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A pan-cancer analysis of prognostic genes

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 recen...

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Autores principales: Anaya, Jordan, Reon, Brian, Chen, Wei-Min, Bekiranov, Stefan, Dutta, Anindya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4815555/
https://www.ncbi.nlm.nih.gov/pubmed/27047702
http://dx.doi.org/10.7717/peerj.1499
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author Anaya, Jordan
Reon, Brian
Chen, Wei-Min
Bekiranov, Stefan
Dutta, Anindya
author_facet Anaya, Jordan
Reon, Brian
Chen, Wei-Min
Bekiranov, Stefan
Dutta, Anindya
author_sort Anaya, Jordan
collection PubMed
description 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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spelling pubmed-48155552016-04-04 A pan-cancer analysis of prognostic genes Anaya, Jordan Reon, Brian Chen, Wei-Min Bekiranov, Stefan Dutta, Anindya PeerJ Bioinformatics 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. PeerJ Inc. 2016-02-16 /pmc/articles/PMC4815555/ /pubmed/27047702 http://dx.doi.org/10.7717/peerj.1499 Text en © 2016 Anaya http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Anaya, Jordan
Reon, Brian
Chen, Wei-Min
Bekiranov, Stefan
Dutta, Anindya
A pan-cancer analysis of prognostic genes
title A pan-cancer analysis of prognostic genes
title_full A pan-cancer analysis of prognostic genes
title_fullStr A pan-cancer analysis of prognostic genes
title_full_unstemmed A pan-cancer analysis of prognostic genes
title_short A pan-cancer analysis of prognostic genes
title_sort pan-cancer analysis of prognostic genes
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4815555/
https://www.ncbi.nlm.nih.gov/pubmed/27047702
http://dx.doi.org/10.7717/peerj.1499
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