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Cancer develops, progresses and responds to therapies through restricted perturbation of the protein-protein

Jordi Serra-Musach1, Helena Aguilar, Francesco Iorio

  • 1Translational Research Laboratory, Breast Cancer Unit, Catalan Institute of Oncology (ICO), Bellvitge Institute for Biomedical Research (IDIBELL), Gran via 199, L'Hospitalet del Llobregat, Barcelona 08908, Catalonia, Spain.

Integrative Biology : Quantitative Biosciences From Nano to Macro
|July 19, 2012
PubMed

Insights

Cancer progression and therapy response may be controlled by restricted network perturbations. This study reveals topological robustness in the interactome network across cancer conditions.

Area of Science:

  • Systems biology
  • Network science
  • Cancer research

Background:

  • Cancer gene products often central in protein-protein interaction networks.
  • Understanding cancer mechanisms and expression signatures benefits from integrated gene/protein relationships.

Purpose of the Study:

  • Investigate cancer development, progression, and therapy response at a systems level.
  • Examine the impact and transmission of cancer-related gene expression changes in the interactome network.
  • Apply power grid concepts (load transfer, cascading failures) to biological networks.

Main Methods:

  • Network analysis of the interactome.
  • Application of power grid failure models to biological networks.
  • Experimental perturbation of cancer nodes (e.g., SNCA overexpression in MCF7 cells).

Main Results:

  • Cancer conditions exhibit topological robustness in the interactome network.
  • Experimental perturbation of a central cancer node (SNCA) also shows robustness.
  • The autophagy pathway was identified as having an opposite topological impact.
  • Shorter path lengths among cancer proteins contribute to restricted network perturbation.

Conclusions:

  • Cancer development, progression, and therapy response may follow controlled, restricted perturbations within the interactome network.
  • The interactome network exhibits inherent robustness to cancer-related changes.
  • Network topology plays a crucial role in understanding cancer at a systems level.

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