Determination of the protein expression profiles of breast cancer cell lines by quantitative proteomics using iTRAQ labelling and tandem mass spectrometry

J Proteomics. 2015 Jun 21:124:50-78. doi: 10.1016/j.jprot.2015.04.018. Epub 2015 Apr 24.

Abstract

Breast cancer is the principal cancer in women worldwide. Although there are serum tumor markers such as CEA and HER2, they are detected in advanced stages of the disease and used as progression and recurrence markers. Therefore, there is a necessity for the identification of new markers that might lead to an early detection and also provide evidence of an effective treatment. The aim of this work was to determine the differential protein expression profiles of four breast cancer cell lines in comparison to a normal control cell line by iTRAQ labelling and tandem mass spectrometry, in order to identify putative biomarkers of the disease. We identified 1,020 iTRAQ-labelled polypeptides with at least one peptide identified with more than 95% in confidence. Overexpressed polypeptides in all cancer cell lines were 78, whilst the subexpressed were 128. We categorised them with PANTHER program into biological processes, being the metabolic pathways the most affected. We detected six groups of proteins with the STRING program involved in DNA topology, glycolysis, translation initiation, splicing, pentose pathway, and proteasome degradation. The main subexpressed protein network included mitochondrial proteins involved in oxidative phosphorylation. We propose BAG6, DDX39, ANXA8 and COX4 as putative biomarkers in breast cancer.

Biological significance: We report a set of differentially expressed proteins in the MCF7 and T47D (Luminal A), MDA-MB-231 (Claudin low) and SK-BR-3 (HER2(+)) breast cancer cell lines that have not been previously reported in breast cancer disease. From these proteins, we propose BAG6, DDX39, ANXA8 and COX4 as putative biomarkers in breast cancer. On the other hand, we propose sets of unique polypeptides in each breast cancer cell line that can be useful in the classification of different subtypes of breast cancer.

Keywords: Breast cancer; Cell lines; Putative biomarkers; Quantitative proteomics; Tandem mass spectrometry; iTRAQ labelling.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomarkers, Tumor / chemistry
  • Biomarkers, Tumor / metabolism*
  • Breast Neoplasms / chemistry
  • Breast Neoplasms / metabolism*
  • Cell Line, Tumor
  • Gene Expression Profiling / methods*
  • Humans
  • Mass Spectrometry / methods*
  • Neoplasm Proteins / chemistry
  • Neoplasm Proteins / metabolism*
  • Peptide Mapping / methods*
  • Staining and Labeling / methods

Substances

  • Biomarkers, Tumor
  • Neoplasm Proteins