Literature DB >> 31308250

Integration and Analysis of CPTAC Proteomics Data in the Context of Cancer Genomics in the cBioPortal.

Pamela Wu1,2,3, Zachary J Heins4, James T Muller3, Lizabeth Katsnelson3, Ino de Bruijn4, Adam A Abeshouse4, Nikolaus Schultz4,5, David Fenyö6,2, Jianjiong Gao7,5.   

Abstract

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) has produced extensive mass spectrometry-based proteomics data for selected breast, colon, and ovarian tumors from The Cancer Genome Atlas (TCGA). We have incorporated the CPTAC proteomics data into the cBioPortal to support easy exploration and integrative analysis of these proteomic datasets in the context of the clinical and genomics data from the same tumors. cBioPortal is an open source platform for exploring, visualizing, and analyzing multidimensional cancer genomics and clinical data. The public instance of the cBioPortal (http://cbioportal.org/) hosts more than 200 cancer genomics studies, including all of the data from TCGA. Its biologist-friendly interface provides many rich analysis features, including a graphical summary of gene-level data across multiple platforms, correlation analysis between genes or other data types, survival analysis, and per-patient data visualization. Here, we present the integration of the CPTAC mass spectrometry-based proteomics data into the cBioPortal, consisting of 77 breast, 95 colorectal, and 174 ovarian tumors that already have been profiled by TCGA for mutations, copy number alterations, gene expression, and DNA methylation. As a result, the CPTAC data can now be easily explored and analyzed in the cBioPortal in the context of clinical and genomics data. By integrating CPTAC data into cBioPortal, limitations of TCGA proteomics array data can be overcome while also providing a user-friendly web interface, a web API, and an R client to query the mass spectrometry data together with genomic, epigenomic, and clinical data.
© 2019 Wu et al.

Entities:  

Keywords:  Cancer Biology; Cancer Biomarker(s); Mass Spectrometry; Phosphoproteome; Proteogenomics

Mesh:

Year:  2019        PMID: 31308250      PMCID: PMC6731080          DOI: 10.1074/mcp.TIR119.001673

Source DB:  PubMed          Journal:  Mol Cell Proteomics        ISSN: 1535-9476            Impact factor:   5.911


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