Credentialing individual samples for proteogenomic analysis

Wei Zhao, Jun Li, Rehan Akbani, Han Liang, Gordon B. Mills

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

An integrated analysis of DNA, RNA and protein, so called proteogenomic studies, has the potential to greatly increase our understanding of both normal physiology and disease development. However, such studies are challenged by a lack of a systematic approach to credential individual samples resulting in the introduction of noise into the system that limits the ability to identify important biological signals. Indeed, a recent proteogenomic CPTAC study identified 26% of samples as unsatisfactory, resulting in a marked increase in cost and loss of information content. Based on a large-scale analysis of RNA-seq and proteomic data generated by reverse phase protein arrays (RPPA) and by mass spectrometry, we propose a protein-mRNA correlation-based (PMC) score as a robust metric to credential single samples for integrated proteogenomic studies. Samples with high PMC scores have significantly higher protein-mRNA correlation, total protein content and tumor purity. Our results highlight the importance of credentialing individual samples prior to proteogenomic analysis.

Original languageEnglish (US)
Pages (from-to)1515-1530
Number of pages16
JournalMolecular and Cellular Proteomics
Volume17
Issue number8
DOIs
StatePublished - Aug 2018
Externally publishedYes

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biochemistry
  • Molecular Biology

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