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Drug resistance is a primary obstacle in cancer treatment. In many patients who at first respond well to treatment, relapse occurs later on. Various mechanisms have been explored to explain drug resistance in specific cancers and for specific drugs. In this paper, we consider resistance to anti-PD-1, a drug that enhances the activity of anti-cancer T cells. Based on results in experimental melanoma, it is shown, by a mathematical model, that resistances to anti-PD-1 can be significantly reduced by combining it with anti-TNF-α. The model is used to simulate the efficacy of the combined therapy with different range of doses, different initial tumor volume, and different schedules. In particular, it is shown that under a course of treatment with 3-week cycles where each drug is injected in the first day of either week 1 or week 2, injecting anti-TNF-α one week after anti-PD-1 is the most effective schedule in reducing tumor volume.

Oncolytic virus (OV) is a replication competent virus that selectively invades cancer cells; as these cells die under the viral burden, the released virus particles proceed to infect other cancer cells. Oncolytic viruses are designed to also be able to stimulate the anticancer immune response. Thus, one may represent an OV by two parameters: its replication potential and its immunogenicity. In this paper we consider a combination therapy with OV and a checkpoint inhibitor, anti-PD-1. We evaluate the efficacy of the combination therapy in terms of the tumor volume at some later time, for example, 6 months from initial treatment. Since T cells kill not only virus-free cancer cells but also virus-infected cancer cells, the following question arises: Does increasing the amount of the checkpoint inhibitor always improve the efficacy? We address this question, by a mathematical model consisting of a system of partial differential equations. We use the model to construct, by simulations, an efficacy map in terms of the doses of the checkpoint inhibitor and the OV injection. We show that there are regions in the map where an increase in the checkpoint inhibitor actually decreases the efficacy of the treatment. We also construct efficacy maps with checkpoint inhibitor vs. the replication potential of the virus that show the same antagonism, namely, an increase in the checkpoint inhibitor may actually decrease the efficacy. These results have implications for clinical trials.

Cross-presentation of apoptotic cell associated antigens by immature dendritic cells prevents the activation of self reactive CD8 T cells. Tolerized self reactive CD8 T cells down-regulate IL-7R expression on their surface. Whether over-expression of IL-7R can reverse their fate and function has not been examined. In this paper, we showed forced expression of IL-7R in OT-I T cells by a transgene enhanced CD8 T cell mediated diabetes in the RIP-mOVA model. Although IL-7R Tg (transgenic) did not completely reverse the deletion of OT-I T cells, it provided a significant survival advantage over w.t OT-I T cells. Furthermore, IL7R Tg OT-I T cells isolated from diabetic pancreata displayed increased production of IFN-γ, higher expression of T-bet, and increased externalization of CD107a. We also found that immature DCs containing apoptotic cells expressed high levels of PDL-1 on their surface. Although IL-7R Tg did not change PD1 expression on activated OT-I cells in vivo, the transgene enabled a significantly lower number of OT-I T cells to induce diabetes in the absence of PDL-1. Our results demonstrated that forced expression of IL-7R not only improved the functionality of tolerized CD8 T cells, it also acted in synergy with PDL-1 deficiency to further promote CD8 T cell cytotoxicity to self antigens.