期刊
GENE REPORTS
卷 24, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.genrep.2021.101243
关键词
Oral squamous cell carcinoma; Poor prognosis; Prognostic biomarker; Protein-protein interaction network; Survival analysis
资金
- Dental Research Center
- Research Center for Molecular Medicine, Hamadan University of Medical Sciences, Hamadan - Iran
The study identified 35 differentially expressed miRNAs in oral squamous cell carcinoma patients with poor prognosis. Pathways and biological processes related to ubiquitination and RNA splicing were affected in the poor prognosis group. Aberrant expression of 22 hub genes was significantly associated with worse overall survival in patients with oral squamous cell carcinoma.
Background: 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. Methods: 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. Results: A total of 35 DEMs were found with the criteria of P < 0.001 and absolute value of Log2 fold change > 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 <0.01. Conclusions: The results showed that a total of 22 genes including EGF, RTN4, RAN, ACTB, and CYCS may be considered as potential biomarkers for prognostic aims of OSCC.
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