biostudies-literatureUnknown7(1)Karimpour MTarbiat Modares UniversityIran National Science FoundationSynthetic lethality offers a promising approach for developing effective therapeutic interventions in cancer when direct targeting of driver genes is impractical. In this study, we comprehensively analyzed large-scale CRISPR, shRNA, and PRISM screens to identify potential synthetic lethal (SL) interactions in pan-cancer and 12 individual cancer types, using a new computational framework that leverages the biological function and signaling pathway information of key driver genes to mitigate the confounding effects of background genetic alterations in different cancer cell lines. This approach has successfully identified several putative SL interactions, including <i>KRAS-MAP3K2</i> and <i>APC-TCF7L2</i> in pan cancer, and <i>CCND1-METTL1</i>, <i>TP53-FRS3</i>, <i>SMO-MDM2</i>, and <i>CCNE1-Life science alliancee202302268https://www.ebi.ac.uk/biostudies/studies/S-EPMC10589366biostudies-literaturePathway-driven analysis of synthetic lethal interactions in cancer using perturbation screens.PMC10589366Behmanesh MMontazeri HTotonchi MKarimpour MfalsePathway-driven analysis of synthetic lethal interactions in cancer using perturbation screens.Synthetic lethality offers a promising approach for developing effective therapeutic interventions in cancer when direct targeting of driver genes is impractical. In this study, we comprehensively analyzed large-scale CRISPR, shRNA, and PRISM screens to identify potential synthetic lethal (SL) interactions in pan-cancer and 12 individual cancer types, using a new computational framework that leverages the biological function and signaling pathway information of key driver genes to mitigate the confounding effects of background genetic alterations in different cancer cell lines. This approach has successfully identified several putative SL interactions, including <i>KRAS-MAP3K2</i> and <i>APC-TCF7L2</i> in pan cancer, and <i>CCND1-METTL1</i>, <i>TP53-FRS3</i>, <i>SMO-MDM2</i>, and <i>CCNE1-2024-01-01T00:00:00Z2024 Jan2025-04-22T17:24:33.153Z2025-04-06T02:09:55.359ZS-EPMC105893663786365110.26508/lsa.202302268