Identification of Thioredoxin-Interacting Protein as a Potential Mediator of Anoikis- Resistance in Ovarian Cancer THESIS Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University By Douglas Michael Spaeth-Cook Jr. Graduate Program in Public Health The Ohio State University 2017 Master's Examination Committee: Courtney Hebert, Advisor Randi Foraker James Chen Copyright by Douglas Michael Spaeth-Cook Jr. 2017 Abstract Epithelial ovarian cancer (EOC) is most commonly diagnosed at advanced stages, resulting in poor prognoses. Unlike most cancers, EOC does not typically spread hematogenously or lymphatically, opting instead for passive diffusion into the peritoneal cavity. This paper proposes a model that simulates the transition from primary tumor to disseminated disease using adherent and non-adherent cell culture conditions. Temporal transcriptomic analysis was performed on a well-studied ovarian cancer cell line that was subjected to this model. This resulted in the identification of TXNIP as a primary gene of interest. To validate the significance of this gene, a TXNIP knockdown cell line was developed using shRNA. Spheroid formation of the knockdown cell line in vitro was analyzed qualitatively and quantitatively using live-cell imaging. The knockdown was found to exhibit an anoikis-resistant phenotype. To assess prognostic relevance of the gene, the TCGA ovarian cancer dataset was queried for differences in patient survival outcomes based on categorization of high or low TXNIP expression in tumor samples, relative to median expression, at the time of initial surgery. High TXNIP expression was found to correlate significantly with longer overall and progression free survival in early stage patients. The same was not true for late stage patients. To assess the effect of platinum agents on TXNIP, carboplatin was used to treat three ovarian cancer cell lines grown in non-adherent conditions for 48 hours. Western blots confirmed that 100 nM ii carboplatin did not affect TXNIP expression at 48 hours. The findings of this paper lead us to believe that TXNIP is a potential mediator of anoikis-resistance in ovarian cancer. iii Dedication This document is dedicated to Jason and Joel David. iv Acknowledgments I would like to thank everyone in the Hays, Chen, Strohecker, and Pollock labs. I could not have completed this project without the help you have given me over the past two years. A special thank you to John Hays and James Chen for your mentorship, guidance, and understanding. Thank you to Courtney Hebert for advising me academically and participating on my thesis committee. Thank you to Randi Foraker for participating on my thesis examination committee and for instructing me in epidemiology. Thank you to James Gentry. Thank you to everyone working on the 5th floor at BRT. Thank you to John Hays and James Chen for assisting me with the methods and analyses presented in this paper. Thank you to Mark Burch for developing the outlier identification technique used in this paper. v Vita June 2007 .......................................................Bexley High School 2012................................................................B.A. Chemistry, Miami University 2013 ...............................................................B.S. Pharmaceutical Sciences, The Ohio State University 2015 to present ..............................................Graduate Research Associate, Department of Biomedical Informatics, The Ohio State University Publications Chen JL, David J, Cook-Spaeth D, Casey S, Cohen D, Selvendiran K, et al. Autophagy Induction Results in Enhanced Anoikis Resistance in Models of Peritoneal Disease. Mol Cancer Res. 2017 Jan;15(1):26–34. Fields of Study Major Field: Public Health Specialization: Biomedical Informatics vi Table of Contents Abstract ............................................................................................................................... ii Dedication .......................................................................................................................... iv Acknowledgments............................................................................................................... v Vita ..................................................................................................................................... vi Publications ........................................................................................................................ vi Fields of Study ................................................................................................................... vi List of Tables ................................................................................................................... viii List of Figures .................................................................................................................... ix Chapter 1: Introduction ....................................................................................................... 1 Chapter 2: Background ....................................................................................................... 2 Chapter 3: Methods ........................................................................................................... 11 Chapter 4: Results ............................................................................................................. 20 Chapter 5: Discussion ....................................................................................................... 24 References: ........................................................................................................................ 29 Appendix A: Tables and Figures ...................................................................................... 32 vii List of Tables Table 1: Images acquired per experiment ......................................................................... 49 Table 2: Results of t-tests .................................................................................................. 50 viii List of Figures Figure 1: Model of peritoneal metastasis .......................................................................... 32 Figure 2: Overview of study design .................................................................................. 33 Figure 3: Z-stack generated with confocal microscopy .................................................... 34 Figure 4: Example of pixel masking ................................................................................. 35 Figure 5: Image analysis workflow................................................................................... 36 Figure 6: ImageJ macro .................................................................................................... 37 Figure 7: Inter-experimental variability in non-adherent conditions ................................ 38 Figure 8: Averages of total spheroid area versus time ...................................................... 39 Figure 9: Beeswarm plots ................................................................................................. 40 Figure 10: Clustering ........................................................................................................ 41 Figure 11: TXNIP mRNA expression versus time in non-adherent conditions. .............. 42 Figure 12: Western blots of knockdown versus control ................................................... 43 Figure 13: Three-dimensional reconstruction of HeyA8 spheroids. ................................. 44 Figure 14: Comparisons of knockdown and control at 48 hours ...................................... 45 Figure 15: Plot of confluency versus time for knockdown and control ............................ 46 Figure 16: Kaplan-Meier plots .......................................................................................... 47 Figure 17: Western blot showing effect of carboplatin on TXNIP expression................. 48 ix Chapter 1: Introduction Currently, there are no effective population-wide screening methods for epithelial ovarian cancer (EOC). Consequently, EOC is most commonly diagnosed at advanced stages. Most EOC patients present with ascites and the disease is known to disseminate via the peritoneal cavity, leading to peritoneal carcinomatosis and metastasis. To aid in the identification of new targeted therapies that increase survival rates, the development of realistic in vitro models of EOC progression are necessary. This paper proposes a model that simulates the transition from primary tumor to disseminated disease using adherent and non-adherent cell culture conditions. In this study, we use temporal transcriptomic analysis to sort genes into clusters and identify outlying genes which we then investigate further. We hypothesized that these outlying genes would play a modulatory role in anoikis-resistance mechanisms in the early stages of tumorsphere formation. The aims of this study are to: 1) refine an in vitro model of ovarian cancer metastasis, 2) use bioinformatics methods to identify potential drivers of anoikis-resistance in ovarian cancer, 3) develop imaging techniques to study tumorsphere formation and growth kinetics, and 4) validate findings using in vitro experiments. 1 Chapter 2: Background Ovarian Cancer Epidemiology Ovarian cancer (OC) is a deadly, heterogeneous disease. According to results from the National Cancer Institute’s Surveillance, Epidemiology, and End Results Program