Identification of AUNIP as a Candidate Diagnostic and Prognostic Biomarker for Oral Squamous Cell Carcinoma

Abstract

Background: Oral squamous cell carcinoma (OSCC) is one of the most common malignant tumors worldwide. Patients with poorly differentiated OSCC often have a poor prognosis. It is essential to search for promising diagnostic and prognostic biomarkers for OSCC. Methods: The differentially expressed genes (DEGs) were obtained using R language. Receiver operating characteristic curve analysis was performed to identify diagnostic markers for OSCC. AUNIP expression was analyzed in publicly available databases and clinical specimens. Bioinformatics analysis and in vitro experiments were conducted to explore biological functions and prognostic value of AUNIP in OSCC. Findings: The gene integration analysis revealed 90 upregulated DEGs. One candidate biomarker, AUNIP, for the diagnosis of OSCC was detected. Weighted gene co-expression network analysis and function enrichment analysis demonstrated that genes positively associated with AUNIP were enriched in cell cycle and the module eigengene was significantly correlated with the survival rate of OSCC patients. In gene set enrichment analysis, the correlation between AUNIP expression and human papillomavirus status in OSCC was verified. The suppression of AUNIP inhibited OSCC cell proliferation and resulted in G0/G1 phase arrest in OSCC cells. The survival analysis showed that AUNIP overexpression interrelated with the poor prognosis of OSCC patients. Interpretation: AUNIP could serve as a candidate diagnostic and prognostic biomarker for OSCC and suppression of AUNIP may be a potential approach to prevent and treat OSCC. Funding Statement: Taishan Scholars Project in Shandong Province (ts201511106) and the National Natural Science Foundation of China (Nos. 61603218). Declaration of Interests: The authors declare no conflicts of interest. Ethics Approval Statement: The samples were approved by Taizhou hospital Ethics Committee in Zhejiang province.