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Cell Rep. 2019 Jul 16;28(3):832-843.e7. doi: 10.1016/j.celrep.2019.06.046.

Breast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry.

Author information

1
Department of Biochemistry, Faculty of Science, Masaryk University, Brno, Czech Republic; Regional Centre for Applied Molecular Oncology, Masaryk Memorial Cancer Institute, Brno, Czech Republic. Electronic address: bouchal@chemi.muni.cz.
2
Department of Biology, Institute of Molecular Systems Biology, Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland; Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA.
3
Regional Centre for Applied Molecular Oncology, Masaryk Memorial Cancer Institute, Brno, Czech Republic.
4
Department of Biochemistry, Faculty of Science, Masaryk University, Brno, Czech Republic.
5
Department of Biochemistry, Faculty of Science, Masaryk University, Brno, Czech Republic; Center for Human Genetics, University of Leuven, Leuven, Belgium.
6
Department of Pharmacology, Yale Cancer Biology Institute, Yale University School of Medicine, West Haven, CT, USA.
7
Department of Biology, Institute of Molecular Systems Biology, Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland; Systems Biology Ireland, University College Dublin, Dublin, Ireland.
8
Regional Centre for Applied Molecular Oncology, Masaryk Memorial Cancer Institute, Brno, Czech Republic; Research Centre for Toxic Compounds in the Environment, Faculty of Science, Masaryk University, Brno, Czech Republic.
9
Department of Biology, Institute of Molecular Systems Biology, Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland; Faculty of Science, University of Zurich, Zurich, Switzerland. Electronic address: aebersold@imsb.biol.ethz.ch.

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.

KEYWORDS:

SWATH-MS; breast cancer; data independent acquisition; proteomics; tissue; transcriptomics; tumor classification

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