Longtime evolution and stationary response of a stochastic tumor-immune system with resting T cells

Author:

Wang Bingshuo1,Li Wei1,Zhao Junfeng2,Trisovic Natasa3

Affiliation:

1. School of Mathematics and Statistics, Xidian University, Xi'an 710071, China

2. School of Mathematics and Statistics, Northwestern Polytechnical University, Xi'an 710071, China

3. Faculty of Mechanical Engineering, Department of Mechanics, University of Belgrade, Belgrade 11000, Serbia

Abstract

<abstract><p>In this paper, we take the resting T cells into account and interpret the progression and regression of tumors by a predator-prey like tumor-immune system. First, we construct an appropriate Lyapunov function to prove the existence and uniqueness of the global positive solution to the system. Then, by utilizing the stochastic comparison theorem, we prove the moment boundedness of tumor cells and two types of T cells. Furthermore, we analyze the impact of stochastic perturbations on the extinction and persistence of tumor cells and obtain the stationary probability density of the tumor cells in the persistent state. The results indicate that when the noise intensity of tumor perturbation is low, tumor cells remain in a persistent state. As this intensity gradually increases, the population of tumors moves towards a lower level, and the stochastic bifurcation phenomena occurs. When it reaches a certain threshold, instead the number of tumor cells eventually enter into an extinct state, and further increasing of the noise intensity will accelerate this process.</p></abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Applied Mathematics,Computational Mathematics,General Agricultural and Biological Sciences,Modeling and Simulation,General Medicine

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