Современные концепции молекулярного патогенеза рака щитовидной железы

Рак щитовидной железы – распространенное злокачественное новообразование эндокринной системы. В последние десятилетия показатели заболеваемости и смертности вследствие этой патологии стремительно увеличиваются. Большинство случаев дифференцированного рака щитовидной железы (фолликулярного и папиллярного гистотипов) клинически проявляются как узловой зоб. Неопределенность результатов цитологической диагностики (категории III и IV по классификации Bethesda (Bethesda System for Reporting Thyroid Cytopathology)) обусловливает сложности в выборе тактики ведения пациентов. Известно, что развитие, прогрессирование, инвазия и метастазирование раковых клеток регулируются множеством молекулярных механизмов. В данной статье описываются некоторые молекулярные аспекты онкогенеза узловых образований щитовидной железы, а также наиболее перспективные диагностические онкомаркеры. В частности, рассматривается роль генных мутаций, белковых маркеров, эпигенетических воздействий микроРНК, гистонов и метилирования ДНК в патогенезе рака щитовидной железы. Изучение патогенеза этого заболевания имеет прогностическую ценность и способствует поиску эффективных лечебно-диагностических методов и их совершенствованию. Поэтому в исследовании были рассмотрены применяемые в настоящий момент тест-панели, направленные на дооперационную дифференциальную диагностику узловых образований щитовидной железы. Анализ и обобщение результатов исследований по данной теме позволят не только расширить понимание фундаментальных процессов онкогенеза, но и наметить перспективные направления планирования экспериментальных научных работ для разработки новых прогностических, диагностических и терапевтических технологий с целью повышения качества медицинской помощи пациентам с раком щитовидной железы.

1. Durante C., Grani G., Lamartina L. et al. The diagnosis and management of thyroid nodules: a review. JAMA 2018;319(9): 914–24. DOI: 10.1001/jama.2018.0898.

2. Сердюкова О.С., Титов С.Е., Малахи- на Е.С., Рымар О.Д. МикроРНК – перспективные молекулярные маркеры обнаружения рака в узлах щитовидной железы. Клиническая и экспериментальная тиреоидология 2018;14(3):140–8.

3. Xing M. Molecular pathogenesis and mechanisms of thyroid cancer. Nat Rev Cancer 2013;13(3):184–99. DOI: 10.1038/nrc3431.

4. Duan H., Liu X., Ren X. et al. Mutation profiles of follicular thyroid tumors by targeted sequencing. Diagn Pathol 2019;14(1):39. DOI: 10.1186/s13000-019-0817-1.

5. Donati B., Ciarrocchi A. Telomerase and telomeres biology in thyroid cancer. Int J Mol Sci 2019;20(12):2887. DOI: 10.3390/ijms20122887.

6. Liu R., Xing M. TERT promoter mutations in thyroid cancer. Endocr Relat Cancer 2016;23(3):R143–55. DOI: 10.1530/erc-15-0533.

7. Beysel S., Eyerci N., Pinarli F.A. et al. VDR gene foki polymorphism as a poor prognostic factor for papillary thyroid cancer. Tumor Biol 2018;40(11):101042831881176. DOI: 10.1177/1010428318811766.

8. Yang L., Sun R., Wang Y. et al. Expression of ANGPTL2 and its impact on papillary thyroid cancer. Cancer Cell Int 2019;19:204. DOI: 10.1186/s12935-019-0908-9.

9. Siołek M., Cybulski C., Gąsior-Perczak D. et al. CHEK2 mutations and the Risk of Papillary Thyroid Cancer. Int J Cancer 2015;137(3):548–52. DOI: 10.1002/ijc.29426.

10. Lu W., Xu Y., Xu J. et al. Identification of differential expressed LncRNAs in human thyroid cancer by a genomewide analyses. Cancer Med 2018;7(8):3935–44. DOI: 10.1002/cam4.1627.

11. Zhang J., Du Y., Zhang X. et al. Downregulation of BANCR promotes aggressiveness in papillary thyroid cancer via the MAPK and PI3K pathways. J Cancer 2018;9(7):1318–28. DOI: 10.7150/jca.20150.

12. Zhao K., Yang H., Kang H., Wu A. Identification of key genes in thyroid cancer microenvironment. Med Sci Monit 2019;25:9602–08. DOI: 10.12659/msm.918519.

13. Lin P., Guo Y., Shi L. et al. Development of a prognostic index based on an immunogenomic landscape analysis of papillary thyroid cancer. Aging 2019;11(2):480–500. DOI: 10.18632/aging.101754.

14. Guan H., Guo Y., Liu L. et al. INAVA promotes aggressiveness of papillary thyroid cancer by upregulating MMP9 expression. Cell Biosci 2018;8:26. DOI: 10.1186/s13578-018-0224-4.

15. Shi Y., Su C., Hu H. et al. Serum MMP-2 as a potential predictive marker for papillary thyroid carcinoma. PLoS One 2018;13(6):e0198896. DOI: 10.1371/journal.pone.0198896.

16. Marečko I., Cvejić D., Šelemetjev S. et al. Enhanced activation of matrix metalloproteinase- 9 correlates with the degree of papillary thyroid carcinoma infiltration. Croat Med J 2014;55(2):128–37. DOI: 10.3325/cmj.2014.55.128.

17. Zhang W., Song B., Yang T. MMP-2, MMP-9, TIMP-1, and TIMP-2 in the peripheral blood of patients with differentiated thyroid carcinoma. Cancer Manag Res 2019;11:10675–81. DOI: 10.2147/cmar.s233776.

18. Bumber B., Kavanagh M., Jakovcevic A. et al. Role of matrix metalloproteinases and their inhibitors in the development of cervical metastases in papillary thyroid cancer. Clin Otolaryngol 2019;45(1):55–62. DOI: 10.1111/coa.13466.

19. Wang C., Tsai S. The non-canonical role of vascular endothelial growth factor-c axis in cancer progression. Exp Biol Med 2015;240(6):718–24. DOI: 10.1177/1535370215583802.

20. Šelemetjev S., Đorić I., Paunović I. et al. Coexpressed high levels of VEGF-C and active MMP-9 are associated with lymphatic spreading and local invasiveness of papillary thyroid carcinoma. Am J Clin Pathol 2016;146(5):594–602. DOI: 10.1093/ajcp/aqw184.

21. Jang J., Kim D., Park H. et al. Preoperative serum VEGF-C but not VEGF-A level is correlated with lateral neck metastasis in papillary thyroid carcinoma. Head Neck 2019;41(8):2602–09. DOI: 10.1002/hed.25729.

22. Jia Z., Wu X., Zhang Y. et al. The correlation between ultrasonographic features, BFGF, and the local invasiveness of thyroid papillary carcinoma. Medicine 2020;99(26):e20644. DOI: 10.1097/md.0000000000020644.

23. Zhou C., Yang C., Chong D. Ecadherin expression is associated with susceptibility and clinicopathological characteristics of thyroid cancer. Medicine 2019;98(30):e16187. DOI: 10.1097/md.0000000000016187.

24. Ali K., Awny S., Ibrahim D. et al. Role of P53, E-cadherin and BRAF as predictors of regional nodal recurrence for papillary thyroid cancer. Ann Diagn Pathol 2019;40:59–65. DOI: 10.1016/j.anndiagpath.2019.04.005.

25. Zhu X., Bai Q., Lu Y. et al. Expression and function of CXCL12/CXCR4/CXCR7 in thyroid cancer. Int J Oncol 2016;48(6):2321–9. DOI: 10.3892/ijo.2016.3485.

26. Werner T., Forster C., Dizdar L. et al. CXCR4/CXCR7/CXCL12-axis in follicular thyroid carcinoma. J Cancer 2018; 9(6):929–40. DOI: 10.7150/jca.23042.

27. Cho H., Kim J., Oh Y. Diagnostic value of HBME-1, CK19, Galectin 3, and CD56 in the subtypes of follicular variant of papillary thyroid carcinoma. Pathol Int 2018;68(11):605–13. DOI: 10.1111/pin.12729.

28. Xin Y., Guan D., Meng K. et al. Diagnostic accuracy of CK-19, Galectin-3 and HBME-1 on papillary thyroid carcinoma: a meta-analysis. Int J Clin Exp Pathol 2017;10(8):8130–40.

29. Erdogan-Durmus S., Ozcan D., Yarikkaya E. et al. CD56, HBME-1 and cytokeratin 19 expressions in papillary thyroid carcinoma and nodular thyroid lesions. J Res Med Sci 2016;21(1):49. DOI: 10.4103/1735-1995.183986.

30. Arcolia V., Journe F., Renaud F. et al. Combination of Galectin-3, CK19 and HBME-1 immunostaining improves the diagnosis of thyroid cancer. Oncol Lett 2017;14(4):4183–9. DOI: 10.3892/ol.2017.6719.

31. Palo S., Biligi D.S. Differential diagnostic significance of HBME-1, CK19 and S100 in various thyroid lesions. Malays J Pathol 2017;39(1):55–67.

32. Vlad M., Golu I., Dema A. et al. The absence of CD56 expression can differentiate papillary thyroid carcinoma from other thyroid lesions. Ind J Pathol Microbiol 2017;60(2):161. DOI: 10.4103/0377-4929.208378.

33. Muthusamy S., Azhar Sha S., Abdullah Suhaimi S.N. et al. CD56 expression in benign and malignant thyroid lesions. Malays J Pathol 2018;40(2):111–9.

34. Bartolazzi A., Sciacchitano S., D’Alessandria C. Galectin-3: the impact on the clinical management of patients with thyroid nodules and future perspectives. Int J Mol Sci 2018;19(2):445. DOI: 10.3390/ijms19020445.

35. Li J., Vasilyeva E., Wiseman S. Beyond immunohistochemistry and immunocytochemistry: a current perspective on Galectin-3 and thyroid cancer. Exp Rev Anticancer Ther 2019;19(12):1017–27. DOI: 10.1080/14737140.2019.1693270.

36. Gadelha M., Kasuki L., Dénes J. et al. MicroRNAs: suggested role in pituitary adenoma pathogenesis. J Endocrinol Invest 2013;36(10):889–95. DOI: 10.1007/bf03346759.

37. Луценко А.С., Белая Ж.Е., Пржиялковская Е.Г. и др. МикроРНК и их значение в патогенезе СТГ-продуцирующих аденом гипофиза. Вестник Российской академии медицинских наук 2017;72(4):290–8.

38. Аушев В.Н. МикроРНК: малые молекулы с большим значением Клиническая онкогематология. Фундаментальные исследования и клиническая практика 2015;8(1):1–12.

39. Wierinckx A., Roche M., Legras- Lachuer M. et al. MicroRNAs in pituitary tumors. Mol Cell Endocrinol 2017; 456:51–61. DOI: 10.1016/j.mce.2017.01.021. Available at:(https://www.sciencedirect.com/science/article/abs/pii/S0303720717300254?via%3Dihub).

40. Weber J., Baxter D., Zhang S. et al. The microRNA spectrum in 12 body fluids. Clin Chem 2010;56(11):1733–41. DOI: 10.1373/clinchem.2010.147405.

41. Celano M., Rosignolo, F., Maggisano V. et al. MicroRNAs as biomarkers in thyroid carcinoma. Int J Genomics 2017;2017:6496570. DOI: 10.1155/2017/6496570.

42. Yu S., Liu Y., Wang J. et al. Circulating microRNA profiles as potential biomarkers for diagnosis of papillary thyroid carcinoma. J Clin Endocrinol Metab 2012;97(6):2084–92. DOI: 10.1210/jc.2011-3059.

43. Lee J., Zhao J., Clifton-Bligh R. et al. MicroRNA-222 and MicroRNA-146B are tissue and circulating biomarkers of recurrent papillary thyroid cancer. Cancer 2013;119(24):4358–65. DOI: 10.1002/cncr.28254.

44. Rosignolo F., Sponziello M., Giacomelli L. et al. identification of thyroid-associated serum microRNA profiles and their potential use in thyroid cancer follow-up. J Endocr Soc 2017; 1(1):3–13. DOI: 10.1210/js.2016-1032.

45. Lee Y., Lim Y., Lee J. et al. Differential expression levels of plasma-derived Mir- 146B and Mir-155 in papillary thyroid cancer. Oral Oncol 2015;51(1):77–83. DOI: 10.1016/j.oraloncology.2014.10.006.

46. Yoruker E., Terzioglu D., Teksoz S. et al. MicroRNA expression profiles in papillary thyroid carcinoma, benign thyroid nodules and healthy controls. J Cancer 2016;7(7): 803–9. DOI: 10.7150/jca.13898.

47. Samsonov R., Burdakov V., Shtam T. et al. Plasma exosomal Mir-21 and Mir-181A differentiates follicular from papillary thyroid cancer. Tumor Biol 2016;37(9):12011–21. DOI: 10.1007/s13277-016-5065-3.

48. Zhang Y., Zhong Q., Chen X. et al. Diagnostic value of MicroRNAs in discriminating malignant thyroid nodules from benign ones on fine-needle aspiration samples. Tumour Biol 2014;35(9):9343–53. DOI: 10.1007/s13277-014-2209-1.

49. Paskaš S., Janković J., Živaljević V. et al. Malignant risk stratification of thyroid FNA Specimens with indeterminate cytology based on molecular testing. Cancer Cytopathol 2015;123(8):471–9. DOI: 10.1002/cncy.21554.

50. Chou C., Yang K., Chou F. et al. Prognostic implications of MiR-146b expression and its functional role in papillary thyroid carcinoma. J Clin Endocrinol Metab 2013;98(2):E196–205. DOI: 10.1210/jc.2012-2666.

51. Rosignolo F., Memeo L., Monzani F. et al. MicroRNA-based molecular classification of papillary thyroid carcinoma. Int J Oncol 2017;50(5):1767–77. DOI: 10.3892/ijo.2017.3960.

52. Geraldo M., Kimura E. Integrated analysis of thyroid cancer public datasets reveals role of post-transcriptional regulation on tumor progression by targeting of immune system mediators. PLoS One 2015;10(11):e0141726. DOI: 10.1371/journal.pone.0141726.

53. Zhang Z., Xiao Q., Li X. et al. MicroRNA-574-5p directly targets FOXN3 to mediate thyroid cancer progression via Wnt/β-Catenin signaling pathway. Pathol Res Pract 2020;216(6):152939. DOI: 10.1016/j.prp.2020.152939.

54. Chandran U., Medvedeva O., Barmada M. et al. TCGA expedition: a data acquisition and management system for TCGA data. PLoS One 2016;11(10):e0165395. DOI: 10.1371/journal.pone.0165395.

55. Li X., Wen R., Wen D. et al. Downregulation of MiR-193a-3p via targeting Cyclin D1 in thyroid cancer. Mol Med Rep 2020;22(3):2199–218. DOI: 10.3892/mmr.2020.11310.

56. Zou X., Gao F., Wang Z. et al. A three- MicroRNA panel in serum as novel biomarker for papillary thyroid carcinoma diagnosis. Chin Med J 2020;133(21):2543–51. DOI: 10.1097/cm9.0000000000001107.

57. Santos C., Schulze A. Lipid metabolism in cancer. FEBS J 2012;279(15):2610–23. DOI: 10.1111/j.1742-4658.2012.08644.x.

58. Liao T., Wang Y., Hu J. et al. Histone methyltransferase KMT5A gene modulates oncogenesis and lipid metabolism of papillary thyroid cancer in vitro. Oncol Rep 2018;39(5):2185–91. DOI: 10.3892/or.2018.6295.

59. Yan K., Lin C., Liao T. et al. EZH2 in cancer progression and potential application in cancer therapy: a friend or foe? Int J Mol Sci 2017;18(6):1172. DOI: 10.3390/ijms18061172.

60. Chien M., Yang P., Lee J. et al. Recurrence-associated genes in papillary thyroid cancer: An analysis of data from the Cancer Genome Atlas. Surgery 2017;161(6):1642–50. DOI: 10.1016/j.surg.2016.12.039.

61. Tsai C., Chien M., Chang Y. et al. Overexpression of histone H3 lysine 27 trimethylation is associated with aggressiveness and dedifferentiation of thyroid cancer. Endocr Pathol 2019;30(4):305–11. DOI: 10.1007/s12022-019-09586-1.

62. Zhang W., Sun W., Qin Y. et al. Knockdown of KDM1A suppresses tumour migration and invasion by epigenetically regulating the TIMP1/MMP9 pathway in papillary thyroid cancer. J Cell Mol Med 2019;23(8):4933–44. DOI: 10.1111/jcmm.14311.

63. Aalinkeel R., Nair B., Reynolds J. et al. Overexpression of MMP-9 contributes to invasiveness of prostate cancer cell line LNCaP. Immunol Invest 2011;40(5):447–64. DOI: 10.3109/08820139.2011.557795.

64. Russo D., Durante C., Bulotta S. et al. Targeting histone deacetylase in thyroid cancer. Expert Opin Ther Targets 2012;17(2):179–93. DOI: 10.1517/14728222.2013.740013.

65. Rodríguez-Rodero S., Delgado-Álvarez E., Díaz-Naya L. et al. Epigenetic modulators of thyroid cancer. Endocrinol Diabetes Nutr 2017;64(1):44–56. DOI: 10.1016/j.endien.2017.02.006.

66. De Morais R., Sobrinho A., de Souza Silva C. et al. The role of the NIS (SLC5A5) gene in papillary thyroid cancer: a systematic review. Int J Endocrinol 2018;2018:1–11. DOI: 10.1155/2018/9128754.

67. Zhang Z., Liu D., Murugan A. et al. Histone deacetylation of NIS promoter underlies BRAF V600E-promoted NIS silencing in thyroid cancer. Endocr Relat Cancer 2013;21(2):161–73. DOI: 10.1530/erc-13-0399.

68. Kim S., Park K., Jeon J. et al. Potential anti-cancer effect of N-hydroxy-7-(2-naphthylthio) heptanomide (HNHA), a novel histone deacetylase inhibitor, for the treatment of thyroid cancer. BMC Cancer 2015;15(1):1003. DOI: 10.1186/s12885-015-1982-6.

69. Fu H., Cheng L., Jin Y. et al. MAPK inhibitors enhance HDAC inhibitorinduced redifferentiation in papillary thyroid cancer cells harboring BRAFV600E: an in vitro study. Mol Ther Oncolytics 2019;12:235–45. DOI: 10.1016/j.omto.2019.01.007.

70. Zafon C., Gil J., Pérez-González B. et al. DNA Methylation in Thyroid Cancer. Endocr Relat Cancer 2019;26(7):R415–39. DOI: 10.1530/erc-19-0093.

71. Якушина В.Д., Лернер Л.В., Казубская Т.П. и др. Молекулярно-генетическая структура фолликулярно-клеточного рака щитовидной железы. Клиническая и экспериментальная тиреоидология 2016;12(2):55–64.

72. Faam B., Ghaffari M., Ghadiri A. et al. Epigenetic modifications in human thyroid cancer. Biomed Rep 2014;3(1):3–8. DOI: 10.3892/br.2014.375.

73. Mitmaker E., Tabah R., How J. Thyroid nodule DNA methylation signatures: an important diagnostic annotation. Clin Cancer Res 2018;25(2):457–59. DOI: 10.1158/1078-0432.ccr-18-2820.

74. Rodríguez-Rodero S., Fernández A., Fernández-Morera J. et al. DNA methylation signatures identify biologically distinct thyroid cancer subtypes. J Clin Endocrinol Metab 2013;98(7):2811–21. DOI: 10.1210/jc.2012-3566.

75. Beltrami C., dos Reis M., Barros-Filho M. et al. Integrated data analysis reveals potential drivers and pathways disrupted by DNA methylation in papillary thyroid carcinomas. Clin Epigenetics 2017;9:45. DOI: 10.1186/s13148-017-0346-2.

76. Mancikova V., Buj R., Castelblanco E. et al. DNA methylation profiling of welldifferentiated thyroid cancer uncovers markers of recurrence free survival. Int J Cancer 2014;135(3):598–610. DOI: 10.1002/ijc.28703.

77. Savvidis C., Papaoiconomou E., Petraki C. et al. The role of KISS1/KISS1R system in tumor growth and invasion of differentiated thyroid cancer. Anticancer Res 2015;35:819–26.

78. Zarkesh M., Zadeh-Vakili A., Azizi F. et al. Altered epigenetic mechanisms in thyroid cancer subtypes. Mol Diagn Ther 2017;22(1):41–56. DOI: 10.1007/s40291-017-0303-y.

79. Ishida E., Nakamura M., Shimada K. et al. DNA hypermethylation status of multiple genes in papillary thyroid carcinomas. Pathobiology 2007;74(6): 344–52. DOI: 10. 1159/000110028.

80. Zhu X., Cheng S. Epigenetic modifications: novel therapeutic approach for thyroid cancer. Endocrinol Metab (Seoul) 2017;32(3):326. DOI: 10.3803/enm.2017.32.3.326.

81. Haugen B., Alexander E., Bible K. et al. 2015 American Thyroid Association management guidelines for adult patients with thyroid nodules and differentiated thyroid cancer: The American Thyroid Association guidelines task force on thyroid nodules and differentiated thyroid cancer. Thyroid 2016;26(1):1–133. DOI: 10.1089/thy.2015.0020.

82. Alexander E., Kennedy G., Baloch Z. et al. Preoperative diagnosis of benign thyroid nodules with indeterminate cytology. N Engl J Med 2012;367(8):705–15. DOI: 10.1056/nejmoa1203208.

83. Sahli Z., Smith P., Umbricht C. et al. Preoperative molecular markers in thyroid nodules. Front Endocrinol 2018;9:179. DOI: 10.3389/fendo.2018.00179.

84. Ali S., Siperstein A., Sadow P. et al. Extending expressed RNA genomics from surgical decision making for cytologically indeterminate thyroid nodules to targeting therapies for metastatic thyroid cancer. Cancer Cytopathol 2019;127(6):362–9. DOI: 10.1002/cncy.22132.

85. Endo M., Nabhan F., Porter K. et al. Afirma gene sequencing classifier compared with gene expression classifier in indeterminate thyroid nodules. Thyroid 2019;29(8):1115–24. DOI: 10.1089/thy.2018.0733.

86. Krane J., Cibas E., Endo M. et al. The Afirma Xpression Atlas for thyroid nodules and thyroid cancer metastases: insights to inform clinical decision-making from a fine-needle aspiration sample. Cancer Cytopathol 2020;128(7):452–9. DOI: 10.1002/cncy.22300.

87. Angell T., Wirth L., Cabanillas M. et al. Analytical and clinical validation of expressed variants and fusions from the whole transcriptome of thyroid FNA samples. Front Endocrinol 2019;(10):612. DOI: 10.3389/fendo.2019.00612.

88. Lupo M., Walts A., Sistrunk J. et al. Multiplatform molecular test performance in indeterminate thyroid nodules. Diagn Cytopathol 2020;48(12):1254–64. DOI: 10.1002/dc.24564.

89. Zhang M., Lin O. Molecular testing of thyroid nodules: A Review of current available tests for fine-needle aspiration specimens. Arch Pathol Lab Med 2016;140(12):1338–44. DOI: 10.5858/arpa.2016-0100-ra.

90. Nikiforova M., Wald A., Roy S. et al. Targeted next-generation sequencing panel (ThyroSeq) for detection of mutations in thyroid cancer. J Clin Endocrinol Metab 2013;98(11):E1852–60. DOI: 10.1210/jc.2013-2292.

91. Valderrabano P., Zota V., McIver B. et al. Molecular assays in cytopathology for thyroid cancer. Cancer Control 2015;22(2):152–7. DOI: 10.1177/107327481502200205.

92. Nikiforov Y., Baloch Z. Clinical validation of the ThyroSeq v3 genomic classifier in thyroid nodules with indeterminate FNA cytology. Cancer Cytopathol 2019;127(4): 225–30. DOI: 10.1002/cncy.22112.

93. Якушина В.Д., Зайцева М.А., Пав- лов А.Е. и др. Разработка таргетной панели для молекулярно-генетической диагностики рака щитовидной железы. Медицинская генетика 2016;15(9):44–8.