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UC San Francisco Electronic Theses and Dissertations UCSF UC San Francisco Electronic Theses and Dissertations Title The genetics of splicing in cancer Permalink https://escholarship.org/uc/item/0sr370mt Author Chen, Justin Publication Date 2014 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California Copyright 2014 by Justin W. Chen ii To the most incredible women in my life: Alana, Darlene, and Yvonne iii ACKNOWLEDGEMENTS This work could not have been done without the assistance and support from countless people, some of whom I’d like to thank here. First and foremost, is my thesis adviser, Bill Weiss. Bill has constantly encouraged me to follow the data and has never tried to pigeon‐hole me into a particular project or avenue of thought. His support has allowed me to explore problems and pose my own solutions to questions I was interested in, and not just what interested him. I owe my growth as a scientist directly to his mentorship. Similarly, my thesis committee members Davide Ruggero and Joe Costello have dispensed helpful advice throughout my graduate career as they both served on my qualifying committee, and Joe was gracious enough to let spend a quarter in his lab as a rotation student. Many Weiss Lab members, both past and present, have contributed directly and indirectly to my thesis. Chris Hackett got the ball rolling before I was even thinking about graduate school by setting up the modifier screen and harvesting tissues. Chris was a great example of what a graduate student should strive to be, and I have tried to emulate him whenever possible. Clay Gustafson has been a tremendous colleague and mentor as well. Even though we work on drastically different projects, he has been very generous with his time and has made a strong effort to think critically about experimental difficulties I’ve faced along the way. Along with Chris, I have enjoyed commiserating with my fellow graduate students in the lab, Jasmine Lau and Justin Meyerowitz. Christine Cheng and Robyn Wong have been a big help whenever I’ve needed a little technical assistance. I’ve also been fortunate enough to be able to pick the brains of several scientists who have come through the lab: Miller Huang, Shirin Ilkhanizadeh, Anders Persson, Erin Simonds, and Fredrik Swartling. iv Scientists outside of the lab have made a fantastic support group throughout the years. Kasia Skrzypczynska has remained a steadfast neighbor in the outer sunset, and Robyn Mills, Julie VanderMeer, and Mike Sachs have been terrific friends. Stacy Musone and Bani Tamraz were the first grad students I got to know before I even knew I wanted to go to grad school, and we’ve kept in touch over the years. I also probably would not have gone to grad school had Pui Kwok not taken a chance on hiring me as a technician in his lab and in the process reinvigorating my interest in science. My co‐ed basketball team, Busta Buckets, never quite made it to the playoffs, but I’ve enjoyed my time on the hardcourt with fellow BMSers (and affiliates) Leonard Chavez, Nicole and Ian Galloway, Karen Ring, Noelle Huskey, Krister Barkovich, Lionel Lim, and Pankaj Sahai. There’s nothing like escaping the lab like getting destroyed in the paint! I cannot thank my family (and my near‐family, Ken) too much for all of the support they have afforded me throughout the years. My sister Darlene, a fantastic immunologist in her own right, has been a wonderful scientific sounding board despite our disparate scientific backgrounds. I am supremely fortunate to have been able to meet, date, and marry my wife Alana during graduate school. She has been completely understanding of the long hours and random scientific conversations that sometimes occur when we’re in the presence of other scientists. Together, we have a wonderful dog, a Golden‐Retriever and Yellow Labrador mix named Starbuck who never fails to greet me with a wagging tail. She is the best remedy for a long day in the lab. v CONTRIBUTIONS Chapter 1 is taken directly from a manuscript written as a review and has been published online in advance of print: Chen J and Weiss WA. “Alternative Splicing in Cancer: Implications for Biology and Therapy.” Oncogene. Advance Online Publication (2014) doi:10.1038/onc.2013.570 Chapters 2 and 4 are taken from a manuscript that is currently in submission: “The Genetics of Splicing in Neuroblastoma” by Justin Chen, Christopher S. Hackett, Shile Zhang, Young K. Song, Robert J.A. Bell, Annette Molinaro, David A. Quigley, Allan Balmain, Jun S. Song, Joseph F. Costello, W. Clay Gustafson, Terry Van Dyke, Pui‐Yan Kwok, Javed Khan, and William A. Weiss. Chapter 3 is modified from this same manuscript: Christopher Hackett set up the initial backcrossed modifier screen and harvested the SCG and CB. He also genotyped the mice with the help of Pui‐Yan Kwok’s lab and ran exon arrays on the SCG with the assistance of Young Song in Javed Khan’s lab with arrays provided by Terry Van Dyke. David Quigley in Allan Balmain’s lab provided the eQTL software used in this analysis. Shile Zhang provided RNA‐Seq data on human neuroblastoma patients. Rob Bell in Jun Song's lab provided somatic mutation calls from TCGA GBM samples and ran my scripts on the germline variants. Annette Molinaro provided statistical support. Clay Gustafson provided helpful experimental insights and William Weiss oversaw the project. I have performed all other experiments and wrote the manuscript. vi ABSTRACT Alternative splicing plays critical roles in normal development and can promote growth and survival in cancer. Genes that have canonical splice variants that function antagonistically can be ectopically expressed to drive malignant progression. Additionally, aberrant splicing, the production of noncanonical and cancer‐specific mRNA transcripts, can lead to loss‐of‐function in tumor suppressors or activation of oncogenes and cancer pathways. Emerging data suggests that aberrant splicing products and loss of canonically spliced variants correlate with stage and progression in malignancy. Not only do these data illuminate roles for alternative splicing in cancer and intersections between alternative splicing pathways and therapy, but they illustrate the importance of understanding the genetic basis of splicing. Using a transgenic model of neuroblastoma, we set up a backcrossed genetic system to derive distinct virtual genomes of over 100 individual mice in which we have profiled exon expression in two different neural tissues. We identified splicing quantitative trait loci (sQTL) which map genetic control of splicing and define key splicing motifs. We identify these motifs as sites of recurrent somatic mutations in cancer. We also use this analysis to identify novel effector splicing events. Among these, we show that a triplet splicing event within FUBP1 modulates levels of the MYC oncoprotein in human neuroblastoma‐derived cell line, and correlates with outcome in neuroblastoma. vii TABLE OF CONTENTS ACKNOWLEDGEMENTS ................................................................................................................ iv CONTRIBUTIONS ........................................................................................................................ vi ABSTRACT ................................................................................................................................. vii TABLE OF CONTENTS ................................................................................................................... viii LIST OF TABLES .......................................................................................................................... ix LIST OF FIGURES ......................................................................................................................... x CHAPTER 1: INTRODUCTION ........................................................................................................ 1 CHAPTER 2: THE GENETICS OF SPLICING IN NEUROBLASTOMA .......................................................... 29 CHAPTER 3: DISCUSSION AND CONCLUSIONS ................................................................................. 50 CHAPTER 4: MATERIALS AND METHODS ....................................................................................... 55 REFERENCES ............................................................................................................................... 67 APPENDICES ............................................................................................................................... 85 LIBRARY RELEASE ....................................................................................................................... 176 viii LIST OF TABLES TABLE 2.1: RECURRENT GENES WITH SPLICING MOTIF MUTATIONS ................................................... 42 TABLE 4.1: GENOTYPING MARKERS ............................................................................................... 62 APPENDIX A: CB CIS‐SQTL ........................................................................................................... 85 APPENDIX B: SCG CIS‐SQTL ......................................................................................................... 121 APPENDIX C: TRANS‐SQTL ........................................................................................................... 160 APPENDIX D: DIFFERENTIALLY EXPRESSED GENES ON CHR 10 BETWEEN RS13480474 AND RS38621064 168 APPENDIX E: DIFFERENTIALLY EXPRESSED GENES ON CHR X BETWEEN RS33478059 AND RS13483805 169 APPENDIX
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