Identification of the Optimal Pattern of the Injection and Dosage of DC Immunotherapy Using the Mathematical Models Based on Ordinary Differential Equations

Background: Mathematical modeling offers the possibility to select the optimal dose of a drug or vaccine. Considerable evidence show that many bacterial components can activate dendritic cells (DCs). Our previous report showed that multiple doses of DCs matured with Listeria monocytogenes led to tumor regression whereas multiple doses of CpG-matured DCs affected tumor reversely. Objective: To assess a combined pattern of DC vaccination proposed by a mathematical model for tumor regression. Methods: WEHI164 cells were inoculated subcutaneously in the right flank of BALB/c mice. Bone marrow-derived DCs were matured by Listeria monocytogenes and CpG motifs. DCs were injected using specific patterns and doses predicted by mathematical modeling. Effector cell-mediated cytotoxicity, gene expression of T cell-related transcription factors, as well as tumor growth and survival rate, were assessed in different groups. Results: Our study indicated that the proposed mathematical model could simulate the tumor and immune system interaction, and it was verified by decreasing tumor size in the List+CpG group. However, comparing the effect of different treatment modalities on Th1/Treg transcription factor expression or cytotoxic responses revealed no advantage for combined therapy over other treatment modalities. Conclusions: These results suggest that finding new combinations of DC vaccines for the treatment of tumors will be promising in the future. The results of this study support the mathematical modelling for DC vaccine design. However, some parameters in this model must be modified to provide a more optimized therapy approach.