A pan-cancer analysis of prognostic genesl

被引：26

作者：

Anaya, Jordan ^{[1
,2
]}

Reon, Brian ^{[1
]}

Chen, Wei-Min ^{[3
,4
]}

Bekiranov, Stefan ^{[1
]}

Duna, Anindya ^{[1
]}

机构：

[1] Univ Virginia, Dept Biochem & Mol Genet, Charlottesville, VA USA

[2] Omnesres Com, Charlottesville, VA USA

[3] Univ Virginia, Ctr Publ Hlth Genom, Charlottesville, VA USA

[4] Univ Virginia, Biostat Sect, Dept Publ Hlth Sci, Charlottesville, VA USA

来源：

PEERJ | 2016年 / 4卷

关键词：

Cancer; RNA-SEQ; TCGA; Pan-cancer; Prognostic; Cox; Regression; mRNA; NETWORK ANALYSIS; LANDSCAPE; REGRESSION; DATABASE; MODELS; COMMON;

D O I：

10.7717/peerj.1499

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

070301 [无机化学]; 070403 [天体物理学]; 070507 [自然资源与国土空间规划学]; 090105 [作物生产系统与生态工程];

摘要：

Numerous studies have identified prognostic genes in individual cancers, but a thorough pan-cancer analysis has not been performed. In addition, previous studies have mostly used microarray data instead of RNA-SEQ, and have not published comprehensive lists of associations with survival. Using recently available RNA-SEQ and clinical data from The Cancer Genome Atlas for 6,495 patients, we have investigated every annotated and expressed gene's association with survival across 16 cancer types. The most statistically significant harmful and protective genes were not shared across cancers, but were enriched in distinct gene sets which were shared across certain groups of cancers. These groups of cancers were independently recapitulated by both unsupervised clustering of Cox coefficients (a measure of association with survival) for individual genes, and for gene programs. This analysis has revealed unappreciated commonalities among cancers which may provide insights into cancer pathogenesis and rationales for co-opting treatments between cancers.

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