Objective: MicroRNAs (miRNAs) are small endogenous non-coding RNAs that pair with target messengers regulating gene expression. They are involved in biological processes including development, organogenesis, tissue differentiation, cell cycle and metabolism. Changes in miRNA levels occur in human cancers, including thyroid cancer. Fine needle aspiration (FNA) with cytologic evaluation is the most reliable tool for malignancy prediction in thyroid nodules, but cytologic diagnosis remains indeterminate for 20% of nodules. In this study we evaluated the expression of miR-146b, miR-155, miR-187, miR-197, miR-221, miR-222 and miR-224 to distinguish benign and malignant thyroid nodules.
Methods: The study included 88 samples obtained by FNA of thyroid nodules from 86 patients (45 benign, 43 malignant). miRNA expression was evaluated by quantitative RT-PCR and statistical analysis of data was performed.
Results: All miRNAs increased in malignant nodules with respect to benign ones, but only the expression of miR-146b, miR-155, miR-187, miR-221, miR-222 and miR-224 significantly raised. Using data mining techniques we obtained a criterion able to classify a nodule as benign or malignant on the basis of miRNAs expression values. The decision model based on the expression of miR-146b, miR-155 and miR-221 was valid for 86/88 nodules (97.73%). To evaluate how much general is the criterion in correctly classifying a nodule not present in our study group, we adopted cross-validation techniques, obtaining a reliability of 78.41% (Sensitivity=79.07% and Specificity=77.77%).
Conclusions: The expression profiles of three miRNAs allowed to distinguish benign from malignant thyroid lesions starting from FNA, and may improve the accuracy of cytological analysis.
Declaration of interest: The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research project.
Funding: This work was supported, however funding details unavailable.
05 - 09 May 2012
European Society of Endocrinology