Dynamic modularity in protein interaction networks predicts breast cancer outcome

Nat Biotechnol. 2009 Feb;27(2):199-204. doi: 10.1038/nbt.1522. Epub 2009 Feb 1.

Abstract

Changes in the biochemical wiring of oncogenic cells drives phenotypic transformations that directly affect disease outcome. Here we examine the dynamic structure of the human protein interaction network (interactome) to determine whether changes in the organization of the interactome can be used to predict patient outcome. An analysis of hub proteins identified intermodular hub proteins that are co-expressed with their interacting partners in a tissue-restricted manner and intramodular hub proteins that are co-expressed with their interacting partners in all or most tissues. Substantial differences in biochemical structure were observed between the two types of hubs. Signaling domains were found more often in intermodular hub proteins, which were also more frequently associated with oncogenesis. Analysis of two breast cancer patient cohorts revealed that altered modularity of the human interactome may be useful as an indicator of breast cancer prognosis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Breast Neoplasms / diagnosis*
  • Breast Neoplasms / metabolism*
  • Computational Biology
  • Computer Simulation
  • Data Interpretation, Statistical
  • Female
  • Gene Regulatory Networks / physiology*
  • Humans
  • Kaplan-Meier Estimate
  • Neoplasm Proteins / genetics
  • Neoplasm Proteins / metabolism
  • Prognosis
  • Protein Interaction Mapping / methods*
  • ROC Curve
  • Reproducibility of Results
  • Signal Transduction / physiology*
  • Statistics, Nonparametric
  • Ubiquitin-Protein Ligases / genetics
  • Ubiquitin-Protein Ligases / metabolism

Substances

  • Neoplasm Proteins
  • BRAP protein, human
  • Ubiquitin-Protein Ligases