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EBV) Variations, Mirnas, and Ebers in Ebl, AML and Across Cancers University of Massachusetts Medical School eScholarship@UMMS GSBS Dissertations and Theses Graduate School of Biomedical Sciences 2019-04-30 Comprehensive Computational Assessment And Evaluation of Epstein Barr virus (EBV) Variations, miRNAs, And EBERs in eBL, AML And Across Cancers Mercedeh J. Movassagh University of Massachusetts Medical School Let us know how access to this document benefits ou.y Follow this and additional works at: https://escholarship.umassmed.edu/gsbs_diss Part of the Computational Biology Commons, Disease Modeling Commons, Genomics Commons, Immune System Diseases Commons, Translational Medical Research Commons, and the Virus Diseases Commons Repository Citation Movassagh MJ. (2019). Comprehensive Computational Assessment And Evaluation of Epstein Barr virus (EBV) Variations, miRNAs, And EBERs in eBL, AML And Across Cancers. GSBS Dissertations and Theses. https://doi.org/10.13028/nfs6-2431. Retrieved from https://escholarship.umassmed.edu/gsbs_diss/1022 Creative Commons License This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License This material is brought to you by eScholarship@UMMS. It has been accepted for inclusion in GSBS Dissertations and Theses by an authorized administrator of eScholarship@UMMS. For more information, please contact [email protected]. Comprehensive computational assessment and evaluation of Epstein Barr virus (EBV) variations, miRNAs, and EBERs in eBL, AML and across cancers A Dissertation Presented By MERCEDEH JAVANBAKHT MOVASSAGH Submitted to the Faculty of the University Of Massachusetts Graduate School Of Biomedical Sciences, Worcester in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY April 30th, 2018 i Comprehensive computational assessment and evaluation of EBV variations, miRNAs and EBERs in eBL, AML and across cancers A Dissertation Presented By MERCEDEH JAVANBAKHT MOVASSAGH The signatures of the Dissertation Defense Committee signify completion and approval as to style and content of the Dissertation _____________________________________________ Jeffrey Bailey, M.D., Ph.D, Thesis Advisor ___________________________________________ Lucio Castilla, Ph.D, Member of Committee _____________________________________________ Sean Ryder, Ph.D., Member of Committee _____________________________________________ Eleanor Karlson, Ph.D., Member of Committee _____________________________________________ David Wald, M.D., Ph.D., External Member of Committee The signature of the Chair of the Committee signifies that the written dissertation meets the requirements of the Dissertation Committee _____________________________________________ Zhiping Weng, Ph.D., Member of Committee The signature of the Dean of the Graduate School of Biomedical Sciences signifies that the student has met all graduation requirements of the school. _____________________________________________ Mary Ellen Lane, Ph.D., Dean of the Graduate School of Biomedical Sciences Program in Bioinformatics and Integrative Biology April 30th, 2016 ii DEDICATION This thesis is dedicated to my husband Arjan van der Velde, my best friend, my partner in life who was by my side throughout the last 3 years of my PhD. This thesis is also dedicated to my parents Farivar Movassagh and Janet Hassanpour, who have supported me tremendously emotionally throughout all of the years of my life and held my hand with love and my aunt Rana Mazandarani who has always been there for me through thick and thin. iii ACKNOWLEDGEMENTS This thesis would not have been possible without the support of my family, classmates, bioinformatic department at UMASS and guidance of my advisor Dr. Jeffrey Bailey. Many thanks to my husband Arjan van der Velde, who was always by my side. I was also very lucky to have a wonderful committee who was extremely helpful and gave me an intellectually very nourishing experience at UMASS. Hence, I would like to thank Dr. Zhiping Weng, Dr. Sean Ryder, Dr. Lucio Castilla and Dr. Eleanor Karlsson for being such wonderful TRAC committee members. Adittionally, I would like to thank my current and previous collegues. I list each of them in no particular order. Ozkan Aydemir PhD, Cliff Odour PhD, Yasin Kaymaz PhD, Nicholas Hathaway, Patrick Marsh, Deborah Chin, and Peter Owuor. The support from my friends and classmates at UMASS was unimaginiable during my PhD both scientifically and emotionally. I would like to name a few of these people although I know there are many more. Jenniffer Eunmi Moon, Shirley Xue Li, Micheal Purcaro, Kathleen Morrill, Elisa Donrad PhD, Jake Gellatly, Jooyoung Lee, Houda Belaghzal, Betul Akgol, Menna Albarqi, Kashfia Neherin, Pryia Saikumar, Kyvan Dang, Brent Horowitz, Pranitha Vangala, Kellie Alexander, Oscar Duan and Serkan Sayin. I would also like to thank Dr. Ann Moormann for sharing her samples and her immense input/help in the immunology portion of my thesis. Catherine Forconi PhD, for being so open about teaching me a lot of immunology facts while being so nice about it. A special thanks to Dr. Zhiping Weng for letting me use her iv cluster at UMASS and being so hospitable when my lab moved to Brown. I would like to also thank the department administrators Heidi Beberman and Christine Tonevski for all their kindness and effors. A big thanks to Dr. Sean Ryder for being an inspirational professor intellectualy through my course work and rotation at UMASS. Finally, thanks to my PI, Jeff Bailey who supported me and helped steer me through my PhD and taught me a lot of scientific skills, intellectual insight and writing skills. v Abstract Viruses are known to be associated with 20% of human cancers. Epstein Barr virus (EBV) in particular is the first virus associated with human cancers. Here, we computationally detect EBV and explore the effects of this virus across cancers by taking advantage of the fact that EBV microRNAs (miRNAs) and Epstein Barr virus small RNAs (EBERs) are expressed at all viral latencies. We identify and characterize two sub-populations of EBV positive tumors: those with high levels of EBV miRNA and EBERS expression and those with medium levels of expression. Based on principal component analysis (PCA) and hierarchical clustering of viral miRNAs across all samples we observe a pattern of expression for these EBV miRNAs which is correlated with both the tumor cell type (B cell versus epithelial cell) and with the overall levels of expression of these miRNAs. We further investigated the effect of the levels of EBV miRNAs with the overall survival of patients across cancers. Through Kaplan Meier survival analysis we observe a significant correlation with levels of EBV miRNAs and lower survival in adult AML patients. We also designed a machine learning model for risk assessment of EBV in association with adult AML and other clinical factors. Our next aim was to identify targets of EBV miRNAs, hence, we used a combination of previously known methodologies for miRNA target detection in vi addition to a multivariable regression approach to identify targets of these viral miRNAs in stomach cancer. Finally, we investigate the variations across EBV subtype specific EBNA3C gene which interacts with the host immune system. Preliminary data suggests potential regional variations plus higher pathogenicity of subtype 1 in comparison to subtype 2 EBV. Overall, these studies further our understanding of how EBV manipulates the tumor microenvironment across cancer subtypes. vii Table of Contents Comprehensive computational assessment and evaluation of EBV variations, miRNAs and EBERs in eBL, AML and across cancers .............................................................. i DEDICATION ........................................................................................................................................ ii ACKNOWLEDGEMENTS .................................................................................................................. iii Abstract ................................................................................................................................................. v Table of Contents ............................................................................................................................. vii List of Figures .................................................................................................................................... ix List of Tables ...................................................................................................................................... xi List of Copyrighted Material Produced by Author ............................................................. xiii List of Third Party Copyrighted Material ............................................................................... xiv I CHAPTER I: Introduction .............................................................................................................. 1 I.1 Preface ............................................................................................................................................ 1 I.2 Introduction .................................................................................................................................. 1 I.2.1 Epstein Barr Virus (EBV) ................................................................................................................ 1 I.2.2 EBV and Overall Malignancies and Ailments ...................................................................... 3 I.2.3 Non-coding RNAs and EBV ............................................................................................................
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