Abstract A021: Evolutionary immunotherapy in NSCLC: An integrated approach
Authors: Prabhakaran Sandhya , Bursell Taylor M. , Luddy Kimberly , Pineiro Julian , Bravo Rafael , West Jeffrey , Johnson Megan , Robertson-Tessi Mark , Beg Amer A. , Gray Jhanelle E. , Antonia Scott , Gatenby Robert A. , Anderson Alexander R. A. 
Published: February 2024

Abstract
Purpose: Our study examines tumor growth dynamics and immunosuppression under the presence of immune attack to identify optimal immune pulsing treatment strategies. Motivation: Checkpoint inhibitors disrupting the PD-1/PD-L1 axis are used in multiple cancer subtypes. However, not all patients respond, and predictive biomarkers are needed to better stratify patients. Therapy for PD-L1, the most studied biomarker, has given mixed results in non-small cell lung cancer (NSCLC). The complexity of the immune response and plastic nature of PD-L1/PD-1 expression on tumor and immune cells contributes to the heterogeneity of success. IFN-γ, a cytokine released by activated immune cells, induces PD-L1 expression in some tumor cells. Chronic IFN-γ results in long-term PD-L1 expression. However, relaxation dynamics following removal of IFN-γ remains unexplored. In this study, we investigate these complex PD-L1 dynamics through a unique combination of in vitro studies and mathematical modeling. METHODS: In vitro experimental data: We have collected in vitro and temporal confocal microscopy images of PD-L1 expression on NSCLC cells, which were either untreated or treated for 48 hours with high dose IFN-γ followed by chronic low dose IFN-γ for 21 days.Agent-based model: To reinforce our in vitro experiments and findings, we developed a hybrid agent-based model (ABM) to study PD-L1 dynamics. The agents in the ABM are tumor cells having variable PD-L1 expression, and immune cells that secrete IFN-γ. Tumor cells can be randomly seeded or seeded as a cluster of cells. IFN-γ is modeled as either a binary well-mixed pulse (to simulate the in vitro experimental setup), or as a diffusible via a reaction-diffusion process (to simulate the tumor-immune cell interactions in an in-vivo spatial manner). This allows us to investigate the effects of various pulsing strategies of immunotherapy on tumor evolution where each pulse can be a variable dose of immune cells, given at regular or irregular intervals. RESULTS: Our in vitro experimental data and microscopy images confirm that PD-L1 expression continues to increase within the cells after a 48-hour IFN-γ exposure followed by low levels of IFN-γ. Our ABM has been calibrated to capture in vitro data dynamics for different conditions. Our initial results indicate that pulsing immunotherapy may lead to better overall immune efficacy than continuous immunotherapy, by preventing sustained suppression that increases immune cell exhaustion, despite the potential for tumor regrowth between pulses. We also hypothesize that pulsing immunotherapy will have different immunosuppression effects when tumors are clustered or randomly distributed. CONCLUSION: We have quantified the temporal dynamics of PD-L1 expression in NSCLC cells under different conditions of IFN-γ, and built an ABM to study tumor-immune evolution under various pulsing strategies. The results of this work could lead to improved therapy schedules in patients responsive to checkpoint inhibitors that exploit the complex dynamics of immune response and suppression.
Citation Format: Sandhya Prabhakaran, Taylor M. Bursell, Kimberly Luddy, Julian Pineiro, Rafael Bravo, Jeffrey West, Megan Johnson, Mark Robertson-Tessi, Amer A. Beg, Jhanelle E. Gray, Scott Antonia, Robert A. Gatenby, Alexander R. A. Anderson. Evolutionary immunotherapy in NSCLC: An integrated approach [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr A021.