Tumor hypoxia, which arises due to the rapid growth of tumor cells and insufficient vascularization, can create regions of low oxygen and nutrients that are associated with poorer responses to a range of anticancer therapies, including immunotherapy. To improve the efficacy of immunotherapy in hypoxic tumors, combining it with hypoxia-activated prodrugs (e.g., evofosfamide) has been recently shown to be effective in preclinical models. Although evofosfamide has been shown to enhance treatment outcomes when combined with immunotherapy, the underlying mechanisms and ability to be widely applicable remain unclear. To address this issue, we developed a set of ordinary differential equations that simulated the growth and decline of tumors and their vascularization in response to immunotherapy and evofosfamide treatment. Our model is calibrated using data from in vivo experiments on mice implanted with colon adenocarcinoma cells. The results show that treating hypoxic mice with immunotherapy and evofosfamide leads to a 45.07 ± 2.55% greater reduction in tumor burden when compared to hypoxic mice treated with immunotherapy alone. The model accurately predicts the temporal evolution of the different treatment scenarios, including 1) control, 2) hypoxic mice that received immunotherapy, 3) normoxic mice that received immunotherapy, 3) mice that received evofosfamide, and 4) hypoxic mice that received both evofosfamide and immunotherapy. Interestingly, the model values to fit those five treatment protocols are unable to accurately predict the response of normoxic tumors to combination evofosfamide and immunotherapy. However, increasing the total tumor death rate by a factor of 2.52 ± 0.53 significantly improves the concordance correlation coefficient from -0.064 ± 0.003 all the way to 0.981 ± 0.001. Our findings demonstrate the potential of evofosfamide to improve the response of hypoxic tumors to immunotherapy, and our mathematical model provides a valuable tool for predicting the efficacy of combination treatments in hypoxic and normoxic tumors.
© 2026 - The Mathematical Oncology Blog
© 2026 - The Mathematical Oncology Blog