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Controlling Directed Protein Interaction Networks in Cancer

Krishna Kanhaiya1, Eugen Czeizler1,2, Cristian Gratie1

  • 1Computational Biomodeling Laboratory, Turku Centre for Computer Science, and Department of Computer Science, Åbo Akademi University, Turku, 20500, Finland.

Scientific Reports
|September 6, 2017
PubMed

Insights

This study introduces a new computational method to identify key control points in cancer networks. The findings suggest potential new therapeutic strategies by targeting essential proteins for personalized cancer medicine.

Area of Science:

  • Network science
  • Computational biology
  • Cancer research

Background:

  • Control theory is applied to network science, particularly in bio-medicine and cancer research.
  • Structural controllability identifies driver nodes for network control.
  • Cancer networks present complex control dynamics.

Purpose of the Study:

  • To develop an efficient method for targeted structural controllability of cancer networks.
  • To analyze breast, pancreatic, and ovarian cancer using protein-protein interaction networks.
  • To identify driver nodes among FDA-approved drug-target nodes for potential cancer therapies.

Main Methods:

  • Constructing protein-protein interaction networks for specific cancer types.
  • Focusing on survivability-essential proteins within these networks.
  • Applying a novel computational approach to determine structural controllability and identify driver nodes.

Main Results:

  • Essential proteins in cancer networks are controllable by a small set of driver nodes.
  • The method successfully identified drug-target driver nodes.
  • Some identified drug-target nodes are not currently used in therapies for the analyzed cancer types, and some are not used in any cancer therapy.

Conclusions:

  • Computational modeling of cancer control dynamics can reveal new therapeutic strategies.
  • The developed method aids in understanding cancer network control for personalized medicine.
  • Targeting identified driver nodes offers potential for novel and efficient cancer treatments.

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