Identification of potential biomarkers and available drugs for oral squamous cell carcinoma

BACKGROUND: Oral squamous cell carcinoma (OSCC) is the most common oral tumor globally. However, optimal therapeutic targets for OSCC have not been identified. This study aimed to identify the potential gene markers and available drugs for OSCC. METHODS: Two transcriptional datasets containing OSCC gene expression data (GSE30784 and GSE23558) were selected from the Gene Expression Omnibus database. The interactive web tool GEO2R was then used to analyze the differentially expressed genes (DEGs) analysis. A Venn diagram was used to integrate the DEGs screened out by the two microarrays. Subsequently, a protein-protein interaction (PPI) network analysis of DEGs was performed using the Cytoscape, Database for Annotation, Visualization and Intergrated Discovery, and STRING databases. In addition to constructing the PPI networks among these DEGs, we chose several significant gene modules to conduct further gene-drug interaction analyses. Lastly, the existing drugs that target these module genes were selected to explore their therapeutic efficacy in treating OSCC. RESULTS: A total of 199 DEGs were screened out by the two microarrays. They were found to be associated with several processes, including the epoxygenase P450 pathway and the organelle membrane. The significant module genes in the PPI networks were CYP2E1, SCEL, KRT4, and KRT19. One existing drug, etoposide, which targets the CYP2E1 gene, was acquired. CONCLUSIONS: Four potential biomarkers (CYP2E1, SCEL, KRT4, and KRT19) and one existing drug (etoposide) were obtained for gene expression prediction through a series of bioinformatics methods.