Engineering TCR-controlled fuzzy logic into CAR T cells enhances therapeutic specificity
- PMID: 40220754
- PMCID: PMC12107475
- DOI: 10.1016/j.cell.2025.03.017
Engineering TCR-controlled fuzzy logic into CAR T cells enhances therapeutic specificity
Abstract
Chimeric antigen receptor (CAR) T cell immunotherapy represents a breakthrough in the treatment of hematological malignancies, but poor specificity has limited its applicability to solid tumors. By contrast, natural T cells harboring T cell receptors (TCRs) can discriminate between neoantigen-expressing cancer cells and self-antigen-expressing healthy tissues but have limited potency against tumors. We used a high-throughput platform to systematically evaluate the impact of co-expressing a TCR and CAR on the same CAR T cell. While strong TCR-antigen interactions enhanced CAR activation, weak TCR-antigen interactions actively antagonized their activation. Mathematical modeling captured this TCR-CAR crosstalk in CAR T cells, allowing us to engineer dual TCR/CAR T cells targeting neoantigens (HHATL8F/p53R175H) and human epithelial growth factor receptor 2 (HER2) ligands, respectively. These T cells exhibited superior anti-cancer activity and minimal toxicity against healthy tissue compared with conventional CAR T cells in a humanized solid tumor mouse model. Harnessing pre-existing inhibitory crosstalk between receptors, therefore, paves the way for the design of more precise cancer immunotherapies.
Keywords: CAR T cells; TCR; cancer immunotherapy; fuzzy logic; humanized in vivo toxicity model; on-target/off-tumor toxicity; robotics; systems immunology; theoretical modeling.
Copyright © 2025 Elsevier Inc. All rights reserved.
Conflict of interest statement
Declaration of interests The authors declare no competing interests.
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