Improving the efficiency of thyroid cancer diagnostics in difficult diagnostic conditions using molecular diagnostic methods

Purpose of the study. To develop a diagnostic calculator for assessing the expression of profile microRNAs (miRNAs) that are significant for the oncogenesis of thyroid cancer, to introduce it into clinical practice and to evaluate the effectiveness of the proposed method for early diagnosis of malignant neoplasms of the thyroid gland in uncertain diagnostic situations after fine-needle aspiration biopsy (FNAB).
Material and methods. The previously developed «Method for Diagnosing Malignant Neoplasms of the Thyroid Gland» (patent RU2820815 C1) was tested on 284 patients of the dispensary group with nodular formations of the thyroid gland according to the results of ultrasound and an uncertain conclusion after FNAB. The number of patients with papillary thyroid carcinoma was 83 (29,2%), follicular carcinoma 43 (15,1%) and with benign thyroid pathology (follicular adenoma) – 158 (55,6%) people. The expression of miRNA-146b and –574–3p in cytological samples of thyroid nodules after FNAB was assessed using the real-time PCR method.
Results. In thyroid cancer patients, the expression of miRNA-146b was higher (p=0,007) compared to patients with benign pathology, while the expression activity of miRNA-574–3p was lower (p=0,013). To assess the index of reciprocal paired dysregulation of miRNA-146b and miRNA-574–3p expression in thyroid cells, it is recommended to determine the ratio of the expression values of the corresponding molecules. If the ratio index of miRNA-146b and miRNA-574–3p expression is higher than 4.5, then a conclusion is made about a malignant neoplasm of the thyroid gland. The diagnostic coefficient calculated by the developed formula using the logistic regression method also allows diagnosing malignant neoplasm of the thyroid gland when compared with the cutoff level. The proposed methods are highly informative.
Conclusion. Evaluation of the expression of miRNA-146b and miRNA-574–3p in the cells of thyroid nodules obtained by FNAB allows improving the diagnosis of malignant pathology in mutation-negative thyroid nodules with uncertain FNAB results.

1. Grussendorf M., Ruschenburg I., Brabant G. Malignancy rates in thyroid nodules: A long-term cohort study of 17,592 patients. Eur. Thyroid. J. 2022; 11: e220027. DOI: 10.1530/ETJ-22–0027.

2. Miranda-Filho A., Lortet-Tieulent J., Bray F., Cao B., Franceschi S., Vaccarella S., Dal Maso L. Thyroid Cancer Incidence Trends by Histology in 25 Countries: A Population-Based Study. Lancet Diabetes Endocrinol. 2021; 9: 225–234. DOI: 10.1016/S2213–8587(21)00027–9.

3. Titov S., Demenkov P. S., Lukyanov S. A. Preoperative detection of malignancy in fine needle aspiration cytology (FNAC) smears with indeterminate cytology (Bethesda III, IV) by a combined molecular classifier. J Clin Pathol. 2020; 73(11): 722–727. DOI: 10.1136/jclinpath-2020–206445

4. Paschke R., Cantara S., Crescenzi A., Jarzab B., Musholt T.J., Sobrinho Simões M. European Thyroid Association Guidelines regarding Thyroid Nodule Molecular Fine-Needle Aspiration Cytology Diagnostics. Eur. Thyroid J. 2017; 6: 115–129. DOI: 10.1159/000468519.

5. Ali S.Z., Baloch Z.W., Cochand-Priollet B., Schmitt F.C., Vielh P., Vander Laan P.A. The 2023 Bethesda System for Reporting Thyroid Cytopathology. Thyroid. 2023; 33: 1039–1044. DOI: 10.1089/thy.2023.0141.

6. Hlozek J., Pekova B., Rotnágl J., Holy R., Astl J. Genetic Changes in Thyroid Cancers and the Importance of Their Preoperative Detection in Relation to the General Treatment and Determination of the Extent of Surgical Intervention – A Review. Biomedicines. 2022; 10: 1515. DOI: 10.3390/biomedicines10071515.

7. Semina E.V., Rysenkova K.D., Troyanovskij K.E., Shmakova A.A., Rubina K.A. MicroRNA in oncology: from mechanisms of gene expression regulation to reprogramming of the metastatic niche. Biohimiya (Biochemistry). 2021; 86(5): 672–688 (in Russ.). DOI:10.31857/S0320972521050055.

8. Knyazeva, M., Korobkina E., Karizky A., Sorokin M., Buzdin A., Vorobyev S., Malek A. Reciprocal dysregulation of MiR-146b and MiR-451 contributes in malignant phenotype of follicular thyroid tumor. Int J Mol Sci. 2020; 21(17): 5950. DOI: 10.3390/ijms21175950.

9. He H., Jazdzewski K., Li W., Liyanarachchi S., Nagy R., Volinia S. et al. The role of microRNA genes in papillary thyroid carcinoma. Proceedings of the National Academy of Sciences of the United States of America. 2005; 102 (52): 19075–19080. DOI: 10.1073/pnas.0509603102.

10. Bandyk Ya.A., Kniazeva M.S., Garanin A.Y., Katsuba K.E., Zabegina L.M., Sharonova T.V. et al. Possibilities for differential diagnosis of thyroid follicular neoplasia by evaluation of small noncoding RNA. Voprosy Onkologii (Problems in Oncology). 2024; 70(2): 189–201. (In Rus). DOI: 10.37469/0507–3758–2024–70–2–189–201.

11. Titov S.E., Lukyanov S.A., Sergiyko S.V., Veryaskina Yu.A., Ilyina T.E., Kozorezov E.S., Vorobyov S.L. Problems of follicular thyroid carcinoma diagnostics. Head and Neck Tumors (HNT). 2023; 13(3): 10–23. (In Rus). DOI: 10.17650/2222–1468–2023–13–3–10–23.

12. Wei Z.L., Gao A.B., Wang Q., Lou X.E., Zhao J., Lu Q.J. MicroRNA-221 promotes papillary thyroid carcinoma cell migration and invasion via targeting RECK and regulating epithelial–mesenchymal transition. OncoTargets Ther. 2019; 12: 2323–2333. DOI: 10.2147/OTT.S190364.

13. Castagna M.G., Marzocchi C., Pilli T., Forleo R., Pacini F., Cantara S. MicroRNA expression profile of thyroid nodules in fine-needle aspiration cytology: A confirmatory series. J. Endocrinol. Investig. 2019;42:97–100. DOI: 10.1007/s40618–018–0880–6.

14. Malek A.V., Knyazeva M.S., Kil Yu.V. Method for analyzing microRNA in samples of biological material.Patent for invention RU2783509 C1, 14.11.2022. (in Russ.).

15. Makarova J.A., Shkurnikov M.U., Wicklein D., Lange T., Samatov T.R., Turchinovich A.A., Tonevitsky A.G. Intracellular and extracellular microRNA: An update on localization and biological role. Progress in Histochemistry and Cytochemistry. 2016; 51(3–4): 33–49. DOI: 10.1016/j.proghi.2016.06.001.

16. Silaghi C.A., Lozovanu V., Georgescu C.E., Georgescu R.D., Susman S., Năsui B.A. et al. Thyroseq v3, Afirma GSC, and microRNA Panels Versus Previous Molecular Tests in the Preoperative Diagnosis of Indeterminate Thyroid Nodules: A Systematic Review and Meta-Analysis. Front. Endocrinol. 2021; 12: 649522. DOI: 10.3389/fendo.2021.649522.

17. Santos M. T., Rodrigues B. M., Shizukuda S., Oliveira A. F., Oliveira M., Figueiredo D. L. et al. Clinical decision support analysis of a microRNA-based thyroid molecular classifier: A real-world, prospective and multicentre validation studies. EBioMedicine. 2022; 82: 104137. DOI: 10.1016/j.ebiom.2022.104137.

18. Rosignolo F., Memeo L., Monzani F. et al. MicroRNA-based molecular classification of papillary thyroid carcinoma. International Journal of Oncology. 2017; 50(5): 1767–1777. DOI: 10.3892/ijo.2017.3960.

19. Napoli F., Rapa I., Mortara U., Massa F., Izzo S., Rigutto A. et al. MicroRNA profiling predicts positive nodal status in papillary thyroid carcinoma in the preoperative setting. Cancer Cytopathol. 2022; 130: 695–704. DOI: 10.1002/cncy.22585.

20. Zabegina L.M., Titov S.E., Ivanov M.K., Nazarova I.V., Malek A.V. MicroRNA from TPO (+) exosom as potential marker for differentiating malignant and bening forms of folcular thyroid tumors. Geny i kletki (Genes & Cells). 2020; 15(S3): 49–50. (in Russ.). DOI: 10.23868/gc122630

21. Sheikholeslami S., Shabani N., Shivaee S., Tavangar S.M., Yeganeh M., Hedayati M. Overexpression of miR-129–1, miR-146b, miR-183, and miR-197 in follicular thyroid carcinoma and adenoma tissues. Mol. Cell Probes. 2020; 51: 1–6. DOI: 10.1016/j.mcp.2020.101536.