Identifying potential markers in Breast Cancer subtypes using plasma label-free proteomics

J Proteomics. 2017 Jan 16:151:33-42. doi: 10.1016/j.jprot.2016.07.030. Epub 2016 Aug 4.

Abstract

Breast Cancer (BC) is the most common neoplasia among women and has a high mortality rate worldwide. Over the past several decades, increasing molecular knowledge of BC has resulted in its stratification into 4 major molecular subtypes according to hormonal receptor expression. Unfortunately, although the data accumulated thus far has improved BC prognosis and treatment, there have been few achievements in its diagnosis. In this study, we applied a Label-free Nano-LC/MSMS approach to reveal systemic molecular features and possible plasma markers for BC patients. Compared to healthy control plasma donors, we identified 191, 166, 182, and 186 differentially expressed proteins in the Luminal, Lumina-HER2, HER2, and TN subtypes. In silico analysis demonstrated an overall downregulation of cellular basal machinery and, more importantly, brought new focus to the known pathways and signaling molecules in BC that are related to immune system alterations. Moreover, using western blot analysis, we verified high levels of BCAS3, IRX1, IRX4 and IRX5 in BC plasma samples, thus highlighting the potential use of plasma proteomics in investigations into cancer biomarkers.

Significance: The results of this study provide new insight into Breast Cancer (BC). We determined the plasma proteomic profile of BC subtypes. Furthermore, we report that the signaling pathways correlating with late processes in BC already exhibit plasma alterations in less aggressive subtypes. Additionally, we validated the high levels of particular proteins in patient samples, which suggests the use of these proteins as potential disease markers.

Keywords: Biomarkers; Breast Cancer; Label-free proteomics; Plasma.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Biomarkers, Tumor
  • Breast Neoplasms / classification
  • Breast Neoplasms / diagnosis*
  • Case-Control Studies
  • Female
  • Gene Expression Regulation, Neoplastic
  • Humans
  • Middle Aged
  • Prognosis
  • Proteomics / methods*
  • Signal Transduction

Substances

  • Biomarkers, Tumor