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An Interrogation of ORF Versus Crispra Pooled-Screening Technologies Used to Define Cancer Drug-Resistance Landscapes

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An Interrogation of ORF Versus Crispra Pooled-Screening Technologies Used to Define Cancer Drug-Resistance Landscapes An Interrogation of ORF Versus CRISPRa Pooled-Screening Technologies Used to Define Cancer Drug-Resistance Landscapes. The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Goodale, Amy Brown. 2020. An Interrogation of ORF Versus CRISPRa Pooled-Screening Technologies Used to Define Cancer Drug- Resistance Landscapes.. Master's thesis, Harvard Extension School. Citable link https://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37364877 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA An Interrogation of ORF Versus CRISPRa Pooled -Screening Technologies Used To Define Cancer Drug-Resistance Landscapes. Amy Goodale A Thesis in the Field of Biotechnology for the Degree of Master of Liberal Arts in Extension Studies Harvard University March 2020 Copyright 2019 [Amy Goodale] Abstract Resistance to cancer therapies is an ever-present problem, and preemptively understanding the underlying genetic causes will improve patient care, help predict clinical response rates, and elucidate new drug targets. Within the last several years, studying the drug-resistance landscape of a cancer type has been made easier with two gain-of-function pooled genetic-screening systems – open reading frames (ORFs) and CRISPR activation (CRISPRa). The ORF and CRISPRa screening systems produce the same overexpression phenotypes, but with ORF technology the gene of interest is exogenously expressed as a cDNA. Although directed overexpression of single genes provides valuable information, the genes are expressed at non-physiological levels, which can cause artifacts and non-meaningful biological insights. CRISPRa technology has the advantage of activating the endogenous gene transcript, and its splice isoforms, while expanding the capacity to conduct large-scale genetic screens. Despite these differences between the two technologies, both have proven successful in unfolding some of the unknown mechanisms of drug-resistance in cancer. However, recent works have shown that the two gain-of-function mechanisms provide minimally concordant gene hit lists when screened in the same NRAS-mutant melanoma cell line. This study examines why the two technologies yield some discrepancies by generating follow-up, pooled ORF and CRISPRa libraries. These libraries contain the same set of genes hits from the primary screens, and secondary screens are performed in the same cell line. The data show that genes that were identified with only one of the methodologies in the primary screens, are confirmed more strongly with the same methodology in the secondary screens. Both ORF and CRISPRa validate the same percentage of gene hits, but unique sets of ‘ORF-only’ and ‘CRISPRa-only’ genes are defined. Follow-up assays show that certain genes do not emerge in an ORF screen because the ORF itself is lethal or is not expressed post-transduction. Other genes do not score with CRISPRa because the overall significance of the hit is decreased by averaging the magnitudes of all the sgRNAs for the gene. Altogether, the two activation systems produce distinctive results due to ineffective ORF and CRISPRa constructs, library design, and unaccountable biological factors specific to the cancer model of choice. Dedication I dedicate this work to my father, who shaped me into the scientist and person I am today. Missing you always. v Acknowledgments I would like to first thank Max Herman for the unconditional love and support throughout this entire process. I would like to extend my sincerest gratitude towards my incredible Thesis Director, Federica Piccioni. Thank you for everything, but most importantly, for all the laughs. This work could not have been completed without the amazing talents of Briana Fritchman, Desiree Hernandez, Nicole Persky, Marissa Feeley, and Mudra Hegde. Thank you for helping me on this journey. Finally, thank you to John Doench and David Root for extending me the offer to complete this project in the Genetic Perturbation Platform at the Broad Institute. It has been a wonderful six years. vi Table of Contents Dedication ................................................................................................................................. v! Acknowledgments ................................................................................................................... vi! List of Figures ......................................................................................................................... ix! Chapter I. Introduction............................................................................................................. 1! Combating Cancer Drug Resistance and Identifying New Therapies ...................... 1! Pooled Genetic Screens to Study Cancer Drug Resistance ...................................... 3! Overexpression Perturbation Technologies ............................................................... 5! Overexpression Screens in the Context of a MEK Inhibitor .................................. 11! Comparing ORF versus CRISPRa............................................................................ 12! Chapter II. Materials and Methods ....................................................................................... 14! Cell Culture ................................................................................................................ 14! Secondary Library Generation .................................................................................. 15! Lentivirus Production and Titering .......................................................................... 17! CRISPRa cell line generation and activity testing .................................................. 20! Secondary Library Viral Titrations .......................................................................... 21! Secondary ORF and CRISPRa Screens ................................................................... 22! Genomic DNA Isolation, PCR and Sequencing ...................................................... 23! V5 Immunoassay ....................................................................................................... 26! CRISPRa sgRNA Cloning and Western Blots for Gene Activation ...................... 28! Chapter III. Results ................................................................................................................ 32! vii Comparing Gene Hits Lists from Primary ORF and CRISPRa Screens ................ 32! Designing the Secondary Libraries .......................................................................... 37! Assay Development for Secondary CRISPRa Screen............................................. 41! Post-Screen Assessment ............................................................................................ 44! Quality Control Analyses of the Secondary Screening Data .................................. 49! Analysis of Secondary Screening Data .................................................................... 55! Chapter IV. Discussion .......................................................................................................... 70! References .............................................................................................................................. 77! viii List of Figures Figure 1. Schematic representation of a pooled, positive-selection drug screen. ................ 5! Figure 2. Schematic representation of the CRISPR-Cas9 system. ....................................... 8! Figure 3. Schematic representation of the CRISPRa Calabrese system. ............................ 10! Figure 4. Comparing genome-wide primary screens shows minimal overlap. .................. 34! Figure 5. Distribution of primary screen fold-changes by hit type. .................................... 36! Figure 6. Primary screen fold-changes for constructs of representative genes. ................. 37! Figure 7. Secondary screen design and analysis scheme. ................................................... 38! Figure 8. Alignment of the truncated ORF and wild-type NRAS sequences. ................... 40! Figure 9. Schematic representation of the dCas9-VP64 vector. ......................................... 41! Figure 10. Gene expression is activated with CRISPRa in MelJuso. ................................. 43! Figure 11. Titration results of the secondary ORF and CRISPRa lentiviral libraries. ...... 44! Figure 12. Schematic representation of secondary ORF and CRISPRa screens. .............. 46! Figure 13. Cumulative population doublings of MelJuso during secondary screens. ....... 47! Figure 14. gDNA samples were successfully amplified by PCR. ...................................... 49! Figure 15. All samples recovered sufficient sequencing reads. .......................................... 51! Figure 16. Not all ORFs are successfully represented in the screen................................... 52! Figure 17. Replicates of secondary screens show strong pairwise correlations. ............... 54! Figure 18. Non-targeting control sgRNAs show minimal fold-change.............................. 55! Figure 19. Volcano plots of secondary screens. ................................................................... 57! ix Figure 20. Trametinib and Selumetinib treatments are highly correlated across secondary screens....................................................................................................................................
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