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

doi:10.1016/j.isci.2020.101079

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

iScience. 2020 Jun 26;23(6):101079. doi: 10.1016/j.isci.2020.101079. Epub 2020 Apr 18.

Authors

Stefani N Thomas¹, Betty Friedrich², Michael Schnaubelt¹, Daniel W Chan¹, Hui Zhang³, Ruedi Aebersold⁴

Affiliations

¹ Department of Pathology, Clinical Chemistry Division, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
² Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, Otto-Stern-Weg 3, 8093 Zürich, Switzerland.
³ Department of Pathology, Clinical Chemistry Division, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA. Electronic address: huizhang@jhu.edu.
⁴ Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, Otto-Stern-Weg 3, 8093 Zürich, Switzerland; Faculty of Science, University of Zürich, Zürich, Switzerland. Electronic address: aebersold@imsb.biol.ethz.ch.

Abstract

The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) established a harmonized method for large-scale clinical proteomic studies. SWATH-MS, an instance of data-independent acquisition (DIA) proteomic methods, is an alternate proteomic approach. In this study, we used SWATH-MS to analyze remnant peptides from the original retrospective TCGA samples generated for the CPTAC ovarian cancer proteogenomic study. The SWATH-MS results recapitulated the confident identification of differentially expressed proteins in enriched pathways associated with the robust Mesenchymal high-grade serous ovarian cancer subtype and the homologous recombination deficient tumors. Hence, SWATH/DIA-MS presents a promising complementary or orthogonal alternative to the CPTAC proteomic workflow, with the advantages of simpler and faster workflows and lower sample consumption, albeit with shallower proteome coverage. In summary, both analytical methods are suitable to characterize clinical samples, providing proteomic workflow alternatives for cancer researchers depending on the context-specific goals of the studies.

Keywords: Biological Sciences; Cancer Systems Biology; Proteomics.

Abstract

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