Dynamical analysis of the delayed immune response to cancer

Abstract

In the antitumor response, cytotoxic CD8 + T cells and the functional organization of CD4 + T cells play an important role. During this research, a mathematical model is built. In this model, the ability of CD4 + T cells, to trigger the tumor cell population control, is analyzed. The cytokine IFN-gamma is used as a mediator and it is linked with the antitumor action. The computational model simulates the cellular interactions. With the aid of this model, one can visualize the future development in this field, based on recent data. A therapeutic scheme can be proposed, where CD4 + T cells play a “leading role.” Thus the proposed mathematical model can prove to be useful in the field of computational oncology. In this article, we have worked on the dynamical analysis of the developed mathematical model. Furthermore, we have worked on numerical simulations with the aid of smart programming tools for nonlinear systems. The parametric values are evaluated with the aid of the Markov chain Monte Carlo (MCMC) approximation algorithm. Therefore, the present article illustrates the functional dynamics that occur between CD4 + T cells, cytotoxic CD8 + T cells, and cancer, and provides deeper evaluation of complex personalized treatment strategy.

Keywords

• Nonlinear model
• Dynamical analysis
• MCMC
• cytokine
• cancer treatment.