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Abstract
Hallmark gene mutations shape cancer cell vulnerabilities and inform drug discovery1–3. A systematic map of hallmark gene mutation-defined cancer dependencies and therapeutic responses is essential to uncover novel targets and refine therapeutic strategies. Here, we present the first pan-cancer blueprint of hallmark vulnerabilities, systematically linking hallmark gene mutation markers to cancer cell dependencies and drug sensitivities across 22 cancer cohorts. We integrated multi-omics data from patient tumours with large-scale CRISPR-Cas9 screens and pharmacologic profiling of over a thousand cancer cell lines. Our analysis revealed the cancer type-specific nature of hallmark gene expression programs, uncovered previously unrecognised mutation-target gene dependencies, and highlighted metabolic programs as a dominant class of functional vulnerabilities. Notably, we identified oxidative phosphorylation (OXPHOS) addiction in CDKN2A-loss lung squamous cell carcinoma (LUSC) and experimentally validated this dependency. Our validation highlights the greater selectivity of CDKN2A-loss LUSC cells to metformin, an FDA-approved antidiabetic drug known for its OXPHOS inhibitory activity. Proteogenomic integration further prioritised targets overexpressed in mutant tumours, constituting therapeutic windows. Pharmacologic profiling identified both oncology and non-oncology agents with selective activity in mutation-defined subgroups, revealing opportunities for drug repurposing. Our machine learning framework, Comet-X, for the first time fully leveraged gene mutation combinations to predict these target dependencies and drug responses. The resulting pan-cancer mutation-dependency map provides a comprehensive resource of hallmark gene targets and candidate therapeutics, stratified by mutation markers, to pave the way for drug development, clinical trial design and discovery research.
Competing Interest Statement
The authors have declared no competing interest.
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