Speaker
Description
Chimeric antigen receptor T-cell (CAR T) therapy has demonstrated remarkable efficacy in hematological malignancies. However, resistance remains a major clinical challenge, as it can compromise treatment response and promote relapse. Among the mechanisms that may underlie resistance, loss or downregulation of the target antigen is particularly relevant, since it enables tumor cells to escape immune recognition.
In this work, we develop a spatial agent-based model based on cellular automata to investigate the role of tumor phenotypic heterogeneity and antigen-dependent cytotoxicity in the emergence of resistance. The model represents interactions between tumor cells and CAR T-cells on a lattice and incorporates experimental measurements of antigen expression obtained from flow cytometry. Tumor proliferation includes a stochastic phenotypic inheritance mechanism that allows antigen levels to vary across generations.
Simulations reproduce sequential co-culture experiments and show that reduced cytotoxicity against low-antigen cells promotes the clonal selection of resistant subpopulations. This process can be interpreted as a therapy-driven drift in antigen expression, analogous to resistance dynamics described in other targeted therapies, and reveals evolutionary dynamics of the antigen under treatment pressure. These findings highlight the importance of accounting for treatment-specific efficacy when designing more effective therapeutic strategies.
