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Leiserson, Mark D M; Vandin, Fabio; Wu, Hsin-Ta; Dobson, Jason R; Eldridge, Jonathan V; Thomas, Jacob L; Papoutsaki, Alexandra; Kim, Younhun; Niu, Beifang; McLellan, Michael; Lawrence, Michael S; Gonzalez-Perez, Abel; Tamborero, David; Cheng, Yuwei; Ryslik, Gregory A; Lopez-Bigas, Nuria; Getz, Gad; Ding, Li; Raphael, Benjamin J
Nature genetics, 02/2015, Volume: 47, Issue: 2Journal Article
Cancers exhibit extensive mutational heterogeneity, and the resulting long-tail phenomenon complicates the discovery of genes and pathways that are significantly mutated in cancer. We perform a pan-cancer analysis of mutated networks in 3,281 samples from 12 cancer types from The Cancer Genome Atlas (TCGA) using HotNet2, a new algorithm to find mutated subnetworks that overcomes the limitations of existing single-gene, pathway and network approaches. We identify 16 significantly mutated subnetworks that comprise well-known cancer signaling pathways as well as subnetworks with less characterized roles in cancer, including cohesin, condensin and others. Many of these subnetworks exhibit co-occurring mutations across samples. These subnetworks contain dozens of genes with rare somatic mutations across multiple cancers; many of these genes have additional evidence supporting a role in cancer. By illuminating these rare combinations of mutations, pan-cancer network analyses provide a roadmap to investigate new diagnostic and therapeutic opportunities across cancer types.
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