Identification of a Prognostic Model Based on Fatty Acid Metabolism-Related Genes of Head and Neck Squamous Cell Carcinoma - Du, Peiyu; Chai, Yue; Zong, Shimin; Yue, Jianxin; Xiao, Hongjun (Frontiers in Genetics, 2022)
Background： The fatty acid metabolism (FAM) is known to impact tumorigenesis, tumor progression and treatment resistance via enhancing lipid synthesis, storage and catabolism. However, the role of FAM in head and neck squamous cell carcinoma (HNSCC) has remained elusive. Objective: Provide a bioinformatic profiling of the fatty acid catabolic metabolism-related gene risk signature for the malignancy, prognosis and immune phenotype of HNSCC. Method: The relevant data of HNSCC were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Fatty acid metabolism-related genes (DEGs) were screened to establish a prognostic signature by a multivariate Cox proportional hazards regression model. Following Cox regression with differentially expressed genes, our prognosis model (PS-score) was built by LASSO-Cox analysis. GO and KEGG pathway analyses to DEGs between fatty acid metabolism-related high-risk and low-risk groups were performed. Results: We found 12 risk signature genes that had high prognostic values to predicted clinical and molecular characteristics of HNSCC. A prognostic nomogram of 1-, 3-, and 5-year survival was established and validated. Correlation analysis showed that our risk profile was closely related to immune cells involved in the microenvironment of HNSCC. Furthermore, the fatty acid catabolic metabolism-related gene risk signature was also found to be significantly correlated with immune cell infiltration. Conclusion: We have biuld a FAM-related gene expression-based risk signature that could predict the prognosis of HNSCC independently; and our study might contribute to better understanding of metabolic pathways and further developing of novel therapeutic approaches for HNSCC.