In recent years, the global incidence of thyroid cancer has been increasing. Despite the significant progress in the diagnostic tools applied for papillary thyroid cancer (PTC) diagnosis, commonly used methods require undergoing invasive diagnostic procedures, such as liquid biopsy, which still, in some cases, remains imprecise. In this case, novel screening and diagnostic biomarkers are still being evaluated using highly specialized techniques, which could increase PTC detection. Currently, a number of genes and proteins associated with PTC development are currently under investigation to assess their clinical utility. Accordingly, a literature search was undertaken to collect novel information about the diagnosis of and prognosis for PTC with a particular emphasis on the role of microRNA (miRNA) evaluation. The early identification of novel biomarkers is essential for facilitating appropriate therapeutic decisions. Moreover, the evaluation of plasma- and serum-derived miRNA measurements could be considered as equivalent thyroid cancer screening tools in the future. On the other hand, the PTC pathogenesis could be evaluated further with the use of miRNA evaluation, which may bring novel insights for potential medical target determination.

The incidence of papillary thyroid cancer (PTC) has increased in recent years. To improve the diagnostic management of PTC, we propose the use of microRNAs (miRNAs) as a biomarker. Our aim in this study was to evaluate the miRNA expression pattern in PTC using NanoString technology. We identified ten miRNAs deregulated in PTC compared with reference tissue: miR-146b-5p, miR-221-3p, miR-221-5p, miR-34-5p, miR-551b-3p, miR-152-3p, miR-15a-5p, miR-31-5p, and miR-7-5p (FDR < 0.05; |fold change (FC)| ≥ 1.5). The gene ontology (GO) analysis of differentially expressed miRNA (DEM) target genes identified the predominant involvement of epidermal growth factor receptor (EGFR), tyrosine kinase inhibitor resistance, and pathways in cancer in PTC. The highest area under the receiver operating characteristic (ROC) curve (AUC) for DEMs was found for miR-146-5p (AUC = 0.770) expression, indicating possible clinical applicability in PTC diagnosis. The combination of four miRNAs (miR-152-3p, miR-221-3p, miR-551b-3p, and miR-7-5p) showed an AUC of 0.841. Validation by real-time quantitative polymerase chain reactions (qRT-PCRs) confirmed our findings. The introduction of an miRNA diagnostic panel based on the results of our study may help to improve therapeutic decision making for questionable cases. The use of miRNAs as biomarkers of PTC may become an aspect of personalized medicine.