Mixed effects modeling of the synergy between immune checkpoint and thrombin inhibitors in a preclinical mouse model of colon cancer

Abstract

Immune checkpoint blockade (ICB) therapy has revolutionized cancer treatment, though it is still effective in only about 20-40% of patients. To increase the efficacy of ICB therapy, combinations of ICB antibodies such as anti-PD1 and anticoagulants (e.g., thrombin inhibitors) have been studied in preclinical mouse models and clinical trials. We developed a Bliss-type analysis to quantify the synergy between anti-PD1 and dabigatran etexilate using published tumor growth data from a mouse model. We then developed a minimal mechanistic computational model to quantitatively study the synergy between anti-PD1 and the thrombin inhibitor dabigatran etexilate in a published study (Metelli et al.) of a preclinical mouse model of colon cancer. Our model included tumor cells, CD8+ T cells, and the pleiotropic cytokine TGF{beta}, whose production in platelets is influenced by thrombin, and described a potential mechanism of interplay among these components in the tumor microenvironment. We performed nonlinear mixed-effects modeling to capture mouse-to-mouse variation in tumor growth under different treatment conditions. The estimated parameter values pointed to several underlying mechanisms of synergy, including increased expansion of CD8+ T cells in the tumor microenvironment in the presence of anti-PD1 and dabigatran etexilate. These predictions can be further validated in future experiments. Thus, the combination of longitudinal tumor growth data, mechanistic population dynamics modeling, and nonlinear mixed-effects modeling can be used to study synergy between ICB and other drugs in controlling tumor growth.