Synergistic Effect of Anti-PD-L1 Treatment and CD8+ T-Cell Activating Nanotherapy in Pancreatic Ductal Adenocarcinoma Evaluated via 3D Mathematical Modeling.

Abstract

Summary: Although targeting programmed cell death ligand 1 (PD-L1) has been ineffective in reducing pancreatic ductal adenocarcinoma (PDAC) burden in preclinical and clinical studies, it is unknown if increasing activated CD8+ T-cell numbers, independently or in combination with anti-PD-L1 therapeutics, would improve tumor response. To facilitate evaluation of novel combinatorial strategies targeting PDAC, this study developed a modeling framework to assess therapies targeting PD-L1 and T-cell activation. Chitosan nanoparticles (CNP) loaded with a model antigen have recently shown promising anti-tumor effects by increasing dendritic cell (DC) mediated T-cell activation in a murine PDAC model. Using these in vivo data, along with in vitro and primary and liver metastatic PDAC in situ data, a 3D continuum mixture model of PDAC was rigorously calibrated and solved through distributed computing. The model was applied to analyze the response to anti-PD-L1 and/or antigen-CNP therapies at primary and liver metastatic sites. The results show realistic evaluation of combination therapy targeting PDAC at primary and liver metastatic sites. With the given parameter set, the model projects that anti-PD-L1 therapy and antigen-CNP would synergistically decrease tumor burden at primary and liver metastatic sites to 53.2% and 58.4% of initial burden 5.0 and 5.2 days post-treatment initiation, respectively. Delaying antigen-CNP application 3 or 5 days after anti-PD-L1 and gemcitabine administration further limited metastatic PDAC to <50% of initial burden 15 days post-treatment initiation. In conclusion, the proposed modeling approach enables realistic evaluation of novel combinations of agents, with the goal to design improved PDAC therapy.