An Insilico Analysis: Three Upregulated microRNAs as Potential Diagnostic Biomarkers of Papillary Thyroid Carcinoma (PTC)

Background Papillary Thyroid Carcinoma (PTC) is a variant of thyroid cancer with the highest incidence. Many studies have proven that specific microRNAs are differentially expressed in PTC and have high potential as biomarkers. Therefore, this study aims to identify upregulated microRNAs that have the potential to be a diagnostic biomarkers of Papillary Thyroid Carcinoma (PTC) through an in silico approach. Methods This study conducted a comprehensive analysis of miRNA expression patterns using datasets available through A Database of Differentially Expressed miRNAs in Human Cancers (dbDEMC). The dataset was then processed through a data mining approach with a cutoff of P-value < 0.05 and log ₂ FC > 1.5 to identify miRNAs that were significantly and consistently upregulated in the datasets. The target genes are predicted through miRDIP, miRTarBase, and miRPathDB. Gene ontology and pathway enrichment analysis were performed in ShinyGO and EnrichR. To assess the diagnostic ability of the three miRNAs, CancerMIRNome is used to identify the ROC curve analysis results of each miRNA. Results Our study found 85 differentially regulated miRNAs in PTC. Among those, 3 miRNAs, namely hsa-miR-221-3p, hsa-miR-222-3p, and hsa-miR-146b-5p, were significantly and consistently upregulated in all datasets. Functional enrichment on the target gene set also found that these three miRNAs have a significant contribution to PTC carcinogenesis. ROC curve analysis through CancermiRNome showed that each of the three miRNAs has excellent diagnostic performance with the AUC values respectively 0,93, 0,93, and 0,91. Conclusion In summary, our study identified hsa-miR-221-3p, hsa-miR-222-3p, and hsa-miR-146b-5p as promising diagnostic biomarkers for PTC.