Objectives This retrospective study presents an integrative transcriptomic approach for recurrent and/or metastatic head and neck squamous cell carcinoma (R/M HNSCC) by developing an immune response predictive score (IORPS) derived from tumor microenvironment (TME) transcriptomic profiles. Methods A total of 30 R/M HNSCC patients treated with pembrolizumab or nivolumab, with available immune TME profiling data, were analyzed. IORPS was constructed based on the cumulative weighting of differentially expressed gene (DEG) expression levels. The predictive performance of conventional biomarkers, individual DEGs, and IORPS was evaluated for immunotherapy response and prognostic outcomes. The clinical relevance of IORPS was further validated using two external cohorts from the GEO database (CLB-IHN: GSE159067 and GHPS: GSE159141). Results By comparing immune tumor microenvironment (TME) profiles between good and poor responders, GZMH , IFNG , and FASLG were identified as key DEGs with significantly higher expression in favorable immunotherapy responders. The IORPS, derived from transcriptomic profiling, demonstrated robust predictive accuracy for both immunotherapy response and survival outcomes in patients with R/M HNSCC. Conclusion Compared with the variable predictive performance of current biomarkers such as TPS and CPS, IORPS provides improved accuracy and reliability in identifying and stratifying patients most likely to benefit from immune checkpoint blockade therapy.
Wang et al. (Thu,) studied this question.
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