Feedback analysis identifies a combination target for overcoming adaptive resistance to targeted cancer therapy

Oncogene. 2020 May;39(19):3803-3820. doi: 10.1038/s41388-020-1255-y. Epub 2020 Mar 10.

Abstract

Targeted drugs aim to treat cancer by directly inhibiting oncogene activity or oncogenic pathways, but drug resistance frequently emerges. Due to the intricate dynamics of cancer signaling networks, which contain complex feedback regulations, cancer cells can rewire these networks to adapt to and counter the cytotoxic effects of a drug, thereby limiting the efficacy of targeted therapies. To identify a combinatorial drug target that can overcome such a limitation, we developed a Boolean network simulation and analysis framework and applied this approach to a large-scale signaling network of colorectal cancer with integrated genomic information. We discovered Src as a critical combination drug target that can overcome the adaptive resistance to the targeted inhibition of mitogen-activated protein kinase pathway by blocking the essential feedback regulation responsible for resistance. The proposed framework is generic and can be widely used to identify drug targets that can overcome adaptive resistance to targeted therapies.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antineoplastic Agents / pharmacology
  • Colorectal Neoplasms / drug therapy*
  • Colorectal Neoplasms / genetics
  • Colorectal Neoplasms / pathology
  • Drug Resistance, Neoplasm / genetics*
  • Gene Expression Regulation, Neoplastic / drug effects
  • Gene Regulatory Networks / drug effects
  • HCT116 Cells
  • Humans
  • MAP Kinase Signaling System / drug effects
  • Molecular Targeted Therapy*
  • Oncogenes / drug effects
  • Protein Kinase Inhibitors / pharmacology
  • Proto-Oncogene Proteins c-akt
  • src-Family Kinases / antagonists & inhibitors
  • src-Family Kinases / genetics*

Substances

  • Antineoplastic Agents
  • Protein Kinase Inhibitors
  • src-Family Kinases
  • Proto-Oncogene Proteins c-akt