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Copyright by Craig R. Bush 2007 COMMITTEE CERTIFICATION OF APPROVED VERSION The committee for Craig Randall Bush certifies that this is the approved version of the following dissertation: FUNCTIONAL GENOMIC ANALYSIS OF PPAR-GAMMA IN HUMAN COLORECTAL CANCER CELLS Committee: E. Aubrey Thompson, Ph.D, Supervisor Bruce A. Luxon, Ph.D, Supervisor E. Brad Thompson, MD Allan R. Brasier, MD Larry A. Denner, Ph.D Rudy Guerra, Ph.D ______________________________ Dean, Graduate School FUNCTIONAL GENOMIC ANALYSIS OF PPAR-GAMMA IN HUMAN COLORECTAL CANCER CELLS By Craig Randall Bush, B.S. Dissertation Presented to the Faculty of The University of Texas Graduate School of Biomedical Sciences at Galveston in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Approved by the Supervisory Committee E. Brad Thompson, MD E. Aubrey Thompson, Ph.D Bruce A. Luxon, Ph.D Allan R. Brasier, MD Larry A. Denner, Ph.D Rudy Guerra, Ph.D December, 2006 Galveston, Texas Key words: systems biology machine-learning © 2007, Craig R. Bush DEDICATION To my wife, Lu ACKNOWLEDGEMENTS I wish to first and foremost thank both of my mentors, Drs. E. Aubrey Thompson and Bruce A. Luxon for their guidance and wisdom through this long and difficult exercise. Aubrey, here’s to sitting out on the lanai, looking out over that salt marsh, and pondering the wonders of the world. Bruce, thank you for taking a chance on me and then taking another. I will never forget that. I would like to acknowledge the other members of my supervisory committee, Drs. E. Brad Thompson, Allan R. Brasier, Larry A. Denner, and Rudy Guerra for their advice and insight. Special thanks to members of my laboratories for all of their hard work. At the Mayo Clinic in Jacksonville, Florida: Drs. Brian Necela and Weidong Su, Mrs. Nancy Rutkoski and Miss Jennifer Havens. At the University of Texas Medical Branch in Galveston, Texas: Mrs. Mala Sinha. Likewise, I wish to also thank Drs. Panagiotis Anastasidadis and Masahiro Yanagisawa and Ms. Michelle Guigneaux for their technical assistance. I would also like to thank my wife Lu for her patience and encouragement. I simply do not think I could have completed this work without her. I wish to extend my gratitude to the Keck Center for Computational Biology at Rice University for granting me a three year pre-doctoral National Library of Medicine fellowship and Sankyo Ltd. (Tokyo, Japan) for financial support and use of their compound. Finally, I would like to thank Dr. David Niesel for taking time out of his busy schedule to talk to me that one afternoon in the Summer of 2000. iv FUNCTIONAL GENOMIC ANALYSIS OF PPAR-GAMMA IN HUMAN COLORECTAL CANCER CELLS Publication No._____________ Craig Randall Bush, Ph.D The University of Texas Graduate School of Biomedical Sciences at Galveston, 2007 Supervisors: E. Aubrey Thompson and Bruce A. Luxon The gamma isoform of peroxisome-proliferator activated receptor (PPARγ) is a member of the super family of nuclear hormone receptors and shows much promise as a chemopreventative and therapeutic target for colorectal cancer. Activation of PPARγ by thiazolidinediones (TZDs) inhibits proliferation and induces differentiation in human colon cancer cells. RS5444, a novel TZD, is a high affinity and high specificity ligand for PPARγ. We have shown that RS5444 markedly reduced the proliferation of MOSER S human colorectal cancer cells under anchorage dependent and independent conditions. The inhibitory effect of RS5444 was irreversible. RS5444 also significantly repressed the invasive phenotype, but not motility, of these tumor cells. Towards elucidating the activated PPARγ controlled genomic program responsible for these observed phenotypes, functional genomic analysis was performed using a two-class longitudinal microarray data set in the presence and absence of RS5444. Differential expression of genes was calculated using an empirical Bayesian modification to the multivariate HotellingT2 score. We have demonstrated this statistical machine learning technique to be superior in controlling type II error in our dataset than more commonly used algorithms for two-class analysis. Likewise, through the use of v several bioinformatics techniques, including frequency-based pathway and ontology analysis, we found a yet unappreciated tumor-suppressing network involving a feedback mechanism between PPARγ, DSCR1 and calcineurin-mediated signaling of NFATc in colorectal cancer cells. To this end, we have demonstrated a direct connection between NFATc and DSCR1 in MOSER S colorectal cancer cells. Likewise, we have demonstrated a correlation between the sensitivity of PPARγ in other colorectal cancer cells, and the messenger abundance of DSCR1. Finally, we have demonstrated that knockdown of DSCR1 messenger obviates the phenotypic effects of activated PPARγ in vitro. To our knowledge these data represent, for the first time, a network between PPARγ, DSCR1, and NFATc signaling in the context of tumor-suppressor activity. This preliminary evidence is consistent with our working hypothesis that an oncology patient’s receptiveness to TZD treatment may be largely dependent on the specific tumor’s endogenous abundance of DSCR1. We believe without a critical endogenous level of DSCR1, activated PPARγ may revert to a tumor-activator instead of a tumor -suppressor. vi TABLE OF CONTENTS LIST OF TABLES X LIST OF FIGURES XI LIST OF ABBREVIATIONS XIV GLOSSARY XVII CHAPTER 1: BACKGROUND 1 SYSTEMS BIOLOGY 1 The Systems Biology Paradigm Shift......................................................................1 Functional Genomics’ Role in Discovery Research ..............................................11 Systems biology and reverse-engineering complexity ..........................................13 Examples of tools that have been used to solve systems problems .......................14 PEROXISOME PROLIFERATOR-ACTIVATED RECEPTORS 24 Nuclear hormone receptors....................................................................................24 PPAR family ..........................................................................................................25 PPARγ....................................................................................................................28 PPARγ and colorectal cancer.................................................................................33 DSCR1, CALCINEURIN AND NFAT 36 DSCR1 as a tumor suppressor ...............................................................................36 NFATc as a tumor promoter..................................................................................37 Calcineurin.............................................................................................................38 The signaling axis of DSCR1-Calcineurin-NFATc...............................................39 CHAPTER 2: MATERIALS AND METHODS 44 CHEMICAL REAGENTS 44 vii PLASMIDS AND VECTORS 44 CELL LINES 45 WESTERN BLOTTING 47 TRANSIENT TRANSFECTION ASSAY 48 ANCHORAGE-DEPENDENT AND –INDEPENDENT CELL PROLIFERATION 49 COLONY FORMATION ASSAY 50 MIGRATION AND INVASION ASSAYS 51 SHRNA GENE SILENCING 52 RNA ISOLATION 52 QUANTITATIVE REAL-TIME PCR (QPCR) 54 ESTIMATION OF RS5444’S EC50 56 MICROARRAY ANALYSIS 57 QUALITY CONTROL AND PREPROCESSING OF AFFYMETRIX MICROARRAY PROBE-LEVEL DATA 58 STATISTICAL MODELS FOR DIFFERENTIAL EXPRESSION OF LONGITUDINAL MICROARRAY DATA 60 Non-parametric model ...........................................................................................60 Polynomial Regression Model...............................................................................62 Empirical Bayesian Model.....................................................................................64 GENE ONTOLOGY ANALYSIS 68 CHAPTER 3: RESULTS 70 BIOACTIVITY OF RS5444, A HIGH AFFINITY PPARγ SPECIFIC AGONIST 70 CHARACTERIZATION OF MOSER S HUMAN COLORECTAL CANCER CELLS 76 CHARACTERIZATION OF MOSER S CELLULAR PHYSIOLOGY UPON PPARγ ACTIVATION BY RS5444 77 viii RS5444 did not alter PPAR receptor abundance or transcriptional activity........77 Activation of PPAR caused inhibition of MOSER S anchorage-dependent and – independent growth.......................................................................................80 The anti-proliferative effect of RS5444 was irreversible ......................................87 Activation of PPAR by RS5444 inhibited invasiveness of MOSER S cells........87 FUNCTIONAL GENOMICS ANALYSIS OF RS5444 EFFECT ON MOSER S COLORECTAL CANCER CELLS 92 EXPERIMENTAL DESIGN OF MICROARRAY TIME COURSE EXPERIMENT 93 QUALITY CONTROL AND PREPROCESSING OF AFFY MICROARRAY DATA 96 Quality Control Step: Visual Inspection of CEL images.......................................96 Determination of Preprocessing Algorithm...........................................................99 Quality Control Step: Unsupervised Clustering .................................................106 Probe Set Filters...................................................................................................106 Analysis of Performance of Differential Expression Models..............................109 Differential Expression Analysis by empirical Bayes HotellingT2 score ...........113 Descriptive statistics of GCRMA summarized expression..................................115 Time course kinetic classes..................................................................................124 Ontology analysis of gene expression..................................................................124 IPA infers a DSCR1-calcineurin-NFATc