Optimization of CD200 checkpoint immunotherapy for treating glioblastoma.

Abstract

Glioblastoma Multiforme (GBM) is a lethal brain cancer with a median survival between 10-14 months. The standard of care for GBM is a combination of resection, followed by chemotherapy, and radiotherapy. Recent advances in cancer immunotherapy have significantly improved the survival of patients in selected solid tumors. However, in the case of GBM, current immunotherapy has failed, potentially, due to obstacles including immunosuppressive molecules in the tumor microenvironment. CD200 is an immunosuppressive protein that is overexpressed on tumors suppressing the immune system. The University of Minnesota developed a novel CD200 checkpoint immunotherapy, currently in Phase I clinical trial (NCT04642937), targeting the activation receptors on immune cells with a peptide ligand to overcome its immunosuppressive effect on recurrent GBM. While the treatment shows promising results in patient outcomes, the CD200 mechanism in the dendritic cells is still unclear. In this study, we postulate a detailed pathway and develop an Ordinary Differential Equation model, based on the law of mass action, to describe its behavior. Using Global Sensitivity analysis techniques, we explore the parameter space and identify potential targets on the pathway to optimize the CD200 checkpoint therapy and improve its clinical impact.