Proteogenomic characterization of human colon and rectal cancer

Bing Zhang, Jing Wang, Xiaojing Wang, Jing Zhu, Qi Liu, Zhiao Shi, Matthew C. Chambers, Lisa J. Zimmerman, Kent F. Shaddox, Sangtae Kim, Sherri R. Davies, Sean Wang, Pei Wang, Christopher R. Kinsinger, Robert C. Rivers, Henry Rodriguez, R. Reid Townsend, Matthew J.C. Ellis, Steven A. Carr, David L. TabbRobert J. Coffey, Robbert J.C. Slebos, Daniel C. Liebler, Michael A. Gillette, Karl R. Klauser, Eric Kuhn, D. R. Mani, Philipp Mertins, Karen A. Ketchum, Amanda G. Paulovich, Jeffrey R. Whiteaker, Nathan J. Edwards, Peter B. McGarvey, Subha Madhavan, Daniel Chan, Akhilesh Pandey, Ie Ming Shih, Hui Zhang, Zhen Zhang, Heng Zhu, Gordon A. Whiteley, Steven J. Skates, Forest M. White, Douglas A. Levine, Emily S. Boja, Tara Hiltke, Mehdi Mesri, Kenna M. Shaw, Stephen E. Stein, David Fenyo, Tao Liu, Jason E. McDermott, Samuel H. Payne, Karin D. Rodland, Richard D. Smith, Paul Rudnick, Michael Snyder, Yingming Zhao, Xian Chen, David F. Ransohoff, Andrew N. Hoofnagle, Melinda E. Sanders, Yue Wang, Li Ding

Research output: Contribution to journalArticlepeer-review

1056 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)382-387
Number of pages6
Issue number7518
StatePublished - Sep 18 2014
Externally publishedYes

ASJC Scopus subject areas

  • General


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