Back

Targeting ZC3H12C improves T cell persistence and antitumor function in adoptive T cell therapy

Kavishwar, G.; Perl, M.; Heuser-Loy, C.; Knoedler, L.; Shah, D.; Mastrogiovanni, F.; Herfeld, K.; Noronha, P.; Kovacs-Sautter, M.; Krieger, M.; Loipfinger, S.; Silveira, C. R. F.; Goettert, S.; Schelker, R.; Becker, L.-M.; Vadasz, T.; Gerlach, C.; Lutzny-Geier, G.; Gattinoni, L.; Poeck, H.; Schmidl, C.

2026-05-02 immunology
10.64898/2026.04.30.721618 bioRxiv
Show abstract

Adoptive T cell therapy (ACT) has achieved remarkable clinical responses in hematologic malignancies but remains limited by progressive T cell dysfunction under chronic antigen stimulation. Here, we identify ZC3H12C as a conserved feature of dysfunctional T cells and show that its disruption enhances the durability and antitumor activity of engineered T cells. By integrating single-cell chromatin accessibility and transcriptomic profiling of human tumor-infiltrating lymphocytes (TILs), we identified the ZC3H12C locus as selectively remodeled in exhausted T cells. ZC3H12C induction is largely absent across acute T cell activation contexts, indicating regulation that is specific to chronic antigen-driven dysfunction. Genetic disruption of ZC3H12C improves T cell expansion, cytotoxicity, and expression of effector molecules during repeated in vitro stimulation, translating into enhanced tumor control in vivo across both T cell receptor (TCR) and chimeric antigen receptor (CAR) T cell therapy platforms. Improved efficacy is observed in hematologic, solid, and metastatic tumor models and is accompanied by increased T cell persistence. Further, ZC3H12C is enriched in clinical pre-infusion CAR T cell products associated with non-response. Together, these findings identify ZC3H12C as a T cell dysfunction-specific target to improve ACT performance.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.