期刊
NATURE GENETICS
卷 47, 期 2, 页码 106-114出版社
NATURE PUBLISHING GROUP
DOI: 10.1038/ng.3168
关键词
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资金
- US National Science Foundation (NSF) [IIS-1016648]
- US National Institutes of Health (NIH) [R01HG005690, R01HG007069, R01CA180776]
- National Human Genome Research Institute (NHGRI) grant [U01HG006517]
- Career Award at the Scientific Interface from the Burroughs Wellcome Fund
- Alfred P. Sloan Research Fellowship
- NSF CAREER Award [CCF-1053753]
- NSF fellowship GRFP [DGE 0228243]
- NHGRI of the US NIH
- Ellison Foundation
- Dana-Farber Cancer Institute Strategic Initiative
- ICREA Funding Source: Custom
- Direct For Computer & Info Scie & Enginr
- Division of Computing and Communication Foundations [1053753] Funding Source: National Science Foundation
- Direct For Computer & Info Scie & Enginr
- Div Of Information & Intelligent Systems [1016648] Funding Source: National Science Foundation
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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