Identify an Innovative Fatty Acid Metabolism-Related Gene in Head and Neck Squamous Cell Carcinoma

Abstract Background: Head and neck squamous cell carcinomas (HNSCCs) are the sixth largest group of malignancies worldwide. Due to the highly aggressive, heterogeneousness and tumor microenvironment, the variable prognosis of HNSCC patients is changeable. Fatty acid metabolism-related genes (FAMGs) play a vital role in the development of malignant tumors, but the role in HNSCC is still unclear. The purpose of this study was to establish a reliable prognostic model based on FAMGs for evaluating the prognosis and immunotherapy of HNSCC patients and find the key prognostic genes to provide guidance for the early diagnosis and treatment. Methods: We obtained cancer-related data from various public databases. The FAMGs risk score model was established and proved by a combination of univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) regression analysis. Combining risk scores and clinical characteristics, a nomogram was created and validated. Subsequently, the function, immune difference, immune infiltration, enrichment analysis, and hub genes of the groups with high‐ and low‐risk scores were analyzed. Consequently, the mode's validity was evaluated comprehensively by combining single gene analysis and pan-cancer analysis. Results: we screened out 73 differentially expressed FAGMs and 9 genes associated with prognosis to construct a prognostic risk score model for genes related to fatty acid metabolism. The FAMGs signature was an independent prognostic factor for HNSCC, and patients in the low-risk group had higher overall survival (OS) than those in the high-risk group. In addition, we found differences in immune cell infiltration and enrich pathways between the different risk score groups. Finally, through the risk assessment model, combined with multiple databases, PTGDS, a high-risk and prognosis-related gene, was screened. And it showed a trend of low expression in many cancers, which predicted the prognosis of many cancers, especially in HNSCC. Conclusion: Metabolism-related genes affect the prognosis and survival of patients with HNSCC through affecting tumor microenvironment. And PTGDS can predict the survival and prognosis of cancer patients as an independent effective prognostic factor, particularly in HNSCC.