Using Boolean Logic Modeling of Gene Regulatory Networks to Exploit the Links Between Cancer and Metabolism for Therapeutic Purposes

IEEE J Biomed Health Inform. 2016 Jan;20(1):399-407. doi: 10.1109/JBHI.2014.2368391. Epub 2014 Nov 6.

Abstract

The uncontrolled cell proliferation that is characteristically associated with cancer is usually accompanied by alterations in the genome and cell metabolism. Indeed, the phenomenon of cancer cells metabolizing glucose using a less efficient anaerobic process even in the presence of normal oxygen levels, termed the Warburg effect, is currently considered to be one of the hallmarks of cancer. Diabetes, much like cancer, is defined by significant metabolic changes. Recent epidemiological studies have shown that diabetes patients treated with the antidiabetic drug Metformin have significantly lowered risk of cancer as compared to patients treated with other antidiabetic drugs. We utilize a Boolean logic model of the pathways commonly mutated in cancer to not only investigate the efficacy of Metformin for cancer therapeutic purposes but also demonstrate how Metformin in concert with other cancer drugs could provide better and less toxic clinical outcomes as compared to using cancer drugs alone.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Antineoplastic Agents / pharmacology*
  • Antineoplastic Agents / therapeutic use
  • Computational Biology
  • Diabetes Mellitus, Type 2* / complications
  • Diabetes Mellitus, Type 2* / drug therapy
  • Diabetes Mellitus, Type 2* / metabolism
  • Gene Regulatory Networks / drug effects*
  • Gene Regulatory Networks / genetics
  • Humans
  • Hypoglycemic Agents / pharmacology*
  • Hypoglycemic Agents / therapeutic use
  • Metformin / pharmacology
  • Metformin / therapeutic use
  • Models, Theoretical
  • Neoplasms* / complications
  • Neoplasms* / drug therapy
  • Neoplasms* / genetics
  • Neoplasms* / metabolism

Substances

  • Antineoplastic Agents
  • Hypoglycemic Agents
  • Metformin