Dataset Information

Proteogenomic characterization of human colon and rectal cancer

ABSTRACT: Explore This Study at the NCI Proteomic Data Commons

Zhang, B., et al., Nature (2014) doi:10.1038/nature13438 Published online

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 Colon Adenocarcinoma (COAD) samples and 31 are from the Rectum Adenocarcinoma (READ) 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 here.
READ tumor sample genomic data can be downloaded from here.

Normal colon epithelium sample mass spectrometry data can be downloaded from here.
Mass spectrometry data for comparison and reference (CompRef) sample standards run with this study can be downloaded from here.
Peptide-Spectrum-Matches and Protein Reports from the CPTAC Common Data Analysis Pipeline (CDAP) can be downloaded from here.
Network analysis of this study can be viewed at the NetGestalt CRC Portal here.

This work was accomplished by the Proteome Characterization Center (PCC) at Vanderbilt University led by Dr. Daniel C. Liebler.

Dataset imported into MassIVE from https://cptac-data-portal.georgetown.edu/cptac/s/S022 on 08/26/19
Dataset source: https://pdc.esacinc.com/pdc/browse/filters/study_name:TCGA_Colon_Cancer_Proteome

INSTRUMENT(S): LTQ Orbitrap Velos

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Daniel C Liebler

PROVIDER: MSV000084238 | MassIVE | Mon Aug 26 14:03:00 BST 2019

SECONDARY ACCESSION(S): PXD015905

REPOSITORIES: MassIVE

ACCESS DATA

Publications

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>The goal of the CPTAC, TCGA Cancer Proteome Study of Colorectal Tissue is to analyze the proteomes of TCGA tumor samples that have been comprehensively characterized by molecular methods (<a href="http://www.ncbi.nlm.nih.gov/pubmed/22810696" target="_blank">Cancer Genome Atlas Network, Nature 2012</a>).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. This work was accomplished by the Proteome Characterization Center (PCC) at Vanderbilt University led by Dr. Daniel C. Liebler. Clinical data files contain both the human readable TCGA bar codes and the UUIDs for each sample.Complete Data Analysis from Vanderbilt University as published in Nature (Zhang, B., et al., Nature (2014) doi:10.1038/nature13438 Published online) is available <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S022">here</a>.Data available on this study page (peptide spectrum matches and protein reports) are from the CPTAC Common Data Analysis Pipeline.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>. Colon tissue samples (ascending and descending) were obtained from 30 patients. Each sample was analyzed with label free global proteomic profiling. These colon samples, while derived from colon cancer subjects, did not contain tumor. Samples were obtained from the <a href="http://www.vicc.org/jimayersinstitute" target="_blank">Jim Ayers Institute for Precancer Detection and Diagnosis.</a> Data sets below are labeled with the patient identification number and contain data for both ascending and descending tissue samples. Data from colon tumor samples are available in the <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S016" target="_blank">TCGA Colorectal Cancer study</a>.<ul><li>Dataset imported into MassIVE from <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S016">https://cptac-data-portal.georgetown.edu/cptac/s/S016</a> and <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S019">https://cptac-data-portal.georgetown.edu/cptac/s/S019</a> on 06/23/16</li><li>Dataset source: <a href="https://pdc.esacinc.com/pdc/browse/filters/study_name:TCGA_Colon_Cancer_Proteome">https://pdc.esacinc.com/pdc/browse/filters/study_name:TCGA_Colon_Cancer_Proteome</a></li></ul>

Project description:<a href="https://pdc.esacinc.com/pdc/browse/filters/study_name:TCGA_Ovarian_JHU_Glycoproteome|TCGA_Ovarian_JHU_Proteome|TCGA_Ovarian_PNNL_Proteome|TCGA_Ovarian_PNNL_Phosphoproteome_Velos_Qexatvive" target="_blank">Explore This Study at the NCI Proteomic Data Commons</a><a href="http://www.ncbi.nlm.nih.gov/pubmed/27372738" target="_blank">Zhang H, Liu T, Zhang Z, Payne SH, Zhang B, McDermott JE et al., Cell (2016), DOI: 10.1016/j.cell.2016.05.069, Published online June 29, 2016.</a>To provide a detailed analysis of the molecular components and underlying mechanisms associated with ovarian cancer, we performed a comprehensive mass-spectrometry-based proteomic characterization of 174 ovarian tumors previously analyzed by The Cancer Genome Atlas (TCGA), of which 169 were high-grade serous carcinomas (HGSCs). Integrating our proteomic measurements with the genomic data yielded a number of insights into disease, such as how different copy-number alternations influence the proteome, the proteins associated with chromosomal instability, the sets of signaling pathways that diverse genome rearrangements converge on, and the ones most associated with short overall survival. Specific protein acetylations associated with homologous recombination deficiency suggest a potential means for stratifying patients for therapy. In addition to providing a valuable resource, these findings provide a view of how the somatic genome drives the cancer proteome and associations between protein and post-translational modification levels and clinical outcomes in HGSC.Information on the complete TCGA Ovarian Serous Cystadenocarcinoma (OV) cohort can be found <a href="https://portal.gdc.cancer.gov/projects/TCGA-OV" target="_blank">here</a>. The Cancer Genome Atlas Research Network published on the Genomic characterization of the OV cohort in <a href="http://www.ncbi.nlm.nih.gov/pubmed/21720365" target="_blank">Nature</a> on June 30, 2011Genomic data for the 174 TCGA samples used in the CPTAC Proteome study 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-OV%22%5D%7D%7D%5D%7D" 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/S020" target="_blank">here</a>.<ul><li>Dataset imported into MassIVE from <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S026">https://cptac-data-portal.georgetown.edu/cptac/s/S026</a> on 08/28/19</li><li>Dataset source: <a href="https://pdc.esacinc.com/pdc/browse/filters/study_name:TCGA_Ovarian_JHU_Glycoproteome|TCGA_Ovarian_JHU_Proteome|TCGA_Ovarian_PNNL_Proteome|TCGA_Ovarian_PNNL_Phosphoproteome_Velos_Qexatvive" target="_blank">https://pdc.esacinc.com/pdc/browse/filters/study_name:...</a></li></ul>

Project description:<a href="https://pdc.esacinc.com/pdc/browse/filters/study_name:TCGA_Breast_Cancer_Proteome|TCGA_Breast_Cancer_Phosphoproteome" target="_blank">Explore This Study at the NCI Proteomic Data Commons</a>Global proteome and phosphoproteome data have been acquired for 105 TCGA breast cancer samples using iTRAQ (isobaric Tags for Relative and Absolute Quantification) protein quantification methods. Samples were selected from each of the 4 breast tumor subtypes (Luminal A, Luminal B, Basal-like, HER2-enriched) described in the publication, <a href="http://www.ncbi.nlm.nih.gov/pubmed/23000897" target="_blank">Comprehensive molecular portraits of human breast tumors (Cancer Genome Atlas Network, Nature 2012)</a>.Three TCGA samples and 1 common internal reference control sample are included in each iTRAQ experiment, consisting of 25 proteome and 13 phosphoproteome files. The internal reference is comprised of a mixture of 40 TCGA samples (of the 105 breast cancer samples) with equal representation of the 4 breast subtypes. Three of the TCGA samples have been assayed in duplicate for quality control purposes.05TCGA_AO-A12D-01A_AN-A04A-01A_BH-A0AV-01A_Proteome_BI iTRAQ proteome data were acquired twice, before (20130310) and after (20130416) maintenance of the Q Exactive MS system. The "20130416" dataset was used in the final publication (see <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S029" target="_blank">here</a>).Global proteome and phosphoproteome data were acquired for three normal breast samples in Experiment 37. Samples "263d3f-I", "blcdb9-I", and "c4155b-C" are normal breast tissue samples that were measured in the iTRAQ-114, -115, and -116 channels, respectively. All normal samples were compared to the internal reference sample in the iTRAQ-117 channel (see CPTAC, TCGA Breast Cancer iTRAQ Sample Mapping file below).Information on the complete TCGA Breast invasive carcinoma cohort (BRCA) can be found <a href="https://portal.gdc.cancer.gov/projects/TCGA-BRCA" target="_blank">here</a>. Genomic data for the 105 TCGA samples used in the CPTAC Proteome study 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-BRCA%22%5D%7D%7D%5D%7D" target="_blank">here</a>.<ul><li>Dataset imported into MassIVE from <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S015">https://cptac-data-portal.georgetown.edu/cptac/s/S015</a> on 10/15/18</li><li>Dataset source: <a href="https://pdc.esacinc.com/pdc/browse/filters/study_name:TCGA_Breast_Cancer_Proteome|TCGA_Breast_Cancer_Phosphoproteome" target="_blank">https://pdc.esacinc.com/pdc/browse/filters/study_name:...</a></li></ul>

Project description:<a href="https://pdc.esacinc.com/pdc/browse/filters/study_name:TCGA_Breast_Cancer_Proteome|TCGA_Breast_Cancer_Phosphoproteome" target="_blank">Explore This Study at the NCI Proteomic Data Commons</a><a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature18003.html" target="_blank">Mertins P, Mani DR, Ruggles KV, Gillette MA, Clauser KR, Wang P et al., Nature (2016) doi:10.1038/nature18003 Published online 25 May 2016</a>Somatic mutations have been extensively characterized in breast cancer, but the effects of these genetic alterations on the proteomic landscape remain poorly understood. Here we describe quantitative mass-spectrometry-based proteomic and phosphoproteomic analyses of 105 genomically annotated breast cancers, of which 77 provided high-quality data. Integrated analyses provided insights into the somatic cancer genome including the consequences of chromosomal loss, such as the 5q deletion characteristic of basal-like breast cancer. Interrogation of the 5q trans-effects against the Library of Integrated Network-based Cellular Signatures, connected loss of CETN3 and SKP1 to elevated expression of epidermal growth factor receptor (EGFR), and SKP1 loss also to increased SRC tyrosine kinase. Global proteomic data confirmed a stromal-enriched group of proteins in addition to basal and luminal clusters, and pathway analysis of the phosphoproteome identified a G-protein-coupled receptor cluster that was not readily identified at the mRNA level. In addition to ERBB2, other amplicon-associated highly phosphorylated kinases were identified, including CDK12, PAK1, PTK2, RIPK2 and TLK2. We demonstrate that proteogenomic analysis of breast cancer elucidates the functional consequences of somatic mutations, narrows candidate nominations for driver genes within large deletions and amplified regions, and identifies therapeutic targets.Global proteome and phosphoproteome data have been acquired for 105 TCGA breast cancer samples using iTRAQ (isobaric Tags for Relative and Absolute Quantification) protein quantification methods. Samples were selected from each of the 4 breast tumor subtypes (Luminal A, Luminal B, Basal-like, HER2-enriched) described in the publication, Comprehensive molecular portraits of human breast tumors (Cancer Genome Atlas Network, Nature 2012).Three TCGA samples and 1 common internal reference control sample are included in each iTRAQ experiment, consisting of 25 proteome and 13 phosphoproteome files. The internal reference is comprised of a mixture of 40 TCGA samples (of the 105 breast cancer samples) with equal representation of the 4 breast subtypes. Three of the TCGA samples have been assayed in duplicate for quality control purposes.05TCGA_AO-A12D-01A_AN-A04A-01A_BH-A0AV-01A_Proteome_BI iTRAQ proteome data were acquired twice, before (20130310) and after (20130416) maintenance of the Q Exactive MS system. The "20130416" dataset was used in the final publication. The replicate dataset 05TCGA_AO-A12D-01A_AN-A04A-01A_BH-A0AV-01A_Proteome_BI_20130310_Replicate can be obtained <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S015" target="_blank">here</a>.Global proteome and phosphoproteome data were acquired for three normal breast samples in Experiment 37. Samples "263d3f-I", "blcdb9-I", and "c4155b-C" are normal breast tissue samples that were measured in the iTRAQ-114, -115, and -116 channels, respectively. All normal samples were compared to the internal reference sample in the iTRAQ-117 channel (see CPTAC, TCGA Breast Cancer iTRAQ Sample Mapping file below).Additional supplementary datasets are provided below that were too large to store at Nature Journal: <ul><li>Gene-by-Gene CNA-RNA and CNA-Protein Pearson correlations with p-values and Benjamini-Hochberg adjusted p-values</li><li>Phosphoproteome dataset "Phosphoproteome-P3": This table contains phosphosite iTRAQ log2 ratios for the 83 QC-passed samples (77 tumors + 3 tumor replicates + 3 normal breast samples). Phosphosite abundances are normalized (see Supplementary Methods, "Normalization").</li><li>Phosphoproteome raw files and datasets for PIK3CA- and TP53-mutant isogenic cell lines (TMT10-plex quantification; see Supplementary Methods)</li><li>Proteome Peptide Spectrum Match reports exported from Spectrum Mill for each of the 37 iTRAQ4 experiments, including the RefSeq FASTA file used for searches, and a Spectrum Mill quality metrics report</li></ul>Information on the complete TCGA Breast invasive carcinoma cohort (BRCA) can be found <a href="https://portal.gdc.cancer.gov/projects/TCGA-BRCA" target="_blank">here</a>. Genomic data for the 105 TCGA samples used in the CPTAC Proteome study 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-BRCA%22%5D%7D%7D%5D%7D"target="_blank">here</a>.<ul><li>Dataset imported into MassIVE from <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S029">https://cptac-data-portal.georgetown.edu/cptac/s/S029</a> on 08/28/19</li><li>Dataset source: <a href="https://pdc.esacinc.com/pdc/browse/filters/study_name:TCGA_Breast_Cancer_Proteome|TCGA_Breast_Cancer_Phosphoproteome" target="_blank">https://pdc.esacinc.com/pdc/browse/filters/study_name:...</a></li></ul>

Project description:<a href="https://cptac-data-portal.georgetown.edu/study-summary/S056" target="_blank">Proteogenomics of Lung Adenocarcinoma, Gillette et al., 2020 publication is here</a> Lung cancer is a leading cause of cancer death in the United States and in 2019 it is estimated that there will be over 228,000 new cases (<a href="https://www.cancer.org/cancer/non-small-cell-lung-cancer/about/key-statistics.html" target="_blank">American Cancer Society</a>). There are two main types, small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). A majority of patients (85%) have NSCLC, with a significant portion of those individuals having a histological subtype lung adenocarcinoma (LUAD) <a href="https://www.ncbi.nlm.nih.gov/pubmed/29364287" target="_blank">Herbst et al., 2018 Nature</a>. To advance the proteogenomic understanding of LUAD, the CPTAC program has investigated 111 tumors, (with 102 tumors paired with normal adjacent tissue samples) and subjected these samples to global proteome and phosphoproteome analysis. An optimized workflow for mass spectrometry of tissues using isobaric tags (TMT (tandem mass tags)-10) was used (<a href="https://www.ncbi.nlm.nih.gov/pubmed/29988108" target="_blank">Mertins et al., Nature Protocols 2018</a>). Proteome and phosphoproteome data from the LUAD discovery cohort is available below along with peptide spectrum matches (PSMs) and protein summary reports from the CPTAC common data analysis pipeline (CDAP).Clinical Data for LUAD tumors are provided below. Updates will be available as the LUAD cohort characterization proceeds. Genomic Data for LUAD tumors is available from the NCI Genomic Data Commons (GDC), <a href="https://portal.gdc.cancer.gov/projects/CPTAC-3" target="_blank">here</a> Imaging Data for LUAD tumors is available from NCI, The Cancer Imaging Archive (TCIA), <a href="https://wiki.cancerimagingarchive.net/display/Public/CPTAC-LUAD" target="_blank">here</a> This release includes over 4500 files and 914 GB of data. <ul><li>Dataset imported into MassIVE from <a href="https://cptac-data-portal.georgetown.edu/study-summary/S046">https://cptac-data-portal.georgetown.edu/study-summary/S046</a> on 01/29/21</li></ul>

Dataset Information

Proteogenomic characterization of human colon and rectal cancer

Publications

Proteogenomic characterization of human colon and rectal cancer.

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