Annals of Translational Medicine · 2020 · 10 citations · 40 references
DentistryCancer BiologyOral PathologyCarcinogenesisOral Cancer BiologyOral OncologyOral Cancer BiomarkersOral CarcinogenesisOral MucosaOral Mucosal DiseasesOral Mucosal LesionsOral NeoplasiaCircular Ribonucleic AcidsCircular Rna TranscriptomicsCircular RnasOral Epithelial CarcinogenesisOral Leukoplakia AssessmentOral Mucosal HistopathologyPotentially Malignant Oral Mucosal DisordersPremalignant Oral Lesions
BACKGROUND: Emerging evidence indicates that circular RNAs (circRNAs) play an indispensable role in a variety of tumors, yet the function of circRNAs in premalignant lesions is still obscure. Oral leukoplakia (OLK) is one of the most common premalignant lesions of the oral mucosa. Our study aimed to comprehensively investigate whether circRNAs contribute to the occurrence and development of OLK. METHODS: We obtained six pairs of OLK and normal oral mucosal (NOM) tissue samples and subjected them to high-throughput sequencing to detect the expression of circRNA. In total, 26 pairs of NOM and OLK tissues were used for validation. Key circRNAs were selected and further validated by real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR), ribonuclease (RNase) R digestion, and Sanger sequencing. Visualization analysis of circular human leukocyte antigen-C (circHLA-C) was performed in the UCSC Genome Browser (genome.ucsc.edu). Functional analysis of differentially expressed (DE) circRNAs were processed by Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Furthermore, TargetScan (www.targetscan.org) was applied to predict targeted micro RNAs (miRNAs) and messenger RNAs (mRNAs) of circRNAs and a competing endogenous RNA (ceRNA) network related with identified circRNAs was constructed in Cytoscape (v2.8.0). RESULTS: Profile data showed that 366 circRNAs were significantly altered in OLK tissues, including 65 upregulated and 301 downregulated circRNA transcripts. Compared with sequencing results, seven selected circRNAs expressed the same changing tendency. The amplest upregulated circRNA in our sequencing data, circHLA-C, was confirmed through back-splice junction sequences by Sanger sequencing after RNase R digestion. Correlation analysis demonstrated that circHLA-C correlated positively with the degree of dysplasia. Furthermore, receiver operating characteristic (ROC) curve analysis indicated that circHLA-C had potential diagnostic value with excellent accuracy and specificity. CONCLUSIONS: According to the literature, we were the first to uncover the expression profiles of circRNAs in OLK. Our research performed a comprehensive bioinformatics analysis of DE circRNAs in OLK and identified circHLA-C as a promising diagnostic biomarker with potential as a therapeutic genetic target for OLK.
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