Spatiotemporal Agent-Based Modeling of Immune Control Gates in the Tumor-Draining Lymph Node
Abstract
The abscopal effect, where local radiotherapy (RT) induces regression of distant tumors, reveals the immune system's latent capacity for systemic tumor control. Although RT reliably triggers antigen release and type-I interferon (IFN-I) signaling that licenses dendritic cells (DCs) to activate CD8⁺ T cells, these priming events seldom propagate beyond the irradiated site. This failure highlights a regulatory bottleneck within the tumor-draining lymph node (tdLN), where local activation must be converted into systemic immunity. Here, we develop a spatiotemporal agent-based model (ABM) that formalizes the tdLN as an immune control architecture rather than a passive priming site. The model incorporates DC licensing, CD8⁺ T-cell scanning and differentiation, checkpoint saturation, and fibroblastic reticular cell (FRC)–guided topology that shapes DC–T-cell encounter probabilities. This integrated framework reproduces four mechanistic gates underlying abscopal failure: (i) threshold-dependent amplification of early immune cues, (ii) temporal synchronization among DC influx, antigen persistence, and T-cell availability, (iii) topology-driven spatial biasing of interactions by the FRC scaffold, and (iv) density-induced checkpoint dominance that suppresses otherwise antigen-rich contexts. Systemic amplification emerges only when DC licensing, antigen durability, and IFN-I timing align with FRC-guided topology to sustain productive DC–T-cell encounters. Simulations further reveal how immunotherapies such as STING agonism, DC maturation signals, and checkpoint blockade each engage distinct control gates within the tdLN, reshaping immune trajectories through non-overlapping mechanisms. Together, this work defines the control logic governing tdLN-mediated immune propagation and demonstrates how coordinated modulation of topology, timing, and feedback can transform rare abscopal responses into reproducible systemic immunity.
Bio coming soon.