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A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
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Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
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Updated: Jul 19, 2025

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
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Proteogenomic data and resources for pan-cancer analysis.

Yize Li1, Yongchao Dou2, Felipe Da Veiga Leprevost3

  • 1Department of Medicine, Washington University in St. Louis, St. Louis, MO 63130, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63130, USA.

Cancer Cell
|August 15, 2023
PubMed
Summary

The National Cancer Institute

Keywords:
CPTACdata harmonizationmulti-omicsopen datapan-cancerproteogenomics

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Area of Science:

  • Oncology
  • Genomics
  • Proteomics
  • Bioinformatics

Background:

  • The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) generates multi-omics data to link genomic changes to cancer.
  • Understanding cancer requires integrating diverse data types like genomics and proteomics.

Purpose of the Study:

  • To create a harmonized, pan-cancer dataset for over 1000 tumors across 10 cohorts.
  • To facilitate multi-omics data integration and analysis for cancer research.
  • To support biological discoveries through comprehensive proteogenomic data.

Main Methods:

  • Harmonization of genomic, transcriptomic, proteomic, and clinical data.
  • Generation of a large-scale, multi-cohort dataset (>1000 tumors).
  • Development of data dissemination and computational resources.

Main Results:

  • A cohesive and powerful dataset for pan-cancer investigations has been generated.
  • Efforts in data harmonization and dissemination by the CPTAC pan-cancer working group are outlined.
  • Computational resources are being provided to aid biological discoveries.

Conclusions:

  • The harmonized multi-omics dataset enables comprehensive pan-cancer research.
  • Addressing challenges in multi-omics data integration, particularly with proteomics data, is crucial.
  • CPTAC's efforts advance the understanding of cancer through proteogenomics.