2431 - A Novel Optimization Framework for Combined Therapy: Using Phase Diagrams to Personalize Radio-Immunotherapy and Validating the Transition from Immune-Limited to Immune-Escape Growth
Presenter(s)
N. Yoon1, J. H. Suh2, J. G. Scott3, and Y. B. Cho2; 1Adelphi University, Garden City, NY, 2Department of Radiation Oncology, Cleveland Clinic Foundation, Cleveland, OH, 3Department of Radiation Oncology, Taussig Cancer Institute, Cleveland Clinic Foundation, Cleveland, OH
Purpose/Objective(s): The interplay between radiotherapy (RT) and the immune system is non-linear and highly sensitive to treatment parameters. Recent mathematical modeling identified a critical "bifurcation" point where tumor dynamics transition from immune-limited (controlled) to immune-escape (uncontrolled) growth. This study aims to validate these bifurcation findings and utilize a novel optimization framework to determine how RT fractionation and the timing of systemic therapies can be synchronized to maintain immune-mediated tumor suppression.
Materials/Methods: We employed a 2D discrete mathematical model simulating the dynamic interactions between tumor cells and tumor-infiltrating lymphocytes. To analyze system stability, we utilized Trace-Determinant (TD) analysis of the Jacobian matrix. Within this plane, stable equilibria represent an immune-limited state, while unstable equilibria signify immune escape. We specifically modeled the tumor’s immune suppression capability (k) as a primary driver of these shifts. A comprehensive phase diagram was developed to map these dynamics, allowing for the simulation of various RT fractionation schedules and systemic therapy arrival times to identify optimal treatment pathways.
Results: TD plane analysis demonstrated that "unfavorable" clinical progression is characterized by early bifurcation into immune escape, driven by the emergence of multiple unstable equilibria as the suppression constant (k) increases. The model successfully quantified the impact of immunotherapy, showing that systemic agents can "reset" the system's equilibrium. Our phase diagrams revealed that the success of tumor control is highly dependent on the synergy between RT dose per fraction and the timing of systemic administration. Specifically, the framework identified "therapeutic windows" where specific fractionation schedules effectively prevented bifurcation, even in tumors with high immune-suppressive capabilities.
Conclusion: This validated mathematical framework provides a robust tool for deciphering the complexities of the radio-immune response. By identifying the bifurcation threshold between immune-limited and immune-escape states, this model offers a predictive platform to personalize combined modality therapy. These findings suggest that optimizing the timing and fractionation of RT in conjunction with systemic agents can shift tumor dynamics toward a stable controlled state, potentially improving long-term outcomes for patients receiving radio-immunotherapy.