Abstract 2139: Enabling cancer drug target discovery through genome-scale identification of synthetic lethal paralog pairs
Authors: Phoebe C. Parrish, James D. Thomas, Shriya Kamlapurkar, Robert K. Bradley, Alice H. Berger
Journal: Cancer Research (2021)

Abstract Genome-scale CRISPR-Cas9 screens have enabled the identification of essential genes that can serve as cancer drug targets. However, single-gene knockout screens frequently underestimate the essentiality of paralogs, ancestrally duplicated genes that often functionally compensate for one another's loss; we have observed this directly in single-gene CRISPR screen data from a lung cancer cell line (P &amp;lt; 1E-16). Since the human genome is highly duplicated, our ability to identify novel drug targets is greatly limited. To identify paralog pairs essential for cancer cell survival, we developed a multiplexed CRISPR approach that uses paired guide RNAs to knock out human paralogs individually and in pairs. Our library includes 2,060 paralogs (1,030 pairs); the largest human paralog CRISPR library to date. We screened lung adenocarcinoma (PC9) and cervical carcinoma (HeLa) cell lines to identify synthetic lethal paralogs which have minimal growth effects when targeted individually but whose simultaneous loss leads to severely decreased growth. We found that 128 (16%) of the paralog pairs in our study were synthetic lethal and essential in at least one cell line. Gene set enrichment analysis revealed that our top paralogs are overrepresented in pathways related to cell cycle regulation, protein secretion, DNA repair, and PI3K-AKT signaling (FDR q-value &amp;lt; 2.52E-4). Importantly, 15 (18%) synthetic lethal paralog pairs have at least one member that is currently druggable. We validated our screen results using in vitro competition assays and DepMap CRISPR data analysis. For known synthetic lethal paralogs MAGOH and MAGOHB, competition assay data confirmed significantly reduced growth in the dual gene knockout condition versus single-gene knockouts (P &amp;lt; 0.05) and analysis of DepMap CRISPR score correlation with paralog expression showed that MAGOHB is more essential in cell lines with low MAGOH expression (P &amp;lt; 4.6E-41). For novel synthetic lethal paralogs CCNL1/CCNL2, PSMB5/PSMB8, and OXSR1/STK39, DepMap CRISPR score vs. expression correlation analysis again confirmed our findings as cell lines with low expression of paralog 1 showed lower CRISPR scores when paralog 2 was knocked out (P &amp;lt; 1.2E-8 for each pair), suggesting that our novel synthetic lethal paralogs are essential across a range of cancer cell lines. These interactions are also being validated via competition assay, and CRISPR knockout efficiency will be confirmed via Western blot and genomic DNA sequencing. Our studies point to a number of novel synthetic lethal paralogs that could serve as lung cancer drug targets. These paralogs could be targeted alone or in combination with existing therapies to suppress lung cancer growth and prevent acquired drug resistance. Paralog synthetic lethal therapies could make a major impact on clinical care by improving patient outcomes. Citation Format: Phoebe C. Parrish, James D. Thomas, Shriya Kamlapurkar, Robert K. Bradley, Alice H. Berger. Enabling cancer drug target discovery through genome-scale identification of synthetic lethal paralog pairs [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2139.