Mathematical Model of the Impact of Chemotherapy and Anti-Angiogenic Therapy on Drug Resistance in Glioma Growth

TL;DR

This paper develops a mathematical model to understand glioma growth, drug resistance, and the effects of combined chemotherapy and anti-angiogenic therapy, providing insights for optimizing treatment strategies.

Contribution

It introduces a novel mathematical model capturing glioma dynamics with drug resistance and therapy interactions, aiding in treatment optimization.

Findings

Identification of three equilibrium points in glioma dynamics

Numerical simulations show combined therapies impact tumor cell populations

Model suggests optimal dosages for therapy effectiveness

Abstract

This research presents a mathematical model of glioma growth dynamics with drug resistance, capturing interactions among five cell populations: glial cells, sensitive glioma cells, resistant glioma cells, endothelial cells, and neuron cells, along with two therapy agent populations: chemotherapy and anti-angiogenic therapy. Glioma is a malignant tumor originating from glial cells, undergoes chemotherapy-induced mutations, leading to drug-resistant glioma cells. This not only impacts glioma cells but also normal cells. Combining chemotherapy and anti-angiogenic therapy, the model employs a Holling type II response function, considering optimal dosages for treatment optimization. Through analysis, three equilibrium are identified: two stable and one unstable equilibrium points. Numerical simulations, employing phase portraits and trajectory diagrams, illustrate the combined therapies impact on glioma cells. In summary, this concise model explores glioma dynamics and drug resistance, offering insights into the efficacy of combined therapies, crucial for optimizing glioma treatment.