CPTAC, TCGA Cancer Proteome Study of Ovarian Tissue
Ontology highlight
ABSTRACT:
Global proteome data have been acquired for 174 TCGA ovarian cancer tumor samples by 2 Proteome Characterization Centers (PCCs), Pacific Northwest National Laboratory (PNNL) and Johns Hopkins University (JHU). Both PCCs used iTRAQ (isobaric Tags for Relative and Absolute Quantification) protein quantification methods. Thirty-two of the 174 TCGA tumor samples were assayed at both sites yielding a total of 206 proteome characterizations. Glycoproteome (122 tumors) and phosphoproteome (69 tumors) analyses were also conducted, at JHU and PNNL respectively.
Information on the complete TCGA Ovarian Serous Cystadenocarcinoma (OV) cohort can be found here.
The Cancer Genome Atlas Research Network published on the Genomic characterization of the OV cohort in Nature on June 30, 2011
Genomic data for the 174 TCGA samples used in the CPTAC Proteome study can be downloaded from here.
OTHER RELATED OMICS DATASETS IN: phs000178.v6.p6PAe005191PAe005196PAe005192PAe005122PAe005304PAe005186PAe005188PRJNA225826
INSTRUMENT(S): LTQ Orbitrap Velos, Q Exactive
ORGANISM(S): Homo Sapiens (ncbitaxon:9606)
SUBMITTER: 
Richard Smith Hui Zhang
PROVIDER: MSV000084252 | MassIVE | Thu Aug 29 00:42:00 BST 2019
SECONDARY ACCESSION(S): PXD015903
REPOSITORIES: MassIVE
Publications
Integrated genomic analyses of ovarian carcinoma.
Nature 20110629 7353
A catalogue of molecular aberrations that cause ovarian cancer is critical for developing and deploying therapies that will improve patients' lives. The Cancer Genome Atlas project has analysed messenger RNA expression, microRNA expression, promoter methylation and DNA copy number in 489 high-grade serous ovarian adenocarcinomas and the DNA sequences of exons from coding genes in 316 of these tumours. Here we report that high-grade serous ovarian cancer is characterized by TP53 mutations in almo ...[more]
Similar Datasets
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><p><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></p><p>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.</p><p>TCGA_VU_N95<br/>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.</p><p>TCGA_VU_N95_Custom<br/>The Custom assembly represents the same samples, the sequence database has been augmented with nonsynonymous sequence variants detected by TCGA.<br/></p><p>TCGA_VU_N95-Normal_VU_N60<br/>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.</p><p>TCGA_Colorectal_Cancer_proBAM_PSM_genome_mapping_files<br/>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.</p><p>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>.<br/>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>.<br/></p><p>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>.<br/>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>.<br/>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>.<br/>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>.<br/><br/>This work was accomplished by the Proteome Characterization Center (PCC) at Vanderbilt University led by Dr. Daniel C. Liebler.</p><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>
2019-08-26 | MSV000084238 | MassIVE
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><p>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>).</p><p>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.</p><p>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>.</p><p>Data available on this study page (peptide spectrum matches and protein reports) are from the CPTAC Common Data Analysis Pipeline.</p><p>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>.<br/>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>.<br/><br/>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>.</p><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>
2016-06-23 | MSV000079852 | MassIVE
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><p><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></p><p>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.</p><p>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>.<br/>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, 2011</p><p>Genomic 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>.</p><p>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>.</p><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>
2019-08-28 | MSV000084246 | MassIVE
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><p>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>.</p><p>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.</p><p>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>).</p><p>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).</p><p>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>.<br/>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>.</p><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>
2018-10-18 | MSV000083043 | MassIVE
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><p><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></p><p>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.</p><p>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).</p><p>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.</p><p>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>.</p><p>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).</p><p>Additional supplementary datasets are provided below that were too large to store at Nature Journal:<br/><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></p><p>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>.<br/>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>.</p><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>
2019-08-28 | MSV000084248 | MassIVE
Project description:<p>Comparison and Reference (CompRef) Samples, initially characterized in the <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S010">System Suitability Study</a>, were analyzed along with the <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S016">TCGA colorectal cancer tumor samples</a> and with the <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S019">normal colon epithelium samples</a>. These interstitial CompRef experiments are global proteomic profiling of the P6 (luminal) and P5 (basal) human-in-mouse xenograft breast carcinoma pooled samples.</p><p>One CompRef sample was run after every 5 samples of TCGA colorectal cancer tumor tissue, alternating between the P6 and P5 CompRef samples to generate 20 total data sets (designated as 01CompRef_P6_VU through 20CompRef_P5_VU).</p><p>Twelve CompRef samples were run with the 30 normal colon epithelium samples to produce 12 data sets (designated as 21CompRef_P6_VU through 32CompRef_P5_VU).</p>These experiments were used to monitor the consistency of laboratory protocols and mass spectrometry instrument performance during the TCGA colorectal cancer analysis.<ul><li>Dataset imported into MassIVE from <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S017" target="_blank">https://cptac-data-portal.georgetown.edu/cptac/s/S017</a> on 08/31/18</li></ul>
2018-08-31 | MSV000082875 | MassIVE
Project description:<p><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><br><br>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).</p><p><em>Clinical Data</em> for LUAD tumors are provided below. Updates will be available as the LUAD cohort characterization proceeds.<br><em>Genomic Data</em> 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><br><em>Imaging Data</em> 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><br>This release includes over 4500 files and 914 GB of data.</p>
<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>
2021-02-01 | MSV000086793 | MassIVE
Project description:The objective of the Time-Dependent Proteome Study was to evaluate changes in the proteome and phosphoproteome when there is a delay in freezing tissues following sample (tumor) excision. The biospecimens used are from human-in-mouse breast cancer tumor samples.<br/><a href="http://www.ncbi.nlm.nih.gov/pubmed/24719451" target="_blank">Ref: Mertins P et al., (2014) Mol Cell Proteomics, Apr 9. E-Publication</a><ul><li>Dataset imported into MassIVE from <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S011">https://cptac-data-portal.georgetown.edu/cptac/s/S011</a> and <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S012">https://cptac-data-portal.georgetown.edu/cptac/s/S012</a> on 08/29/19</li></ul>
2019-08-30 | MSV000084260 | MassIVE
Project description:Comparison and Reference (CompRef) Samples, initially characterized in the <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S010" target="_blank">System Suitability Study</a>, were analyzed along with the TCGA Breast Cancer tumor samples. These 5 iTRAQ experiments include proteome and phosphoproteome interrogation of both the P5 (basal) and P6 (luminal) human-in-mouse xenograft breast carcinoma pooled samples. The CompRef experiments were intercalated between the TCGA Breast Cancer experiments to monitor the consistency of laboratory protocols and mass spectrometry instrument performance.<ul><li>Dataset imported into MassIVE from <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S018">https://cptac-data-portal.georgetown.edu/cptac/s/S018</a> on 08/25/19</li></ul>
2019-08-25 | MSV000084233 | MassIVE
Project description:<p>The objective of the Time-Dependent Proteome Study, was to evaluate changes in the proteome and phosphoproteome when there is a delay in freezing tissues following sample (tumor) excision. The biospecimens used are from patient-derived ovarian cancer tumors.<br><a href="http://www.ncbi.nlm.nih.gov/pubmed/24719451" target="_blank">Ref: Mertins P et al., (2014) Mol Cell Proteomics, Apr 9. E-Publication</a><br><a href="http://www.ncbi.nlm.nih.gov/pubmed/25670172" target="_blank">Ref: Gajadhar, A.S., et al., (2015) Cancer Res. Apr 1;75(7):1495-503. Epub 2015 Feb 10.</a></p><ul><li>Dataset imported into MassIVE from <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S013">https://cptac-data-portal.georgetown.edu/cptac/s/S013</a> on 11/05/18</li></ul>
2018-11-05 | MSV000083107 | MassIVE