Abstract 2278: Expanding cancer therapy options by leveraging synthetic lethal interactions between druggable paralogs

Abstract

Abstract Synthetic lethal therapies are a promising approach to expand therapeutic options for cancer patients. Since synthetic lethal therapies target tumor cells specifically, they have fewer off-target effects than oncogene targeted approaches. To identify new cancer drug targets, we focused on paralogs, ancestrally-duplicated genes that frequently retain redundant or overlapping functions. To find synthetic lethal human paralogs, we developed paired guide RNAs for Paralog gENetic interaction mapping (pgPEN), a pooled CRISPR-Cas9 single and double knockout approach targeting over 2,000 paralogs. We applied pgPEN to two cancer cell lines and found that 12% of human paralogs exhibit synthetic lethality in at least one context. To our knowledge, pgPEN represents the largest experimental assessment of human paralog synthetic lethality to date. We next identified paralog pairs to prioritize for follow-up study. A key drawback to synthetic lethal therapies is that many genetic interactions are context-dependent. To identify likely penetrant interactions, we compared our data to other published paralog screens and computational predictions of paralog synthetic lethality. We found that over 75% (n=96) of pgPEN hits were predicted to be broadly synthetic lethal, and nearly 10% (n=10) of pairs were synthetic lethal in multiple paralog screens. Finally, we prioritized paralogs targeted by existing small molecule therapies. Of the 122 synthetic lethal pairs identified by pgPEN, 16% (n=20) are currently druggable. We mined drug repurposing data from DepMap to find pairs where a paralog-targeting drug showed a stronger effect in cell lines with low target gene copy number or expression relative to cell lines with normal target gene copy number or expression. These drugs could selectively target cancer cells in cases where one or both paralogs is lost in tumors but retained in normal tissue. We also leveraged The Cancer Genome Atlas tumor sequencing data to find paralog pairs where one member is recurrently lost in cancer. Taken together, these studies identify druggable, highly penetrant synthetic lethal paralog interactions. In combination with tumor sequencing data, we identify high-priority paralog drug targets that can be further tested and translated to the clinic. Paralog synthetic lethal therapies could provide a relatively low-toxicity therapeutic approach to improve the efficacy of cancer treatments and prevent the emergence of acquired resistance. Citation Format: Phoebe C. Parrish, James D. Thomas, Austin M. Gabel, Shriya Kamlapurkar, Robert K. Bradley, Alice H. Berger. Expanding cancer therapy options by leveraging synthetic lethal interactions between druggable paralogs [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2278.