CAR-T cell therapy for glioblastoma: insight from mathematical modeling.

Introduction: Glioblastoma is a rare, aggressive brain tumor marked by high therapeutic resistance, poor prognosis, and limited treatment options. Emerging immunotherapies, particularly Chimeric Antigen Receptor (CAR) T-cell therapy, offer promising alternatives to standard care. However, adapting CAR-T cell strategies from hematologic malignancies to solid tumors like glioblastoma presents substantial challenges. Methods: We extended existing mathematical models to investigate glioblastoma treatment dynamics with CAR-T cell therapy. Simulations were based on clinical trial-inspired scenarios targeting IL13Rα2, HER2, and EGFRvIII antigens, assessing both single-dose and cyclic dosing regimens. The models incorporated key biological processes, including tumor growth, CAR-T cell proliferation delays, and resistance mechanisms. Results: Cyclic CAR-T cell administration outperformed single-dose strategies in reducing tumor burden. Incorporating resistance and treatment delays into the models provided critical insights into relapse dynamics and therapeutic durability. Discussion: This study presents a comprehensive modeling framework for CAR-T cell therapy in glioblastoma, highlighting the importance of dosing regimens and resistance dynamics. The findings offer valuable guidance for optimizing therapeutic strategies to enhance patient outcomes.