Optimal Immunotherapy of Oncolytic Viruses and Adopted Cell Transfer in Cancer Treatment

Abstract

We investigate therapeutic effects of monotherapy of oncolytic viruses, of adopted cell transfer, as well as the two combined therapies over a short time treatment period by applying optimal control techniques. The goal is to minimize the number of susceptible tumor cells and the costs associated with the therapy over the treatment period. We verify that there exists an optimal control pair and derive the necessary conditions. The optimality system is solved numerically to provide optimal protocols under different scenarios with respect to initial tumor sizes and parameter values. Although the two types of therapy do not work synergistically when the viral killing rate by immune cells is large, a small anti-viral killing can improve therapy success of either monotherapy of oncolytic viruses or combined therapy of oncolytic viruses and adopted T cell transfer. This finding can be accomplished either by manipulating certain genes of viruses via genetic engineering or by chemical modification of viral coat proteins to avoid detection by the immune cells.

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

“…Distributed delay was also adopted in [24] to study its impact on stability of equilibria. Spatial models of reaction-diffusion equations were discussed in [25] for Turing instability while optimal control theory was applied in [26][27][28][29] to derive optimal treatment strategies. Models of interactions between glioma and immune system with various complexities were proposed and studied in [25][26][27][30][31][32][33][34].…”