Breast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry
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Abstract
Accurate classification of breast tumors is vital for patient management decisions and enables more precise cancer treatment. Here, we present a quantitative proteotyping approach based on sequential windowed acquisition of all theoretical fragment ion spectra (SWATH) mass spectrometry and establish key proteins for breast tumor classification. The study is based on 96 tissue samples representing five conventional breast cancer subtypes. SWATH proteotype patterns largely recapitulate these subtypes; however, they also reveal varying heterogeneity within the conventional subtypes, with triple negative tumors being the most heterogeneous. Proteins that contribute most strongly to the proteotype-based classification include INPP4B, CDK1, and ERBB2 and are associated with estrogen receptor (ER) status, tumor grade status, and HER2 status. Although these three key proteins exhibit high levels of correlation with transcript levels (R > 0.67), general correlation did not exceed R = 0.29, indicating the value of protein-level measurements of disease-regulated genes. Overall, this study highlights how cancer tissue proteotyping can lead to more accurate patient stratification.
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- Authors
- Bouchal, P., Schubert, O. T., Faktor, J., Capkova, L., Imrichova, H., Zoufalova, K., Paralova, V., Hrstka, R., Liu, Y., Ebhardt, H. A., Budinska, E., Nenutil, R., & Aebersold, R.
- Affiliations
- Masaryk University (CZ)
- University of California, Los Angeles (US)
- Masaryk Memorial Cancer Institute (CZ)
- Yale University (US)
- University College Dublin (IE)
- University of Zurich (CH)
- Corresponding author
- Bouchal, Pavel
- Aebersold, Ruedi
- ORCID
- Venue
- Cell Reports
- Publisher
- Elsevier BV
- Published
- 2019-07
- Volume
- 28
- Issue
- 3
- Pages
- 832-843.e7
- ISSN
- 2211-1247 (ISSN-L)
- PMC
- PMC6656695
- OpenAlex
- W2957606438
- Cited by
- 94
- References
- 5
- Citations by year
- 2026: 5 · 2025: 4 · 2024: 11 · 2023: 14 · 2022: 17 · 2021: 20 · 2020: 19 · 2019: 4
- FWCI
- 5.97
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Cell Reports (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Lirias (submittedVersion, cc-by)
- Repository for Publications and Research Data (ETH Zurich) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- ETH Zürich Research Collection (cc-by)
- Funders
- European Research Council (20140AdG 670821)
- Ministerstvo Školství, Mládeže a Tělovýchovy (LO1413)
- RECETOX Přírodovědecké Fakulty Masarykovy Univerzity (LM2015051)
- Ministerstvo Zdravotnictví Ceské Republiky
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (31003A_166435)
- Grantová Agentura České Republiky (17-05957S)
- Topics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
- Physical Sciences › Chemistry › Spectroscopy › Mass Spectrometry Techniques and Applications
- Keywords
- breast cancer, proteotyping, SWATH mass spectrometry, breast cancer subtypes, triple-negative breast cancer, tumor heterogeneity, INPP4B, CDK1, ERBB2, estrogen receptor status, HER2 status, tumor grade, protein expression, transcript-protein correlation, patient stratification
- MeSH terms
- Breast Neoplasms, Female, Humans, Phosphoric Monoester Hydrolases, Receptors, Estrogen, CDC2 Protein Kinase, Erb-b2 Receptor Tyrosine Kinases, Receptor, ErbB-2, Proteome, Proteomics, Tandem Mass Spectrometry, High-Throughput Screening Assays
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