Synthetic lethality represents a promising therapeutic approach in precision oncology, exploiting genetic vulnerabilities that are exclusive to tumor cells while sparing normal tissues. By targeting non-oncogenic partners of mutated genes that cancers become dependent on, synthetic lethal interactions provide a strategy to selectively kill cancer cells. Here we present SLAYER (Synthetic Lethality AnalYsis for Enhanced taRgeted therapy), a computational pipeline that enables systematic identification and exploration of synthetic lethal interactions (SLIs) by integrating cancer genomic data and genome-wide CRISPR knockout screens. SLAYER associates the DepMap genome-wide CRISPR viability profiles across 808 cancer cell lines with derived gene mutations and mutation-associated pathway enrichment scores to identify potential SLIs. Among the predicted SLIs, inhibition of the aryl hydrocarbon receptor (AhR) was identified as synthetically lethal with RB1 mutations in bladder cancer. We experimentally validated this finding using a commercial AhR inhibitor drug in RB1-proficient and RB1-mutant bladder cancer cell lines. Interestingly, the SLI appears to be indirect, suggesting the RB1 mutational landscape rewires cellular dependencies that confer susceptibility to AhR inhibition during tumor evolution. Our SLAYER framework provides an integrated approach to systematically predict and prioritize synthetic lethal candidates for experimental testing and clinical translation.
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Cohen et al. (2024) studied this question.
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