Overexpression of mir-129-1, miR-146b, mir-183, and mir-197 in follicular thyroid carcinoma and adenoma tissues

Abstract

Follicular thyroid carcinoma (FTC) is responsible for approximately 10% of thyroid malignancies. Since this type of malignancy indicates no capsular and vascular invasions, adenoma and follicular carcinoma of thyroid are not distinguishable. It has been proved that microRNAs, which regulate approximately 30% of coding proteins, have an association with follicular thyroid adenoma (FTA) and carcinoma of the thyroid. Therefore, the aim of this study was to assess the expression of some miRNAs for detecting the most appropriate miRNA as potential biomarker in the diagnosis of FTA and FTC patients. Reverse transcription quantitative polymerase chain reaction (RT-qPCR) was applied to determine the expression levels of miR-129-1, miR-146b,-183 and miR-197 in 48 cases (16 FTC, 16 FTA and 16 hyperplasia/multinodular goiter (MNG) cases). The significance of miRNA differential expression levels among groups were assessed using Multivariate test by Statistical Package for Science Software (SPSS v.20) and Graph Pad Prism v.8. Results indicated that all of the miRNAs had significant overexpression in FTC and FTA versus MNG cases, and also increased expression level in FTC in comparison with FTA, however it was not significant. The results of ROC curve analysis determined the significant overexpression and prognostic value of miR-129-1 in FTA cases and miR-146b in both FTA and FTC cases compared to MNG group. Although all of the earlier mentioned microRNAs were overexpressed in FTC and FTA cases, the ROC curve results demonstrated that miR-129-1 had agreeable AUC for FTA cases. Therefore, it seems that it's cut-off point could be helpful in distinguishing between FTA and multinodular goiter cases. On the other hand, although miR-146b has excellent diagnostic value in both FTA and FTC groups, it seems that this microRNA is unable to act as a specific biomarker to discriminate between FTA and FTC cases. This data need to be confirmed in a large cohort study and other biological samples such as plasma.