Abstract C039: A pan-cancer map of paralog dependencies reveals novel synthetic lethal targets and biomarker-defined vulnerabilities

Abstract Background: Synthetic lethality offers a powerful strategy for precision cancer therapy by exploiting vulnerabilities in gene-gene interactions. Unlike single-gene perturbations, many therapeutics – such as CDK4/6 inhibitors – target paralogous proteins, suggesting that synthetic lethal nodes might be composed of gene-pairs that share redundant or compensatory functions. Historically, efforts to identify synthetic lethal relationships have relied on correlating single-gene dependencies with gene expression profiles across panels of cancer models. However, this correlative approach is non-experimental in nature and may miss important synthetic lethal pairs, especially when the number of models harboring loss of one gene in the pair is limited. Systematic and experimental interrogation is thus essential to uncover these vulnerabilities. Identifying such interactions, along with their associated biomarkers, provides a foundation for the development of novel combinatorial therapies targeting oncogenic drivers, tumor-suppressor and passenger gene deletions. Methods: To systematically map paralog dependencies, we performed large-scale digenic CRISPR screens across 240 diverse cancer models spanning 17 lineages. Our library targets 4,546 single genes and 7,644 gene pairs encompassing druggable targets and their extended networks. Each gene is targeted with 6 sgRNAs, and each gene-pair with 18 sgRNA combinations – constituting the most comprehensive digenic CRISPR library to date. Each Cas9-expressing cancer model was transduced at low multiplicity of infection with ∼500x sgRNA coverage, and cellular fitness assessed at screen day 21. Results: Leveraging an adapted version of the Chronos pipeline optimized for inferring gene-pair interactions, we identified 65 pan-essential paralog pairs, as well as numerous context-specific paralog dependencies associated with genetic alterations, lineage features and expression profiles. Among these, the INTS6/INTS6L pair emerged as a novel paralog synthetic lethal interaction, with INTS6L representing a targetable vulnerability in tumors including prostate cancer that are co-deficient for INTS6 and RB1 – a finding we validated in vitro and in vivo. We further uncovered strong dependency on KRAS/NRAS activity in FGFR-fusion cancers, which exhibit marked sensitivity to the pan-RAS inhibitor RMC-6236 and to the combination of RMC-6236 and the FGFR2 inhibitor RLY-4008 which synergistically enhanced antiproliferative effects in these models. Conclusions: This study presents a systematic and high-resolution map of paralog dependencies across cancer, uncovering novel synthetic lethal interactions and biomarker-associated vulnerabilities. By expanding functional genomic screens to paralog pairs, we unveil a new dimension of cancer dependencies. These insights provide a valuable foundation for the rational development of next-generation therapeutic strategies that harness genetic redundancy and synthetic lethality – offering new precision oncology opportunities for tumors currently lacking effective targeted therapies. Citation Format: Jayu Jen, Yao He, Dennie T. Frederick, Alex Marzoratti, Sean Chen, Tanay Thakar, Alan Zhang, Arianny Acosta, Guangyan Li, Baomou Feng, Mira Chokshi, Alison Liu, Alina Guo, Devishi Kesar, Diego Rodriguez, Nancy Jung, Zaid Bayyat, William R. Sellers. A pan-cancer map of paralog dependencies reveals novel synthetic lethal targets and biomarker-defined vulnerabilities [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2025 Oct 22-26; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2025;24(10 Suppl):Abstract nr C039.