P04.19.B OPTIMIZING CHEMORADIOTHERAPY FOR MALIGNANT GLIOMAS USING A VALIDATED MATHEMATICAL MODEL AND IN-SILICO TRIALS

Abstract BACKGROUND Malignant gliomas (MGs), including glioblastomas, are among the most aggressive cancers, characterized by rapid progression and resistance to standard therapies such as temozolomide (TMZ) and radiotherapy. Standard treatments, such as the Stupp protocol, offer limited survival benefits and high toxicity. This study aims to optimize chemoradiotherapy (CRT) protocols using a validated mathematical model and in silico trials to improve patient outcomes. Finally, our model can be adapted to other cancers with similar resistance mechanisms, suggesting broader utility. MATERIAL AND METHODS We developed a mathematical model using ordinary differential equations to simulate MG dynamics and CRT response. The model integrates key biological processes, such as cell proliferation, tumor dormancy, and resistance mechanisms. Key features include Ki-67, the role of persister cells in the development of TMZ resistance and the impact of treatment timing on survival. We calibrated and validated the model using experimental data from a mouse subventricular zone (SVZ) model developed through retroviral expression of EGFR-wt in primary cultures of neural stem cells from mice. For calibration, we administered 3 daily sessions of 3 Gy each, beginning a week post-tumor injection, and monitored tumor progression via bioluminescence using the In Vivo Imaging System (IVIS), which tracks tumor cell viability. In addition, survival data from prior TMZ experiments were utilized. To validate the model, we compared in vivo and in silico OS from CRT treatments. Finally, we translated the model and the optimal treatment into humans. RESULTS Our in silico simulations revealed that concomitant CRT protocols, incorporating treatment breaks, resulted in a 17% improvement in median overall survival (OS) in mice compared to the standard Stupp protocol, with reduced toxicity. Metronomic CRT protocols also showed promising results. Notably, spaced TMZ monotherapy achieved survival outcomes comparable to CRT, underscoring its efficacy in this context. When translated to human scenarios, extended treatment protocols with concomitant CRT or concomitant CRT plus adjuvant TMZ separated by treatment breaks resulted in a median OS of up to 48 months, a 280% increase over the standard Stupp protocol. These results underscore the potential of optimized protocols to enhance OS and reduce side effects. CONCLUSION This study highlights the power of mathematical modeling and in silico trials in optimizing oncology, providing valuable insights into the design of more effective CRT regimens for MGs. Our findings indicate that extended treatment schedules with treatment breaks could significantly improve OS and quality of life. Clinical trials are required to confirm our findings in real-world settings.