dc.contributor.author | White, Forest M. | |
dc.date.accessioned | 2015-10-30T18:27:35Z | |
dc.date.available | 2015-10-30T18:27:35Z | |
dc.date.issued | 2014-07 | |
dc.date.submitted | 2013-09 | |
dc.identifier.issn | 0028-0836 | |
dc.identifier.issn | 1476-4687 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/99534 | |
dc.description.abstract | Extensive genomic characterization of human cancers presents the problem of inference from genomic abnormalities to cancer phenotypes. To address this problem, we analysed proteomes of colon and rectal tumours characterized previously by The Cancer Genome Atlas (TCGA) and perform integrated proteogenomic analyses. Somatic variants displayed reduced protein abundance compared to germline variants. Messenger RNA transcript abundance did not reliably predict protein abundance differences between tumours. Proteomics identified five proteomic subtypes in the TCGA cohort, two of which overlapped with the TCGA ‘microsatellite instability/CpG island methylation phenotype’ transcriptomic subtype, but had distinct mutation, methylation and protein expression patterns associated with different clinical outcomes. Although copy number alterations showed strong cis- and trans-effects on mRNA abundance, relatively few of these extend to the protein level. Thus, proteomics data enabled prioritization of candidate driver genes. The chromosome 20q amplicon was associated with the largest global changes at both mRNA and protein levels; proteomics data highlighted potential 20q candidates, including HNF4A (hepatocyte nuclear factor 4, alpha), TOMM34 (translocase of outer mitochondrial membrane 34) and SRC (SRC proto-oncogene, non-receptor tyrosine kinase). Integrated proteogenomic analysis provides functional context to interpret genomic abnormalities and affords a new paradigm for understanding cancer biology. | en_US |
dc.description.sponsorship | National Cancer Institute (U.S.). Clinical Proteomic Tumor Analysis Consortium (Award U24CA159988) | en_US |
dc.description.sponsorship | National Cancer Institute (U.S.). Clinical Proteomic Tumor Analysis Consortium (Award U24CA160035) | en_US |
dc.description.sponsorship | National Cancer Institute (U.S.). Clinical Proteomic Tumor Analysis Consortium (Award U24CA160034) | en_US |
dc.description.sponsorship | National Cancer Institute (U.S.). Specialized Program of Research Excellence (Award P50CA095103) | en_US |
dc.description.sponsorship | National Cancer Institute (U.S.) (Cancer Center Support Grant P30CA068485) | en_US |
dc.description.sponsorship | National Institutes of Health (U.S.) (Grant GM088822) | en_US |
dc.description.sponsorship | Leidos Biomedical Research, Inc. (Contract 13XS029) | en_US |
dc.language.iso | en_US | |
dc.publisher | Nature Publishing Group | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1038/nature13438 | en_US |
dc.rights | Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. | en_US |
dc.source | PMC | en_US |
dc.title | Proteogenomic characterization of human colon and rectal cancer | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Zhang, Bing, Jing Wang, Xiaojing Wang, Jing Zhu, Qi Liu, Zhiao Shi, Matthew C. Chambers, et al. “Proteogenomic Characterization of Human Colon and Rectal Cancer.” Nature 513, no. 7518 (July 20, 2014): 382–387. | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Biological Engineering | en_US |
dc.contributor.mitauthor | White, Forest M. | en_US |
dc.relation.journal | Nature | en_US |
dc.eprint.version | Author's final manuscript | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dspace.orderedauthors | Zhang, Bing; Wang, Jing; Wang, Xiaojing; Zhu, Jing; Liu, Qi; Shi, Zhiao; Chambers, Matthew C.; Zimmerman, Lisa J.; Shaddox, Kent F.; Kim, Sangtae; Davies, Sherri R.; Wang, Sean; Wang, Pei; Kinsinger, Christopher R.; Rivers, Robert C.; Rodriguez, Henry; Townsend, R. Reid; Ellis, Matthew J. C.; Carr, Steven A.; Tabb, David L.; Coffey, Robert J.; Slebos, Robbert J. C.; Liebler, Daniel C.; Carr, Steven A.; Gillette, Michael A.; Klauser, Karl R.; Kuhn, Eric; Mani, D. R.; Mertins, Philipp; Ketchum, Karen A.; Paulovich, Amanda G.; Whiteaker, Jeffrey R.; Edwards, Nathan J.; McGarvey, Peter B.; Madhavan, Subha; Wang, Pei; Chan, Daniel; Pandey, Akhilesh; Shih, Ie-Ming; Zhang, Hui; Zhang, Zhen; Zhu, Heng; Whiteley, Gordon A.; Skates, Steven J.; White, Forest M.; Levine, Douglas A.; Boja, Emily S.; Kinsinger, Christopher R.; Hiltke, Tara; Mesri, Mehdi; Rivers, Robert C.; Rodriguez, Henry; Shaw, Kenna M.; Stein, Stephen E.; Fenyo, David; Liu, Tao; McDermott, Jason E.; Payne, Samuel H.; Rodland, Karin D.; Smith, Richard D.; Rudnick, Paul; Snyder, Michael; Zhao, Yingming; Chen, Xian; Ransohoff, David F.; Hoofnagle, Andrew N.; Liebler, Daniel C.; Sanders, Melinda E.; Shi, Zhiao; Slebos, Robbert J. C.; Tabb, David L.; Zhang, Bing; Zimmerman, Lisa J.; Wang, Yue; Davies, Sherri R.; Ding, Li; Ellis, Matthew J. C.; Reid Townsend, R. | en_US |
dc.identifier.orcid | https://orcid.org/0000-0002-1545-1651 | |
mit.license | PUBLISHER_POLICY | en_US |
mit.metadata.status | Complete | |