Orthogonal Proteomic Platforms and Their Implications for the Stable Classification of High-Grade Serous Ovarian Cancer Subtypes

Stefani N. Thomas, Betty Friedrich, Michael Schnaubelt, Daniel W. Chan, Hui Zhang, Ruedi Aebersold

Research output: Contribution to journalArticle

Abstract

The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) has established a two-dimensional liquid chromatography-tandem mass spectrometry (2DLC-MS/MS) workflow using isobaric tagging to compare protein abundance across samples. The workflow has been used for large-scale clinical proteomic studies with deep proteomic coverage within and outside of CPTAC. SWATH-MS, an instance of data-independent acquisition (DIA) proteomic methods, was recently developed as an alternate proteomic approach. In this study, we analyzed remaining aliquots of peptides using SWATH-MS from the original retrospective TCGA samples generated for the CPTAC ovarian cancer proteogenomic study (Zhang et al., 2016). The SWATH-MS results indicated that both methods confidently identified differentially expressed proteins in enriched pathways associated with the robust Mesenchymal subtype of high-grade serous ovarian cancer (HGSOC) and the homologous recombination deficient tumors also present in the original study. The results demonstrated that SWATH/DIA-MS presents a promising complementary or orthogonal alternative to the CPTAC harmonized proteomic method, with the advantages of simpler, faster, and cheaper workflows, as well as lower sample consumption. However, the SWATH/DIA-MS workflow resulted in shallower proteome coverage. Overall, we concluded that both analytical methods are suitable to characterize clinical samples such as in the high-grade serous ovarian cancer study, providing proteomic workflow alternatives for cancer researchers depending on the specific goals and context of the studies.
Original languageEnglish (US)
Article number101079
JournaliScience
Volume23
Issue number6
DOIs
StatePublished - Jun 26 2020

Keywords

  • Biological Sciences
  • Cancer Systems Biology
  • Proteomics

PubMed: MeSH publication types

  • Journal Article

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