Mathematical Modeling Predicts Optimal Immune Checkpoint Inhibitor and Radiotherapy Combinations and Timing of Administration.

Radiotherapy (RT) combined with immune checkpoint inhibitor (ICI) therapy has attracted substantial attention due to its potential to improve outcomes for patients with several types of cancer. However, the optimal administration timepoints and drug combinations remain unclear because the mechanisms underlying RT-induced changes in immune checkpoint molecule expression and interaction with their ligand(s) remain unclear. In this study, we demonstrated the dynamics of lymphocyte-mediated molecular interactions in tissue samples from patients with esophageal cancer throughout RT schedules. Single-cell RNA sequencing and spatial transcriptomic analyses were performed to investigate the dynamics of these interactions. The biological signal in lymphocytes transitioned from innate to adaptive immune reaction, with increases in ligand-receptor interactions, such as PD-1-PD-L1, CTLA4-CD80/86, and TIGIT-PVR interactions. A mathematical model was constructed to predict the efficacy of five types of ICIs when administered at four different timepoints. The model suggested that concurrent anti-PD-1/PD-L1 therapy or concurrent/adjuvant anti-CTLA4/TIGIT therapy would exert a maximal effect with RT. This study provides rationale for clinical trials of RT combined with defined ICI therapy, and these findings will support future studies to search for more effective targets and timing of therapy administration.