Abstract
SummaryThe 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.
Highlights
Advances in sample preparation workflows, mass spectrometry instrumentation, and data processing software have positioned proteomics to provide comprehensive insights into complex biological processes at a level close to the underlying biochemical mechanisms
We used SWATH-MS to analyze remnant peptides from the original retrospective The Cancer Genome Atlas (TCGA) samples generated for the Clinical Proteomic Tumor Analysis Consortium (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
Summary
Advances in sample preparation workflows, mass spectrometry instrumentation, and data processing software have positioned proteomics to provide comprehensive insights into complex biological processes at a level close to the underlying biochemical mechanisms. The workflows for many of these large-scale proteomic studies entail extensive offline fractionation of the peptides generated from enzymatically digested proteins, followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Because each fraction analyzed typically requires 1–5 mg of total peptides, the required quantity of the original tissue sample is in the milligram level. More rapid proteomic workflows have been developed (Anagnostopoulos et al, 2017; Hebert et al, 2014; Kulak et al, 2014; Richards et al, 2015), they have not yet been deployed for large-scale clinical proteomic studies
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