth factor, tissue plasminogen activator [221, 222] and other growth factors. MatrigelTM is effective for the attachment and differentiation of both normal and transformed cells [223-227]. Studies have shown that HSCs and PSCs cultured on basement membrane components maintain the ability to store lipids in 76

cytoplasm vesicles [23]; they have also been reported to reverse activated stellate cell phenotypes to a quiescent state [228-230].

In diseased states such as chronic pancreatitis and pancreatic cancer, PSCs are activated and surrounded by a dense desmoplastic reaction, a predominant component of which is collagen I. It would be reasonable to expect that PSC function on a collagen matrix is significantly different than in the healthy state where the cells are surrounded by normal basement membrane.

Thus, to better understand the complex crosstalk between ECM and PSCs and assess the early molecular events of PSC activation, studies in this thesis investigated gene expression patterns using RNA extracted from quiescent rat PSCs cultured on different matrices (i.e. MatrigelTM and collagen I), which mimic the in vivo microenvironment in health and diseased pancreas respectively. In addition, rat PSCs cultured on traditional uncoated plastic were also included in this study.

4.2 Methods

4.2.1 Preparation of MatrigelTM Coated Petri Dishes and Cell

Recovery a) Reagents

1. MatrigelTM Basement Membrane Matrix High Concentration,

Growth Factor Reduced (BD, Sydney, Australia) 10mL

Cell Recovery Solution (BD, Sydney, Australia) 100mL

Note: BD MatrigelTM contains TGFβ, insulin-like growth factor, fibroblast

growth factor, tissue plasminogen activator and other growth factors which

occur naturally in the EHS tumour. Therefore, to avoid confounding factors,

growth factor reduced MatrigelTM were used for this study. 77

2. Rat PSC isolation reagents as listed in Section 3.3.1

b) Method

Frozen MatrigelTM was slowly thawed on ice in a 4°C cold room overnight.

Culture Petri dishes and pipettes were placed in a sealed plastic bag and placed at -20°C.

MatrigelTM was diluted 1:3 with ice-cold IMDM and mixed in order to obtain a homogenous (bubble-free) solution using cold sterile plastic ware placed on ice. Diluted

MatrigelTM (3mL) was then poured onto ice-cold 10cm culture Petri dishes and evenly distributed by gentle tilting of dishes. The MatrigelTM was then left to solidify in a 37°C culture incubator for at least 5 hours. Rat PSCs were isolated using the method described in Section 3.3.1 and 1x106 cells were seeded onto MatrigelTM coated dishes and cultured in IMDM containing 10% FBS for 72 hours. Culture medium was changed every 24 hours. After 72 hours, medium was gently removed and dishes were washed three times with cold PBS. BD cell recovery solution was then added onto each culture dish. The MatrigelTM containing cells were scraped off the plate and recovered in an ice- cold 50mL Falcon tube. The dish was then rinsed with 2mL BD cell recovery solution which was added to the 50mL Falcon tube. Tubes were then inverted 3-4 times and left to rest on ice until full dissolution of the MatrigelTM. Subsequently, the tubes were centrifuged at 200g for 5min at 4°C. The supernatant was discarded and cells were washed twice with ice-cold PBS and centrifuged at 200g. The cell pellet was then lysed for either RNA or protein extraction.

[Note: BD cell recovery solution allows for the recovery of cells cultured on BD

MatrigelTM basement membrane matrix without enzymatic digests and lengthy incubation periods at high temperatures. Cells are released without damage thereby 78

avoiding biochemical changes during incubation and digestion of extracellular portions of cell-surface receptors and adhesion molecules].

4.2.2 Preparation of Collagen I Coated Petri Dishes and Cell Recovery a) Reagents

1. Rat tail collagen I (BD, Sydney, Australia) 10mL

2. Rat PSC isolation reagents as listed in Section 3.3.1

b) Method

Culture Petri dishes and pipettes were placed in a sealed plastic bag and refrigerated overnight at -20ºC. Rat tail collagen type I stock 100mg in 0.02N acetic acid (3.32mg/mL) was diluted to a final concentration 2.31mg/mL using ice-cold PBS in a 50mL Falcon tube. Sterile ice cold 1N NaOH (the same volume as collagen I stock) was then added to the diluted collagen I solution. The contents of the tube were mixed well. 3mL of the solution was then aseptically dispersed into culture dishes and left to gel in an incubator at 37°C for 5 hours. Rat PSCs were isolated using the method described in Section 3.3.1 and 5×105 cells were seeded onto collagen I coated dishes and cultured in IMDM containing 10% FBS for 72 hours. Culture medium was changed every 24 hours. Cells were washed three times with PBS. The collagen layer containing cells was then scraped into 5mL sterilised collagenase V solution and left for 20 minutes at 37°C water bath under intermittent shaking. Cells were then centrifuged at 200g for 5 minutes at 4°C and the supernatant was discarded. Cells were washed twice with ice- cold PBS and centrifuged at 200g. The cell pellet was then lysed for either RNA or protein extraction. 79

[Note: collagenase cleaves the peptide bonds in native, triple-helical collagen. Because of its unique ability to hydrolyse native collagen, it is widely used in isolation of cells from animal tissue. Therefore, different enzyme (i.e. cell recovery solution and collagenase) are known not to cause any confounding effects on the cells].

4.2.3 Culture and Recovery of Rat PSCs from Uncoated Petri Dishes a) Reagents

Rat PSC isolation reagents as listed in Section 3.3.1

b) Method

Rat PSCs were isolated using the method described in Section 3.3.1 and 4x105 cells were seeded onto Petri dishes and cultured in IMDM containing 10% FBS for 72 hours. Culture medium was changed every 24 hours and at the end of 72 hours, cells were washed twice with 1mL PBS and detached from the Petri dish by adding 2mL of warmed 0.05% EDTA-trypsin for 2 minutes. Trypsin was neutralised by adding 4mL of warmed 10% FBS IMDM. Solutions were then centrifuged at 200g for 5 minutes at 4ºC and the supernatant was discarded. Cells were washed twice with PBS and centrifuged at 200g. The cell pellet was then lysed for either RNA or protein extraction.

Note: Different enzymes are known not to cause any confounding effects on the cells.

4.2.4 RNA Extraction for Microarray Analysis

RNA was extracted from cultured PSCs using a commercial kit (Qiagen RNeasy plus mini kit) as described in Section 3.3.8. Eluted RNA was stored at -80°C for future use.

4.2.5 Assessment of RNA Quality a) Nanodrop® Spectrophotometer (ND-1000)

RNA concentration was assessed by measuring the absorbance of the extract at

260nm (Beer’s law: concentration of RNA = 44 x A260 x Dilution factor). 1-2 μl of

RNA was loaded onto the pedestal and optical density measurements at 230, 260 and

280nm were recorded. Ratios of measurements at A260/A230 and A260/A280 were calculated; these readings were used to detect the presence of any protein and/or organic solvent contaminants in the samples. Generally, pure RNA has an A260/A280 ratio in the range of 1.9 to 2.1 and an A260/A230 in the range of 1.8-2.2.

b) Agilent 2100 Bioanalyzer

Integrity, quantity and size distribution of RNA samples were also assessed using the Agilent 2100 bioanalyzer, which is based on microfluidics and electrophoresis.

The quality of RNA was assessed by a scoring system referred to as a RNA integrity number (RIN), ranging from 1 (low integrity) to 10 (high integrity). Samples were scored according to the degree of degradation and presence of contaminants such as genomic DNA and proteins. Samples with a RIN of ≥ 9 were used for further studies.

4.2.6 Microarray (Affymetrix Rat Gene 1.0 ST Array)

The gene expression profiles of rat PSCs cultured on MatrigelTM, collagen I and plastic were analysed by whole rat genome microarray purchased from Affymetrix (Rat

Gene 1.0 ST Array). This array was able to detect 27,342 rat genes, with approximately

26 probes on average per gene (referred to as a probe set).

The hybridisation process was performed in the Ramaciotti Centre, UNSW, according to an established protocol. Briefly, RNA samples (100ng) were first reverse 81

transcribed into cDNA, and products were then transcribed and amplified in vitro to synthesise cRNA. These cRNA products were used for a second cycle of reverse transcription and in vitro transcription (IVT). The cRNA was also biotin-labeled during

IVT. It was then fragmented by metal-induced hydrolysis and RNA fragments were loaded on the array chips for target hybridisation. After hybridisation, the chips were washed and stained. Signal was then detected and analysed.

4.2.7 Microarray Data Analysis

Gene Spring Viewer software (provided by Garvan Institute of Medical

Research, Sydney) was used for data analysis. Raw expression data were first assessed by comparing the overall probe expression levels across array chips to identify any outliers that may hinder further analysis. The chips were then clustered into groups based on the similarity of overall probe expression. Robust multi-array analysis was then performed in order to correct for non-specific signals and also to normalise probe expression levels such that array chips were able to be compared with one another.

After normalisation, average probe set expressions (which represented gene expression) were calculated within each sample group and finally, comparison of gene expressions was performed between rat PSC cultured on collagen I vs MatrigelTM, MatrigelTM vs plastic and collagen I vs plastic groups. Genes were identified as differentially expressed if they had a fold change greater than two and a p-value <0.05. Highly dysregulated genes were identified by setting the fold change to greater than two, the p- value to less than 0.001 and the false discovery rate (FDR) to less than 0.25. Functions of differentially expressed genes were investigated by searching the Gene Ontology database (www.geneontology.org) and the biological significance of dysregulated genes 82

was investigated by performing Gene Set Enrichment Analysis with the use of GSEA v2.0 software (downloaded from www.broad.mit.edu/gsea/).

4.3 Results

4.3.1 Rat PSCs cultured on MatrigelTM, Collagen I and Plastic

Rat PSCs cultured on collagen I and plastic showed flattened, myofibroblast-like cell shapes whereas those grown on MatrigelTM formed cell clusters connected by a filamentous network (Figure 4.1).

4.3.2 RNA Quality

RNA was extracted from 2 preparations of rat PSCs cultured on MatrigelTM, 3 preparations cultured on collagen I and 4 preparations cultured on plastic. The average

RNA yield from 1-2 million cells was 4μg. The purity and integrity of RNA were assessed as described in the Methods section. No contamination or degradation was observed in the samples. Average A260/A280 was equal to 2.08 ± 0.12. Results of the agilent bioanalyzer confirmed the assessment of RNA quality by Nanodrop® spectrophotometer and formaldehyde agarose gel electrophoresis as all RNA samples were scored with RIN > 9.

Figure 4.1

Rat PSCs Cultured on MatrigelTM and Collagen I for 72 Hours

MatrigelTM Collagen I

A representative photomicrograph of rat PSCs cultured on MatrigelTM and collagen I for 72 hours. Cells on collagen I showed flattened, myofibroblast-like phenotype, whereas those grown on MatrigelTM formed three dimensional cell clusters connected by a filamentous network. Magnification x100.

4.3.3 Microarray Result a) Hierarchical Cluster (HCL) analysis of each array

HCL analysis is usually used in the microarray data analysis to find groups of variable and individuals that are similar in some way. Hierarchical Clustering procedure can obtain a hierarchical clustering for a subset list of genes. The line distance between each member indicated the similarity/dissimilarity between each clusters (Figure 4.2).

Smallest distances were found within each matrix (e.g. plastic, collagen I, MatrigelTM).

Longer distances were found between cells cultured on collagen I and cells cultured on

MatrigelTM, and the longest distance were found between the cells cultured on plastic vs cells cultured on collagen I and MatrigelTM.

b) Number of dysregulated genes

When comparing rat PSCs cultured on collagen I vs MatrigelTM, MatrigelTM vs plastic and collagen I vs plastic, 293, 839 and 533 genes respectively were differentially expressed. These genes exhibited a fold change greater than two (FC > 2), p value <

0.05, and a false discovery rate (FDR) < 0.25. To identify significantly dysregulated genes, the above genes were further filtered by adjusting the p-value to less than 0.001.

This yielded 146 (collagen I vs MatrigelTM), 619 (MatrigelTM vs plastic) and 432

(collagen I vs plastic) differentially expressed genes respectively (Supplementary Table

1-3). This thesis will focus on the comparison between the cells cultured on collagen I and cells grown on MatrigelTM based on the concept that the culture conditions on collagen I and MatrigelTM were more physiologically relevant than culture on plastic and the top 15 dysrgulated genes between the PSCs cultured on these two matrices were listed below (Table 1).

Figure 4.2

Hierarchical Clustering of Gene Array Probe Sets

Distance

Hierarchical clustering of all probe sets. The line distance between each member indicates the similarity/dissimilarity between each cluster. n=4, 3 or 2 separate preparations of rat PSCs cultured on plastic, collagen I and MatrigelTM respectively. As expected, genes from cells cultured on same matrices (e.g. plastic, collagen or

MatrigelTM) clustered together. However, there is large difference in cells cultured on different matrices.

Table 1

Top 15 Dysregulated Genes in Rat PSCs Cultured on Collagen I vs MatrigelTM

Direction Gene (FC>2, p<0.001, FDR<0.25)

Transgelin FBJ osteosarcoma oncogene B Up Similar to cysteine-rich protein 1 (cysteine-rich intestinal protein) FBJ osteosarcoma oncogene Lumican Interleukin-1 alpha Chymotrypsinogen B1 Fatty acid binding protein 4, adipocyte Carboxypeptidase A1 Ischemia related factor vof-16 Down Solute carrier family 7, member 11 Glycerol-3-phosphate dehydrogenase 1 (soluble) Phospholipase A2, group VII (plasma) Islet amyloid polypeptide Proprotein convertase subtilisin/kexin type 2

4.3.4 Biological Functions of Differentially Expressed Genes

In order to investigate the functions of differentially expressed genes (which could provide important clues about their roles in cell-ECM interactions and PSC activation), a search was conducted using the Gene Ontology (GO) database. The biological contexts as well as the inter-relationships of the dysregulated genes were assessed by Gene Set Enrichment Analysis (GSEA). This allows organising genes into hierarchical categories so as to uncover the PSC regulatory network on the basis of biological process and molecular function, leading to the identification of leading edge gene subsets. The significantly (p<0.05, FDR<0.25) altered functional pathways are listed in Table 2 (collagen I vs MatrigelTM), Table 3 (MatrigelTM vs plastic) and Table 4

(collagen I vs plastic). Interestingly, when using MatrigelTM as normal PSC gene expression profile, and comparing it to activated PSCs (cultured on activating matrices- collagen I or plastic), certain altered pathways are common to collagen and plastic

(Table 5).

For further study, genes coding the proteins transgelin, lumican, Fos and IL-1 were selected for further validation. Details of these genes will be discussed in Chapter

Table 2

Altered Functional Pathways in Comparison of Collagen I vs MatrigelTM (p<0.05, FDR<0.25)

Upregulated Pathways NAME SIZE* REGULATION_OF_SECRETION 17 CYTOKINESIS 15 TRANSLATION 129 CARBOHYDRATE_BIOSYNTHETIC_PROCESS 28 MACROMOLECULE_BIOSYNTHETIC_PROCESS 216 STRUCTURAL_MOLECULE_ACTIVITY 136 STRUCTURAL_CONSTITUENT_OF_RIBOSOME 75 MOTOR_ACTIVITY 18 ACTIN_BINDING 51 CHEMOKINE_RECEPTOR_BINDING 19 ACTIN_FILAMENT_BINDING 17 CHEMOKINE_ACTIVITY 19 G_PROTEIN_COUPLED_RECEPTOR_BINDING 22 CYTOKINE_ACTIVITY 47 HYDROLASE_ACTIVITY__HYDROLYZING_O_GLYCOSYL_ 20 COMPOUNDS

Downregulated Pathways NAME SIZE SECONDARY_ACTIVE_TRANSMEMBRANE_TRANSPORTER_ACTIVIT 22 ATPASE_ACTIVITY__COUPLED_TO_MOVEMENT_OF_SUBSTANCES 28 ION_TRANSMEMBRANE_TRANSPORTER_ACTIVITY 97 HYDROLASE_ACTIVITY__ACTING_ON_ACID_ANHYDRIDES__CATA 27 LYZING_TRANSMEMBRANE_MOVEMENT_OF_SUBSTANCES ATPASE_ACTIVITY__COUPLED_TO_TRANSMEMBRANE_MOVEMEN 15 T_OF_IONS CHROMATIN_BINDING 24 ACTIVE_TRANSMEMBRANE_TRANSPORTER_ACTIVITY 66 INOSITOL_OR_PHOSPHATIDYLINOSITOL_KINASE_ACTIVITY 16 SH3_SH2_ADAPTOR_ACTIVITY 23 SUBSTRATE_SPECIFIC_TRANSPORTER_ACTIVITY 167 METAL_ION_TRANSMEMBRANE_TRANSPORTER_ACTIVITY 43 SYMPORTER_ACTIVITY 15 TRANSFERASE_ACTIVITY__TRANSFERRING_GROUPS_ 37 OTHER_THAN_AMINO_ACYL_GROUPS TRANSMEMBRANE_TRANSPORTER_ACTIVITY 154 SUBSTRATE_SPECIFIC_TRANSMEMBRANE_TRANSPORTER_ACTIVI 141 MOLECULAR_ADAPTOR_ACTIVITY 26 CATION_TRANSMEMBRANE_TRANSPORTER_ACTIVITY 77 ACETYLTRANSFERASE_ACTIVITY 19 SEQUENCE_SPECIFIC_DNA_BINDING 30 SMALL_GTPASE_BINDING 23 ANION_TRANSMEMBRANE_TRANSPORTER_ACTIVITY 18 TRANSCRIPTION_COFACTOR_ACTIVITY 168 MAGNESIUM_ION_BINDING 38 TRANSCRIPTION_REPRESSOR_ACTIVITY 111

Size: Number of genes in the functional pathway

Table 3

Altered Functional Pathways in Comparison of Collagen I vs MatrigelTM (p<0.05, FDR<0.25) Upregulated Pathways NAME SIZE CELL_DIVISION 17 CELL_MIGRATION 53 ACTIN_BINDING 51

Downregulated Pathways NAME SIZ SECONDARY_ACTIVE_TRANSMEMBRANE_TRANSPORTER_ACTIVIT 22 ACTIVE_TRANSMEMBRANE_TRANSPORTER_ACTIVITY 66 SYMPORTER_ACTIVITY 15 ION_TRANSMEMBRANE_TRANSPORTER_ACTIVITY 97 ANION_TRANSMEMBRANE_TRANSPORTER_ACTIVITY 18 SUBSTRATE_SPECIFIC_TRANSMEMBRANE_TRANSPORTER_ACTIVIT 141 TRANSCRIPTION_ACTIVATOR_ACTIVITY 116 CATION_TRANSMEMBRANE_TRANSPORTER_ACTIVITY 77 GUANYL_NUCLEOTIDE_EXCHANGE_FACTOR_ACTIVITY 36 SUBSTRATE_SPECIFIC_TRANSPORTER_ACTIVITY 167 TRANSCRIPTION_REPRESSOR_ACTIVITY 111 TRANSCRIPTION_FACTOR_ACTIVITY 179 N_ACETYLTRANSFERASE_ACTIVITY 16 TRANSMEMBRANE_TRANSPORTER_ACTIVITY 154 SEQUENCE_SPECIFIC_DNA_BINDING 30 HYDROLASE_ACTIVITY__ACTING_ON_ACID_ANHYDRIDES__ CATALYZING_TRANSMEMBRANE_MOVEMENT_OF_SUBSTANCES 27 INOSITOL_OR_PHOSPHATIDYLINOSITOL_KINASE_ACTIVITY 16 ATPASE_ACTIVITY__COUPLED_TO_MOVEMENT_OF_SUBSTANCES 28 DNA_BINDING 357 METAL_ION_TRANSMEMBRANE_TRANSPORTER_ACTIVITY 43 ATPASE_ACTIVITY__COUPLED_TO_TRANSMEMBRANE_MOVEMENT 15 METALLOENDOPEPTIDASE_ACTIVITY 19 PRIMARY_ACTIVE_TRANSMEMBRANE_TRANSPORTER_ACTIVITY 28 METALLOPEPTIDASE_ACTIVITY 35 TRANSCRIPTION_FACTOR_BINDING 228 TRANSCRIPTION_COFACTOR_ACTIVITY 168 RNA_POLYMERASE_II_TRANSCRIPTION_FACTOR_ACTIVITY 119 TRANSCRIPTION_COACTIVATOR_ACTIVITY 87 TRANSFERASE_ACTIVITY__TRANSFERRING_GROUPS_OTHER_THAN AMINO_ACYL_GROUPS 37 GTPASE_REGULATOR_ACTIVITY 89

Table 4

Altered Functional Pathways in Comparison of Collagen I vs Plastic (p<0.05, FDR<0.25)

Upregulated Pathways NAME SIZE SKELETAL_DEVELOPMENT 57 NEGATIVE_REGULATION_OF_CELL_DIFFERENTIATION 15 REGULATION_OF_SECRETION 17 REGULATION_OF_CELL_DIFFERENTIATION 34 POSITIVE_REGULATION_OF_PROTEIN_MODIFICATION_PROCESS 15 REGULATION_OF_ANGIOGENESIS 16 MULTICELLULAR_ORGANISMAL_DEVELOPMENT 480 METALLOPEPTIDASE_ACTIVITY 35 METALLOENDOPEPTIDASE_ACTIVITY 19 AMINE_TRANSMEMBRANE_TRANSPORTER_ACTIVITY 20 CYTOKINE_ACTIVITY 47 CHEMOKINE_RECEPTOR_BINDING 19 CHEMOKINE_ACTIVITY 19 G_PROTEIN_COUPLED_RECEPTOR_BINDING 22 GROWTH_FACTOR_ACTIVITY 17

Downregulated Pathways NAME SIZE ELECTRON_CARRIER_ACTIVITY 58 OXIDOREDUCTASE_ACTIVITY__ACTING_ON_CH_OH_GROUP_OF 41 _DONORS

Table 5

Common Altered Pathways in Activated Rat PSCs

TM TM Collagen I vs Matrigel Plastic vs Matrigel

Common altered pathways in the comparison of PSCs cultured on Collagen I vs

MatrigelTM and Plastic vs MatrigelTM. Upregulated pathways are in pink column while downregulated pathways are in blue column. When comparing activated PSCs (cultured on collagen I and plastic) to quiescent PSCs (cultured on MatrigelTM), certain altered pathways are common, such as actin binding, cell migration, drug resistance and metabolism and ABC transporters general.

4.4 Discussion

Pancreatic fibrosis is the consequence of ECM disruption, in association with a shift in the types of ECM protein and proteases being produced. PSCs, a quiescent cell of normal pancreas, become activated upon pancreatic injury and secrete excessive amounts of ECM proteins, producing a pathological fibrosis that compromises pancreatic function. PSCs can be readily isolated, purified and have been used as a model of pancreatic fibrosis in vitro. In the field of stellate cell biology, freshly isolated stellate cells cultured on plastic undergo an activation process that mimics to some extent the situation in vivo: the cells start to proliferate, and after some days in culture, display typical features of activated myofibroblasts [30, 74]. Therefore, studies on culture activated PSCs have proven useful in the basic analysis of pancreatic fibrosis.

However, these in vitro assays fail to replicate the complex microenvironment in which

PSCs normally reside. Therefore, the purpose of this study was to identify the effect of

ECM per se on PSC functions.

Combinations of different ECM proteins, growth factors and small molecules have been widely used for manipulating stem and progenitor cell populations [231, 232].

In the current study, a similar approach has been used with PSCs cultured in microenvironments that replicate the in vivo situation. This study has demonstrated that

293 genes (FC>2, p<0.05, FDR<0.25) were dysregulated in cells cultured on MatrigelTM vs collagen I, supporting the concept that ECM per se can dramatically influence cell behaviour. In addition, this study also compared cells cultured on different matrices with cells cultured on the traditional uncoated plastic surface. Not surprisingly, 619 and

432 genes (FC>2, P<0.05, FDR<0.25) were found to be dysregulated between cells grown on MatrigelTM vs plastic and collagen I vs plastic respectively, suggesting that

PSC activation on plastic may not fully represent the in vivo activation process. 95

Nonetheless, certain altered pathways were found to be common to cells grown on collagen and plastic as listed in Table 5 (such as actin binding, cell division and cell migration), suggesting there are some similarity between PSCs grown on plastic vs collagen I, indicating that culture PSCs on plastic provided a valuable tool to study PSC biology in vitro.

In recent years, microarray techniques have been widely used in studies of pancreatic stellate cell biology: i) to determine effects of compounds on PSC function, e.g. endothelin-1 [233] and peroxisome proliferator-activated receptor gamma (PPARγ) on PSC gene expression [140]; and ii) to characterise PSCs derived from pancreata with different diseases [220, 234]. However, there is no information on the PSC genome of cells grown in microenvironments that simulate normal or diseased states of the pancreas.

In this study, PSC gene expression was assessed after 72 hours of culture on different matrices. In vivo, the precise time point for the transition of PSCs from their quiescent state in the healthy organ to an activated phenotype has not been elucidated.

An in vitro study used microarrays to characterise the gene expression profiles of PSCs during culture-induced activation (caused by culture on plastic) on days 2, 4, 7 and 14 after cell isolation. This study has reported that 17% of the dysregulated genes showed continuous expression from day 2 and 83% of the dysregulated genes showed a delayed responsiveness (starting only after day 4 in culture toward the final level of fully activated on day 14) [235]. A time course study would be a better approach to investigate the dynamic changes of each gene during cell activation. However, the purpose of the current study was to identify the driving forces in the PSC activation process. Therefore, PSCs were studied at 72 hours of culture (representing an early time point of PSC activation) that had the potential of identifying key molecules that may 96

play a role in inducing the phenotypic switch that transformed them from quiescent

(MatrigelTM) to activated (collagen I) cells.

To understand the cell biological implications of MatrigelTM induced quiescence and collagen I induced activation, differentially expressed genes were classified into several functional categories. As the biological processes of PSC activation have not been clarified in previous microarray experiments performed with primary PSCs, GO classification of the genes was used for analysing microarray results. Not surprisingly, pathways related to cell - ECM interactions were dysregulated, such as

Extracellular_Region, Extracellular_Matrix and Extracellular_Region_Part, confirming that the ECM plays a crucial role in regulating PSC phenotype. Two genes from

Extracellular_Matrix group, lumican and IL-1α were chosen for further validation for the reasons discussed in the following Chapter 5.

The top 15 dysregulated genes identified in this study might be the key regulators in the process of PSC transformation. Four genes among the top 15 genes were particularly interesting; they are lumican and IL-1α (both belong to extracellular matrix pathway) and transgelin and Fos. Even though transgelin and Fos have not been grouped in the same functional pathway in GO classification, they are particularly important in the known function in cell regulation. Transgelin has been shown to be the most dysregulated gene (protein) in various cancers [236-245]. Fos has been shown to play a role in PSC activation process [132, 246]. Therefore, these four genes were selected for further study.

A similar study comparing gene expression patterns in human hepatic stellate cell (HSC) lines cultured on plastic vs MatrigelTM for 3 days [247] has identified several dysregulated pathways, such as Muscle_Development, Cellular_Morphogenesis,

Organ_Development and Regulation_of_Cell_Growth. These pathways were also found 97

altered in the current study, which confirmed that stellate cells from different organs behave in a similar way when cultured on physiological or non-physiological activating matrices. On the other hand, certain pathways found to be dysregulated in HSCs were not found in the current study, such as Regulation_of_Cell_Size, Cell_Growth, Growth,

Cell_Adhesion, Morphogenesis_and_Development [although the morphology of PSCs cultured on plastic vs MatrigelTM did appear to be microscopically different with respect to cell shape and number under microscope (see Section 4.3.1)]. These differences may be explained by organ-specific differences between HSCs and PSCs.

Gene expression of MMPs (2, 3, 9, and 13) and their inhibitors TIMP1, 2 as well as RECK showed no differences between the cells cultured on MatrigelTM vs collagen I.

One possible reason for this is that these enzymes are tightly controlled at three levels: mRNA, protein and activity. For example, MMP9 is secreted as a zymogen and maintained in the latent form presumably by the interaction of a conserved cysteine in its N-terminal prodomain with the zinc atom in the catalytic sites. Activation by cleavage of the prodomain is essential for enzymatic activity [248]. Therefore, even though microarray results showed no change at gene level, it does not rule out possible changes in enzyme activity.

One of the most consistent features of PSC activation is the loss of vitamin A

(retinyl ester) stores. Interestingly, GO pathways related to retinol metabolism did not show significant dysregulation during the activation process, which was consistent with a previous study on gene expression profile of quiescent vs activated PSCs [235]. One possible reason could be that, as mentioned earlier, after 72 hours in culture on collagen

I, PSCs are still in the intermediate stage of activation as evidenced by the fact that numerous PSCs still retain some vitamin A-containing droplets; these findings suggest 98

that loss of vitamin A lipid droplets could be a consequence instead of the driving force for PSC activation.

4.5 Summary

This Chapter has demonstrated the importance of ECM in regulating the phenotype of PSCs. Investigating gene expression patterns of PSCs cultured on matrices mimicking normal and diseased conditions of the pancreas has the potential to yield important clues about how the ECM influences cell activation processes. Identification of the specific genes mediating PSC activation might provide putative therapeutic targets to prevent or even reverse stellate cell activation.

Chapter 5 - Validation and Functional Studies for

Selected Genes

5.1 Introduction

As discussed in the previous Chapter, studies of PSCs cultured on plastic may not be representative of the in vivo situation where PSCs are surrounded by basement membrane (in health) or a fibrotic collagenous matrix (in disease such as chronic pancreatitis and pancreatic cancer). Analysis of gene expression of PSCs cultured on

MatrigelTM, collagen I and plastic by microarray showed that several genes were dysregulated under the different culture conditions. Four of the top dysregulated genes in PSCs cultured on collagen I vs MatrigelTM were transgelin, lumican, Fos and IL-1α and these were selected for further validation at mRNA and protein levels.

5.1.1 Transgelin

Transgelin, also known as SM22, is a 22KDa actin stress fiber-associated protein of the calponin family [249]. The calponin family of proteins is expressed both in the cytoskeleton and in the contractile apparatus of smooth muscle cells [250].

Calponin proteins are characterised by two unique sequence motifs, an N-terminal calponin homology (CH) domain [251] and one or more calponin-like repeats (CLR) at the carboxyl terminus [252]. Proteins containing CH domains cross-link actin filaments

(e.g. spectrin, filamin, fimbrin), link actin to other cytoskeletal systems (e.g. fimbrin, plectin), and form signaling scaffolds (reviewed in [24, 251]). In addition to regulatory and actin binding roles, CH domains may also function in coupling the actin cytoskeleton to signaling pathways such as protein kinase C (PKC) and ERK [253]. 100

The calponin family of proteins consists of calponin, transgelin, NP25,

ARHGEF6, Vav and IQGAP proteins. These are implicated both in direct interactions with the actin cytoskeleton and regulate functions mentioned above in various cell types

[251].

Transgelin is the product of a single gene (designated TAGLN) that is conserved in yeast, drosophila, molluscs and humans [252] and it contains the CH domain and a single CLR domain [254, 255]. Transgelin is ubiquitously expressed in vascular and visceral smooth muscle [256] and its expression is very high in aorta, lung, uterus and intestine. It is expressed at high levels in freshly isolated smooth muscle cells [257] and also present in mesenchymal cells, fibroblasts and tumour cells of epithelial origin.

It has long been hypothesised that the function of transgelin is to regulate the development and contractile function of smooth muscle cells. Duband et al [258] have found that transgelin starts to appear in the embryonic development of chicken and because of this specific expression, it serves as an early marker of smooth muscle tissue.

However, transgelin knockout mice develop normally without altered blood pressure, heart rate, histology or morphology of tissues, suggesting transgelin is not required for basal homeostatic functions mediated by vascular and visceral smooth muscle cells in the developing mouse [259].

Transgelin has also been reported to be involved in cell migration. Transgelin and calponin have been shown to form podosomes [260], a specialised structures as a potential mechanism for cell migration and invasion [261] in smooth muscle cells.

Transgelin is also a direct target of the transforming growth factor β (TGF-β)/smad3- dependent pathway for epithelial cell migration [262]. Transgelin has also been shown to promote cancer stem cell migration and invasion [263]. 101

Recently, a study postulated that transgelin could be an adaptor that mediates interaction between nuclear actin and DNA [237] based on the known actin binding capacity of transgelin and the recent finding that segments of the primary sequence of transgelin also have high DNA binding potential [237]. Indeed, it is well established that actin plays an important role in nuclear processes, including transcription, chromatin remodelling and transcription factor regulation [264-268].

Transgelin has been studied in several primary tumours including colorectal cancer (CRC), breast cancer, prostate cancer, pancreatic ductal adenocarcinoma, gastric cancer as well as metastatic dissemination. It is becoming increasingly evident that transgelin may act as both a tumour suppressor and a variable tumour biomarker, depending on the tumour type and stage. Studies have shown that in prostate [239, 243], breast [240], colon cancers [242, 244, 245], and pancreatic intra-epithelial neoplasias

(PanIN) (the precursor lesions of pancreatic ductal adenocarcinoma) [241], transgelin expression is decreased or lost. Since transgelin acts to suppress the expression of matrix metalloproteinase 9 (MMP-9) [269] (a MMP involved in tissue remodelling allowing for cancer cells to invade surrounding tissues and migrate), a decrease in transgelin expression may explain the observed upregulation of MMP9 in these cancers which in turn could facilitate local invasion of cancer [256].

In contrast to the decreased expression of transgelin in some cancers noted above, a study in node-positive CRC has shown a significant increase of transgelin expression [237]. These authors [237] have also demonstrated roles for transgelin in promoting cell invasion, survival and resistance to apoptosis using CRC cell lines.

Similar results have been reported in pancreatic adenocarcinoma, where transgelin expression has been shown to be upregulated. Notably, this increased expression of transgelin was mainly observed in stromal cells rather than cancer cells or normal 102

epithelial cells [238]. These findings are also consistent with reports in renal cell carcinoma, showing (by in situ hybridisation) that transgelin was expressed in mesenchymal cells of tumour stroma but not in the malignant cells [236].

Our microarray results showed that transgelin was increased by 12.5 fold in

PSCs cultured on collagen I compared to those grown on MatrigelTM. While increased transgelin expression has been shown in stromal area (where activated PSCs reside) of pancreatic cancer, little is known about transgelin expression in the fibrosis of chronic pancreatitis. The function of transgelin in PSCs has also not been studied to date.

5.1.2 Lumican

Lumican belongs to the family of small leucine-rich repeat proteoglycans which constitutes an important fraction of noncollagenous ECM proteins [270]. Lumican is expressed in a variety of tissues, including skin, artery, lung, intervertebral discs, kidney, bone, aorta and articular cartilage [270].

The role of lumican in maintaining tissue structural homeostasis is well established [271]. Lumican knockout mice have been shown to have serious functional defects including corneal opacity as well as skin and tendon fragility associated with disorganised and loosely packed collagen fibers [272-275]. In addition to the structural organisation of the tissues, this proteoglycan has been shown to participate in the regulation of key biological events including cell proliferation, migration and adhesion.

Ishiwata et al [276] have reported that inhibition of lumican protein synthesis increases proliferation in human embryonic kidney 293 cells; a similar result has been found with

Saos 2 cells (well-differentiated human osteosarcoma cell lines) when inhibit lumican expression [276]. Cell migration and chemotactic response to fibronectin were also found to be decreased in Saos 2 cells [277]. In another study, induction of lumican 103

expression in mouse melanoma cells had no effect on cell proliferation rate, but significantly inhibited anchorage-independent growth, cell migration and invasion of those cells through an ECM gel [278].

Lumican has been reported to be expressed in various tumour tissues and has been both positively and negatively correlated with tumour growth. Lumican expression has been shown to be increased in breast cancer [279], prostate [239, 243] and colorectal cancer [280] and pancreatic cancer [281, 282]. All these reports have shown that lumican was localised in cancer cells and/or stromal cells. However, there are some contradictory reports in the literature about the correlation between lumican protein expression and prognostic factors such as age, sex, tumor grade and patient outcome

[279, 283, 284] in these cancers.

Lumican and fibrosis: Lumican has been found to be predominantly localised in the areas of pathological fibrosis including the thickened intima of human coronary arteries [285], ischemic and reperfused hearts [286], and acute and chronic pancreatitis- like lesions close to pancreatic cancer nests [287, 288]. A recent study of progressive fibrosis in a subset of patients with non-alcoholic fatty liver disease (NAFLD) has reported that lumican was overexpressed not only in moderate to advanced fibrosis, but also in early stages of NAFLD, suggesting that hepatic lumican might be an early marker of a profibrotic state in patients with NAFLD.

The findings of increased lumican expression in fibrotic tissue are supported by our microarray result showing that lumican was increased by 5.0 fold in PSCs cultured on collagen I (representative of a fibrotic matrix) compared to cells grown on

MatrigelTM. This gene was selected for further validation in view of the reports that its expression was correlated with pancreatic cancer outcome and that it may be an early marker for fibrosis. 104

5.1.3 Fos

Fos-Jun hetero or Jun-Jun homodimers form the Activator Protein-1 (AP-1) transcription factor complex [289-291] which has been implicated in various cellular processes, including cell proliferation, survival and apoptosis [290, 291]. Jun has a specific DNA binding activity, while Fos has homology to the putative DNA binding domain of Jun. In growth factor stimulated cells, Jun binds DNA as a dimer with Fos as its natural partner. However, overexpression of Jun protein in the absence of Fos may result in formation of aberrant homodimeric transcription complexes, which could abrogate the normal mechanisms controlling gene expression [289].

The activity of AP-1 is induced by a variety of extracellular stimuli including growth factors, cytokines, and cellular stress [292]. Upon activation, AP-1 binds to a

DNA sequence motif in target genes, thereby regulating their expression [290]. Both

Erk1/2 (extracellular signal-regulated kinase 1 and 2) and JNK (c-Jun N-terminal kinase) pathways are known to regulate the activity of AP-1 [293]. The Erk 1/2 pathway has also been shown to mediate PSC proliferation by increasing AP-1 activity [132]. Indeed,

AP-1 has been shown to be the earliest factor to exhibit maximum DNA binding activity during the PSC transformation process [246].

It is of interest to note that upon exposure to vitamin A, AP-1 activity is decreased in a number of different cell types, and this is thought to be one of the mechanisms mediating vitamin A - related inhibition of cell proliferation [294]. Notably, vitamin A has also been shown to inhibit proliferation of pancreatic stellate cells, making it likely that vitamin A may exert this effect via inhibition of the AP-1 complex in PSCs. Our microarray results have shown that Fos was upregulated by 5 fold in PSCs cultured on collagen I vs cells cultured on MatrigelTM, suggesting that ECM may be capable of modulating PSC functions via the AP-1 complex. 105

5.1.4 IL-1α

As discussed in Chapter 3, IL-1 is an important mediator in the inflammatory response and has been shown to activate PSCs in culture [117]. More importantly, during PSC activation, they can synthesise IL-1 themselves to perpetuate activation even in the absence of the initial triggers [104, 116, 117]. Our microarray results have shown that IL-1α was increased by 4.3 fold in PSCs cultured on collagen I vs

MatrigelTM, confirmed previous findings.

The microarray results have shown that transgelin, lumican, Fos and IL-1α were upregulated in PSCs cultured on collagen I vs MatrigelTM. Therefore, this Chapter describes i) the validation of transgelin, lumican, Fos and IL-1α expression; ii) assessment of the role of transgelin and lumican in PSC activation; and iii) the expression of transgelin and lumican in human chronic pancreatitis tissue sections.

5.2 Methods

5.2.1 Validation of Transgelin, Lumican, Fos and IL-1α mRNA

Expression in Rat PSCs a) Reagents

These were as outlined in Section 3.3.10 with the following modification:

Primer sets for rat transgelin, lumican, Fos, IL-1α (Quantitect Primers, Qiagen

Doncaster, Victoria, Australia)

b) Method

To validate microarray results obtained for transgelin, lumican, Fos and IL-1α genes, RNA was extracted from rat PSCs (n=4) cultured on either MatrigelTM or collagen I as described in Section 4.2.1-4.2.3. cDNA was synthesised by reverse 106

transcription and mRNA levels were assessed by real-time PCR as described in Sections

3.3.9 and 3.3.10.

[Note: Transgelin and lumican were selected for validation at protein level, while Fos and IL-1α were only validated at mRNA level. This was because Fos and IL-1α have been well studied in PSCs and been reported in several papers [117, 246, 294], while the expression and the role of transgelin and lumican in PSCs have not been addressed to date].

5.2.2 Validation of Transgelin Protein Expression by Western Blotting a) Reagents

These were as outlined in Section 3.3.5 with the following modifications/additions:

1. Polyclonal goat anti-rabbit transgelin antibody (Abcam, Cambridge, UK)

2. Horseradish peroxidase (HRP) - labelled goat anti-mouse antibody (DAKO,

Botany, Australia)

b) Method

Rat PSCs were freshly isolated and cultured on MatrigelTM and collagen I for 72 hours and cells were recovered as described in Sections 4.2.1 and 4.2.2. Transgelin western blotting was performed as described in Section 3.3.5 with the following modifications: 5Pg of protein was loaded onto a 10% (w/v) SDS polyacrylamide gel and separated by electrophoresis. Membranes were incubated for one hour in blocking buffer [PBS, skim milk 5%, Tween-20 (T) 0.1%] in order to prevent non-specific binding of the antibody. This was followed by an overnight incubation at 4°C with the polyclonal goat anti-rabbit transgelin antibody [1:1000 in 0.1% Tween-PBS (TPBS) containing 5% skim milk]. HRP-labeled goat anti-rabbit IgG (1:2000 in 0.1% TPBS 107

containing 5% skim milk) was applied as a secondary reagent for 1 hour at room temperature. Equal protein loading for SDS gel was assessed using the housekeeping protein GAPDH as described in Section 3.3.7.

5.2.3 Validation of Lumican Protein Expression by

Immunoprecipitation and Western Blotting

5.2.3.1 Immunoprecipitation of Lumican from PSC Secretions a) Reagents

1. Protein G Sepharose® (Sigma)

2. Polyclonal goat anti-rabbit antibody (Santa Cruz Biotechnology, Inc., Santa

Cruz, CA, USA)

3. Tris-saline azide (TSA) solution pH 8.0

Tris chloride 1.58g/L

Sodium chloride 8.18g/L

Sodium azide 0.025%

b) Method

Rat PSCs were freshly isolated and cultured on MatrigelTM and collagen I for 72 hours as outlined in Section 4.2.1 and 4.2.2. Cell secretions were collected after 72 hours. Due to low abundance of lumican in the PSC secretions (as indicated by our preliminary studies), immunoprecipitation was performed. Briefly, 2 mL of PSC secretions were incubated with 40PL of anti-IgG sepharose beads for 2 hours at room temperature with gentle rotation to avoid non-specific binding. Cleaned secretions were then removed by centrifugation at 1000rpm for 5 minutes and divided into 2 fresh tubes.

To concentrate lumican protein in the secretions, 0.25Pg of anti-lumican antibody was 108

added into one tube, while 0.25Pg of rabbit IgG antibody was added to the other tube as a negative control. Both tubes were incubated at 4ºC overnight with gentle rotation. To precipitate the lumican antibody-protein complex, 20PL of protein G sepharose beads were added into each tube and incubated at 4ºC for 2 hours with gentle rotation. After 2 hours incubation, supernatant was removed and beads were washed by 1mL of PBS, followed by one more wash with TSA solution. After the last wash, 20PL of SDS- loading buffer was added to the beads and beads were boiled for 5 minutes at 99°C to dissociate lumican protein and antibody. Beads were then pelleted by centrifugation for

1 minute at 1000rpm and the supernatant was then used for western blotting.

5.2.3.2 Western Blotting for Lumican a) Reagents

These were as outlined in Section 3.3.5 with the following modifications/additions:

1. Polyclonal goat anti-rabbit lumican antibody (Santa Cruz Biotechnology,

Inc., Santa Cruz, CA, USA)

2. Horseradish peroxidase (HRP)-labelled goat anti-mouse antibody (DAKO,

Botany, Australia)

b) Method

Supernatants obtained after the immunoprecipitation process were loaded onto an 8% (w/v) SDS polyacrylamide gel and separated by electrophoresis. Membranes were incubated for one hour in blocking buffer (PBS, skim milk 5%, Tween-20 0.1%) in order to prevent non-specific binding of the antibody. This was followed by an overnight incubation at 4°C with the polyclonal goat anti-rabbit lumican antibody

(1:500 in 0.1% TPBS containing 5% skim milk). HRP-labeled goat anti-rabbit IgG 109

(1:2000 in 0.1% TPBS containing 5% skim milk) was applied as a secondary reagent for 1 hour at room temperature. Equal protein loading for SDS gel was assessed using the housekeeping protein GAPDH as described in Section 3.3.7.

5.2.4 Assessment of Transgelin and Lumican Expression in Rat PSCs by Immunocytochemistry a) Reagents

1. Antibodies as outlined in Sections 5.2.2 and 5.2.3

2. 0.1% Triton X100 (Sigma)

50uL/50mL H2O 50mL

3. Hydrogen peroxide (H2O2) 1% in H2O

30% H2O2 8.3mL

H2O 241.7mL

4. Phosphate buffered saline solution (PBS) pH 7.4

Sodium chloride (NaCl) 8g/L

Potassium chloride (KCl) 0.2g/L

Di-sodium orthophosphate (Na2HPO4) 1.4g/L

Potassium dihydrogen orthophosphate (KH2PO4) 0.24g/L

5. 1% Bovine serum albumin (BSA; Pierce, Rockford, 1L, USA)

0.1g/10mL in phosphate buffered saline (PBS)

6. CrystalmountTM aqueous mounting medium (Biomeda, Foster City, CA)

b) Method

Sterile coverslips were placed at the bottom of 6-well plates. PSCs were then seeded on coverslips at a density of 3x104 cells per well and grown to 50% confluence. 110

Cells were then fixed by 4% paraformaldehyde and permeabilised using 0.5% Triton

X100. Fixed cells were washed with PBS and then incubated with 1% H2O2 for 30 minutes to block endogenous peroxidase activity. Cells were then washed with PBS and incubated with blocking solution (10% goat serum with 1% BSA in PBS) for 30 minutes. This was followed by overnight incubation at 4˚C with rabbit anti-transgelin antibody (1:200) or rabbit anti-lumican antibody (1:50). Cells incubated with isotype- matched rabbit anti-IgG at the same concentration as the primary antibodies were used as negative controls. After washing with PBS, cells were incubated with HRP-coupled goat anti-rabbit IgG (1:100) secondary antibody for 30 minutes at room temperature.

Cells were washed again with PBS and staining was developed by the chromogenic method using the Dako DAB (diaminobenzidine) kit. Then the cells were counterstained with hematoxylin for 20 seconds at room temperature. After staining, coverslips were placed on the glass slides and the slides were examined by light microscopy for transgelin and lumican staining.

5.2.5 Assessment of Transgelin and Lumican Expression in Quiescent vs Activated Rat PSCs

Since collagen I and plastic are both activating matrices for PSCs, it was of interest to determine whether PSCs activated by these matrices showed a similar trend in terms of upregulated transgelin and lumican expression compared to cells in their quiescent phase. In addition, whether this upregulation of transgelin and lumican was associated with PSC activation is still unknown. Therefore, transgelin and lumican expression were assessed in quiescent rat PSCs compared to activated rat PSCs.

Rat PSCs were isolated and seeded onto two Petri dishes (1.2 million cells per dish) as described in Section 3.3.1. The remaining cells were cultured in a T75 flask. 111

After 24 hours, protein and RNA were collected from each Petri dish (these were considered as quiescent cells) as described in Sections 3.3.5 and 3.3.8. When the cells in the T75 flask attained confluence (about 72 hours), they were passaged and seeded at a density of 1.2 million/dish onto another two Petri dishes. RNA and protein were collected when the cells attained confluence (considered as activated cells). Transgelin and lumican expression at mRNA level was assessed as described in Section 5.2.1 and transgelin protein level was assessed as described in Section 5.2.2. GAPDH was used as equal protein loading control as described in Section 3.3.7.

5.2.6 Inhibition of Transgelin Expression in Rat PSCs Using Small

Interfering RNA (siRNA)

The rationale for inhibiting transgelin in PSCs was to assess whether the function of this protein is involved in cell proliferation and/or αSMA expression. a) Reagents

1. Lipofectamine 2000 (L2K) (Invitrogen, Carlsbad, CA, USA)

2. Opti-MEM (Invitrogen, Carlsbad, CA, USA)

3. Transgelin siRNA (ON-TARGET plus siRNA, Dharmacon, Thermo Fisher

Scientific, MA, USA)

4. Non-silencing siRNA (Dharmacon, Thermo Fisher Scientific, MA, USA)

b) Method

siRNA denotes synthesised short double strands of RNA capable of interfering with the expression of specific genes [295]. siRNA has been shown to occur naturally in plants [296]. Small interfering RNAs directed against a wide range of target genes in 112

various species are now commercially available and represent a potent tool for in vitro and in vivo studies.

The day before transfection, culture activated rat PSCs were seeded into 6-well plates at a density of 30,000 cells/well. For the calculation of the transfection mix, all volumes were increased by 10% to allow for pipetting error. On the day of transfection, a 10x stock solution (corresponding to a 1:50 dilution of the original stock of 1mg/ml) of lipofectamine (L2K) was prepared. 2.2Pl of L2K was added to 107.8Pl of Opti-MEM

(per well). The solution was then mixed gently using a pipette and incubated for 5 minutes at room temperature. A 10x siRNA or non-silencing RNA stock solution

(corresponding to 1PM of siRNA or non-silencing RNA, i.e. 1:20 of the original stock of 20PM) was then prepared by adding 5.5Pl to 104.5Pl opti-MEM and mixed carefully.

110Pl of the 10 x L2K stock was then added to 110Pl of the 10x siRNA or non- silencing RNA solution, mixed gently with a pipette and incubated for 20 minutes at room temperature. During this incubation, cell medium containing 10% serum was removed from the cells and the cells were then washed once with Opti-MEM (reduced serum media commonly used during cell transfection) followed by addition of 1ml of

Opti-MEM and incubation for 20 minutes. 880Pl of Opti-MEM was then added to the siRNA/non-silencing RNA + L2K solutions, mixed well with a pipette and 1ml of the appropriate transfection complex added into the dedicated well. For each transfection, a mock no transfection control (L2K only) was included. Cells were then incubated with the transfection complex for 5 hours. At the end of this period, medium was replaced with fresh 10% IMDM (without antibiotics). Transgelin mRNA and protein levels were assessed after 48 and 72 hours.

113

5.2.7 Effect of Transgelin Inhibition on αSMA Expression in Rat PSCs

48 and 72 hours post transfection, cells were lysed and αSMA expression was assessed by western blotting as outlined in Section 3.3.5.

5.2.8 Effect of Transgelin Inhibition on Rat PSC Proliferation a) Reagents

1. Culture Medium (Invitrogen, Carlsbad, CA, USA)

Iscove’s modified Dulbecco’s medium (IMDM), containing:

Fetal bovine serum 0.1%

Glutamine 4mM

2. Cell counting kit-8 (Dojindo, Auspep Pty Ltd, Parkville, VIC, Australia)

b) Method

Rat PSCs were seeded at a density of 30,000 cells/well in a 6 well plate and transfected with transgelin siRNA. After 48 hours of transfection, medium was changed to 1mL/well of fresh 10% IMDM (without antibiotics) and cells were incubated for another 24 hours. Proliferation was assessed using the cell counting kit-8 according to the manufacturer’s instructions. Briefly, 100Pl of the cell counting kit-8 solution were added to each well and the plate was incubated at 37°C in 95% air / 5% CO2 for 1-4 hours. The optical density of the wells was determined at 450nm. This assay uses a tetrazolium salt which produces a water-soluble formazan dye upon reduction in the presence of dehydrogenases in cells. The amount of formazan produced is directly proportional to the number of living cells.

114

5.2.9 Effect of Transgelin Inhibition on Proliferation of Rat PSCs

Cultured on Different Matrices a) Reagents

These were as outlined in Section 5.2.1.

b) Method

24 hours after transfection, rat PSCs were detached from culture plates by trypsinisation. Cells were then seeded back onto MatrigelTM and collagen I coated culture plates and incubated for 24 hours. Medium was then replaced with 1mL of fresh

10% IMDM and cells were incubated for another 24 hours. Proliferation was assessed as described in Section 5.2.8.

5.2.10 Transgelin and Lumican Expression in Human Chronic

Pancreatitis Tissue Sections a) Reagents

1. Polyclonal rabbit anti-transgelin antibody (Abcam, Cambridge, UK)

2. Polyclonal rabbit anti-lumican (Santa Cruz Biotechnology, Inc., Santa Cruz, CA,

USA)

3. Rabbit isotype control IgG (DAKO, Botany, NSW, Australia)

4. Biotin-labelled goat anti-rabbit IgG (Vector Laboratories, Burlingame, CA, USA)

5. Avidin-biotin-peroxidase complex (ABC Kit, Vector Laboratories, Burlingame,

CA, USA)

6. Xylene

7. Ethanol

8. Methanol 115

9. Antigen retrieval buffer pH 6.0

Tris-sodium citrate 2.94g

H2O 1000mL

Tween 20 0.5mL

10. Hydrogen peroxide (H2O2) 1% in methanol and H2O

30% H2O2 8.3mL

Methanol 8.3mL

H2O 233.4mL

11. Phosphate buffered saline solution (PBS) pH 7.4

Sodium chloride (NaCl) 8g/L

Potassium chloride (KCl) 0.2g/L

D-sodium orthophosphate (Na2HPO4) 1.4g/L

Potassium dihydrogen orthophosphate (KH2PO4) 0.24g/L

12. Washing buffer: PBS containing 0.5% Tween-20

13. Goat serum

14. DAB substrate chromogen system (DAKO, Botany, Australia)

15. Bluing reagent

30% NH4OH 1.5mL

70% Ethanol 98.5mL

16. Mayer’s hematoxylin

17. Histomount (National Diagnostics, Atlanta, Georgia, USA)

b) Method

In preparation for immunohistochemistry, paraffin-embedded sections of the pancreas were dewaxed and rehydrated as follows. Sections were incubated in a 60ºC 116

oven for 30 minutes followed by immersion three times in fresh xylene for 5 minutes.

Sections were then dipped in absolute ethanol twice for 5 minutes each, followed by two immersions of 5 minutes in 95% ethanol. After another two immersions of 5 minutes in 70% ethanol, sections were rinsed twice in tap water. Antigen retrieval was performed as follows: 400mL of citrate buffer were heated in a 2L beaker in the microwave until cloudy and sections were soaked in citrate buffer and incubated for 15 minutes in an oven set to 104ºC. Sections were allowed to cool for 1 hour on the bench in citrate buffer followed by two washes in water. Sections were then incubated in methanol containing 1% H2O2 for 10 minutes in order to inhibit endogenous peroxidase reactivity. This was followed by three washes of 5 minutes in PBS. Sections were then incubated in a blocking solution containing PBS and 10% goat serum for 30 minutes and then with a polyclonal goat anti-rabbit transgelin antibody (1:200 dilution) or lumican (1:50 dilution) overnight at 4°C. Rabbit isotype IgG (at the same concentration as transgelin or lumican) was used as a negative control. After 3 washes of 5 minutes each with PBS, sections were incubated with biotin-labelled goat anti-rabbit IgG (1:200) for 1 hour at room temperature, followed by 5 minutes incubation with ABC kit to amplify the signal. This was again followed by 3 washes of 5 minutes each with PBS.

Colour was developed using the 3, 3-diaminobenzidine tetrahydrochloride / DAB) substrate chromogen system for 1-10 minutes after which sections were thoroughly washed in tap water. Counterstaining was performed with Mayer’s hematoxylin for 1 minute followed by washing in tap water for 1 minute. Colour differentiation was achieved by brief (30s) immersions in bluing reagent solution followed by a 1 minute wash in tap water. Dehydration of sections involved the following steps: 5 minutes in

70% ethanol, followed by 5 minutes in 95% ethanol. This was followed by three five minute washes in 100% ethanol and three immersions of 5 minutes each in xylene. 117

Coverslips were mounted using histomount media. Whole slides were then scanned using the Aperio ScanScope XT system and images obtained using Aperio software.

5.2.11 Statistical Analysis

Data are expressed as mean r SEM and analysed as appropriate by the Kruskal-

Wallis test followed by Dunn’s post-hoc test, one-way ANOVA followed by Tukey’s post-hoc test or Student’s t test (for paired data). The analyses were performed using the

GraphPad Prism Software.

5.3 Results

5.3.1 Validation of Transgelin, Lumican, Fos and IL-1α mRNA of Rat

PSCs Cultured on Collagen I vs MatrigelTM

Freshly isolated rat PSCs were cultured on either MatrigelTM or collagen I for 72 hours. mRNA levels of transgelin, lumican, Fos and IL-1α were assessed by real-time

PCR. Transgelin, lumican, Fos mRNA levels were up-regulated 45.4±9.2, 2.3±0.14, and

18.6±6.18 fold (p<0.05, n=4 separate rat PSC preparations) respectively in PSCs cultured on collagen I compared to PSCs grown on MatrigelTM, confirming our microarray results (Figure 5.1-5.3). IL-1α mRNA level was no different in PSCs cultured on collagen I vs MatrigelTM (p=0.1749, n=4 separate rat PSC preparations)

(Figure 5.4).

118

Figure 5.1

Expression of Transgelin mRNA in Rat PSCs Cultured on MatrigelTM vs Collagen I

Relative normalised transgelin mRNA expression

MatrigelTM Collagen I

Expression of transgelin in rat PSCs cultured on MatrigelTM vs collagen I for 72 hours.

Transgelin mRNA expression was assessed by real-time quantitative PCR and showed a significant upregulation in rat PSCs cultured on collagen I vs PSCs cultured on

Matrigel (*p<0.05, collagen I vs MatrigelTM; n=4 separate rat PSC preparations).

Transgelin mRNA levels were normalised against house keeping gene 18S levels.

119

Figure 5.2

Expression of Lumican mRNA in Rat PSCs Cultured on MatrigelTM vs Collagen I

Relative normalised lumican mRNA expression

MatrigelTM Collagen I

Expression of lumican in rat PSCs cultured on MatrigelTM vs collagen I for 72 hours.

Lumican mRNA expression was assessed by real-time quantitative PCR and showed a significant upregulation in rat PSCs cultured on collagen I vs PSCs cultured on

Matrigel (*p<0.05, collagen I vs MatrigelTM; n=4 separate rat PSC preparations).

Lumican mRNA levels were normalised against house keeping gene 18S levels.

120

Figure 5.3

Expression of Fos mRNA in Rat PSCs Cultured on MatrigelTM vs Collagen I

Relative normalised Fos mRNA

expression

MatrigelTM Collagen I

Expression of Fos in rat PSCs cultured on MatrigelTM vs collagen I for 72 hours. Fos mRNA expression was assessed by real-time quantitative PCR and showed a significant upregulation in PSCs cultured on collagen I vs PSCs cultured on MatrigelTM (*p<0.05, collagen I vs MatrigelTM; n=4 separate rat PSC preparations). Fos mRNA levels were normalised against house keeping gene 18S levels.

121

Figure 5.4

Expression of IL-1α mRNA in Rat PSCs Cultured on MatrigelTM vs Collagen I

Relative normalised IL-1α mRNA

expression

MatrigelTM Collagen I

Expression of IL-1α in rat PSCs cultured on MatrigelTM vs collagen I for 72 hours. IL-

1α mRNA expression was assessed by real-time quantitative PCR. There was a trend towards upregulation of IL-1α mRNA expression in rat PSCs cultured on collagen I compared to PSCs cultured on MatrigelTM. However, this upregulation was not statistically significant (p=0.1749, n=3 separate rat PSC preparations). IL-1α mRNA levels were normalised against house keeping gene 18S levels.

122

5.3.2 Validation of Transgelin and Lumican Protein Expression in

PSCs Cultured on MatrigelTM vs Collagen I

To determine whether the observed upregulation of mRNA for transgelin and lumican translated into an increase at the protein level, transgelin and lumican protein expression was assessed by western blotting.

Transgelin protein was upregulated 14.45 fold (p<0.05, n=3 separate rat PSC preparations) in PSCs cultured on collagen I vs MatrigelTM. Equal protein loading was confirmed by analyses of the housekeeping gene GAPDH (Figure 5.5).

Since lumican is a secreted protein, its expression was assessed by western blotting of PSC secretions. However, even after immunoprecipitation (to concentrate lumican protein in PSC secretions) lumican expression was undetectable by immunoblotting. MiaPaCa-2 (pancreatic cancer cells, known to be positive [281]) cell lysate was used as positive control (Figure 5.6).

5.3.3 Immunocytochemistry of Transgelin and Lumican

To identify the cellular location of transgelin and lumican proteins within PSCs, immunocytochemistry was performed. Strong positive transgelin staining was observed in the cytoplasm and nucleus of PSCs (Figure 5.7). However, PSCs were negative for lumican (Figure 5.8).

123

Figure 5.5

Expression of Transgelin Protein in Rat PSCs Cultured on MatrigelTM vs Collagen I

Transgelin 22kDa

GAPDH 36kDa

MatrigelTM Collagen I

Densitometry units

(% of MatrigelTM)

MatrigelTM Collagen I

Expression of transgelin in rat PSCs cultured on MatrigelTM vs collagen I for 72 hours.

The figure shows a representative western blot and densitometry analysis of transgelin expression. Transgelin protein levels were significantly upregulated in rat PSCs cultured on collagen I vs PSCs cultured on MatrigelTM (*p<0.05, collagen I vs

MatrigelTM; n=3 separate rat PSC preparations). GAPDH was used as a loading control.

124

Figure 5.6

Immunoprecipitation of Rat PSC Secretions for Lumican Western Blotting

Lumican 60KDa

Denatured rabbit IgG heavy chain 50KDa

Rabbit IgG Lumican MiaPaCa-2

Representative image for lumican western blotting. From left to right are negative control (PSC secretions immunoprecipitated using rabbit IgG), PSC secretions immunoprecipitated using lumican antibody, and positive control (MiaPaCa-2

(pancreatic cancer cell line) lysates, known to express lumican [281]). MiaPaCa-2 cells lysates had a strong positive band of lumican at the expected molecular weight (60KDa), but no signal was detected in PSC secretions. The thick at 50KDa are denatured rabbit

IgG heavy chain bands.

125

Figure 5.7

Expression of Transgelin in Rat PSCs

Negative control Transgelin (rabbit IgG)

Expression of transgelin by rat PSCs. Strong positive staining for transgelin was observed in the cytoplasm and nucleus of PSCs using immunocytochemistry. The panel on the left shows no staining in the negative control. Magnification×100.

126

Figure 5.8

Immunocytochemistry of Lumican in Rat PSCs

Negative control Lumican (rabbit IgG)

Immunocytochemistry of lumican on rat PSCs. No staining of lumican was demonstrated in rat PSCs. The panel on the left shows isotype negative control.

Magnification×100.

127

5.3.4 Transgelin and Lumican Expression in Quiescent vs Activated

Rat PSCs

To determine whether the upregulation of transgelin and lumican mRNA expression was associated with PSC activation, the expression of these proteins in activated PSCs was compared to that in quiescent PSCs. The results showed a significant upregulation of transgelin (20.16 ± 5.94 fold, p<0.05, n=4 separate rat PSC preparations) (Figure 5.9) and lumican mRNA (4.59 ± 1.25 fold, p<0.05, n=4 separate rat PSC preparations) (Figure 5.10) in activated PSCs compared to quiescent PSCs.

In addition, transgelin was also upregulated at protein level (2.957 ± 0.29 fold, p<0.05, n=4 separate rat PSC preparations) in activated PSCs (Figure 5.11).

Interestingly, a double band for transgelin was observed in activated PSCs while only one band was observed in quiescent PSCs (see details in discussion section). Since lumican expression was undetectable in cell secretions using western blotting, its expression in quiescent vs activated PSCs could not be assessed.

128

Figure 5.9

Transgelin mRNA Expression in Quiescent vs Activated Rat PSCs

Relative normalised transgelin mRNA expression

MatrigelTM Collagen I

Normalised transgelin mRNA expression in quiescent vs activated rat PSCs. Transgelin mRNA expression was significantly increased in PSCs compared to quiescent PSCs

(*p<0.05; n = 4 separate rat PSC preparations). Transgelin mRNA levels were normalised against house keeping gene 18S levels.

129

Figure 5.10

Lumican mRNA Expression in Quiescent vs Activated Rat PSCs

Relative normalised lumican mRNA expression

MatrigelTM Collagen I

Normalised lumican mRNA expression in quiescent vs activated rat PSCs. Lumican mRNA expression was significantly increased in activated PSCs compared to quiescent

PSCs (*p<0.05; n = 4 separate PSC preparations). Lumican mRNA levels were normalised against house keeping gene 18S levels.

130

Figure 5.11

Transgelin Protein Expression in Quiescent vs Activated Rat PSCs

Transgelin 22KDa

GAPDH 36KDa

Q A Q A Q A Q A Q A

Densitometry units (% of Quiescent)

TM Matrigel Collagen I

Expression of transgelin protein in quiescent vs activated rat PSCs. Transgelin expression was significantly increased in activated rat PSCs compared to quiescent

PSCs (*p<0.05; n=4 separate rat PSC preparations). A double band for transgelin was observed in activated PSCs, while only one band was observed in quiescent PSCs

(details in discussion section).

131

5.3.5 Inhibition of Transgelin Expression by Transgelin siRNA

In order to study the role of transgelin in PSC activation, PSCs were transfected with transgelin siRNA to inhibit the expression of the protein. 48 hours post- transfection, PSCs exhibited a 97.814r0.41% (p<0.001, tagln siRNA vs ns siRNA; n=3 separate rat PSC preparations) knockdown of transgelin gene expression, and this effect was sustained over 72 hours (94.638r0.89% knockdown; p<0.001, tagln siRNA vs ns siRNA; n=3 separate rat PSC preparations) (Figure 5.12). To confirm whether this knockdown also influenced protein expression, western blotting was performed. The results demonstrated a 78.52r11.07% and 84.29r5.77% (p<0.001, tagln siRNA vs ns siRNA; n=3 separate rat PSC preparations) knockdown at protein level at 48 hours and

72 hours post-transfection (Figure 5.13).

132

Figure 5.12

Effect of Transfection of Rat PSCs with siRNA for Transgelin on Transgelin mRNA Expression

Normalised transgelin mRNA expression

** **

mockk ns tagln mockk ns tagln siRNAA siRNA siRNAA siRNA

48 hours 72 hours

Effect of transfection of rat PSCs with siRNA for transgelin (tagln) on transgelin mRNA

expression. Rat PSCs were transfected with lipofectamine only (mock), non-silencing

siRNA (ns siRNA) and transgelin siRNA (tagln siRNA). Transfection of PSCs with

siRNA for transgelin significantly decreased transgelin mRNA expression compared to

PSCs transfected with ns siRNA at both 48 and 72 hours (**p<0.001, tagln siRNA vs ns

siRNA; n=3 separate rat PSC preparations).

133

Figure 5.13

Effect of Transfection of Rat PSCs with siRNA for Transgelin on Transgelin Protein Expression

Transgelin

GAPDH mockck nss taglnn mockock nss tagln siRNANA siRNANA siRNANA siRNA 48 hours 72 hours

Densitometry units (% of mock) ** ** mockk ns taglnln mockck ns tagln siRNAA siRNANA siRNANA siRNA 48 hours 72 hours

Effect of transfection of rat PSCs with siRNA for transgelin (tagln) on transgelin protein expression. The figure shows a representative western blot and densitometry analysis of transgelin expression. Rat PSCs were transfected with lipofectamine only (mock), non silencing siRNA (ns siRNA) and transgelin siRNA (tagln siRNA). Transfection of rat

PSCs with siRNA for transgelin significantly decreased transgelin protein expression in

PSCs at both 48 and 72 hours (**p<0.001, tagln siRNA vs ns siRNA; n=3 separate rat

PSC preparations). 134

5.3.6 Effect of Transgelin Inhibition on Rat PSCs Activation

(Cultured on Plastic, MatrigelTM and Collagen I) a. Effect of Transgelin Inhibition on αSMA Expression by Rat PSCs Cultured

on Plastic

The effect of decreased transgelin expression on PSC αSMA levels was assessed by western blotting at 48 hours and 72 hours after transfection. Inhibition of transgelin had no effect on PSC αSMA expression at both time points (Figure 5.14)

b. Effect of Transgelin Inhibition on Proliferation of Rat PSCs

i) Cultured on Plastic

Inhibition of transgelin expression resulted in a significant reduction (26.41 r

3.72%, p<0.001, n=4 separate rat PSC preparations) of PSC proliferation compared to control cells (mock transfected cells), as assessed at 72 hours post-transfection (Figure

5.15).

ii) Cultured on MatrigelTM or Collagen I

To determine whether the effect of transgelin on PSC proliferation was influenced by the culture surface on which the cells were grown, PSCs were transfected with siRNA for transgelin and then cultured on MatrigelTM or collagen I-coated plates for 48 hours. Similar to the results observed for PSCs cultured on plastic, significant reductions of PSC proliferation were observed in cells cultured on MatrigelTM and collagen I (by 19.38r2.6% and 28.47r5.1% respectively, p<0.05 vs ns siRNA, n=4 separate rat PSC preparations) (Figure 5.15). The type of matrix (fibrotic or basement membrane like) did not appear to influence this effect.

135

Figure 5.14

Inhibition of Transgelin Expression on αSMA Expression by Rat PSCs

αSMA

GAPDH

mockck nss taglnn mockck nss tagln siRNAN A siRNAA siRNANA siRNA

48 hours 72 hours

Densitometry units (% of mock)

mockk ns taglnln mockckck ns tagln siRNA NA siRNANA siRNANA siRNA 48 hours 72 hours

Effect of transfection of rat PSCs with siRNA for transgelin on αSMA expression. αSMA expression was assessed 48 hours and 72 hours post transfection by western blotting.

Inhibition of transgelin expression had no effect on αSMA expression by rat PSCs (n=4 separate rat PSC preparations).

136

Figure 5.15

Inhibition of Transgelin Expression on Proliferation of Rat PSC Cultured on Different Matrices

Plastic MatrigelTM Collagen I

Proliferation ** (% of mock) ** **

ns taglnn ns taglnn ns tagln

siRNAA siRNANA siRNAA siRNANA siRNAA siRNA

Effect of silencing transgelin (tagln) on proliferation of rat PSCs cultured on different matrices (plastic, MatrigelTM and collagen I). Inhibition of transgelin expression significantly decreased PSC proliferation compared to non-silencing siRNA (ns siRNA) control of PSCs cultured on different matrices (**p<0.001, tagln siRNA vs ns siRNA; n=4 separate rat PSC preparations).

137

5.3.7 Transgelin Expression in Human Chronic Pancreatitis Tissue

Sections

In chronic pancreatitis tissue sections (n=2 patients), transgelin was expressed in fibrotic areas and peri-acinar spaces but not in acinar cells (Figure 5.16). To confirm that transgelin was mainly expressed in fibrotic areas in the pancreas, serial sections were stained for total collagen using Sirius red (n=2 patients). Result showed that the areas that stained positive for transgelin were also positive for Sirius red (Figure 5.17).

5.3.8 Lumican Expression in Human Chronic Pancreatitis Tissue

Sections

Tissue sections from chronic pancreatitis (n=2 patients) were immunostained for lumican (Figure 5.18). Lumican was expressed in fibrotic areas and, in contrast to transgelin, also in acinar cells, confirming previous reports in the literature [281]. To confirm that lumican was expressed in fibrotic areas in the pancreas, serial sections were stained for total collagen using Sirius red (n=2 patients). Result showed that the areas that stained positive lumican also were positive for Sirius red (Figure 5.19).

138

Figure 5.16

Expression of Transgelin in Human Chronic Pancreatitis Tissue

* *

Isotype Negative Control Transgelin

Expression of transgelin (indicated by arrow) in human chronic pancreatitis tissue sections. The figure shows representative paraffin-embedded chronic pancreatitis tissue sections immunostained for transgelin (n=2 different patients). Strong positive staining for transgelin was observed in stromal areas, duct and periacinar space, but not in acinar cells (indicated by star). The panel on the left shows no staining in the negative control (Scale bar =100μm). Magnification: x100.

139

Figure 5.17

Co- localisation of Transgelin and Collagen in Human Chronic Pancreatitis

Patient 1 Patient 2

Negative Isotype Control

Transgelin

Sirius Red

Co-localisation of transgelin and sirius red (stain for collagen) on human chronic pancreatitis serial tissue sections. The figure shows representative immunostaining for negative isotype control (on the top), transgelin (middle) and collagen (sirius red on the bottom) from 2 patients. The stromal areas which are positive for transgelin also showed positive staining for collagen (Scale bar =100μm).

140

Figure 5.18

Expression of Lumican in Human Chronic

Pancreatitis Tissue

* *

Isotype Negative Control Lumican

Expression of lumican (indicated by arrow) in human chronic pancreatitis tissue sections (n=2 different patients). The figure shows representative paraffin-embedded pancreatic sections immunostained for lumican from human chronic pancreatitis patients. Strong positive staining for lumican was observed in stromal area and acinar cells (indicated by star). The panel on the left shows no staining in the negative control

(Scale bar =100μm). Magnification: x100.

141

Figure 5.19

Co- localisation of Lumican and Collagen in Human Chronic Pancreatitis

Patient 1 Patient 2

Negative Isotype Control

Lumican

Sirius Red

Co localisation of lumican and sirius red (stain for collagen) on human chronic pancreatitis serial tissue sections. The figure shows representative immunostaining for negative isotype control (on the top), lumican (middle) and collagen (on the bottom) from 2 patients. The fibrotic areas which were positive for lumican also showed positive staining for collagen (Scale bar =100μm). 142

5.4 Discussion

As detailed in Chapter 4, microarray results showed the upregulation of transgelin, lumican, Fos and IL-1α in PSCs cultured on collagen I vs PSCs grown on

MatrigelTM. The studies described in this Chapter first attempted to validate the microarray results at messenger RNA level using real time PCR. Transgelin, lumican and Fos mRNA were all significantly upregulated in PSCs cultured on collagen I vs

MatrigelTM, confirming microarray data. IL-1α mRNA also showed a trend towards an increase in PSCs cultured on collagen I (p=0.1749), although the difference did not achieve statistical significance. Of the four genes noted here, transgelin and lumican were selected for further validation and study since little is known about the role of these proteins with respect to PSC function. In contrast, IL-1α and Fos have been relatively well studied and the expression of these genes has been reported to be associated with PSC activation [117, 246, 294].

Transgelin and lumican protein expression was validated by western blotting.

Transgelin was upregulated in PSCs cultured on collagen I vs MatrigelTM. However, lumican protein expression could not be demonstrated in PSCs either by western blotting or immunocytochemistry. A previous publication regarding lumican expression in stellate cells has demonstrated its expression only at mRNA level [282]. In the present study, lumican protein was undetectable in PSC secretions (even after immunoprecipitation). It is possible that more sensitive measurement such as ELISA or a better antibody may be required to measure lumican protein in cell secretions.

Traditionally, most PSC experiments reported in the literature have been performed with cells grown on plastic. Therefore, transgelin and lumican expression were compared in PSCs cultured on plastic vs PSCs cultured on MatrigelTM or collagen

I. Interestingly, the fold change of transgelin and lumican gene expression (as assessed 143

by microarray) in PSCs cultured on collagen I vs MatrigelTM (upregulated by 12.5 fold and 5.0 fold respectively) was similar to that observed for these genes in PSCs cultured on plastic vs MatrigelTM (transgelin and lumican increased by 11.8 fold and 6.6 fold respectively). Furthermore, there was no difference in the expression of these two genes in PSCs grown on collagen I vs plastic. Thus, microarray results suggested that in activated PSCs, the expression of these two genes was similar no matter what the activating matrix was (i.e. collagen I or plastic). Therefore, subsequent work related to transgelin function was performed with PSCs cultured on plastic.

Because the expression of transgelin and lumican were influenced by collagen I

(an activating matrix), it would not be unreasonable to postulate that these two genes are involved in the PSC activation process. To determine whether freshly isolated, quiescent PSCs were different from activated PSCs in the expression of transgelin and lumican, mRNA levels of these two genes were assessed in the two phenotypes of PSCs.

The results showed a significant upregulation of transgelin and lumican mRNA in activated PSCs. The upregulation of transgelin mRNA level in activated PSCs was also confirmed by western blotting at the protein level, suggesting that upregulation of transgelin was associated with PSC activation process.

Western blotting for transgelin in PSCs yielded an interesting finding; a double band for transgelin was observed in activated PSCs while only one band was observed in quiescent PSCs, indicating there are two isoforms of transgelin in activated PSCs.

More interestingly, transgelin siRNA only depleted the band that was not seen in the quiescent PSCs. It has previously been reported that rat tissue extracts have two transgelin homologs, sized 22KDa and 20KDa. The 20KDa band presumably results from proteolytic removal of the C-terminal end of the 22KDa polypeptide [297]. A more recent paper has also reported the same result, i.e. a shorter protein formed 144

through cleavage of the COOH terminus [255]. The properties of these two polypeptides may be different; the smaller isoform of bovine transgelin protein homolog showed stronger F-actin gelling activity than the larger form [298], suggesting that different isoforms of transgelin may have different key functions in vivo.

To localise transgelin in PSCs, immunocytochemistry was performed. Results showed that transgelin was expressed in the cytoplasm as well as in the nuclear compartment. Transgelin is known to localise in cytoplasm, where it binds to actin

[299]. Expression of this protein in the nucleus has also been described in other cell types, such as H9c2 cells (derived from embryonic rat ventricle) [300], bone marrow- derived mesenchymal stem cells [301] and colorectal cancer cells [237]. Indeed, many of the actin-binding proteins (more than 60 classes) localise to the nucleus [302] and these nuclear actin-binding proteins are associated with transcriptional regulation and

DNA repair [303].

Transgelin function in PSCs was then examined by inhibiting transgelin expression using siRNA techniques. Results showed that inhibition of transgelin expression significantly reduced PSC proliferation by 26.41% compared to vehicle control cells (mock), suggesting transgelin may play a role in supporting cell growth.

However, some studies have shown an inhibitory effect of transgelin on cell growth, such as HepG2 cells [304], LNCaP cells (human prostate adenocarcinoma cell line)

[243] and vascular smooth muscle cells [305]. All these reports suggested that transgelin exerts variable effects on cell growth in different cell types which could be due to the variable effect of transgelin on the structure of the actin filament in different cells.

The effect of transgelin inhibition on growth of PSCs on different matrices was also assessed in this study. Results showed that transgelin knockdown not only 145

decreased the proliferation of PSCs cultured on plastic, but also of PSCs cultured on physiological matrices (MatrigelTM and collagen I). As discussed in Chapter 2, activated

PSCs play a key role in the intense fibrotic reaction in chronic pancreatitis and pancreatic cancer. Therefore, targeting stellate cells (by inducing apoptosis or decreasing cell proliferation) is a mainstay of anti-fibrotic therapy. Even though this study only showed a small but statistically significant decrease in cell proliferation, it must be noted that the cells in these experiments were in a “basal” state. In vivo, stellate cells are surrounded by a number of proliferative factors such as cytokines, PDGF and secretions from surrounding cells [306] and therefore are already activated. It is possible that targeting transgelin in vivo may result in a much larger effect on proliferation of these pre-activated cells.

Transgelin has been reported to be involved in cellular functions other than proliferation, such as cell migration, invasion and apoptosis. It has been reported that silencing transgelin expression inhibits TGFβ induced lung epithelial cell migration

[262]. Inhibition of transgelin expression also decreases cancer stem cell (human hepatocellular carcinoma CD133+ Huh7 cells) invasiveness [307]. A similar effect has also been reported in colorectal cancer cell lines where silencing transgelin reduced cell invasion and clonogenic survival and also induced cell apoptosis [237]. The authors suggested that transgelin may act as a nuclear transcriptional factor, which may explain the multiple roles that transgelin appears to play in different cell types or organs. A direct investigation of the interactions between transgelin and other macromolecules in the nucleus will be required to clarify this issue.

There have been no reports to date about the expression of transgelin and lumican in chronic pancreatitis. This study is the first to report that transgelin is highly expressed in human chronic pancreatitis tissues. The expression is strongest in stromal 146

areas and peri-acinar spaces but absent in acinar cells. Transgelin expression has been shown to be upregulated in fibrotic areas of hepatic sections from liver cirrhosis patients showing intense staining in broad cirrhotic septa. In contrast, in normal liver, transgelin is expressed in the wall of blood vessels, in portal areas and in some fibroblasts in portal areas but not in epithelial cells and hepatocytes [308]. Transgelin expression was also found to be upregulated in the lungs of patients with idiopathic pulmonary fibrosis and its expression was localised to fibroblastic foci, and smooth muscle [262]. The findings of upregulated transgelin expression in pancreatic fibrosis concur well with the studies noted above and suggest that transgelin may play a role in fibrogenesis in the pancreas.

More importantly, the absence of transgelin expression in normal acinar cells may allow us to specifically target stellate cells in vivo, thereby minimising any off target effects.

Lumican expression has been reported in several other human tissues and organs.

The expression level in the adult is high in heart, placenta, skeletal, muscle, kidney and pancreas, but low in the brain, lung and liver [309]. In normal pancreas, lumican expression is observed in alpha cells, islets and in normal acinar cell. In contrast, in pancreatic cancer, strong lumican expression is observed in cancer cells [281, 287], fibroblasts and collagen fibers close to cancer cells [281]. The study described in this thesis is the first to demonstrate that lumican is expressed in human chronic pancreatitis with lumican staining observed in fibrotic areas and also in acinar cells. This concurs with a recent study reporting lumican positivity in pancreatic acinar cells and islet cells as well as in the chronic pancreatitis-like lesions adjacent to cancer tissue [287].

5.5 Summary

This Chapter has described for the first time the upregulation of transgelin, lumican and Fos in PSCs cultured on collagen I vs MatrigelTM and provided evidence 147

that the upregulation of transgelin and lumican was associated with the PSC activation process. Importantly, inhibition of transgelin expression in PSCs reduced stellate cell

“basal” proliferation on both activating and non-activating matrices. In chronic pancreatic tissue sections, transgelin was strongly expressed only in fibrotic areas and was absent in acinar cells, suggesting that transgelin could be used as a specific target to modulate PSC function and thereby influence fibrogenesis. On the other hand, lumican which was also highly expressed in chronic pancreatitis tissue sections was localised to both acinar cells and PSCs, limiting its use as a specific target for control of stellate cell function. Nonetheless, the biology of lumican in PSCs may be worthy of further study. 148

Chapter 6 - Summary and Conclusion

6.1 Background

Fibrosis is a characteristic feature of both alcohol induced chronic pancreatitis and pancreatic cancer. It is now well established that activated pancreatic stellate cells are the principal source of collagen in the fibrotic matrix of these conditions. While it is generally accepted that transformation of PSCs from a quiescent to a myofibroblast-like

(activated) phenotype is a central event in fibrogenesis, the mechanisms mediating the activation of PSCs are yet to be fully elucidated.

6.2 Summary of Present Work

The overall hypothesis for the studies described in this thesis was that alcohol induced pancreatic fibrosis is a result of excessive ECM synthesis by PSCs activated synergistically by alcohol and cytokines and that the composition of ECM, in turn, influences gene expression patterns of PSCs during the activation process.

Many of the cytokines released during pancreatic inflammation have been reported to activate PSCs individually. Potential sources of these activating factors are resident cells of the pancreas (e.g. acinar cells) and infiltrating inflammatory cells.

Notably, PSCs themselves can also synthesise these cytokines, which can have autocrine effects thereby perpetuating PSC activation. During episodes of alcohol– induced necroinflammation, PSCs are likely to be exposed not only to alcohol itself but also to several cytokines known to be upregulated at the same time. Therefore, ethanol and cytokines may exert a synergistic effect on PSC activation. Studies described in

Chapter 3 assessed this possibility. It was found that ethanol, IL-1 and TNFα at very low doses alone have negligible effects on PSC activation but the combination of 149

ethanol with IL-1 or TNFα (at the same low concentrations) activated PSCs.

Recognition of these effects suggests a role for PSCs in the development of pancreatic fibrosis particularly when exposed to a combination of ethanol and cytokines. It is important to note that the PSCs used in this study were preactivated by culture on uncoated plastic. The fact that the combination of low doses of ethanol with IL-1 and

TNFα could activate PSCs even further, suggests that, in vivo, PSCs activated during pancreatic injury by cellular stressors such as oxidant stress (induced by ethanol) may be capable of significant additional activation by cytokines released during pancreatic necroinflammation. Overall, this work suggests that an important mechanism mediating disease progression in alcoholic pancreatitis involves an enhanced response of PSCs when exposed simultaneously to synergistically activating factors, resulting in increased profibrogenic functions of the cells.

The ECM is known to contribute considerably to the progression of a wide range of diseases. Given the fact that the ECM composition is dramatically changed in chronic pancreatitis and pancreatic cancer, it was of interest to identify the influence of ECM proteins per se on PSC function. Chapter 4 of this thesis described in vitro studies using microarrays to delineate gene expression patterns of PSCs cultured on different matrices so as to mimic the in vivo situation. This work identified 146 genes that were significantly dysregulated in cells cultured on MatrigelTM vs cell cultured on collagen I

(fold change>2, p<0.001, FDR<0.25). This study supported the concept that the gene expression pattern of PSCs is influenced by ECM composition. Four of the most highly dysregulated genes were further validated at mRNA level (transgelin, lumican, Fos and

IL-1) and protein level (transgelin and lumican).

At the mRNA level, 3 genes (transgelin, lumican and FOS) were upregulated in

PSCs cultured on collagen I vs MatrigelTM, confirming the microarray results. 150

Furthermore, transgelin was also upregulated at the protein level, further supporting the notion that these factors were associated with the PSC activation process. These findings concurred well with the observation in human chronic pancreatitis tissue sections, where transgelin expression was specifically localised to fibrotic areas (and absent from acinar cells).

The lack of transgelin expression in acinar cells makes it an attractive molecule to target, in order to specifically modulate PSC function without affecting other cells.

The fact that siRNA studies inhibiting transgelin expression in PSCs demonstrated consequent inhibition of PSC activation, suggests that targeting transgelin may represent a useful approach in vivo to inhibit pancreatic fibrosis.

6.3 Conclusion

The work described in this thesis has provided evidence in support of the hypothesis that PSCs can be activated synergistically by alcohol and cytokines. In addition it has shown that the gene expression profile of PSCs is altered by ECM components during PSC activation. Furthermore, a possible molecular target specific for

PSCs in the diseased pancreas has been identified.

6.4 Future Studies

Several studies of interest might arise from the data presented in this thesis:

1. In the study of the synergistic effect of PSCs by ethanol and cytokines, only

a few cytokines alone or in combination with ethanol have been examined.

In the in vivo system, PSCs are exposed to a number of cytokines at the

same time. Therefore, future studies could include an analysis of the 151

combination of the effect of ethanol and several cytokines on PSC functions

(culture on plastic).

2. Microarray analysis of PSCs cultured on collagen I vs MatrigelTM yielded

146 dysregulated genes (Fold change>2, p<0.001, and FDR<0.25). This

study validated 4 highly dysregulated genes of interest. However, other

genes related to other cell functions (actin binding, oxidant stress) were also

found to be dysregulated and would be worthy of further study.

3. The upregulation of transgelin is associated with PSC activation as indicated

by increased expression at mRNA and protein level. In addition, it appears

that there is an additional transgelin homolog in the activated vs quiescent

PSCs. Evidence from other cell types, suggests that different transgelin

isoforms may have different functions in vivo [297]. Future studies to

further characterise transgelin homolog in quiescent and activated PSCs

would be useful.

4. Transgelin has been reported to play a role in cell proliferation, migration

and apoptosis by altered connection to actin filament bundles with a

consequent effect on the capability of cells for migration and attachment

[260]. Studies described in this thesis have shown that inhibition of

transgelin affects one PSC function i.e. proliferation; future studies could

characterise the role of transgelin in other PSC functions such as cell

adhesion, migration and apoptosis.

5. To investigate the effect of alcohol on transgelin expression by PSCs

cultured on different matrices. My preliminary results have shown that

alcohol (50mM), a known activator of PSCs, decreased transgelin mRNA

level when PSCs were cultured on MatrigelTM [p<0.05 vs CTRL (no alcohol) 152

medium, n=3 separate rat PSC preparations]. This could be because the

known inhibitory effect of MatrigelTM on PSC activation, prevented the cells

from responding to alcohol. With regard to the activating matrix collagen I,

alcohol (50mM) had no effect on transgelin expression. This was also an

unexpected finding. Since collagen and ethanol are both activating factors

for PSCs and the combination of the two factors would have been expected

to activate PSCs and therefore to increase transgelin expression. However,

these were preliminary studies and transgelin expression by PSCs needs to

be further investigated.

6. Lumican, Fos and IL-1 have also been shown to regulate cell functions,

such as migration and activation. Future studies could further characterise

the role of these genes in PSC function.

153

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180

Supplementary Data

Supplementary Table 1

Dysregulated Genes in the Comparison of Collagen vs Matrigel (FC>2, P<0.001, FDR<0.25)

Upregulated Genes ProbeSetID FC GeneSymbol Description 10917034 12.5171 Tagln transgelin 10719432 8.2915 Fosb FBJ osteosarcoma oncogene B similar to Cysteine-rich protein 1 10887622 6.1105 LOC691657 (Cysteine-rich intestinal protein) (CRIP) 10886031 5.0446 Fos FBJ osteosarcoma oncogene 10895083 5.0362 Lum Lumican 10876324 4.5395 Tpm2 tropomyosin 2 10849833 4.3025 Il1a Interleukin 1 alpha 10725778 4.1196 Nupr1 nuclear protein 1 10857655 3.833 Lmcd1 LIM and cysteine-rich domains 1 10734242 3.7265 Mfap4 microfibrillar-associated protein 4 10729096 3.7004 Psat1 phosphoserine aminotransferase 1 10747550 3.695 ------10857278 3.538 Fbln2 fibulin 2 sushi-repeat-containing protein, X- 10934865 3.4742 Srpx2 linked 2 nuclear receptor subfamily 4, group A, 10868940 3.4392 Nr4a3 member 3 10895747 3.0066 Avpr1a arginine vasopressin receptor 1A 10777788 2.9682 Spon2 spondin 2, extracellular matrix protein 10905179 2.9588 Apol9a apolipoprotein L 9a 10825328 2.9453 Phgdh 3-phosphoglycerate dehydrogenase 10891780 2.9453 Fbln5 fibulin 5 platelet-derived growth factor, D 10907845 2.9311 Pdgfd polypeptide solute carrier family 7 (cationic amino 10756393 2.8278 Slc7a1 acid transporter, y+ system), member 1 10909407 2.8216 Thy1 thymus cell antigen 1, theta 10805746 2.793 Cdh11 cadherin 11 nitric oxide synthase 2, inducible, 10736312 2.7801 Nos2 macrophage 181

10878112 2.6533 Jun Jun oncogene nuclear receptor subfamily 4, group A, 10845384 2.5468 Nr4a2 member 2 10876838 2.5111 Klf4 Kruppel-like factor 4 (gut) 10827809 2.4678 RT1-S3 RT1 class Ib, locus S3 cysteine-rich secretory protein LCCL 10808377 2.4564 Crispld2 domain containing 2 similar to Bifunctionalmethylenetetrahydrofolate 10870316 2.456 LOC680308 dehydrogenase/cyclohydrolase, mitochondrial precursor 10864715 2.4411 Vgll4 vestigial like 4 (Drosophila) 10860951 2.4164 Asns asparagine synthetase 10848281 2.4143 Grem1 gremlin 1 CD74 antigen (invariant polypeptide of 10802013 2.4132 Cd74 major histocompatibility complex, class II antigen-associated) 10776512 2.385 Rasl11b RAS-like family 11 member B 10749839 2.3808 Vgll3 vestigial like 3 (Drosophila) 10882168 2.3742 Mmp23 matrix metallopeptidase 23 RGD130993 10923381 2.3708 similar to 2810022L02Rik protein 0 10724967 2.3567 Dkk3 dickkopf homolog 3 (Xenopuslaevis) 10828146 2.3485 Ng23 Ng23 protein similar to Bifunctionalmethylenetetrahydrofolate 10863512 2.3329 LOC680308 dehydrogenase/cyclohydrolase, mitochondrial precursor 10841579 2.3204 Myl9 myosin, light chain 9, regulatory 10925291 2.306 Cxcr7 chemokine (C-X-C motif) receptor 7 10855185 2.3026 ------10869525 2.2964 ------cyclin-dependent kinase inhibitor 1C 10727056 2.2616 Cdkn1c (P57) phosphodiesterase 1A, calmodulin- 10846694 2.2474 Pde1a dependent translocation associated membrane 10818892 2.2468 Tram1l1 protein 1-like 1 10813107 2.2281 Esm1 endothelial cell-specific molecule 1 growth arrest and DNA-damage- 10900358 2.223 Gadd45b inducible 45 beta cytochrome P450, family 27, subfamily 10924411 2.222 Cyp27a1 a, polypeptide 1 10731047 2.2114 Ablim1 actin-binding LIM protein 1 10924507 2.2107 Des desmin 10873639 2.2098 Mfap2 microfibrillar-associated protein 2 10782271 2.2012 Plau plasminogen activator, urokinase 10851263 2.2004 Samhd1 SAM domain and HD domain, 1 10782187 2.1986 Itgbl1 integrin, beta-like 1 182

cytochrome c oxidase subunit VIb 10703970 2.1979 Cox6b2 polypeptide 2 10874728 2.1932 Mxra8 matrix-remodelling associated 8 DEAD (Asp-Glu-Ala-Asp) box 10793999 2.1932 Ddx41 polypeptide 41 10755644 2.1599 Scarf2 scavenger receptor class F, member 2 10781378 2.1503 Hr hairless C1q and tumor necrosis factor related 10732889 2.1473 C1qtnf2 protein 2 10775731 2.1394 Cxcl13 chemokine (C-X-C motif) ligand 13 10859799 2.1273 Il6 interleukin 6 10723822 2.0934 Tsku tsukushin 10741330 2.048 Tmem204 transmembrane protein 204 10897760 2.0472 Atf4 activating transcription factor 4 ST3 beta-galactoside alpha-2,3- 10916016 2.0294 St3gal4 sialyltransferase 4

Downregulated Genes ProbeSetID absFC GeneSymbol Description 10811177 13.2931 Ctrb1 chymotrypsinogen B1 10745931 11.5512 ------10814286 9.3497 Fabp4 fatty acid binding protein 4, adipocyte 10854327 7.9679 Cpa1 carboxypeptidase A1 10909382 7.5697 Vof16 ischemia related factor vof-16 solute carrier family 7 (cationic amino 10823057 7.486 Slc7a11 acid transporter, y+ system), member 11 10930564 6.9185 ------10940473 6.1853 ------glycerol-3-phosphate dehydrogenase 1 10899187 5.9207 Gpd1 (soluble) 10930580 5.6407 ------10728028 5.0237 ------10790023 4.9888 ------10922843 4.67 ------10930593 4.4452 ------phospholipase A2, group VII (platelet- 10926683 4.3817 Pla2g7 activating factor acetylhydrolase, plasma) 10800214 4.3341 ------10910762 4.2314 ------10859547 4.2278 Iapp islet amyloid polypeptide proproteinconvertasesubtilisin/kexin 10840332 4.1849 Pcsk2 type 2 10881669 3.9817 Cort cortistatin 10929263 3.8619 Scg2 secretogranin II 183

10802710 3.5099 ------10936959 3.4936 Slc38a5 solute carrier family 38, member 5 10702293 3.2863 ------10796230 3.2707 ------10868881 3.2019 Col15a1 collagen, type XV, alpha 1 10930560 3.1928 ------10911797 3.1308 Gsta4 glutathione S-transferase, alpha 4 10918738 2.9498 Scg3 secretogranin III 10736413 2.9243 ------10865696 2.9153 ------10727640 2.7727 ------10709880 2.7602 Ampd3 adenosine monophosphate deaminase 3 10805225 2.71 ------cellular repressor of E1A-stimulated 10765335 2.7052 Creg1 genes 1 10864773 2.7016 ------10892704 2.7016 ------10910770 2.6658 ------proteoglycan 4, (megakaryocyte stimulating factor, articular superficial 10768412 2.6568 Prg4 zone protein, camptodactyly, arthropathy, coxavara, pericarditis syndrome) uncoupling protein 2 (mitochondrial, 10709093 2.6182 Ucp2 proton carrier) 10733047 2.596 ------10733045 2.5762 ------ATP-binding cassette, sub-family C 10785826 2.5453 Abcc4 (CFTR/MRP), member 4 10830367 2.5285 ------RGD135952 similar to chromosome 1 open reading 10872829 2.5091 9 frame 63 EP300 interacting inhibitor of 10901436 2.5039 Eid3 differentiation 3 homeodomain interacting protein kinase 10861997 2.5024 Hipk2 2 10765036 2.4712 ------10839868 2.4694 ------10746483 2.4485 Itga3 integrin alpha 3 10834598 2.4074 ------10805227 2.3892 ------10862453 2.381 ------peroxisome proliferator activated 10857984 2.3592 Pparg receptor gamma 10727429 2.3373 Gstp1 glutathione-S-transferase, pi 1 10810152 2.3163 ------ATP-binding cassette, sub-family C 10785846 2.3142 Abcc4 (CFTR/MRP), member 4 10765109 2.3047 ------184

10930595 2.292 ------ATPase, aminophospholipid transporter 10772582 2.2835 Atp8a1 (APLT), class I, type 8A, member 1 10720531 2.2428 ------10796989 2.2381 ------10762224 2.227 ------CCAAT/enhancer binding protein 10706131 2.2162 Cebpa (C/EBP), alpha 10908102 2.2075 ------10930620 2.2062 ------oligonucleotide/oligosaccharide-binding 10923270 2.1967 Obfc2a fold containing 2A 10908106 2.1714 ------10777176 2.1484 ------10802708 2.1479 ------RGD130861 10879221 2.1199 similar to KIAA0467 protein 6 10802706 2.1189 ------10930598 2.0858 ND5 NADH dehydrogenase subunit 5 10802541 2.0798 ------similar to paired immunoglobin-like 10760920 2.0185 LOC681182 type 2 receptor beta pyruvate dehydrogenase kinase, 10860900 2.0151 Pdk4 isoenzyme 4

185

Supplementary Table 2

Dysregulated Genes in the Comparison of Plastic vs Matrigel (FC>2, P<0.001, FDR<0.25) Upregulated Genes ProbeSetI FC GeneSymbol Description D 10767388 20.3648 Cd55 CD55 antigen 10767605 7.8245 Cntn2 contactin 2 10749839 8.3657 Vgll3 vestigial like 3 (Drosophila) 10797949 6.8447 Bmp6 bone morphogenetic protein 6 10753982 9.0595 Ccdc80 coiled-coil domain containing 80 10777788 8.0999 Spon2 spondin 2, extracellular matrix protein 10782187 6.53 Itgbl1 integrin, beta-like 1 potassium voltage gated channel, Shal- 10818141 12.2323 Kcnd3 related family, member 3 similar to Cysteine-rich protein 1 10887622 6.135 LOC691657 (Cysteine-rich intestinal protein) (CRIP) 10728912 8.7353 ------10873814 5.9835 ------10925291 8.6743 Cxcr7 chemokine (C-X-C motif) receptor 7 10924507 3.8261 Des desmin 10923381 4.5531 RGD1309930 similar to 2810022L02Rik protein 10708834 3.2108 Pak1 p21 (CDKN1A)-activated kinase 1 10917034 11.7547 Tagln transgelin 10811906 2.9916 RGD1559896 similar to RIKEN cDNA 2310022B05 growth arrest and DNA-damage- 10900358 4.0068 Gadd45b inducible 45 beta sema domain, immunoglobulin domain 10860499 3.6907 Sema3d (Ig), short basic domain, secreted, (semaphorin) 3D 10851350 7.2293 Tgm2 transglutaminase 2, C polypeptide tumor necrosis factor receptor 10903725 4.4481 Tnfrsf11b superfamily, member 11b (osteoprotegerin) 10823903 4.8286 Gucy1b3 guanylatecyclase 1, soluble, beta 3 10876324 5.3134 Tpm2 tropomyosin 2 10857278 3.1015 Fbln2 fibulin 2 meteorin, glial cell differentiation 10931247 4.3761 Metrnl regulator-like serine (or cysteine) peptidase inhibitor, 10798135 2.3918 Serpinb9 clade B, member 9 186

similar to Neurogenic locus notch 10754592 3.8072 RGD1564641 homolog protein 2 precursor (Notch 2) (hN2) 10922857 17.0248 Il1rl1 interleukin 1 receptor-like 1 10734382 2.5175 Pmp22 peripheral myelin protein 22 WNT1 inducible signaling pathway 10842043 2.6106 Wisp2 protein 2 10713844 2.6845 Fads3 fatty acid desaturase 3 RGD1560177 similar to RIKEN cDNA 2810489O06 10815321 2.7223 _predicted (predicted) 10731047 3.1286 Ablim1 actin-binding LIM protein 1 cyclin-dependent kinase inhibitor 1C 10727056 2.3588 Cdkn1c (P57) 10818708 29.2263 F3 coagulation factor III 10741330 2.3246 Tmem204 transmembrane protein 204 10776710 3.9927 RGD1305269 similar to hypothetical protein similar to ABI gene family, member 3 10753629 4.8244 RGD1562717 (NESH) binding protein phospholipase A2, group IIA (platelets, 10873341 2.2319 Pla2g2a synovial fluid) 10895747 7.9236 Avpr1a arginine vasopressin receptor 1A hydroxysteroid 11-beta dehydrogenase 10770795 2.2638 Hsd11b1 1 cytidine monophosphate (UMP-CMP) 10883960 3.034 Cmpk2 kinase 2, mitochondrial heat shock protein family, member 7 10873732 6.9656 Hspb7 (cardiovascular) S100 calcium binding protein A6 10817065 3.1008 S100a6 (calcyclin) 10743961 3.5333 RGD1561781 similar to RIKEN cDNA 2600017H02 10853816 2.4432 Cav1 caveolin, caveolae protein 1 10939725 2.7306 Hs6st2 heparan sulfate 6-O-sulfotransferase 2 10742348 2.1324 Irgm immunity-related GTPase family, M 10770082 2.3768 Ifi204 interferon activated gene 204 10910336 3.9822 Rpp25 ribonuclease P 25 subunit (human) similar to putative protein, with at least 10889027 2.0455 RGD1309228 9 transmembrane domains, of eukaryotic origin (43.9 kD) (2G415) 10771655 2.8447 Cxcl10 chemokine (C-X-C motif) ligand 10 similar to neuroblastoma-amplified 10883651 2.6136 LOC690073 protein insulin-like growth factor binding 10899465 5.3357 Igfbp6 protein 6 interferon-induced protein with 10729791 3.9655 Ifit1lb tetratricopeptide repeats 1-like B 10749325 2.6964 Cygb cytoglobin 10770471 2.1872 Disp1 dispatched homolog 1 (Drosophila) 10797648 5.9212 Ogn osteoglycin 10909407 3.5677 Thy1 thymus cell antigen 1, theta 187

10717295 6.9656 Vnn1 vanin 1 La ribonucleoprotein domain family, 10910612 3.2126 Larp6 member 6 10896541 3.6356 Nov nephroblastoma overexpressed gene similar to G protein-coupled receptor 10761446 20.6804 LOC687426 133 10918075 2.5806 Coro2b coronin, actin binding protein, 2B 10825328 3.0402 Phgdh 3-phosphoglycerate dehydrogenase 10938485 2.3141 Fam123b family with sequence similarity 123B 10862634 3.5989 Scrn1 secernin 1 10906926 4.5798 Rnd1 Rho family GTPase 1 similar to Nuclear membrane binding 10910619 2.6155 RGD1560011 protein NUCLING 10876838 5.0013 Klf4 Kruppel-like factor 4 (gut) 10745292 13.2701 Lgals9 lectin, galactose binding, soluble 9 10940688 5.09 ------10764221 2.0563 Csrp1 cysteine and glycine-rich protein 1 G protein-coupled receptor, family C, 10859277 2.5272 Gprc5a group 5, member A insulin-like growth factor binding 10778390 5.1097 Igfbp3 protein 3 aldehyde dehydrogenase family 1, 10911380 5.5529 Aldh1a2 subfamily A2 10797857 11.4782 Edn1 endothelin 1 10918600 3.5698 Cgnl1 cingulin-like 1 10799684 6.6516 RGD1564327 similar to integrin alpha 8 10773435 4.2243 Cpz carboxypeptidase Z 10707597 2.4171 Atp10a ATPase, class V, type 10A 10791552 3.0397 Gpm6a glycoprotein m6a mannosideacetylglucosaminyltransferas 10733069 2.8115 Mgat1 e 1 latent transforming growth factor beta 10888424 2.237 Ltbp1 binding protein 1 10802023 7.3515 Arsi arylsulfatasei 10912584 2.6973 Amotl2 angiomotin like 2 10749983 5.959 Cxadr coxsackie virus and adenovirus receptor 10915648 2.5863 Rab3d RAB3D, member RAS oncogene family polymerase I and transcript release 10747531 2.4664 Ptrf factor 10859494 3.1805 Pde3a phosphodiesterase 3A, cGMP inhibited 10891303 3.6949 Tgfb3 transforming growth factor, beta 3 10927692 2.643 Fhl2 four and a half LIM domains 2 10815176 3.5417 Phf17 PHD finger protein 17 10801975 3.9207 MGC108823 similar to interferon-inducible GTPase 10896263 3.7895 Cthrc1 collagen triple helix repeat containing 1 10851263 2.7298 Samhd1 SAM domain and HD domain, 1 10708665 5.9987 Rab30 RAB30, member RAS oncogene family 10819489 4.9421 Gbp5 guanylate nucleotide binding protein 5 10819644 8.7479 Ddah1 dimethylargininedimethylaminohydrola 188

se 1 Ral GEF with PH domain and SH3 10769016 2.757 Ralgps2 binding motif 2 10708896 2.5754 Garp glycoprotein A repetitions predominant 10897096 2.5497 Gsdmd gasdermin D 10851947 2.8483 Ptgis prostaglandin I2 (prostacyclin) synthase 10753425 6.8968 Mx1 myxovirus (influenza virus) resistance 1 10909892 14.4717 Cryab crystallin, alpha B brain abundant, membrane attached 10822075 2.8695 Basp1 signal protein 1 von Willebrand factor A domain 10882159 2.2033 Vwa1 containing 1 10770109 3.5958 RGD1562462 similar to Ifi204 protein 10770577 2.4122 Tgfb2 transforming growth factor, beta 2 10861242 4.484 Aass aminoadipate-semialdehyde synthase 10940656 2.0372 ------platelet-derived growth factor, D 10907845 3.3345 Pdgfd polypeptide 10798646 2.2627 Amph amphiphysin 10747550 3.1393 ------similar to 10852636 2.0795 LOC691966 Sulfide:quinoneoxidoreductase, mitochondrial precursor Rho-associated coiled-coil containing 10883726 2.0317 Rock2 protein kinase 2 interferon-induced protein with 10714903 5.4059 Ifit3 tetratricopeptiderepeats 3 10800166 2.0263 Gata6 GATA binding protein 6 10723383 6.9049 RGD1305254 similar to transmembrane protein 2 interferon-induced protein with 10714907 8.1069 Ifit1 tetratricopeptide repeats 1 10767095 3.0109 Inhbb inhibin beta-B 10725778 2.7073 Nupr1 nuclear protein 1 10787841 2.2884 Sc4mol sterol-C4-methyl oxidase-like poly (ADP-ribose) polymerase family, 10754426 2.3894 Parp9 member 9 10813107 2.0976 Esm1 endothelial cell-specific molecule 1 Tax1 (human T-cell leukemia virus type 10855576 2.1105 Tax1bp1 I) binding protein 1 10815049 4.1147 Spry1 sprouty homolog 1 (Drosophila) 10932773 2.6579 Chrdl1 kohjirin 10940611 3.7841 ------10818715 2.3337 Arhgap29 Rho GTPase activating protein 29 10905179 3.2355 Apol9a apolipoprotein L 9a family with sequence similarity 20, 10760738 3.0228 Fam20c member C C1q and tumor necrosis factor related 10732889 2.049 C1qtnf2 protein 2 10937725 2.4678 Figf c-fos induced growth factor 189

10939472 2.6887 Ripply1 ripply1 homolog (zebrafish) 10904543 5.6514 ------10858499 3.1097 Mfap5 microfibrillar associated protein 5 10907211 2.1586 Lima1 LIM domain and actin binding 1 UDP-N-acetyl-alpha-D- 10885628 3.5599 Galntl1 galactosamine:polypeptide N- acetylgalactosaminyltransferase-like 1 10781829 2.9278 Klf5 Kruppel-like factor 5 similar to Colorectal mutant cancer 10804316 2.2283 RGD1561988 protein (MCC protein) 10885299 3.5286 Rhoj ras homolog gene family, member J 10770070 3.9609 Cadm3 cell adhesion molecule 3 interferon, alpha-inducible protein 10882317 6.7213 G1p2 (clone IFI-15K) 10762247 3.596 Oas1b 2-5 oligoadenylatesynthetase 1B 10887615 3.7349 Crip2 cysteine-rich protein 2 10738522 2.3507 Nags N-acetylglutamate synthase 10709788 2.1514 RGD1306959 similar to C11orf17 protein 10854239 2.4195 LOC500066 similar to Protein FAM40B 10937241 3.9687 RGD1563606 similar to cysteine-rich protein 2 10817552 2.2601 Txnip thioredoxin interacting protein 10940690 2.4599 ------a disintegrin-like and metallopeptidase 10752852 8.1301 Adamts5 (reprolysin type) with thrombospondin type 1 motif, 5 (aggrecanase-2) 10882168 2.8126 Mmp23 matrix metallopeptidase 23 10729096 2.8524 Psat1 phosphoserine aminotransferase 1 activated leukocyte cell adhesion 10750878 4.0111 Alcam molecule 10937254 2.1411 Pls3 plastin 3 (T-isoform) 10775628 5.3412 Anxa3 annexin A3 10726758 4.7834 Irf7 interferon regulatory factor 7 10774274 2.59 Egfr epidermal growth factor receptor solute carrier family 1 10778620 2.0756 Slc1a4 (glutamate/neutral amino acid transporter), member 4 receptor (calcitonin) activity modifying 10774115 5.0523 Ramp3 protein 3 10732644 13.8096 Stc2 stanniocalcin 2 10891910 7.3831 isg12(b) putative ISG12(b) protein 10824892 12.3847 Selenbp1 selenium binding protein 1 10914546 6.1682 ------peptidylprolylisomerase (cyclophilin)- 10701734 2.1831 Ppil4 like 4 10932066 2.2895 Klhl13 kelch-like 13 (Drosophila) 10838242 2.2165 Wt1 Wilms tumor 1 10775769 2.0456 Sept11 septin 11 10819523 2.2141 Gbp2 guanylate nucleotide binding protein 2 10855185 2.1864 ------190

10767243 2.5612 Lypd1 Ly6/Plaur domain containing 1 10723576 11.2207 Prss23 protease, serine, 23 10935555 3.9161 Fhl1 four and a half LIM domains 1 10752630 2.5434 Epha3 Eph receptor A3 10750524 9.7712 Mx2 myxovirus (influenza virus) resistance 2 10754000 3.1604 Cd200r1 CD200 receptor 1 10734242 2.4792 Mfap4 microfibrillar-associated protein 4 10728631 2.6918 Fads2 fatty acid desaturase 2 discoidin domain receptor family, 10827916 4.0749 Ddr1 member 1 10747330 2.506 Jup junction plakoglobin DEXH (Asp-Glu-X-His) box 10747426 2.1619 Dhx58 polypeptide 58 10880074 3.7331 Tinagl1 tubulointerstitial nephritis antigen-like 1 10707707 2.8089 Mtmr10 myotubularin related protein 10 cytochrome P450, family 27, subfamily 10924411 2.4391 Cyp27a1 a, polypeptide 1 10708591 2.0306 Sytl2 synaptotagmin-like 2 epidermal growth factor-containing 10774638 2.2174 Efemp1 fibulin-like extracellular matrix protein 1 solute carrier family 9 10741189 2.8723 Slc9a3r2 (sodium/hydrogen exchanger), member 3 regulator 2 angiogenin, ribonuclease A family, 10779835 2.3133 Ang1 member 1 radical S-adenosyl methionine domain 10889399 4.4033 Rsad2 containing 2 CDC42 effector protein (Rho GTPase 10887939 2.4075 Cdc42ep3 binding) 3 10841579 2.632 Myl9 myosin, light chain 9, regulatory sarcoglycan, gamma (dystrophin- 10784346 2.9693 Sgcg associated glycoprotein) 10790811 4.177 Bst2 bone marrow stromal cell antigen 2 Ras association (RalGDS/AF-6) domain 10859636 2.0678 Rassf8 family (N-terminal) member 8 ST3 beta-galactoside alpha-2,3- 10750672 3.9557 St3gal6 sialyltransferase 6 ribonuclease, RNase A family, 1-like 2 10779843 3.0524 Rnase1l2 (pancreatic) 10849260 8.7692 Duoxa1 dual oxidase maturation factor 1 10915923 4.2294 Hnt neurotrimin glucose-fructose oxidoreductase domain 10794573 2.3586 Gfod1 containing 1 sema domain, immunoglobulin domain 10860327 2.4835 Sema3c (Ig), short basic domain, secreted, (semaphorin) 3C 10791565 3.187 Vegfc vascular endothelial growth factor C 10712997 4.6191 Cd248 CD248 molecule, endosialin 191

tumor necrosis factor (ligand) 10793038 2.8195 Tnfsf13b superfamily, member 13b family with sequence similarity 26, 10830264 3.5931 Fam26e member E 10827809 2.8381 RT1-S3 RT1 class Ib, locus S3 10919537 2.5974 Il20rb interleukin 20 receptor beta 10894552 3.4155 Nuak1 NUAK family, SNF1-like kinase, 1 cytochrome P450, subfamily 11B, 10904553 8.8048 Cyp11b1 polypeptide 1 10801973 2.5126 RGD1309362 similar to interferon-inducible GTPase 10939744 2.1483 Gpc4 glypican 4 10829993 2.5067 MGC112715 hypothetical protein LOC690899 10729673 3.7248 Prkg1 protein kinase, cGMP-dependent, type 1 10758771 2.5764 Oas1i 2 ' -5 ' oligoadenylatesynthetase 1I 10922489 4.6758 Hs6st1 heparan sulfate 6-O-sulfotransferase 1 wingless-related MMTV integration site 10873021 7.0483 Wnt4 4 dehydrogenase/reductase (SDR family) 10873838 2.096 Dhrs3 member 3 10860812 2.3464 RGD1561472 similar to mKIAA2005 protein sterile alpha motif domain containing 9- 10860806 2.3464 Samd9l like sterile alpha motif domain containing 9- 10860809 2.3464 Samd9l like similar to Colorectal mutant cancer 10804319 2.2641 RGD1561988 protein (MCC protein) 10717069 2.1475 Pde7b phosphodiesterase 7B 10860801 3.6111 RGD1563091 similar to OEF2 10861986 2.3075 Insig1 insulin induced gene 1 10881256 2.0127 LOC313672 similar to CG11206-PA nuclear receptor subfamily 4, group A, 10868940 2.5026 Nr4a3 member 3 interferon induced transmembrane 10712171 2.7569 Ifitm1 protein 1 solute carrier family 7 (cationic amino 10756393 2.0839 Slc7a1 acid transporter, y+ system), member 1 10798194 6.0151 Agtr1a angiotensin II receptor, type 1a 10868595 2.5876 ------10858370 4.2129 Usp18 ubiquitin specific peptidase 18 10762740 2.3904 Oasl1 2'-5' oligoadenylatesynthetase-like 1 10877069 2.4072 Lpar1 lysophosphatidic acid receptor 1 10758777 4.2518 Oas1a 2'-5' oligoadenylatesynthetase 1A PTPRF interacting protein, binding 10859693 2.1329 Ppfibp1 protein 1 (liprin beta 1) 10709687 2.3562 Olfml1 olfactomedin-like 1 10784355 2.0592 Ebpl emopamil binding protein-like 10918869 2.6435 Col12a1 collagen, type XII, alpha 1 10882534 2.2794 RGD1311939 similar to AI115348 protein 10848281 2.4138 Grem1 gremlin 1 192

similar to 10839320 3.2047 LOC691966 Sulfide:quinoneoxidoreductase, mitochondrial precursor 10808959 2.0518 Nrp1 neuropilin 1 X Kell blood group precursor related X 10939260 2.2099 Xkrx linked 10891780 3.0129 Fbln5 fibulin 5 10859117 2.1178 ------10759989 8.0919 RGD1307396 similar to RIKEN cDNA 6330406I15 10775484 2.1397 Arhgap24 Rho GTPase activating protein 24 10733056 2.0671 Ifi47 interferon gamma inducible protein 47 a disintegrin-like and metallopeptidase 10752839 4.0154 Adamts1 (reprolysin type) with thrombospondin type 1 motif, 1 10897054 2.0192 Ly6e lymphocyte antigen 6 complex, locus E interferon induced with helicase C 10845708 2.1126 Ifih1 domain 1 10907834 2.0924 Casp12 caspase 12 10726991 5.4932 ------signal transducer and activator of 10893067 2.698 Stat2 transcription 2 proline arginine-rich end leucine-rich 10767763 2.3591 Prelp repeat protein sterile alpha motif domain containing 9- 10860815 2.8861 Samd9l like 10846781 2.351 Tfpi tissue factor pathway inhibitor RAS-like, estrogen-regulated, growth- 10866535 2.2547 Rerg inhibitor 10912412 2.1429 Tfdp2 transcription factor Dp 2 10817057 3.039 S100a4 S100 calcium-binding protein A4 10779832 2.4132 Rnase4 ribonuclease, RNase A family 4 10787856 2.6103 Tll1 tolloid-like 1 10840773 2.7468 Angpt4 angiopoietin 4 similar to hypothetical protein 10789727 2.2477 RGD1306164 FLJ90798 10762747 2.2309 Oasl2 2'-5' oligoadenylatesynthetase-like 2 10930428 2.2339 Emilin2 elastin microfibrilinterfacer 2 10821989 5.2569 ------10771406 3.6478 Plac8 placenta-specific 8 10792421 2.1641 Plat plasminogen activator, tissue collagen and calcium binding EGF 10802338 2.2434 Ccbe1 domains 1 10839268 10.4031 Duox1 dual oxidase 1 10873027 4.3291 ------10766869 2.9309 Cd34 CD34 molecule oxidized low density lipoprotein (lectin- 10866030 5.2793 Olr1 like) receptor 1 10827820 2.006 RT1-149 RT1-149 protein 10785895 2.0318 ------193

10821698 2.0443 Osmr oncostatin M receptor 10913095 2.1111 Ube1l ubiquitin-activating enzyme E1-like 10813253 4.8871 C6 complement component 6 10857783 3.8812 Il17re interleukin 17 receptor E similar to DNA segment, Chr 4, 10869656 2.749 RGD1308059 Brigham &Womens Genetics 0951 expressed 10783583 2.6861 Jub ajuba 10917883 3.5252 Loxl1 lysyl oxidase-like 1 10859880 2.2363 Insig1 insulin induced gene 1 10763604 4.0952 Gpr39 G protein-coupled receptor 39 cystathionase (cystathionine gamma- 10827517 2.4338 Cth lyase) 10777748 3.7374 Fgfr3 fibroblast growth factor receptor 3 10792344 20.3346 Sfrp1 secreted frizzled-related protein 1 10709875 2.946 Adm adrenomedullin 10901401 2.1243 ------similar to Glutaminyl-peptide 10882461 4.6493 RGD1562284 cyclotransferase precursor (QC) 10813048 2.2815 Ppap2a phosphatidic acid phosphatase 2a 10801761 2.0717 Prdm6 PR domain containing 6 10828162 2.6065 C2 complement component 2 10870481 2.0097 Ppap2b phosphatidic acid phosphatase type 2B coagulation factor II (thrombin) 10820586 2.399 F2r receptor

Downregulated Genes ProbeSetI absFC GeneSymbol Description D 10940473 8.7768 ------10850480 5.7202 RGD1308023 similar to CG5521-PA 10800214 10.1122 ------10714353 4.5026 Tmem2 transmembrane protein 2 10750505 9.9936 Pcp4 Purkinje cell protein 4 10743227 11.0512 Rasd1 RAS, dexamethasone-induced 1 10801967 3.9435 Chsy3 chondroitin sulfate synthase 3 10877907 3.4035 Adfp adipose differentiation related protein glycerol-3-phosphate dehydrogenase 1 10899187 6.7089 Gpd1 (soluble) 10864797 3.92 Plxnd1 plexin D1 SHC (Src homology 2 domain 10849423 7.8274 Shc4 containing) family, member 4 10850494 5.321 RGD1308023 similar to CG5521-PA 10773853 8.2484 Lif leukemia inhibitory factor 10850488 6.9351 RGD1308023 similar to CG5521-PA 10851587 4.811 Matn4 matrilin 4 10910762 4.7629 ------10772194 2.7776 Hopx HOP homeobox 194

FAT tumor suppressor homolog 4 10815057 2.4073 Fat4 (Drosophila) solute carrier family 6 (neurotransmitter 10857314 2.2085 Slc6a6 transporter, taurine), member 6 10805227 3.1091 ------10880159 2.5334 ------10880161 2.5334 ------10886942 4.3544 ------10764551 6.998 Ptgs2 prostaglandin-endoperoxide synthase 2 10727260 4.4092 Ccnd1 cyclin D1 10886948 4.3857 ------10886972 4.3857 ------10886914 4.3857 ------10901409 2.1878 Chst11 carbohydrate sulfotransferase 11 trichorhinophalangeal syndrome I 10903676 2.3886 Trps1 (human) 10728028 4.8917 ------ATPase, aminophospholipid transporter 10772582 4.0383 Atp8a1 (APLT), class I, type 8A, member 1 10887000 4.4145 ------uncoupling protein 2 (mitochondrial, 10709093 2.5092 Ucp2 proton carrier) 10802734 2.6249 Smad7 MAD homolog 7 (Drosophila) 10802710 3.4825 ------10886978 4.3487 ------10886902 4.3487 ------10886946 4.4486 ------10859547 7.9856 Iapp islet amyloid polypeptide similar to Hypothetical protein 10766080 2.8349 RGD1560022 4832420M10 10762378 2.593 Tbx3 T-box 3 10886944 4.2517 ------tumor protein p53 inducible nuclear 10841339 2.9503 Trp53inp2 protein 2 10886932 4.4747 ------10886982 4.4747 ------10886952 4.4747 ------10886998 4.4747 ------10886906 4.4747 ------10886924 4.4747 ------10886962 4.4747 ------10886872 4.4747 ------10886912 4.4747 ------10886908 4.4747 ------10886926 4.4747 ------10886976 4.4747 ------10886918 4.4747 ------10886954 4.4747 ------10886878 4.4747 ------195

10886970 4.4747 ------10886968 4.4747 ------10886936 4.4747 ------serine (or cysteine) peptidase inhibitor, 10929288 3.4211 Serpine2 clade E, member 2 phospholipase A2, group IVA 10768376 2.1096 Pla2g4a (cytosolic, calcium-dependent) potassium voltage-gated channel, 10766782 4.8704 Kcnh1 subfamily H (eag-related), member 1 10830367 3.9001 ------pleckstrin homology-like domain, 10895406 3.6082 Phlda1 family A, member 1 10860351 4.9397 Hgf hepatocyte growth factor 10850490 6.9376 RGD1308023 similar to CG5521-PA 10796564 2.7054 Plxdc2 plexin domain containing 2 10940654 6.2799 ------10780908 2.2382 Sacs sacsin 10712657 4.196 Cpt1a carnitinepalmitoyltransferase 1a, liver 10886964 4.3288 ------10800919 3.625 Egr1 early growth response 1 ATP-binding cassette, sub-family C 10785826 2.4232 Abcc4 (CFTR/MRP), member 4 10847735 2.9648 RGD1309969 similar to RIKEN cDNA 2600010E01 10746172 2.7434 Nog noggin 10817711 2.1332 Notch2 notch gene homolog 2 (Drosophila) 10850484 4.8036 RGD1308023 similar to CG5521-PA 10886882 4.272 ------aldo-ketoreductase family 1, member 10854406 2.7097 Akr1b8 B8 10831077 2.85 Ier3 immediate early response 3 similar to Hypothetical protein 10766082 2.4934 RGD1560022 4832420M10 phospholipase A2, group VII (platelet- 10926683 4.5263 Pla2g7 activating factor acetylhydrolase, plasma) 10907881 12.5797 Mmp3 matrix metallopeptidase 3 10705213 4.3905 Tgfb1 transforming growth factor, beta 1 10813128 2.65 ------10850459 5.2987 RGD1308023 similar to CG5521-PA 10805225 3.8574 ------ATP-binding cassette, sub-family C 10785846 2.1972 Abcc4 (CFTR/MRP), member 4 10749892 2.2415 Robo1 roundabout homolog 1 (Drosophila) 10753737 2.0699 ------10736413 2.5394 ------10798169 9.3122 Foxq1 forkhead box Q1 10784896 3.7321 Slc25a37 solute carrier family 25, member 37 phytanoyl-CoA hydroxylase interacting 10829738 4.0337 Phyhipl protein-like 196

10850478 5.9712 RGD1308023 similar to CG5521-PA similar to chromosome 1 open reading 10872829 2.3501 RGD1359529 frame 63 10777176 2.3565 ------10850492 5.0597 RGD1308023 similar to CG5521-PA 10895144 2.5868 Dusp6 dual specificity phosphatase 6 10859086 3.062 LOC689790 similar to osteoclast inhibitory lectin low density lipoprotein receptor-related 10837881 2.0597 Lrp4 protein 4 10909358 2.1894 ------10745931 4.4036 ------10733045 3.0535 ------10922843 4.9046 ------prostate transmembrane protein, 10852144 4.247 Pmepa1 androgen induced 1 10812524 2.1587 Arsb arylsulfatase B 10716712 2.0598 Stxbp5 syntaxin binding protein 5 (tomosyn) 10749307 2.3119 Rhbdf2 rhomboid 5 homolog 2 (Drosophila) similar to TBC1 domain family, 10810341 2.3874 RGD1308221 member 8 (with GRAM domain); vascular Rab-GAP/TBC-containing 10886960 4.018 ------10886928 4.018 ------10864773 2.647 ------10892704 2.647 ------10810150 2.5157 ------10834598 2.554 ------10724542 3.0232 Dchs1 dachsous 1 (Drosophila) EP300 interacting inhibitor of 10901436 3.3859 Eid3 differentiation 3 pyruvate dehydrogenase kinase, 10860900 2.8116 Pdk4 isoenzyme 4 10866512 3.4775 Mgp matrix Gla protein 10727640 2.6521 ------10803276 2.1042 Zfp521 zinc finger protein 521 10798163 2.678 LOC364707 similar to forkhead box F2 10844223 2.4904 Ptges prostaglandin E synthase 10775338 2.3379 Pkd2 polycystic kidney disease 2 10891679 9.1086 Gpr68 G protein-coupled receptor 68 nuclear factor of kappa light 10750848 2.2762 Nfkbiz polypeptide gene enhancer in B-cells inhibitor, zeta 10802706 2.0837 ------10929725 4.0385 Arl4c ADP-ribosylation factor-like 4C Rho, GDP dissociation inhibitor (GDI) 10866526 4.1417 Arhgdib beta 10811999 2.0018 ------10810152 3.5114 ------10737429 3.1443 Mmd monocyte to macrophage 197

differentiation-associated 10727429 3.2884 Gstp1 glutathione-S-transferase, pi 1 10927633 2.5665 Rnf149 ring finger protein 149 10716746 3.2893 RGD1564259 similar to OTTHUMP00000040155 10814430 3.4759 Cp ceruloplasmin ATP-binding cassette, sub-family D 10906428 2.1264 Abcd2 (ALD), member 2 10810236 2.1671 Lphn1 latrophilin 1 10886986 4.1006 ------10887004 4.1006 ------B-cell translocation gene 2, anti- 10767767 3.179 Btg2 proliferative peroxisome proliferator activated 10857984 2.9974 Pparg receptor gamma similar to Elongation factor 1-gamma 10766078 2.0059 LOC364063 (EF-1-gamma) (eEF-1B gamma) colony stimulating factor 3 10738051 8.9534 Csf3 (granulocyte) 10850486 5.05 RGD1308023 similar to CG5521-PA 10804125 2.9983 Spry4 sprouty homolog 4 (Drosophila) 10814286 9.8273 Fabp4 fatty acid binding protein 4, adipocyte 10720531 2.1938 ------10886892 3.8677 ------10886966 3.8677 ------10886956 3.8677 ------10886916 3.8677 ------10887012 3.8677 ------10886992 3.8677 ------10886904 3.8677 ------10886934 3.8677 ------10886950 3.8677 ------10887006 3.8677 ------10886940 3.8677 ------10886990 3.8677 ------10886980 3.8677 ------10886996 3.8677 ------10886984 3.8677 ------10886910 3.8677 ------10886922 3.8677 ------10887002 3.8677 ------ectonucleotidepyrophosphatase/phosph 10903736 2.3884 Enpp2 odiesterase 2 10859857 2.2863 ------10733047 3.1933 ------10706750 2.0618 Tead2 TEA domain family member 2 10886888 3.6519 ------10930598 2.2859 ND5 NADH dehydrogenase subunit 5 10802708 2.4679 ------10851581 3.1624 Slpi secretory leukocyte peptidase inhibitor 198

10865696 3.7375 ------similar to Hypothetical protein 10766085 2.581 RGD1560022 4832420M10 10940554 4.8479 ------proline rich Gla (G-carboxyglutamic 10847957 2.5164 Prrg4 acid) 4 (transmembrane) 10920298 2.0011 Dag1 dystroglycan 1 sema domain, immunoglobulin domain 10860481 5.0397 Sema3a (Ig), short basic domain, secreted, (semaphorin) 3A 10712299 2.1699 Taldo1 transaldolase 1 10765109 2.2991 ------10716053 3.0946 Ins1 insulin 1 10743774 3.9549 Ntn1 netrin 1 10893231 2.0555 Mmp19 matrix metallopeptidase 19 10808601 2.0909 ------10727008 3.5011 Ins2 insulin 2 10804245 2.6229 Dpysl3 dihydropyrimidinase-like 3 10908102 2.0123 ------10930622 2.1982 ------10800840 2.0162 ------immunoglobulin superfamily, member 10817868 2.1103 Igsf3 3 10886864 3.6607 ------10796989 2.0739 ------10722743 2.1957 Mctp2 multiple C2 domains, transmembrane 2 10861213 2.1797 Tspan12 tetraspanin 12 similar to ribosomal protein L22 10703432 2.3575 LOC365157 proprotein 10879726 4.5077 Zc3h12a zinc finger CCCH type containing 12A 10730472 2.383 ------10879221 2.1681 RGD1308616 similar to KIAA0467 protein B-cell translocation gene 1, anti- 10895069 2.3584 Btg1 proliferative integrin alpha 5 (fibronectin receptor 10907689 2.7604 Itga5 alpha) 10774171 3.4482 Upp1 uridinephosphorylase 1 latent transforming growth factor beta 10891165 2.0081 Ltbp2 binding protein 2 10869202 2.2226 ------solute carrier family 20 (phosphate 10839771 2.0425 Slc20a1 transporter), member 1 10886862 3.4381 ------10878938 2.239 Plk3 polo-like kinase 3 (Drosophila) 10832920 2.1907 Ddit4 DNA-damage-inducible transcript 4 10886868 3.5235 ------10886974 3.7534 ------10908106 2.0018 ------10707177 2.542 Nav2 neuron navigator 2 199

a disintegrin and metallopeptidase 10726371 2.3152 Adam12 domain 12 (meltrin alpha) 10811177 14.0724 Ctrb1 chymotrypsinogen B1 similar to paired immunoglobin-like 10760920 2.1531 LOC681182 type 2 receptor beta sema domain, immunoglobulin domain 10910406 7.5944 Sema7a (Ig), and GPI membrane anchor, (semaphorin) 7A 10910770 3.2143 ------10765105 2.4719 ------10762224 2.3703 ------solute carrier family 7 (cationic amino 10823057 8.008 Slc7a11 acid transporter, y+ system), member 11 10842465 2.2767 Snai1 snail homolog 1 (Drosophila) oligonucleotide/oligosaccharide-binding 10923270 2.4301 Obfc2a fold containing 2A proproteinconvertasesubtilisin/kexin 10840332 3.9514 Pcsk2 type 2 sprouty-related, EVH1 domain 10774345 2.1482 Spred2 containing 2 nuclear factor of activated T-cells, 10780507 2.1014 Nfatc4 cytoplasmic, calcineurin-dependent 4 10801833 10.4848 Megf10 multiple EGF-like domains 10 10910768 4.2494 ------10815369 3.9338 Postn periostin, osteoblast specific factor 10744460 3.7864 Cxcl16 chemokine (C-X-C motif) ligand 16 10733849 2.1672 LOC24906 RoBo-1 10844302 2.1274 Dnm1 dynamin 1 developmentally regulated protein 10812470 2.1359 Tpo1 TPO1 10853469 2.1503 Fzd1 frizzled homolog 1 (Drosophila) 10806341 2.3613 Zfp423 zinc finger protein 423 10918738 2.5952 Scg3 secretogranin III solute carrier family 1 (glial high 10821824 2.3806 Slc1a3 affinity glutamate transporter), member 3 10790023 6.2092 ------10779873 2.5684 RGD1308093 similar to FLJ00128 protein 10886856 3.1595 ------10834109 2.1648 Il1rn interleukin 1 receptor antagonist solute carrier family 4, sodium 10782533 2.2377 Slc4a7 bicarbonate cotransporter, member 7 myeloid/lymphoid or mixed-lineage 10703189 2.0948 Mllt4 leukemia (trithorax homolog, Drosophila); translocated to, 4 10892067 2.313 ------adenylatecyclase activating polypeptide 10855727 2.5883 Adcyap1r1 1 receptor 1 10886848 2.8943 ------200

10711125 2.2103 ------10862453 2.3698 ------10930564 3.5224 ------10839868 2.394 ------similar to core 2 beta-1,6-N- 10812645 2.0819 RGD1563891 acetylglucosaminyltransferase 3 similar to abhydrolase domain 10745378 2.2888 RGD1304598 containing 1; alpha/beta hydrolase-1; lung alpha/beta hydrolase 1 10739357 2.7165 Sox9 SRY-box containing gene 9 10802541 2.1206 ------10936959 3.065 Slc38a5 solute carrier family 38, member 5 potassium intermediate/small 10816824 2.5111 Kcnn3 conductance calcium-activated channel, subfamily N, member 3 development and differentiation 10883808 2.1996 Ddef2 enhancing factor 2 10886884 4.7144 ------10930580 2.505 ------10929263 3.4585 Scg2 secretogranin II 10709880 2.498 Ampd3 adenosine monophosphate deaminase 3 solute carrier family 16 10833635 3.2556 Slc16a10 (monocarboxylic acid transporters), member 10 10901166 4.224 Angptl4 angiopoietin-like 4 10842239 6.3679 Mmp9 matrix metallopeptidase 9 10880204 2.3437 Epb4.1 erythrocyte membrane protein band 4.1 similar to hypothetical protein 10853931 5.714 LOC500046 FLJ21986 10925449 3.1324 Twist2 twist homolog 2 (Drosophila) similar to RIKEN cDNA A530088I07 10860235 2.0955 LOC311984 gene 10881669 2.6822 Cort cortistatin 10889649 2.6615 ------10716080 3.9998 Dusp5 dual specificity phosphatase 5 10902290 2.2459 Nav3 neuron navigator 3 plasminogen activator, urokinase 10704956 2.2345 Plaur receptor 10825573 3.2674 ------10854327 6.8854 Cpa1 carboxypeptidase A1 10910764 2.6208 ------10880977 2.1885 Padi3 peptidyl arginine deiminase, type III 10886850 3.4621 ------10892977 2.5991 ------10931717 4.9484 C3 complement component 3 10911797 2.4882 Gsta4 glutathione S-transferase, alpha 4 pleckstrin homology domain 10807235 2.0731 Plekhg4 containing, family G (with RhoGef domain) member 4 201

10834022 2.761 Arrdc3 arrestin domain containing 3 10781562 2.0656 ------10748802 2.2404 Sdk2 sidekick homolog 2 (chicken) similar to hypothetical protein 10766072 2.1886 RGD1560572 D230039L06 10762028 2.1458 ------cytochrome P450, family 26, subfamily 10863608 3.9648 Cyp26b1 b, polypeptide 1 proteoglycan 4, (megakaryocyte stimulating factor, articular superficial 10768412 2.529 Prg4 zone protein, camptodactyly, arthropathy, coxavara, pericarditis syndrome) 10720506 2.1061 ------10940615 2.2283 ------UDP-Gal:betaGlcNAc beta 1,3- 10836515 2.0247 B3galt1 galactosyltransferase, polypeptide 1 UDP-Gal:betaGlcNAc beta 1,4- 10803394 2.1403 B4galt6 galactosyltransferase, polypeptide 6 10726269 2.5065 Galnac4s-6st B cell RAG associated protein 10813152 2.295 Emb embigin 10723866 2.7006 Dgat2 diacylglycerol O-acyltransferase 2 guanine nucleotide binding protein (G 10853554 3.5959 Gng11 protein), gamma 11 similar to GTL2, imprinted maternally 10886816 3.6158 RGD1566401 expressed untranslated 10889923 2.7829 Egln3 EGL nine homolog 3 (C. elegans) 10845676 2.6271 Gcg glucagon 10887486 2.0644 ------10911802 9.125 Gsta2 glutathione-S-transferase, alpha type2 10809688 2.2258 Adcy7 adenylatecyclase 7 10919328 2.3221 Chst2 carbohydrate sulfotransferase 2 10871806 2.0486 Fhl3 four and a half LIM domains 3 10719006 2.033 ------solute carrier family 2 (facilitated 10814630 2.6203 Slc2a2 glucose transporter), member 2 cisplatin resistance-associated 10746286 2.023 Crop overexpressed protein 10886938 3.1579 ------10887336 3.0885 ------10819052 3.2491 Lef1 lymphoid enhancer binding factor 1 10796230 2.84 ------10880095 4.1319 Serinc2 serine incorporator 2 10915778 2.2891 ------10797660 4.3187 Aspn asporin 10875375 2.7641 Car8 carbonic anhydrase 8 10702293 2.6394 ------10708587 3.0212 ------

202

Supplementary Table 3

Dysregulated Genes in the Comparison of Collagen vs Plastic (FC>2, P<0.001, FDR<0.25) Upregulated Genes ProbeSetI GeneSymbo FC Description D l 16.646 10743227 Rasd1 RAS, dexamethasone-induced 1 7 10801967 5.0906 Chsy3 chondroitin sulfate synthase 3 10719432 6.3932 Fosb FBJ osteosarcoma oncogene B 14.982 10773853 Lif leukemia inhibitory factor 4 10714353 3.2785 Tmem2 transmembrane protein 2 RGD130802 10850480 3.2274 similar to CG5521-PA 3 10815057 3.1132 Fat4 FAT tumor suppressor homolog 4 (Drosophila) a disintegrin-like and metallopeptidase 10765534 3.7333 Adamts4 (reprolysin type) with thrombospondin type 1 motif, 4 10901409 2.8101 Chst11 carbohydrate sulfotransferase 11 10750505 5.7613 Pcp4 Purkinje cell protein 4 nuclear factor of kappa light polypeptide gene 10750848 4.1207 Nfkbiz enhancer in B-cells inhibitor, zeta 10934865 4.6099 Srpx2 sushi-repeat-containing protein, X-linked 2 10864715 3.4271 Vgll4 vestigial like 4 (Drosophila) nuclear receptor subfamily 4, group A, member 10845384 4.0633 Nr4a2 2 10878112 4.6806 Jun Jun oncogene 10750460 2.8833 Ets2 E26 avian leukemia oncogene 2, 3' domain 10764551 8.2725 Ptgs2 prostaglandin-endoperoxide synthase 2 10840448 2.5068 Rin2 Ras and Rabinteractor 2 10767767 5.9464 Btg2 B-cell translocation gene 2, anti-proliferative 10762378 2.9852 Tbx3 T-box 3 10929725 7.9158 Arl4c ADP-ribosylation factor-like 4C 10903676 2.5445 Trps1 trichorhinophalangeal syndrome I (human) 10776512 4.12 Rasl11b RAS-like family 11 member B 10736312 2.1924 Nos2 nitric oxide synthase 2, inducible, macrophage 10864797 3.0102 Plxnd1 plexin D1 10859799 4.1521 Il6 interleukin 6 SHC (Src homology 2 domain containing) 10849423 5.2447 Shc4 family, member 4 203

10860351 5.7363 Hgf hepatocyte growth factor 10886948 4.1884 ------10886972 4.1884 ------10886914 4.1884 ------10886942 3.9924 ------10887000 4.212 ------10796564 2.8405 Plxdc2 plexin domain containing 2 10780205 2.6256 Mmp14 matrix metallopeptidase 14 (membrane-inserted) nuclear factor of kappa light polypeptide gene 10890024 3.093 Nfkbia enhancer in B-cells inhibitor, alpha ST3 beta-galactoside alpha-2,3-sialyltransferase 10916016 3.3521 St3gal4 4 10831077 3.195 Ier3 immediate early response 3 10775731 3.1702 Cxcl13 chemokine (C-X-C motif) ligand 13 10886978 4.1904 ------10886902 4.1904 ------10886946 4.1885 ------10749892 2.4598 Robo1 roundabout homolog 1 (Drosophila) 10734882 2.5913 Per1 period homolog 1 (Drosophila) 10852907 2.0537 Cdk5 cyclin-dependent kinase 5 low density lipoprotein receptor-related protein 10837881 2.2527 Lrp4 4 10735221 2.0533 Zmynd15 zinc finger, MYND domain containing 15 10886932 4.2018 ------10886982 4.2018 ------10886952 4.2018 ------10886998 4.2018 ------10886906 4.2018 ------10886924 4.2018 ------10886962 4.2018 ------10886872 4.2018 ------10886912 4.2018 ------10886908 4.2018 ------10886926 4.2018 ------10886976 4.2018 ------10886918 4.2018 ------10886954 4.2018 ------10886878 4.2018 ------10886970 4.2018 ------10886968 4.2018 ------10886936 4.2018 ------10886944 3.9201 ------10727260 3.5857 Ccnd1 cyclin D1 10866512 4.2719 Mgp matrix Gla protein 10886964 4.2847 ------10822637 2.3996 Skil SKI-like RGD130802 10850488 4.2719 similar to CG5521-PA 3 10768376 2.0072 Pla2g4a phospholipase A2, group IVA (cytosolic, 204

calcium-dependent) 10705213 4.6428 Tgfb1 transforming growth factor, beta 1 10886960 4.7226 ------10886928 4.7226 ------10755644 3.6112 Scarf2 scavenger receptor class F, member 2 10940654 5.6702 ------10834022 6.0207 Arrdc3 arrestin domain containing 3 RGD156002 10766080 2.5402 similar to Hypothetical protein 4832420M10 2 10886031 5.9308 Fos FBJ osteosarcoma oncogene pleckstrin homology-like domain, family A, 10895406 3.2201 Phlda1 member 1 10753222 2.3002 Runx1 runt related transcription factor 1 RGD130802 10850494 3.1522 similar to CG5521-PA 3 10723822 2.8711 Tsku tsukushin 10851581 4.1153 Slpi secretory leukocyte peptidase inhibitor 10886882 3.951 ------cysteine-rich secretory protein LCCL domain 10808377 3.5398 Crispld2 containing 2 10775900 2.6065 Cxcl1 chemokine (C-X-C motif) ligand 1 10807464 2.3197 Lypla3 lysophospholipase 3 10814430 4.0169 Cp ceruloplasmin 10802734 2.1746 Smad7 MAD homolog 7 (Drosophila) 10793999 2.6702 Ddx41 DEAD (Asp-Glu-Ala-Asp) box polypeptide 41 10844223 2.6525 Ptges prostaglandin E synthase 10863777 2.4563 Antxr1 anthrax toxin receptor 1 10813128 2.5214 ------10746172 2.4853 Nog noggin RGD156002 10766082 2.321 similar to Hypothetical protein 4832420M10 2 10886892 4.6299 ------10886966 4.6299 ------10886956 4.6299 ------10886916 4.6299 ------10887012 4.6299 ------10886992 4.6299 ------10886904 4.6299 ------10886934 4.6299 ------10886950 4.6299 ------10887006 4.6299 ------10886940 4.6299 ------10886990 4.6299 ------10886980 4.6299 ------10886996 4.6299 ------10886984 4.6299 ------10886910 4.6299 ------10886922 4.6299 ------10887002 4.6299 ------205

10704956 3.4976 Plaur plasminogen activator, urokinase receptor 10834109 2.8996 Il1rn interleukin 1 receptor antagonist 10798169 7.9342 Foxq1 forkhead box Q1 nuclear receptor subfamily 4, group A, member 10899387 5.2654 Nr4a1 1 10869499 2.4268 Pappa pregnancy-associated plasma protein A solute carrier family 1 (glial high affinity 10821824 3.1443 Slc1a3 glutamate transporter), member 3 10703953 4.3958 Il11 interleukin 11 CD74 antigen (invariant polypeptide of major 10802013 3.1836 Cd74 histocompatibility complex, class II antigen- associated) UDP-GlcNAc:betaGal beta-1,3-N- 10778708 2.0983 B3gnt2 acetylglucosaminyltransferase 2 10738051 9.6231 Csf3 colony stimulating factor 3 (granulocyte) RGD130992 10732657 2.0526 similar to RIKEN cDNA G431001E03 gene 6 10724542 2.8302 Dchs1 dachsous 1 (Drosophila) UDP-Gal:betaGlcNAc beta 1,4- 10765542 2.0568 B4galt3 galactosyltransferase, polypeptide 3 10775338 2.2842 Pkd2 polycystic kidney disease 2 10743774 4.5663 Ntn1 netrin 1 10907881 8.4025 Mmp3 matrix metallopeptidase 3 RGD130802 10850490 4.4638 similar to CG5521-PA 3 10800214 2.3332 ------10889379 2.2908 Id2 inhibitor of DNA binding 2 10817868 2.2764 Igsf3 immunoglobulin superfamily, member 3 RGD156002 10766085 2.667 similar to Hypothetical protein 4832420M10 2 10886974 4.5635 ------10866526 3.7965 Arhgdib Rho, GDP dissociation inhibitor (GDI) beta 10784896 3.0087 Slc25a37 solute carrier family 25, member 37 serine (or cysteine) peptidase inhibitor, clade E, 10929288 2.4558 Serpine2 member 2 10886986 3.8386 ------10887004 3.8386 ------RGD130802 10850459 3.8708 similar to CG5521-PA 3 sema domain, immunoglobulin domain (Ig), and 10910406 9.9897 Sema7a GPI membrane anchor, (semaphorin) 7A 10781378 2.4788 Hr hairless latent transforming growth factor beta binding 10891165 2.1567 Ltbp2 protein 2 10853469 2.4653 Fzd1 frizzled homolog 1 (Drosophila) 10851587 2.4549 Matn4 matrilin 4 10804245 2.6878 Dpysl3 dihydropyrimidinase-like 3 10800919 2.5956 Egr1 early growth response 1 10775896 4.883 Cxcl2 chemokine (C-X-C motif) ligand 2 206

10891679 6.9479 Gpr68 G protein-coupled receptor 68 potassium voltage-gated channel, subfamily H 10766782 3.0078 Kcnh1 (eag-related), member 1 phytanoyl-CoA hydroxylase interacting protein- 10829738 2.9898 Phyhipl like 10770497 2.1601 Hlx H2.0-like homeobox 10774171 3.6455 Upp1 uridinephosphorylase 1 RGD130802 10850478 4.0311 similar to CG5521-PA 3 10886850 5.0334 ------10886888 3.3506 ------10774375 2.0111 Peli1 pellino homolog 1 (Drosophila) 10832920 2.2706 Ddit4 DNA-damage-inducible transcript 4 10732113 2.2506 Pkd1 polycystic kidney disease 1 homolog 10879726 4.5229 Zc3h12a zinc finger CCCH type containing 12A 10786401 2.7182 Wnt5a wingless-related MMTV integration site 5A RGD130802 10850484 2.9976 similar to CG5521-PA 3 10872266 2.1372 Rnf19b ring finger protein 19B glucosaminyl (N-acetyl) transferase 2, I- 10797929 2.0605 Gcnt2 branching enzyme 10886862 3.4548 ------prostate transmembrane protein, androgen 10852144 3.0349 Pmepa1 induced 1 pleckstrin homology domain containing, family 10807235 2.4677 Plekhg4 G (with RhoGef domain) member 4 a disintegrin-like and metallopeptidase 10813694 2.0053 Adamts12 (reprolysin type) with thrombospondin type 1 motif, 12 10886864 3.4251 ------10815369 4.2013 Postn periostin, osteoblast specific factor 10821383 2.0498 Snx18 sorting nexin 18 10744460 3.9573 Cxcl16 chemokine (C-X-C motif) ligand 16 10886868 3.4468 ------10886848 3.083 ------10903825 9.0352 Has2 hyaluronan synthase 2 solute carrier family 20 (phosphate transporter), 10839771 2.0015 Slc20a1 member 1 RGD130996 10847735 2.0375 similar to RIKEN cDNA 2600010E01 9 10791303 2.0438 Npy1r neuropeptide Y receptor Y1 10903674 2.6837 Trps1 trichorhinophalangeal syndrome I (human) 10804125 2.467 Spry4 sprouty homolog 4 (Drosophila) v-mafmusculoaponeuroticfibrosarcoma 10851391 2.8233 Mafb oncogene family, protein B (avian) 10751793 6.8371 Lrrc15 leucine rich repeat containing 15 10846694 2.4774 Pde1a phosphodiesterase 1A, calmodulin-dependent 10797660 6.8632 Aspn asporin 10798702 3.3857 Inhba inhibin beta-A 207

10886856 3.1152 ------10769370 2.563 Fmo2 flavin containing monooxygenase 2 adenylatecyclase activating polypeptide 1 10855727 2.5392 Adcyap1r1 receptor 1 10801833 9.1622 Megf10 multiple EGF-like domains 10 potassium channel tetramerisation domain 10710958 2.4015 Kctd13 containing 13 leucine rich repeat containing 8 family, member 10775271 2.4829 Lrrc8c C 10907689 2.4468 Itga5 integrin alpha 5 (fibronectin receptor alpha) RGD130802 10850492 2.9264 similar to CG5521-PA 3 10869525 2.3676 ------10895069 2.1093 Btg1 B-cell translocation gene 1, anti-proliferative microtubule associated serine/threonine kinase 10821072 3.4031 Mast4 family member 4 10886728 3.0429 Hhipl1 hedgehog interacting protein-like 1 BMP and activin membrane-bound inhibitor, 10798850 3.9364 Bambi homolog (Xenopuslaevis) a disintegrin and metallopeptidase domain 12 10726371 2.0755 Adam12 (meltrin alpha) RGD156483 10766094 2.3169 similar to 9630058J23Rik protein 3 10891681 2.0367 Gpr68 G protein-coupled receptor 68 10832197 2.2388 Snf1lk SNF1-like kinase RGD156284 similar to Docking protein 5 (Downstream of 10842500 2.5463 6 tyrosine kinase 5) (Protein dok-5) 10853931 5.5366 LOC500046 similar to hypothetical protein FLJ21986 10925449 3.0914 Twist2 twist homolog 2 (Drosophila) 10921195 2.1241 Xiap X-linked inhibitor of apoptosis 10795602 2.2431 Map3k8 mitogen-activated protein kinase kinasekinase 8 10748440 2.003 ------10781273 2.7182 Stc1 stanniocalcin 1 RGD130809 10779873 2.2042 similar to FLJ00128 protein 3 10712657 2.1202 Cpt1a carnitinepalmitoyltransferase 1a, liver potassium voltage-gated channel, shaker-related 10818239 2.1445 Kcna3 subfamily, member 3 basic helix-loop-helix domain containing, class 10867026 5.4241 Bhlhb3 B3 10919328 2.4391 Chst2 carbohydrate sulfotransferase 2 RGD131075 similar to chromosome 20 open reading frame 10840613 2.2607 3 39 10828344 2.1109 RT1-Da RT1 class II, locus Da 10842239 5.189 Mmp9 matrix metallopeptidase 9 10886644 2.7764 Bdkrb1 bradykinin receptor, beta 1 10880095 4.2683 Serinc2 serine incorporator 2 10917183 2.4376 Ncam1 neural cell adhesion molecule 1 10821689 2.3783 Ptger4 prostaglandin E receptor 4 (subtype EP4) 208

10794225 2.2549 Nfil3 nuclear factor, interleukin 3 regulated 10823368 2.2316 Igsf10 immunoglobulin superfamily, member 10 10754943 3.5991 Hes1 hairy and enhancer of split 1 (Drosophila) RGD156057 10766072 2.0518 similar to hypothetical protein D230039L06 2 10857655 3.1373 Lmcd1 LIM and cysteine-rich domains 1 10886994 2.5557 ------ADAM metallopeptidase with thrombospondin 10771830 2.0255 Adamts3 type 1, motif 3 biregional cell adhesion molecule-related/down- 10751115 2.2693 Boc regulated by oncogenes (Cdon) binding protein bone morphogenetic protein receptor, type 1B 10827068 2.0091 Bmpr1b (mapped) 10840138 2.6861 Bmp2 bone morphogenetic protein 2 10886884 3.4434 ------10744376 2.0085 Bcl6b B-cell CLL/lymphoma 6, member B 10881576 2.4356 LOC691317 hypothetical protein LOC691317 10889923 2.5366 Egln3 EGL nine homolog 3 (C. elegans) 10770710 2.4462 Atf3 activating transcription factor 3 10739357 2.1496 Sox9 SRY-box containing gene 9 RGD130802 10850486 2.5195 similar to CG5521-PA 3 10729777 2.2837 Ch25h cholesterol 25-hydroxylase 10895152 2.0773 Kitl kit ligand sema domain, immunoglobulin domain (Ig), 10860481 2.4891 Sema3a short basic domain, secreted, (semaphorin) 3A 10730794 2.1711 Sorcs1 VPS10 domain receptor protein SORCS 1 pleckstrin homology, Sec7 and coiled-coil 10845407 2.3345 Pscdbp domains, binding protein 10940554 2.3984 ------10849833 3.9306 Il1a interleukin 1 alpha ST6 (alpha-N-acetyl-neuraminyl-2,3-beta- 10827400 2.1742 St6galnac3 galactosyl-1,3)-N-acetylgalactosaminide alpha- 2,6-sialyltransferase 3 10886938 2.6064 ------10847817 2.4801 Elf5 E74-like factor 5 10809273 4.2183 Ccl22 chemokine (C-C motif) ligand 22 10891445 2.3675 Ston2 stonin 2 ectonucleotidepyrophosphatase/phosphodiestera 10702250 3.2197 Enpp1 se 1

209

Downregulated Genes GeneSymbo ProbeSetID absFC Description l 10767605 7.2422 Cntn2 contactin 2 11.304 10767388 Cd55 CD55 antigen 6 10.053 potassium voltage gated channel, Shal-related 10818141 Kcnd3 3 family, member 3 10753982 5.8021 Ccdc80 coiled-coil domain containing 80 10797949 3.7242 Bmp6 bone morphogenetic protein 6 10770577 4.7047 Tgfb2 transforming growth factor, beta 2 RGD155989 10811906 2.9907 similar to RIKEN cDNA 2310022B05 6 26.211 10922857 Il1rl1 interleukin 1 receptor-like 1 8 10749839 3.5139 Vgll3 vestigial like 3 (Drosophila) 10896541 5.6719 Nov nephroblastoma overexpressed gene tumor necrosis factor receptor superfamily, 10903725 3.8746 Tnfrsf11b member 11b (osteoprotegerin) 10851350 5.7265 Tgm2 transglutaminase 2, C polypeptide tumor necrosis factor (ligand) superfamily, 10765096 2.3578 Tnfsf18 member 18 sema domain, immunoglobulin domain (Ig), 10860499 3.0307 Sema3d short basic domain, secreted, (semaphorin) 3D 10763889 2.1378 Nuak2 NUAK family, SNF1-like kinase, 2 10782187 2.9701 Itgbl1 integrin, beta-like 1 RGD156464 similar to Neurogenic locus notch homolog 10754592 3.1918 1 protein 2 precursor (Notch 2) (hN2) 10932211 2.2007 Maob monoamine oxidase B G protein-coupled receptor, family C, group 5, 10859277 2.6753 Gprc5a member A epidermal growth factor-containing fibulin-like 10774638 3.3927 Efemp1 extracellular matrix protein 1 RGD156271 similar to ABI gene family, member 3 (NESH) 10753629 3.9371 7 binding protein 10925291 3.7617 Cxcr7 chemokine (C-X-C motif) receptor 7 10777788 2.7289 Spon2 spondin 2, extracellular matrix protein 10746483 2.8033 Itga3 integrin alpha 3 10861997 2.5481 Hipk2 homeodomain interacting protein kinase 2 heat shock protein family, member 7 10873732 4.8157 Hspb7 (cardiovascular) Cbp/p300-interacting transactivator, with 10701846 2.0815 Cited2 Glu/Asp-rich carboxy-terminal domain, 2 10823903 2.8088 Gucy1b3 guanylatecyclase 1, soluble, beta 3 10775761 2.0739 Ccng2 cyclin G2 Ral GEF with PH domain and SH3 binding 10769016 2.8251 Ralgps2 motif 2 10713844 2.0164 Fads3 fatty acid desaturase 3 10779843 4.2792 Rnase1l2 ribonuclease, RNase A family, 1-like 2 210

(pancreatic) discoidin, CUB and LCCL domain containing 10753582 2.9029 Dcbld2 2 RGD130526 10776710 2.6968 similar to hypothetical protein 9 10771655 2.2617 Cxcl10 chemokine (C-X-C motif) ligand 10 10760738 3.2808 Fam20c family with sequence similarity 20, member C aldehyde dehydrogenase family 1, subfamily 10911380 4.2982 Aldh1a2 A2 10912584 2.4773 Amotl2 angiomotin like 2 10708665 5.3781 Rab30 RAB30, member RAS oncogene family 10938485 2.006 Fam123b family with sequence similarity 123B 10773435 3.4111 Cpz carboxypeptidase Z 10899465 3.56 Igfbp6 insulin-like growth factor binding protein 6 10883586 2.0144 Osr1 odd-skipped related 1 (Drosophila) 10797857 7.4061 Edn1 endothelin 1 10915648 2.3138 Rab3d RAB3D, member RAS oncogene family 10889660 3.2396 Ahr aryl hydrocarbon receptor 10940688 3.6858 ------10906926 3.3341 Rnd1 Rho family GTPase 1 RGD156509 10927468 2.0958 similar to hypothetical protein MGC52110 5 10817065 2.1806 S100a6 S100 calcium binding protein A6 (calcyclin) 10933333 2.3085 Prps2 phosphoribosyl pyrophosphate synthetase 2 10798646 2.1389 Amph amphiphysin 10.689 10909892 Cryab crystallin, alpha B 4 cytidine monophosphate (UMP-CMP) kinase 10883960 2.0832 Cmpk2 2, mitochondrial 10749325 2.0452 Cygb cytoglobin 10817552 2.31 Txnip thioredoxin interacting protein 10761446 9.4223 LOC687426 similar to G protein-coupled receptor 133 10712171 3.4336 Ifitm1 interferon induced transmembrane protein 1 10904543 5.2942 ------10937725 2.3516 Figf c-fos induced growth factor 10819914 2.1636 Ankrd13c ankyrin repeat domain 13C 10818708 7.7971 F3 coagulation factor III 10754000 3.4058 Cd200r1 CD200 receptor 1 10939472 2.5252 Ripply1 ripply1 homolog (zebrafish) 10781829 2.7882 Klf5 Kruppel-like factor 5 10817057 4.1442 S100a4 S100 calcium-binding protein A4 10815176 2.7564 Phf17 PHD finger protein 17 10733069 2.2106 Mgat1 mannosideacetylglucosaminyltransferase 1 10873814 2.0475 ------receptor (calcitonin) activity modifying protein 10774115 4.9473 Ramp3 3 10778390 3.275 Igfbp3 insulin-like growth factor binding protein 3 meteorin, glial cell differentiation regulator- 10931247 2.1935 Metrnl like 211

10717295 3.7814 Vnn1 vanin 1 10940611 3.2507 ------10935555 3.9905 Fhl1 four and a half LIM domains 1 10919537 2.7621 Il20rb interleukin 20 receptor beta 10910612 2.1808 Larp6 La ribonucleoprotein domain family, member 6 10910336 2.3492 Rpp25 ribonuclease P 25 subunit (human) 10815049 3.309 Spry1 sprouty homolog 1 (Drosophila) 10749983 3.7803 Cxadr coxsackie virus and adenovirus receptor 10826846 3.5181 Sgms2 sphingomyelin synthase 2 cytochrome P450, subfamily 11B, polypeptide 10904553 9.7836 Cyp11b1 1 10869253 2.2386 Ugcg UDP-glucose ceramideglucosyltransferase ST3 beta-galactoside alpha-2,3- 10750672 4.0322 St3gal6 sialyltransferase 6 10932773 2.2664 Chrdl1 kohjirin 10775628 4.6604 Anxa3 annexin A3 10720533 2.1137 Zfp74 zinc finger protein 74 10797648 3.1044 Ogn osteoglycin 10790966 2.0054 Isyna1 myo-inositol 1-phosphate synthase A1 10781441 2.0786 P2ry5 purinergic receptor P2Y, G-protein coupled, 5 10834800 2.1437 Olfm1 olfactomedin 1 10915923 4.0986 Hnt neurotrimin 10745292 5.371 Lgals9 lectin, galactose binding, soluble 9 10861242 3.1298 Aass aminoadipate-semialdehyde synthase 10868881 3.0595 Col15a1 collagen, type XV, alpha 1 10750878 3.3935 Alcam activated leukocyte cell adhesion molecule 10701734 2.0053 Ppil4 peptidylprolylisomerase (cyclophilin)-like 4 RGD156178 10743961 2.0024 similar to RIKEN cDNA 2600017H02 1 dehydrogenase/reductase (SDR family) 10873838 2.0774 Dhrs3 member 3 10802023 3.8187 Arsi arylsulfatasei 10767243 2.2809 Lypd1 Ly6/Plaur domain containing 1 CDC42 effector protein (Rho GTPase binding) 10887939 2.2464 Cdc42ep3 3 similar to Sulfide:quinoneoxidoreductase, 10839320 3.3958 LOC691966 mitochondrial precursor 10819644 4.5098 Ddah1 dimethylargininedimethylaminohydrolase 1 10914546 4.6233 ------10745931 2.6231 ------10909382 3.696 Vof16 ischemia related factor vof-16 10827916 3.4002 Ddr1 discoidin domain receptor family, member 1 10918600 2.1699 Cgnl1 cingulin-like 1 10845743 2.6439 Fign fidgetin UDP-N-acetyl-alpha-D- 10885628 2.6605 Galntl1 galactosamine:polypeptide N- acetylgalactosaminyltransferase-like 1 sema domain, immunoglobulin domain (Ig), 10860327 2.2371 Sema3c short basic domain, secreted, (semaphorin) 3C 212

brain abundant, membrane attached signal 10822075 2.0327 Basp1 protein 1 10824892 7.5794 Selenbp1 selenium binding protein 1 a disintegrin-like and metallopeptidase 10752852 5.1279 Adamts5 (reprolysin type) with thrombospondin type 1 motif, 5 (aggrecanase-2) 10849260 6.418 Duoxa1 dual oxidase maturation factor 1 10791565 2.6878 Vegfc vascular endothelial growth factor C 10891303 2.2494 Tgfb3 transforming growth factor, beta 3 interferon-induced protein with 10729791 2.0496 Ifit1lb tetratricopeptide repeats 1-like B 10880074 2.9013 Tinagl1 tubulointerstitial nephritis antigen-like 1 10895747 2.6354 Avpr1a arginine vasopressin receptor 1A scavenger receptor class A, member 5 10781131 9.2132 Scara5 (putative) 10939260 2.0846 Xkrx X Kell blood group precursor related X linked 10896263 2.2263 Cthrc1 collagen triple helix repeat containing 1 10777748 3.9563 Fgfr3 fibroblast growth factor receptor 3 10930580 2.2517 ------10709875 3.08 Adm adrenomedullin RGD131193 10882534 2.1008 similar to AI115348 protein 9 10930428 2.1668 Emilin2 elastin microfibrilinterfacer 2 10839268 9.7952 Duox1 dual oxidase 1 RGD156432 10799684 2.8013 similar to integrin alpha 8 7 10753425 3.2043 Mx1 myxovirus (influenza virus) resistance 1 radical S-adenosyl methionine domain 10889399 3.1792 Rsad2 containing 2 10716480 2.3989 Grk5 G protein-coupled receptor kinase 5 10816017 2.2682 MGC72614 hypothetical LOC310540 10786905 4.1 Gdf10 growth differentiation factor 10 10829993 2.0748 MGC112715 hypothetical protein LOC690899 10784641 2.4033 Ptk2b PTK2 protein tyrosine kinase 2 beta 10708535 7.4414 Fzd4 frizzled homolog 4 (Drosophila) 10880710 2.8637 Ephb2 Eph receptor B2 sarcoglycan, gamma (dystrophin-associated 10784346 2.2375 Sgcg glycoprotein) RGD156246 10770109 2.0724 similar to Ifi204 protein 2 10766869 2.6513 Cd34 CD34 molecule 10798194 4.2237 Agtr1a angiotensin II receptor, type 1a solute carrier family 9 (sodium/hydrogen 10741189 2.1463 Slc9a3r2 exchanger), member 3 regulator 2 10873021 4.4458 Wnt4 wingless-related MMTV integration site 4 10712997 3.0891 Cd248 CD248 molecule, endosialin RGD130525 10723383 3.0951 similar to transmembrane protein 2 4 10752839 3.2101 Adamts1 a disintegrin-like and metallopeptidase 213

(reprolysin type) with thrombospondin type 1 motif, 1 10867593 2.1451 Gdf6 growth differentiation factor 6 10702660 2.0358 Akap12 A kinase (PRKA) anchor protein (gravin) 12 10873027 3.5199 ------10787856 2.1993 Tll1 tolloid-like 1 10851839 2.5812 Sulf2 sulfatase 2 solute carrier family 24 10840431 2.8903 Slc24a3 (sodium/potassium/calcium exchanger), member 3 10732644 5.2233 Stc2 stanniocalcin 2 a disintegrin-like and metallopeptidase 10915933 4.2615 Adamts15 (reprolysin type) with thrombospondin type 1 motif, 15 10777232 2.0864 Cd38 CD38 molecule similar to novel protein similar to multidomain RGD156411 10934475 2.1069 presynaptic cytomatrix protein piccolo 7 (presynaptic cytomatrix protein) 10868595 2.0445 ------10757454 2.2215 Cldn15 claudin 15 10800189 2.8436 Cables1 Cdk5 and Abl enzyme substrate 1 ectonucleoside triphosphate 10834213 2.8664 Entpd2 diphosphohydrolase 2 ATPase, Na+/K+ transporting, beta 1 10769476 2.6237 Atp1b1 polypeptide RGD131082 similar to RIKEN cDNA 1200009O22; EST 10862605 2.158 7 AI316813 pterin 4 alpha carbinolaminedehydratase/dimerization 10830003 2.283 Pcbd1 cofactor of hepatocyte nuclear factor 1 alpha (TCF1) 1 10766835 2.1058 Plxna2 plexin A2 10821989 3.8006 ------10817061 2.0081 S100a5 S100 calcium binding protein A5 oxidized low density lipoprotein (lectin-like) 10866030 3.8819 Olr1 receptor 1 10732750 3.2421 Slit3 slit homolog 3 (Drosophila) 10908645 2.578 Bmper BMP-binding endothelial regulator 10897752 2.604 Mgat3 mannoside acetyl glucosaminyltransferase 3 10888404 2.1745 Rasgrp3 RAS, guanyl releasing protein 3 ST6 (alpha-N-acetyl-neuraminyl-2,3-beta- 10749330 2.0102 St6galnac2 galactosyl-1,3)-N-acetylgalactosaminide alpha- 2,6-sialyltransferase 2 CDC42 effector protein (Rho GTPase binding) 10728057 2.6772 Cdc42ep2 2 10808702 2.8775 Tubb3 tubulin, beta 3 10800546 2.1109 Mocos molybdenum cofactor sulfurase