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Modeling the effects of space structure and combination therapies on phenotypic heterogeneity and drug resistance in

Alexander Lorz1, Tommaso Lorenzi, Jean Clairambault

  • 1Sorbonne Universités, UPMC Univ Paris 06, UMR 7598, Laboratoire Jacques-Louis Lions, 75005 , Paris, France, alexander.lorz@upmc.fr.

Bulletin of Mathematical Biology
|December 7, 2014
PubMed

Insights

Tumor cell heterogeneity and drug resistance can be explained by selection driven by the tumor microenvironment. Combination therapies show promise in overcoming resistance and eradicating cancer cells.

Area of Science:

  • Mathematical modeling
  • Cancer biology
  • Pharmacology

Background:

  • Phenotypic heterogeneity and drug resistance in tumors are often viewed as selection processes.
  • Understanding intra-tumor heterogeneity requires considering selection driven by the local cellular environment.

Purpose of the Study:

  • To model cancer cell dynamics within a tumor spheroid under cytotoxic and cytostatic drug treatment.
  • To investigate the impact of spatial structure and combination therapies on phenotypic heterogeneity and drug resistance.
  • To evaluate the efficacy of different combination therapy protocols.

Main Methods:

  • Development of a mathematical model for cancer cell population dynamics.
  • Inclusion of variables for spatial position and drug resistance phenotype expression.
  • Explicit modeling of resource dynamics, drug interactions, and treatment effects.
  • Analysis of combination therapies involving cytotoxic and cytostatic drugs with varied delivery methods.

Main Results:

  • The study analyzes how spatial structure and combination therapies influence phenotypic heterogeneity and chemotherapeutic resistance.
  • The efficacy of combined therapy protocols, including constant infusion and bang-bang delivery, is investigated.
  • The model provides insights into the selection dynamics driving tumor cell heterogeneity and resistance.

Conclusions:

  • Combination therapies, considering drug delivery strategies, are crucial for overcoming cancer cell resistance.
  • The spatial structure of tumors plays a significant role in phenotypic heterogeneity and treatment outcomes.
  • Mathematical modeling offers a framework to understand and potentially overcome drug resistance in cancer treatment.

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