Preexisting TCR Clones Drive Major Pathologic Responses in Patients with HNSCC Treated with Dual Immune Checkpoint Inhibitors

PURPOSE: Immune checkpoint inhibitors (ICI) elicit variable responses in head and neck squamous cell carcinoma (HNSCC), yet mechanisms driving major pathologic responses (MPR) remain poorly defined. We sought to evaluate longitudinal CD8 T-cell repertoire evolution to identify determinants of MPR. PATIENTS AND METHODS: We analyzed high-resolution single-cell T-cell receptor (TCR) sequencing data from paired pretreatment and posttreatment CD8 tumor-infiltrating lymphocytes obtained from patients with HNSCC treated with neoadjuvant anti-PD-1 combined with either anti-CTLA-4 or anti-LAG3. RESULTS: Contrary to the clonal replacement hypothesis, posttreatment CD8 T-cell pools were dominated by preexisting TCR clones regardless of clinical outcome. MPR was uniquely characterized by higher abundance and greater expansion magnitude of super-expanded clones. We developed the TCR adaptivity index (TAI) to quantify coordinate flux (expansion and contraction) of all TCR clones detected across pretreatment and posttreatment time points; this index emerged as the most significant parameter associated with MPR. Importantly, clonal expansion in non-MPR was uncoupled from the productive, therapy-induced transcriptional reprogramming-characterized by markers of effector vigor and cellular fitness-that was observed in MPR. Furthermore, expansion dynamics positively correlated with predicted tumor reactivity as calculated by the tumor-reactive signature (TRS) score. Finally, a TRS-integrated TAI remained significantly correlated with MPR. CONCLUSIONS: Dual-ICI drives MPR predominantly through the adaptivity and functional reprogramming of preexisting immunity. Successful therapy relies on a coordinate repertoire response that promotes transition of putative tumor-reactive super-expanders into productive functional states. TRS-integrated TAI provides a high-throughput framework incorporating clonal dynamics and functional reprogramming to predict therapeutic efficacy.