Modeling codelivery of CD73 inhibitor and dendritic cell-based vaccines in cancer immunotherapy.

Dendritic cells (DCs) are the dominant class of antigen-presenting cells in humans; therefore, a range of DC-based approaches have been established to promote an immune response against cancer cells. The efficacy of DC-based immunotherapeutic approaches is markedly affected by the immunosuppressive factors related to the tumor microenvironment, such as adenosine. In this paper, based on immunological theories and experimental data, a hybrid model is designed that offers some insights into the effects of DC-based immunotherapy combined with adenosine inhibition. The model combines an individual-based model for describing tumor-immune system interactions with a set of ordinary differential equations for adenosine modeling. Computational simulations of the proposed model clarify the conditions for the onset of a successful immune response against cancer cells. Global and local sensitivity analysis of the model highlights the importance of adenosine blockage for strengthening effector cells. The model is used to determine the most effective suppressive mechanism caused by adenosine, proper vaccination time, and the appropriate time interval between injections. [Display omitted] • We propose a hybrid model to describe the immunosuppressive function of adenosine in tumor micro environment. • Our model provides immunologists with a new level of insight into the role of immunosuppressive factors of the immune system. • Our model highlights the importance of adenosine blockage for strengthening effector cells and suppressing Treg cells. • Model simulations are compatible with in vivo experimental data. • The results reveals that the appropriate time interval for administration of adenosine inhibitor is between 2 and 4 days. [ABSTRACT FROM AUTHOR]