Background The postoperative typing of thyroid lesions, which is instrumental in adequate patient treatment, is currently based on histologic examination. However, it depends on pathologist’s qualification and can be difficult in some cases. Numerous studies have shown that molecular markers such as microRNAs and somatic mutations may be useful to assist in these cases, but no consensus exists on the set of markers that is optimal for that purpose. The aim of the study was to discriminate between different thyroid neoplasms by RT-PCR, using a limited set of microRNAs selected from literature. Methods By RT-PCR we evaluated the relative levels of 15 microRNAs (miR-221, −222, −146b, −181b, −21, −187, −199b, −144, −192, −200a, −200b, −205, −141, −31, −375) and the presence of BRAF(V600E) mutation and RET-PTC1 translocation in surgically resected lesions from 208 patients from Novosibirsk oblast (Russia) with different types of thyroid neoplasms. Expression of each microRNA was normalized to adjacent non-tumor tissue. Three pieces of lesion tissue from each patient (39 goiters, 41 follicular adenomas, 16 follicular thyroid cancers, 108 papillary thyroid cancers, 4 medullary thyroid cancers) were analyzed independently to take into account method variation. Results The diagnostic classifier based on profiling of 13 microRNAs was proposed, with total estimated accuracy varying from 82.7 to 99 % for different nodule types. Relative expression of six microRNAs (miR-146b, −21, −221, −222, 375, −199b) appeared significantly different in BRAF(V600E)-positive samples (all classified as papillary thyroid carcinomas) compared to BRAF(V600E)-negative papillary carcinoma samples. Conclusions The results confirm practical feasibility of using molecular markers for typing of thyroid neoplasms and clarification of controversial cases.

Aims: Analysis of molecular markers in addition to cytological analysis of fine-needle aspiration (FNA) samples is a promising way to improve the preoperative diagnosis of thyroid nodules. Previously, we have developed an algorithm for the differential diagnosis of thyroid nodules by means of a small set of molecular markers. Here, we aimed to validate this approach using FNA cytology samples of Bethesda categories III and IV, in which preoperative detection of malignancy by cytological analysis is impossible. Methods: A total of 122 FNA smears from patients with indeterminate cytology (Bethesda III: 13 patients, Bethesda IV: 109 patients) were analysed by real-time PCR regarding the preselected set of molecular markers (the BRAF V600E mutation, normalised concentrations of HMGA2 mRNA, 3 microRNAs, and the mitochondrial/nuclear DNA ratio). The decision tree–based classifier was used to discriminate between benign and malignant tumours. Results: The molecular testing detected malignancy in FNA smears of indeterminate cytology with 89.2% sensitivity, 84.6% positive predictive value, 92.9% specificity and 95.2% negative predictive value; these characteristics are comparable with those of more complicated commercial tests. Residual risk of malignancy for the thyroid nodules that were shown to be benign by this molecular method did not exceed the reported risk of malignancy for Bethesda II histological diagnosis. Analytical-accuracy assessment revealed required nucleic-acid input of ≥5 ng. Conclusions: The study shows feasibility of preoperative differential diagnosis of thyroid nodules of indeterminate cytology using a small panel of molecular markers of different types by a simple PCR-based method using stained FNA smears.

Background: Analysis of molecular markers in addition to cytological analysis of fine-needle aspiration (FNA) samples is a promising way to improve the preoperative diagnosis of thyroid nodules. Nonetheless, in clinical practice, applications of existing diagnostic solutions based on the detection of somatic mutations or analysis of gene expression are limited by their high cost and difficulties with clinical interpretation. The aim of our work was to develop an algorithm for the differential diagnosis of thyroid nodules on the basis of a small set of molecular markers analyzed by real-time PCR. Methods: A total of 494 preoperative FNA samples of thyroid goiters and tumors from 232 patients with known histological reports were analyzed: goiter, 105 samples (50 patients); follicular adenoma, 101 (48); follicular carcinoma, 43 (28); Hürthle cell carcinoma, 25 (11); papillary carcinoma, 121 (56); follicular variant of papillary carcinoma, 80 (32); and medullary carcinoma, 19 (12). Total nucleic acids extracted from dried FNA smears were analyzed for five somatic point mutations and two translocations typical of thyroid tumors as well as for relative concentrations of HMGA2 mRNA and 13 microRNAs and the ratio of mitochondrial to nuclear DNA by real-time PCR. A decision tree–based algorithm was built to discriminate benign and malignant tumors and to type the thyroid cancer. Leave-p-out cross-validation with five partitions was performed to estimate prediction quality. A comparison of two independent samples by quantitative traits was carried out via the Mann–Whitney U test. Results: A minimum set of markers was selected (levels of HMGA2 mRNA and miR-375, − 221, and -146b in combination with the mitochondrial-to-nuclear DNA ratio) and yielded highly accurate discrimination (sensitivity = 0.97; positive predictive value = 0.98) between goiters with benign tumors and malignant tumors and accurate typing of papillary, medullary, and Hürthle cell carcinomas. The results support an alternative classification of follicular tumors, which differs from the histological one. Conclusions: The study shows the feasibility of the preoperative differential diagnosis of thyroid nodules using a panel of several molecular markers by a simple PCR-based method. Combining markers of different types increases the accuracy of classification.

Background: The current approaches to distinguish follicular adenomas (FA) and follicular thyroid cancer (FTC) at the pre-operative stage have low predictive value. Liquid biopsy- based analysis of circulating extracellular vesicles (EVs) presents a promising diagnostic method. However, the extreme heterogeneity of plasma EV population hampers the development of new diagnostic tests. We hypothesize that the isolation of EVs with thyroid-specific surface molecules followed by miRNA analysis, may have improved diagnostic potency. Methods: The total population of EVs was isolated from the plasma of patients with FA (n = 30) and FTC (n = 30). Thyroid peroxidase (TPO)-positive EVs were isolated from the total populations using immune- beads. The miRNA from the TPO(+)EVs obtained from the plasma of FA and FTC patients was assayed by RT-PCR. The diagnostic potency of the selected miRNAs was estimated by the receiver operating characteristic (ROC) analysis. Results: TPO(+)EVs can be efficiently isolated by immunobeads. The analysis of Let-7 family members in TPO(+)EVs allows one to distinguish FA and FTC with high accuracy (area under curve defined by ROC = 0.77–0.84). Conclusion: The isolation of TPO(+)EVs, followed by RT-qPCR analysis of Let-7 family members, may present a helpful approach to manage follicular nodules in the thyroid gland.