Abstract
Abstract Interpreting cancer genomes requires a broad understanding of the composition and organization of cellular processes under selective pressure for mutations. Here, we integrate systematic screens for protein interaction with tumor genetic analysis to elucidate a multiscale hierarchical map of 378 protein systems recurrently altered in one or more cancer types. Diverse gene mutations converge on commonly mutated systems, from small protein complexes in specific tumor types to large molecular assemblies and organelles disrupted in most cancers. Unexpected findings include collagen structural alterations with significant prognostic value; mutations impacting the desmosome in 65% melanomas; complexes related to splicing and DNA repair; and an expanded actomyosin cluster involving PIK3CA. The map implicates 556 cancer genes, many well supported by functional assays, including canonical genes implicated in new tissues (e.g., BRCA1/2 mutations in bladder cancer). This work explains mutational heterogeneity as a collection of convergence points across scales of cell biology. This abstract is also being presented as Poster B52. Citation Format: Fan Zheng, Keiichiro Ono, Erica Silva, Danielle Swaney, Minkyu Kim, Julia Shangguan, Dexter Pratt, Xiaolin Nan, Nevan Krogan, Trey Ideker. A multiscale map of recurrently mutated systems in cancer [abstract]. In: Proceedings of the AACR Special Conference on the Evolving Landscape of Cancer Modeling; 2020 Mar 2-5; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2020;80(11 Suppl):Abstract nr PR14.
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