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Mathematical Approach to Differentiate Spontaneous and Induced Evolution to Drug Resistance During Cancer Treatment

James M Greene1, Jana L Gevertz2, Eduardo D Sontag3,4

  • 1Rutgers University, New Brunswick, NJ.

JCO Clinical Cancer Informatics
|April 11, 2019
PubMed
Abstract

Insights

Cancer drug resistance can be induced by treatment, not just random mutations. Mathematical modeling reveals this induced resistance complicates treatment design and response.

Area of Science:

  • Oncology
  • Mathematical Biology
  • Genetics

Background:

  • Drug resistance is a significant challenge in cancer therapy.
  • Traditionally, resistance is attributed to spontaneous genetic mutations and Darwinian selection.
  • Emerging evidence suggests cancer treatments themselves can induce drug resistance through genetic or epigenetic changes.

Purpose of the Study:

  • To investigate the mechanisms of cancer drug resistance.
  • To develop a framework for understanding both spontaneous and treatment-induced resistance.
  • To analyze the impact of induced resistance on treatment efficacy.

Main Methods:

  • Development of a mathematical modeling framework.
  • Incorporation of spontaneous and drug-induced resistance pathways.
  • Theoretical analysis of model parameters.

Main Results:

  • The model shows that drug-induced resistance can lead to distinct treatment responses.
  • The induction parameter is theoretically identifiable, suggesting measurable biological relevance.
  • A novel in vitro protocol is proposed to assess a treatment's propensity to induce resistance.

Conclusions:

  • Cancer drug resistance is not solely a random process.
  • Treatment-induced resistance is a critical factor influencing therapeutic outcomes.
  • Understanding and quantifying induced resistance is essential for optimizing cancer treatment strategies.

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