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Background CD161 +CD8+ T cells, a cytotoxic T cell subset, remain poorly defined in terms of their clinical significance and functional role in esophageal squamous cell carcinoma (ESCC), which has limited the advancement of precision immunotherapy strategies.Methods We integrated a multicenter cohort of ESCC patients who underwent either surgery or neoadjuvant therapy (chemotherapy or chemoimmunotherapy). Multiplex immunofluorescence staining, survival analyses, and assessment of major pathological response (MPR) and pathological complete response (pCR) were performed to elucidate the clinical relevance of CD161 +CD8+ T cell infiltration. The functional state and cellular interactions of this subset were characterized using single-cell RNA sequencing. A CT-based radiomics model was also developed for non-invasive prediction.Results High intratumoral infiltration of CD161 +CD8+ T cells was identified as an independent prognostic factor for prolonged overall survival and disease-free survival (both p<0.01) and appeared to correlate with a higher MPR and pCR rate following neoadjuvant therapy. This subset was enriched in treatment responders, exhibited transcriptional features associated with cytotoxicity and activation, and showed gene expression profiles suggestive of potential interactions with tumor-associated macrophages, possibly involving the TNFRSF9/TNFSF9 (4-1BB/4-1BBL) signaling axis. A radiomics model built on the XGBoost algorithm accurately predicted the infiltration level of this subset (area under the curve=0.889), and predicted high infiltration was correlated with favorable pathological response.Conclusions We identify CD161 +CD8+ T cells as a pivotal prognostic and predictive biomarker in ESCC. This subset is associated with a putative 4-1BB/TNFSF9-mediated interaction network involving macrophages, correlating with a coordinated anti-tumor immune microenvironment. The CT-based radiomics model could provide a noninvasive means for assessing immune phenotypes, with potential applicability in patient stratification and treatment selection.