Abstract
BACKGROUND: Metabolic reprogramming is one of the essential features of tumorigenesis. Herein, this study aimed to develop a novel metabolism-related gene signature for head and neck squamous cell carcinoma (HNSCC) patients. METHODS: The transcriptomic and clinical data of HNSCC samples were collected from The Cancer Genome Atlas (TCGA) and GSE65858 datasets. The metabolism-related gene-based prognostic signature (MRGPS) was constructed by the Least Absolute Shrinkage and Selection Operator (LASSO) regression model. The time-dependent receiver operating characteristic (ROC) and Kaplan-Meier (K-M) survival curves were plotted for evaluating its predicting performance. At the same time, univariate along with multivariate analysis was carried out to explore its correlation with clinicopathologic factors. Furthermore, GSEA analysis was performed to explore the signaling pathways affected by MRGPS. We also analyzed the associations of MRGPS with the tumor immune microenvironment (TIME), as well as identified potential compounds via Connectivity Map (CMap) and molecular docking. RESULTS: A total of 12 differentially expressed metabolism-related genes were identified and selected to construct the MRGPS. Notably, this signature performed well in predicting HNSCC patients' survival and could serve as an independent prognostic factor in multiple datasets. In addition to the metabolism-related pathway, this signature could also affect some immune-related pathways. The results indicated that MRGPS is correlated with immune cells infiltration and anti-cancer immune response. Furthermore, we identified cephaeline as a potential therapeutic compound for HNSCC. CONCLUSION: Taken together, we established an MRGs-based signature that has the potential to predict the clinical outcome and immune microenvironment, which help to search for potential combination immunotherapy compounds and provide a promising therapeutic strategy for treating HNSCC patients.