Evaluating glycolysis-associated biomarkers for radiotherapy sensitivity in head and neck squamous cancer.

BACKGROUND

Head and neck squamous cell carcinoma (HNSC) present a significant treatment challenge due to variability in radiotherapy response, where glycolysis may play a pivotal role in modulating sensitivity. This study aimed to develop a glycolysis-associated biomarker for radiotherapy sensitivity.

METHODS

We analyzed gene expression and clinical data from 491 HNSC patients and single-cell RNA sequencing to assess glycolysis activity in HNSC. A glycolysis-associated radiosensitivity index (RI) was developed using Cox regression analysis of glycolysis-related genes. Immune microenvironment profiles, functional pathways, and therapeutic responses were analyzed via using ssGSEA, CIBERSORT, TIDE, and pRRophetic. In vitro experiments validated glycolytic activity and radiosensitivity in HNSC cell lines.

RESULTS

The study identified that low glycolytic activity significantly correlates with improved overall survival in HNSC patients following radiotherapy, while high glycolytic activity is associated with radio-resistance. Using a RI based on glycolysis-related gene expression, we successfully stratified patients into RS and RR groups. RS tumors exhibited significantly higher immune cell infiltration and lower TIDE scores, indicating a better response to immunotherapy. In contrast, RR tumors showed increased sensitivity to chemotherapy agents, including platinum and EGFR/HER2 inhibitors. Single-cell RNA sequencing revealed that high-glycolysis tumors had diminished immune cell infiltration, particularly lacking CD8+ T cells, supporting the notion of immune evasion. In vitro validation further demonstrated that radioresistant CAL-27IR cells displayed elevated glycolytic activity and upregulation of key genes associated with the RI, showing the link between glycolysis and radiation resistance.

CONCLUSION

This study emphasizes the importance of glycolytic activity in influencing radiotherapy sensitivity and highlights the potential of the RI as a predictive biomarker, paving the way for improved personalized treatment strategies in HNSC.