A Circulating GPNMB-Based Multimodal Model Integrates Tumor-Immune Crosstalk to Predict Immunotherapy Response in Esophageal Cancer.

Neoadjuvant immunotherapy improves outcomes in esophageal squamous cell carcinoma (ESCC), yet ∼70% of patients fail to respond. Pretreatment biopsies and plasma provide critical opportunities for biomarker discovery. In this study, we performed plasma proteomic profiling and identified soluble glycoprotein nonmetastatic melanoma protein B (sGPNMB) as the most elevated circulating protein in nonresponders. Mechanistically, tumor cell-derived sGPNMB suppressed CD8+ T-cell receptor signaling via the SDC4-CD148 axis to induce functional exhaustion, with secretion being required for its immunosuppressive activity. Cancer-associated fibroblast-epithelial (CAF-Epi) niches promoted SOX2 upregulation in tumor cells, transcriptionally activating GPNMB expression. In humanized patient-derived xenograft models, circulating GPNMB levels predicted response to PD-1 blockade, and GPNMB inhibition synergized with therapy. Across retrospective cohorts and a prospective clinical trial, a multimodal model combining plasma GPNMB levels, CAF-Epi niche detection, and clinical-pathologic features achieved robust predictive accuracy for immunotherapy response and survival. These findings establish a spatial-circulating biomarker framework for precision ESCC immunotherapy. SIGNIFICANCE: Tumor-derived soluble GPNMB, transcriptionally activated by SOX2 within CAF-Epi niches, drives CD8+ T-cell exhaustion and resistance to PD-1 blockade in ESCC. Integrating circulating GPNMB levels with CAF-Epi niche features and clinical-pathologic factors, we develop and validate a clinically scalable multimodal model for predicting immunotherapy response.