Abstract Background: Oropharyngeal squamous cell carcinoma (OPSCC), is a distinct subset of head and neck squamous cell carcinomas, with an increasing incidence largely due to HPV infection. Despite established treatments such as cisplatin-based chemoradiotherapy or cetuximab-RT, outcomes remain poor for advanced cases, with high recurrence rates. There is an urgent need for predictive biomarkers to inform treatment decisions and identify patients at risk of treatment failure. Materials and methods: In a retrospective cohort, we analyzed pre-treatment tumor biopsies from 84 OPSCC patients. We conducted comprehensive profiling of the tumor immune microenvironment (TIME) using histopathological evaluation, immunohistochemistry (IHC), and transcriptomic analysis via the NanoString nCounter® PanCancer Immune Profiling Panel. We correlated tumor-infiltrating lymphocyte density, immune marker expression, and gene expression signatures with clinical outcomes. Results: Patients without recurrence had a TIME enriched with B and T lymphocytes, dendritic cells, and NK cells. Recurrent tumors showed higher neutrophil infiltration. IHC markers including CD3, CD8, CD20, FOXP3, and PD-L1 were significantly associated with improved RFS. Transcriptomic analysis confirmed these findings and enabled the development of a 14-gene Immune Signature Recurrence Score (ISRS). The ISRS achieved high predictive accuracy for recurrence and outperformed conventional clinical predictors. External validation using a published OPSCC dataset supported the prognostic relevance of the ISRS for overall survival and its robustness across independent cohorts, although this represents an indirect validation due to the lack of recurrence data. Conclusion: This exploratory study highlights the prognostic significance of a robust lymphocyte-rich TIME and introduces a clinically relevant 14-gene immune signature that outperforms traditional markers in predicting recurrence in OPSCC. These results suggest that integrating immune gene signatures into routine clinical practice could refine risk stratification and guide personalized therapy.
Beltzung et al. (Mon,) studied this question.