Identification of potential genetic markers in prognosis of oral squamous cell carcinoma patients by bioinformatic analysis

Abstract

Objective To analyze the differentially expressed genes of patients with oral squamous cell carcinoma (OSCC) from paracarcinoma through biological information analysis to preliminarily identify OSCC-associated genes. Methods GSE23558, GSE37991 and GSE30784 were downloaded from the Gene Expression Omnibus (GEO), which is the mRNA expression profile dataset. The differentially expressed genes (DEGs) were identified based on the gene ontology and the Kyoto Encyclopedia of Genes and Genomes. Then, the protein-protein interaction (PPI) network was constructed using the STRING online tool, and Cytoscape was used to filter the critical genes. Furthermore, key genes involved in the survival of patients with OSCC were analyzed using Kaplan-Meier analysis. The expression of hub genes was validated based on GEPIA（http://gepia.cancer-pku.cn/）. Results A total of 212 DEGs were screened, and further analysis revealed 16 core genes, among which the core genes associated with prognosis included aurora kinase A (AURKA), aurora kinase B (AURKB), apoptosis inhibiting factor 5 (BIRC5), cell division cycle 6 (CDC6), E2F transcription factor 7 (E2F7), ubiquitin-like with PHD and ring finger domains 1 (UHRF1). These key genes were highly expressed in patients with oral squamous cell carcinoma, and the survival time of patients was short; the difference was statistically significant (P < 0.05). Conclusion AURKA, AURKB, BIRC5, CDC6, E2F7 and UHRF1 may be useful as potential biomarkers for OSCC prognosis prediction.

Keywords

• oral squamous cell carcinoma，
• bioinformatics，
• biomarker，
• differentially expressed genes，
• microarray，
• aurora kinase，
• baculoviral iap repeat containing 5，
• cell division cycle 6，
• e2f transcription factor 7，
• ubiquitin-like with phd and ring finger domains 1，