Systematic identification of molecular links between core and candidate genes in breast cancer

J Mol Biol. 2015 Mar 27;427(6 Pt B):1436-1450. doi: 10.1016/j.jmb.2015.01.014. Epub 2015 Jan 29.


Despite the remarkable progress achieved in the identification of specific genes involved in breast cancer (BC), our understanding of their complex functioning is still limited. In this manuscript, we systematically explore the existence of direct physical interactions between the products of BC core and associated genes. Our aim is to generate a protein interaction network of BC-associated gene products and suggest potential molecular mechanisms to unveil their role in the disease. In total, we report 599 novel high-confidence interactions among 44 BC core, 54 BC candidate/associated and 96 newly identified proteins. Our findings indicate that this network-based approach is indeed a robust inference tool to pinpoint new potential players and gain insight into the underlying mechanisms of those proteins with previously unknown roles in BC. To illustrate the power of our approach, we provide initial validation of two BC-associated proteins on the alteration of DNA damage response as a result of specific re-wiring interactions. Overall, our BC-related network may serve as a framework to integrate clinical and molecular data and foster novel global therapeutic strategies.

Keywords: DNA damage response; breast cancer; network biology; protein interaction networks.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomarkers, Tumor / genetics
  • Biomarkers, Tumor / metabolism
  • Breast Neoplasms / genetics*
  • Breast Neoplasms / metabolism*
  • Cells, Cultured
  • Computational Biology / methods*
  • DNA Damage / genetics
  • Female
  • Fluorescent Antibody Technique
  • Gene Regulatory Networks*
  • Genetic Predisposition to Disease
  • Humans
  • Immunoprecipitation
  • Neoplasm Proteins / genetics*
  • Neoplasm Proteins / metabolism*
  • Oligonucleotide Array Sequence Analysis
  • Protein Interaction Maps*
  • Two-Hybrid System Techniques


  • Biomarkers, Tumor
  • Neoplasm Proteins