Identification of Novel Prognostic Biomarkers in Head and Neck Squamous Cell Carcinoma using Bioinformatics Analysis

Background: Head and neck squamous cell carcinoma (HNSCC) is a common cancer that is characterized by a complex pathogenesis. Only limited data are available on the primary pathogenic genes and pathways in HNSCC. Objective: This study aimed to identify potential biomarkers of HNSCC and explore its underlying mechanisms. Methods: We screened differentially expressed genes (DEGs) using the Gene Expression Omnibus(GEO) database. Gene Ontology (GO) and Reactome pathway enrichment were analyzed using the STRING database. The protein-protein interaction network of the DEGs was reconstructed using Cytoscape software in STRING. The ONCOMINE and UNLCAN databases were used to identify the expression of hub genes. In addition, we employed UNLCAN to correlate tumor grade with key genes. Results: Finally, the effect of hub genes on overall survival (OS) was analyzed using the Kaplan- Meier method. In total, 22 DEGs were identified. These were related to the mitotic cell cycle, mitotic G1-G1, and S phases, G2/M transition, NOTCH signaling, and regulation of TP53 activity. Seven hub genes were screened with Cytoscape. Increased expression of five hub genes (AURKA, BIRC5, MKI67, UBE2C, and TOP2A) was related to a higher tumor grade and worse OS. Conclusion: We have identified five key genes that may help us understand the carcinogenic mechanisms related to the cell cycle in HNSCC. These genes may be used as biomarkers for survival and treatment of HNSCC.