Integrated bioinformatics analysis of mRNAs and miRNAs identified potential biomarkers of oral squamous cell carcinoma

Abstract

Background: Oral cancer is a frequently encountered neoplasm of the head and neck region, being the eighth most common type of human malignancy worldwide. Despite improvement in its control, morbidity and mortality, rates have improved little in the past decades. The present investigations about gene interaction and pathways still could not clear the appearance and development of oral squamous cell carcinoma (OSCC), completely. The aim of this study is to investigate the key genes and microRNAs interaction in OSCC. Materials and Methods: The microarray datasets GSE13601 and GSE98463, including mRNA and miRNA profiles, were extracted from the GEO database and were analyzed using GEO2R. Functional and pathway enrichment analyses were performed by using the DAVID database. The protein-protein interaction (PPI) network was constructed and analyzed using STRING database and Cytoscape software, respectively. Finally, miRDB was applied to predict the targets of the differentially expressed miRNAs (DEMs). Results: Totally, 97 differentially expressed genes (DEGs) were found in OSCC, including 66 up-regulated and 31 down-regulated genes. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses showed that up-regulated genes were significantly enriched in movement of cell or subcellular component, cell adhesion, biological adhesion, cellular localization, apoptotic signaling pathway, while the downregulated genes were enriched in muscle system process and oxidation-reduction process. From the PPI network, the top 10 nodes with the highest degree were detected as hub genes. In addition, 18 DEMs were screened, which included 7 up-regulated and 11 down-regulated miRNAs. STAT1 was potentially targeted by three miRNAs, including has-miR- 6825-5P, has-miR-4495, and has-miR-5580-3P. Conclusion: The roles of DEMs such as hsa-mir-5580-3p in OSCC through interactions with DEGs CD44, ACLY, ACTR3, STAT1, LAMC2 and YWHAZ may offer a suitable candidate biomarker pattern for diagnosis, prognosis and treatment processes in OSCC.