Assessing the impact of immunotherapy on oncolytic virotherapy in the treatment of cancer

Abstract

Combined oncolytic virotherapy and immunotherapy are novel treatment protocols that represent a promising and advantageous strategy for various cancers, surpassing conventional anti-cancer treatments. This is due to the reduced toxicity associated with traditional cancer therapies. We present a mathematical model that describes the interactions between tumor cells, the immune response, and the combined application of virotherapy and interleukin-2 (IL-2). A stability analysis of the model for both the tumor and tumor-free states is discussed. To gain insight into the impact of model parameters on tumor cell growth and inhibition, we perform a sensitivity analysis using Latin hypercube sampling to compute partial rank correlation coefficient values and their associated p-values. Furthermore, we perform optimal control techniques using the Pontryagin maximum principle to minimize tumor burden and determine the most effective protocol for the administered treatment. We numerically demonstrate the ability of combined virotherapy and IL-2 to eliminate tumors.