Identification of Candidate Biomarkers and Analysis of Prognostic Values in Oral Squamous Cell Carcinoma

Abstract

Objectives:Oral squamous cell carcinoma(OSCC) is the most common oral cancer with a unsatisfied prognosis owing to limited understanding of the disease mechanisms. The aim of this study was to explore and identify the potential biomarkers in OSCC by comprehensive bioinformatics analysis. Materials and Methods:Expression profiles of long non-coding RNAs (lncRNAs), microRNAs (miRNAs) and messenger RNAs(mRNAs) were downloaded from The Cancer Genome Atlas (TCGA) and differentially expressed RNAs(DERNAs) were identified in OSCC by bioinformatics analysis. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathways analysis were used to analyze DERNAs. Subseqently, the competing endogenous RNA (ceRNA) network was constructed in Cytoscape and protein -protein interaction(PPI) network was established in STRING database. We established a risk model on the basis of DElncRNAs. Furthermore, we identified potential biomakers by combining univariate cox regression with overall survival ,and Gene Expression Omnibus(GEO),OSCC cell lines and OSCC specimens was used to validate biomarkers. Results:A total of 1919 DEmRNAs,286 DElncRNAs and 111 DEmiRNAs were identified. Subsequently,46 DElncRNAs,7 DEmiRNAs and 10 DEmRNAs were enrolled in ceRNA network.712 DEmRNAs including 31 hub genes were selectd in PPI network.Meanwhile, a 7 lncRNAs risk model was established and 4 genes (CMA1,GNA14,HCG22, HOTTIP) were identified as prognostic biomarkers in OSCC. Conclusions:This study successfully constructed lncRNA-miRNA-mRNA network suggesting the potential mechanism between mRNA and lncRNA.Furthermore,protein-protein network interpret the potential interaction relationship between mRNAs.Meanwhile, a risk model was established to predict the prognosis in OSCC. Eventually,4 molecules were identified as prognostic biomarkers and potential therapeutic targets for OSCC.