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Proteogenomic characterization of human colon and rectal cancer.

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.

SUBMITTER: Zhang B

PROVIDER: S-EPMC4249766 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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Proteogenomic characterization of human colon and rectal cancer.

Zhang Bing B Wang Jing J Wang Xiaojing X Zhu Jing J Liu Qi Q Shi Zhiao Z Chambers Matthew C MC Zimmerman Lisa J LJ Shaddox Kent F KF Kim Sangtae S Davies Sherri R SR Wang Sean S Wang Pei P Kinsinger Christopher R CR Rivers Robert C RC Rodriguez Henry H Townsend R Reid RR Ellis Matthew J C MJ Carr Steven A SA Tabb David L DL Coffey Robert J RJ Slebos Robbert J C RJ Liebler Daniel C DC

Nature 20140720 7518

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 tu ...[more]

PMID: 25043054

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Project description:<a href="https://pdc.esacinc.com/pdc/browse/filters/study_name:TCGA_Colon_Cancer_Proteome" target="_blank">Explore This Study at the NCI Proteomic Data Commons</a><a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13438.html" target="_blank">Zhang, B., et al., Nature (2014) doi:10.1038/nature13438 Published online</a>Proteomes of colon and rectal tumors previously characterized by the Cancer Genome Atlas (TCGA) were analyzed along with integrated proteogenomic analyses. Ninety-five TCGA tumor samples were used in this study from 90 patients, with 5 samples representing different portions from the same tumor. The samples originated from two TCGA cohorts: 64 are from <a href="https://portal.gdc.cancer.gov/projects/TCGA-COAD" target="_blank">Colon Adenocarcinoma (COAD)</a> samples and 31 are from the <a href="https://portal.gdc.cancer.gov/projects/TCGA-READ" target="_blank">Rectum Adenocarcinoma (READ)</a> collection. The primary data from the liquid chromatography-tandem mass spectrometry (LC-MS/MS) global proteomic profiling of each tumor sample is associated with a data set in the table below. Three protein assemblies are provided from different protein database searches.TCGA_VU_N95 This assembly reflects the 95 TCGA samples for 90 tumors, spanning three search engines (MS-GF+, MyriMatch, and Pepitome), employing a standard RefSeq database and NIST spectral library.TCGA_VU_N95_Custom The Custom assembly represents the same samples, the sequence database has been augmented with nonsynonymous sequence variants detected by TCGA. TCGA_VU_N95-Normal_VU_N60 The third assembly contains the searches of the 95 TCGA samples employed in the first assembly alongside the 60 normal colons analyzed by Vanderbilt University as a control, employing the same three search engines, a standard RefSeq database, and a NIST spectral library.TCGA_Colorectal_Cancer_proBAM_PSM_genome_mapping_files Peptide spectrum matches from the TCGA_VU_N95_Custom IDPicker3 protein assembly were converted to protein BAM (proBAM) format for visualization, available in the metadata folder below.COAD tumor sample genomic data can be downloaded from <a href="https://portal.gdc.cancer.gov/legacy-archive/search/f?filters=%7B%22op%22:%22and%22,%22content%22:%5B%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22cases.project.program.name%22,%22value%22:%5B%22TCGA%22%5D%7D%7D,%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22cases.project.project_id%22,%22value%22:%5B%22TCGA-COAD%22%5D%7D%7D%5D%7D" target="_blank">here</a>. READ tumor sample genomic data can be downloaded from <a href="https://portal.gdc.cancer.gov/legacy-archive/search/f?filters=%7B%22op%22:%22and%22,%22content%22:%5B%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22cases.project.program.name%22,%22value%22:%5B%22TCGA%22%5D%7D%7D,%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22cases.project.project_id%22,%22value%22:%5B%22TCGA-READ%22%5D%7D%7D%5D%7D" target="_blank">here</a>. Normal colon epithelium sample mass spectrometry data can be downloaded from <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S019" target="_blank">here</a>. Mass spectrometry data for comparison and reference (CompRef) sample standards run with this study can be downloaded from <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S017" target="_blank">here</a>. Peptide-Spectrum-Matches and Protein Reports from the CPTAC Common Data Analysis Pipeline (CDAP) can be downloaded from <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S016" target="_blank">here</a>. Network analysis of this study can be viewed at the NetGestalt CRC Portal <a href="http://www.netgestalt.org/index.html" target="_blank">here</a>. This work was accomplished by the Proteome Characterization Center (PCC) at Vanderbilt University led by Dr. Daniel C. Liebler.<ul><li>Dataset imported into MassIVE from <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S022">https://cptac-data-portal.georgetown.edu/cptac/s/S022</a> on 08/26/19</li><li>Dataset source: <a href="https://pdc.esacinc.com/pdc/browse/filters/study_name:TCGA_Colon_Cancer_Proteome" target="_blank">https://pdc.esacinc.com/pdc/browse/filters/study_name:TCGA_Colon_Cancer_Proteome</a></li></ul>

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Proteogenomic characterization of human colon and rectal cancer.

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Proteogenomic characterization of human colon and rectal cancer.

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