4.5 Article

Mathematical modeling and dynamical analysis of anti-tumor drug dose-response

Journal

MATHEMATICAL BIOSCIENCES AND ENGINEERING
Volume 19, Issue 4, Pages 4120-4144

Publisher

AMER INST MATHEMATICAL SCIENCES-AIMS
DOI: 10.3934/mbe.2022190

Keywords

anti-tumor drugs; hormesis; dose-response; mathematical model; critical threshold

Funding

  1. Key Program of the National Nature Science Foundation of China [11831015]
  2. Chinese National Nature Science Foundation [61672388]
  3. National Key Research and Development Program of China [2018YFC1314600]

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This study presents a mathematical model and dynamical analysis to quantify the hormesis of anti-tumor drugs and determine the critical threshold of antibody dose. The research reveals that low dose antibody promotes tumor growth while high dose antibody inhibits tumor growth. These findings provide suggestions for the appropriate drug dosage in the clinical treatment of cancer.
Cancer is a serious threat to human health and life. Using anti-tumor drugs is one of the important ways for treating cancer. A large number of experiments have shown that the hormesis appeared in the dose-response relationship of various anti-tumor drugs. Modeling this phenomenon will contribute to finding the appropriate dose. However, few studies have used dynamical models to quantitatively explore the hormesis phenomenon in anti-tumor drug dose-response. In this study, we present a mathematical model and dynamical analysis to quantify hormesis of anti-tumor drugs and reveal the critical threshold of antibody dose. Firstly, a dynamical model is established to describe the interactions among tumor cells, natural killer cells and M2-polarized macrophages. Model parameters are fitted through the published experimental data. Secondly, the positivity of solution and bounded invariant set are given. The stability of equilibrium points is proved. Thirdly, through bifurcation analysis and numerical simulations, the hormesis phenomenon of low dose antibody promoting tumor growth and high dose antibody inhibiting tumor growth is revealed. Furthermore, we fit out the quantitative relationship of the dose-response of antibodies. Finally, the critical threshold point of antibody dose changing from promoting tumor growth to inhibiting tumor growth is obtained. These results can provide suggestions for the selection of appropriate drug dosage in the clinical treatment of cancer.

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