Identification of potential biomarkers associated with poor prognosis in oral squamous cell carcinoma through integrated bioinformatics analysis: A pilot study

Oral squamous cell carcinoma (OSCC) is the most frequent subtype of oral cancer with 90% of the OC cases. The mortality rate of OSCC is high and the overall survival of the patients is 50%. There is a need to discover novel biomarkers for prognosis of OSCC. The miRNA dataset GSE107830 was downloaded from the GEO database and analyzed to identify differentially expressed miRNAs (DEMs) in OSCC patients with poor prognosis compared to favorable prognosis patients. A protein-protein interaction network was constructed and analyzed. The most significant clusters in the PPI network were identified, and the biological processes (BPs) and pathways associated with each of the clusters were studied. The hub genes were identified and the survival analysis was performed to examine the potential prognostic role of the hub genes in OSCC. A total of 35 DEMs were found with the criteria of P 0.58. The most significant pathways and BPs affected in poor prognosis group were associated with ubiquitination and RNA splicing. The survival analysis revealed that the aberrant expression of 22 hub genes was significantly associated with worse overall survival in OSCC. The most significant Kaplan-Meier curves were achieved from EGF, RTN4, RAN, ACTB, and CYCS genes with the Logrank test P-value of