Analysis of the equilibrium phase in immune-controlled tumors predicts best strategies for cancer treatment

Description

Extensive research and clinical trials have improved our understanding of tumor immunology but despite considerable clinical benefits, current immunotherapies only provide durable responses in a minority of patients. The challenge is to identify key biological parameters preventing immune escape and maintaining an equilibrium state characterized by a stable subclinical tumor mass. Based on a space and size structured partial differential equation model, we developed numerical methods to predict the parameters of the equilibrium without running simulations of the evolution problem. By using global sensitivity analysis methods, we identified the elimination rate of tumor cells by immune cells as the leading parameter influencing the equilibrium size of the tumor and combined therapies that sustain and strengthen the anti-tumor immune response as most effective. Applied to the biological parameters that define a cancer type, such numerical investigation can provide hints for the design and optimization of cancer treatments. Significance: Based on a space and size structured PDE model, the analyses of the equilibrium phase in immune surveillance of cancer provide numerical methods to evaluate the influence of immune response and tumor growth parameters and hints for the design and optimization of cancer treatments.

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