Breast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry

Open access
Date
2019-07-16Type
- Journal Article
Citations
Cited 43 times in
Web of Science
Cited 47 times in
Scopus
ETH Bibliography
yes
Altmetrics
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. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000354204Publication status
publishedExternal links
Journal / series
Cell ReportsVolume
Pages / Article No.
Publisher
ElsevierSubject
Breast cancer; Proteomics; Tumor classification; Tissue; SWATH-MS; Data independent acquisition; TranscriptomicsOrganisational unit
03663 - Aebersold, Rudolf (emeritus) / Aebersold, Rudolf (emeritus)
Funding
166435 - MitoModules: Biomarkers in context (SNF)
670821 - Proteomics 4D: The proteome in context (EC)
More
Show all metadata
Citations
Cited 43 times in
Web of Science
Cited 47 times in
Scopus
ETH Bibliography
yes
Altmetrics