Decoding TCR specificity and T cell fate at the immunological synapse

Liu et al. (2026) introduce proximity labeling for rapid screening of disease-relevant T cell repertoires (PRECISE-seq), a contact-dependent labeling strategy coupled with single-cell multi-omics. The platform is built on two key design features. First, T cells are uniformly equipped with an acceptor peptide via a two-step chemical conjugation. Second, antigen-presenting cells are engineered to express sortase A (SrtA) on their surface. Upon formation of an immunological synapse, SrtA catalyzes transpeptidation to transfer a biotinylated probe onto adjacent T cells. Because this reaction occurs strictly at sites of cell–cell contact, it minimizes background labeling and enables selective tagging independent of activation state or subset identity.

In validation experiments, PRECISE-seq detects antigen-specific T cells at frequencies as low as 0.01%. Notably, labeling intensity scales with TCR-pMHC interaction strength, as shown by graded biotin signals across altered peptide ligands with defined affinities. This provides a quantitative, activation-free readout of functional avidity. Building on this, the authors define a clonotype-level “potency score” that correlates with independently measured EC₅₀ values for CMV-specific TCRs.

Applied to peripheral blood from CMV-seropositive donors, PRECISE-seq retrieves virus-specific clonotypes and reveals that high-potency clones co-express activation and exhaustion programs, consistent with the notion that repeated high-avidity stimulation drives T cell exhaustion. In tumors, however, the analysis uncovers a distinct and unexpected differentiation trajectory. Using the MC38 colon carcinoma model, the authors show that tumor-specific CD8⁺ T cells preferentially adopt a Ly49⁺ regulatory state (T_Ly49). This population expresses natural killer (NK)-associated inhibitory receptors (e.g., Klra3, Klra5), FcεRIg, and the transcription factor Helios (Ikzf2) and is functionally characterized by production of immunosuppressive mediators such as SPP1 (osteopontin) with minimal IFN-γ output. Adoptive transfer experiments demonstrate that T_Ly49 cells actively promote tumor growth, establishing them as bona fide immunosuppressive effectors rather than merely dysfunctional or exhausted T cells. Trajectory analysis further indicates that T_Ly49 diverges from effector memory T cell (T_EM) progenitors along a differentiation pathway distinct from the canonical T_PEX-to-T_EX exhaustion route (Lan et al., 2024), suggesting a parallel fate decision. Importantly, PD-1 blockade markedly reduces the frequency of T_Ly49 while expanding effector T_EM and T_EFF compartments among tumor-specific clonotypes. This shift is mirrored in human datasets across multiple cancer types, including mismatch repair–deficient colorectal cancer, hepatocellular carcinoma, and metastatic melanoma, positioning Ly49/KIR⁺ CD8⁺ T cells as a clinically relevant immunoregulatory state linked to responsiveness to checkpoint blockade.

At the technical level, PRECISE-seq unifies three dimensions that have traditionally been analyzed separately into a single-cell framework. Its ability to infer TCR functional potency directly from labeling intensity, without prior epitope knowledge or in vitro stimulation, is particularly advantageous for translational settings, where preserving endogenous T cell states is critical.

At the biological level, the identification of T_Ly49 as a distinct immunoregulatory fate for tumor-specific CD8⁺ T cells challenges the prevailing view that exhaustion is the dominant dysfunctional endpoint in tumors (Ford et al., 2022). Rather than passively losing effector function, these cells actively support tumor progression through a defined suppressive program, reframing how T cell fate decisions are conceptualized in the tumor microenvironment. Moreover, the finding that PD-1 blockade shifts the balance away from T_Ly49 cells toward effector populations provides a mechanistic lens on checkpoint therapy responsiveness and highlights the T_EM/T_EFF-to-T_Ly49 ratio as a potential predictive biomarker.

Several key questions emerge. First, although T_Ly49 cells are linked to human KIR⁺ CD8⁺ T cells using patient scRNA-seq data (Li et al., 2022), their suppressive function in human tumors remains to be directly established. Whether these cells share analogous differentiation trajectories, effector programs, and sensitivity to αPD-1 antibody requires experimental validation. Second, the relationship between TCR potency and T_Ly49 differentiation is currently correlative. It remains unclear whether high-avidity TCR signaling actively instructs this regulatory fate, or whether extrinsic factors, such as persistent antigen exposure, inflammatory context, or metabolic stress, are the dominant drivers. This question could be addressed by transferring T cells engineered with affinity-graded TCRs against the same antigen into tumor-bearing hosts. More broadly, it raises the possibility that the T cell fate is not linearly dictated by signal strength, but instead follows an optimal “window” in which effector function is maximized while avoiding regulatory or exhausted states (Shakiba et al., 2022). Third, it will be important to determine whether PRECISE-seq labeling intensity faithfully reports functional avidity in solid tumor environments, where hypoxia, acidity, and extracellular matrix constraints may influence cell–cell contact and synapse formation (Wang et al., 2024).

From a translational perspective, applying PRECISE-seq longitudinally to patient samples collected before and during immunotherapy could enable real-time tracking of T cell state transitions, offering mechanistic insight into response and resistance. In the context of adoptive cell therapy, the platform provides a rational framework for selecting TCRs that balance sufficient antigen reactivity with favorable differentiation potential, avoiding receptors whose excessive avidity may inadvertently bias cells toward regulatory fates. Integrating potency measurements with fate prediction may therefore enhance the design of next-generation T cell–based therapies.

This work was supported by the Noncommunicable Chronic Diseases–National Science and Technology Major Project (2024ZD0520600), the National Natural Science Foundation of China (32525028 and 32270994 to G. Li, and 323B2029 to Y. Wang), the Basic Research Program of Jiangsu (BK20255001 and BK20250003 to G. Li), the Nonprofit Central Research Institute Fund of Chinese Academy of Medical Sciences (CAMS) (2021-RC310-014 and 2024-JKCS-15 to G. Li), and the CAMS Innovation Fund for Medical Sciences (2025-I2M-GCC-006 to G. Li). We thank the Suzhou Municipal Key Laboratory (SZS2023005) and the National Center of Technology Innovation for Biopharmaceuticals Fund for R&D Platform for Cell and Gene Therapy.

Author contributions: Rundi Zhu: conceptualization, visualization, and writing—original draft, review, and editing. Yuqian Wang: conceptualization, visualization, and writing—original draft, review, and editing. Guideng Li: conceptualization, funding acquisition, supervision, and writing—original draft, review, and editing.