A transcriptional metabolic gene-set based prognostic signature is associated with clinical and mutational features in head and neck squamous cell carcinoma

Purpose Head and neck squamous cell carcinoma (HNSCC) is a common cancer with high mortality and poor prognosis partially owing to lack of application of predictive markers. Increasing evidence has suggested that metabolic dysregulation plays an important part in tumorigenesis. We aim to identify a prognostic metabolic pathway (MP) signature in HNSCC. Methods Single sample gene-set enrichment analysis (ssGSEA) was used in metabolic gene sets to develop a metabolism-based prognostic risk score (MPRS) for HNSCC using Cox regression analysis (univariate, LASSO, and stepwise multiple cox analysis), which was then validated in different subgroups, and association with clinical and mutational features was analyzed. Results Seventy-two dysregulated metabolic pathways were identified, and a six-MP signature (6MPS) was constructed which can effectively distinguish between the high- and low-risk patients in both training and testing sets, accompanied with high sensitivity and specificity (AUC = 0.7) in prognosis prediction. 6MPS was also applicable to patients of different subgroups. Furthermore, 6MPS is not only an independent prognostic predictor but also associated with clinicopathological and mutational features. Higher tumor stage and tumor mutation burden (TMB) have a higher MPRS. Conclusion 6MPS functions not only as a promising predictor of prognosis and survival but also as potential marker for therapeutic schedule monitoring.