Oncolytic virus therapy through mathematical modeling: the infection-lysis trade-off in cancer dynamics

Abstract

One of the most fatal diseases globally is cancer. Its incidence continues to rise even though early detection methods and therapeutic approaches have been enhanced. So we necessitate ongoing research into its underlying causes and new treatment paradigms. In this paper, we study a mathematical model to treat cancer by oncolytic viruses (OVs), like adenovirus ONYX-15. The model incorporates three variables: the uninfected tumor cell density, the infected tumor cell density and the oxygen concentration. We prove that solutions exist, are non-negative and bounded, and we analyze equilibrium points along with their stability. We find that engineering an effective oncolytic virus requires a finely tuned interplay between two key properties: the virus’s ability to infect tumor cells, and its oncolytic potency. If the virus is excessively cytotoxic to tumor cells but insufficiently infectious, infected cells will be destroyed faster than spreading the infection. This imbalance reduces the overall therapeutic efficacy, as the virus fails to propagate adequately through the tumor population.