| GeneLibs

题目:: Pan-cancer network analysis identifies combinations of rare somatic mutations across pathways and protein complexes.
作者:: 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)
状态:: 发布时间2015-01-28 , 更新时间 2016-10-19
期刊:: Nat Genet
摘要:: 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.
语言:: eng
DOI:

文献库文献相关信息

DataTable pData

联系方式

微信公众号

文献库 文献相关信息

DataTable pData

联系方式

微信公众号

文献库文献相关信息