The role of tumor activation and inhibition with saturation effects in a mathematical model of tumor and immune system interactions undergoing oncolytic viral therapy

Author:

Vithanage G. V. R. K.1,Wei Hsiu‐Chuan2,Jang Sophia R‐J1ORCID

Affiliation:

1. Department of Mathematics and Statistics Texas Tech University Lubbock TX USA

2. Department of Applied Mathematics Feng Chia University Taichung Taiwan

Abstract

We propose and study a mathematical model governing interactions between cancer and immune system with an oncolytic viral therapy (OVT), wherein cancer cells can activate and inhibit immune cells simultaneously with saturations. When the therapy is not applied, it is shown that the interaction can support at most three hyperbolic positive equilibria where two of them are always asymptotically stable and the other is a saddle point. The reachable stable tumor burden can be either small or large depending on initial tumor size. We analyze the full model by proving global asymptotic stability of the virus‐free equilibrium that corresponds to OVT failure. Sufficient conditions based on model parameters are derived under which the model is uniformly persistent. The proposed system is validated using a mouse model of human pancreatic cancer carried out by Koujima et al. Global sensitivity analysis indicates that the rates of tumor‐mediated killing and immune cell exhaustion are critical for tumor progression and therapy success. Numerical bifurcation analysis reveals that the saddle point can be utilized to estimate the maximum tumor load for eradication by OVT. Moreover, an immunosuppressive microenvironment may enhance viral therapy efficacy.

Funder

Ministry of Science and Technology, Taiwan

Publisher

Wiley

Subject

General Engineering,General Mathematics

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Resistance in oncolytic viral therapy for solid tumors;Applied Mathematics and Computation;2024-05

2. The role of immune cells in resistance to oncolytic viral therapy;Mathematical Biosciences and Engineering;2024

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