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:10.1101/793026

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 journal › Article › peer-review

19 Scopus citations

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.

Original language	English (US)
Article number	101079
Journal	iScience
Volume	23
Issue number	6
DOIs	https://doi.org/10.1101/793026 https://doi.org/10.1016/j.isci.2020.101079
State	Published - Jun 26 2020

Bibliographical note

Funding Information:
We acknowledge contributions from Vlad Petyuk who provided scripts and methods from the previously published CPTAC study. We also thank Ludovic Gillet, Isabell Bludau, Ben Collins, and the computational proteomics team at ETH Zürich for their important contributions in discussions. We are grateful to Sciex (Christie Hunter, Mark Cafazzo, and George Manning) for the 5600+ TripleTOF mass spectrometer and access to open-source SWATH data processing software. Funding for the study was provided by the United States National Cancer Institute Clinical Proteomic Tumor Analysis Consortium (NCI CPTAC, U24CA160036 and U24CA210985 to H.Z. and D.W.C.) and the Early Detection Research Network (NCI EDRN, U01CA152813 to H.Z and R. A.) , the European Research Council, European Union ( AdG-233226 Proteomics v.3.0 and AdG-670821 Proteomics 4D to R.A.), and the Swiss National Science Foundation, European Union (grant 31003A_166435 to R.A.).

Publisher Copyright:
© 2020 The Author(s)

Keywords

Biological Sciences
Cancer Systems Biology
Proteomics

PubMed: MeSH publication types

Journal Article

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Publisher link

Find It

Find It at U of M Libraries

Cite this

@article{7e79c844f6e04f3a9f5c855cc8d4e426,

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

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",

author = "Thomas, {Stefani N.} and Betty Friedrich and Michael Schnaubelt and Chan, {Daniel W.} and Hui Zhang and Ruedi Aebersold",

note = "Funding Information: We acknowledge contributions from Vlad Petyuk who provided scripts and methods from the previously published CPTAC study. We also thank Ludovic Gillet, Isabell Bludau, Ben Collins, and the computational proteomics team at ETH Z{\"u}rich for their important contributions in discussions. We are grateful to Sciex (Christie Hunter, Mark Cafazzo, and George Manning) for the 5600+ TripleTOF mass spectrometer and access to open-source SWATH data processing software. Funding for the study was provided by the United States National Cancer Institute Clinical Proteomic Tumor Analysis Consortium (NCI CPTAC, U24CA160036 and U24CA210985 to H.Z. and D.W.C.) and the Early Detection Research Network (NCI EDRN, U01CA152813 to H.Z and R. A.) , the European Research Council, European Union ( AdG-233226 Proteomics v.3.0 and AdG-670821 Proteomics 4D to R.A.), and the Swiss National Science Foundation, European Union (grant 31003A_166435 to R.A.). Publisher Copyright: {\textcopyright} 2020 The Author(s)",

year = "2020",

month = jun,

day = "26",

doi = "10.1101/793026",

language = "English (US)",

volume = "23",

journal = "iScience",

issn = "2589-0042",

publisher = "Elsevier Inc.",

number = "6",

}

TY - JOUR

T1 - Orthogonal Proteomic Platforms and Their Implications for the Stable Classification of High-Grade Serous Ovarian Cancer Subtypes

AU - Thomas, Stefani N.

AU - Friedrich, Betty

AU - Schnaubelt, Michael

AU - Chan, Daniel W.

AU - Zhang, Hui

AU - Aebersold, Ruedi

N1 - Funding Information: We acknowledge contributions from Vlad Petyuk who provided scripts and methods from the previously published CPTAC study. We also thank Ludovic Gillet, Isabell Bludau, Ben Collins, and the computational proteomics team at ETH Zürich for their important contributions in discussions. We are grateful to Sciex (Christie Hunter, Mark Cafazzo, and George Manning) for the 5600+ TripleTOF mass spectrometer and access to open-source SWATH data processing software. Funding for the study was provided by the United States National Cancer Institute Clinical Proteomic Tumor Analysis Consortium (NCI CPTAC, U24CA160036 and U24CA210985 to H.Z. and D.W.C.) and the Early Detection Research Network (NCI EDRN, U01CA152813 to H.Z and R. A.) , the European Research Council, European Union ( AdG-233226 Proteomics v.3.0 and AdG-670821 Proteomics 4D to R.A.), and the Swiss National Science Foundation, European Union (grant 31003A_166435 to R.A.). Publisher Copyright: © 2020 The Author(s)

PY - 2020/6/26

Y1 - 2020/6/26

N2 - 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.

AB - 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.

KW - Biological Sciences

KW - Cancer Systems Biology

KW - Proteomics

UR - http://www.scopus.com/inward/record.url?scp=85086113729&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85086113729&partnerID=8YFLogxK

U2 - 10.1101/793026

DO - 10.1101/793026

M3 - Article

C2 - 32534439

SN - 2589-0042

VL - 23

JO - iScience

JF - iScience

IS - 6

M1 - 101079

ER -

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

Abstract

Bibliographical note

Keywords

PubMed: MeSH publication types

UN SDGs

Publisher link

Find It

Other files and links

Fingerprint

Cite this