pp 1–14 | Cite as

Advances in metabolomics of thyroid cancer diagnosis and metabolic regulation

  • Raziyeh Abooshahab
  • Morteza Gholami
  • Maryam Sanoie
  • Fereidoun Azizi
  • Mehdi HedayatiEmail author


Thyroid cancers (TCs) are the most frequent endocrine malignancy with an unpredictable fast-growing incidence, especially in females all over the world. Fine-needle aspiration biopsy (FNAB) analysis is an accurate diagnostic method for detecting thyroid nodules and classification of TC. Though simplicity, safety, and accuracy of FNAB, 15–30% of cases are indeterminate, and it is not possible to determine the exact cytology of the specimen. This demands the need for innovative methods capable to find crucial biomarkers with adequate sensitivity for diagnosis and prediction in TC researches. Cancer-based metabolomics is a vast emerging field focused on the detection of a large set of metabolites extracted from biofluids or tissues. Using analytical chemistry procedures allows for the potential recognition of cancer-based metabolites for the purposes of advancing the era of personalized medicine. Nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) coupled with separation techniques e.g., gas chromatography (GC) and liquid chromatography (LC) are the main approaches for metabolic studies in cancers. The immense metabolite profiling has provided a chance to discover novel biomarkers for early detection of thyroid cancer and reduce unnecessary aggressive surgery. In this review, we recapitulate the recent advances and developed methods of diverse metabolomics tools and metabolic phenotypes of thyroid cancer, following a brief discussion of recent challenges in the thyroid cancer diagnosis.


Thyroid cancer diagnosis Metabolomics Early detection NMR GC/MS LC/MS 



This study is supported by a research grant from Endocrine Research Center, Shahid Beheshti University of Medical Sciences. The authors are grateful to Dr. S. Adeleh Razavi, Cellular and Molecular Endocrine Research Center (CMERC), Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, for critically reading the manuscript. The authors also would like to thank a graphic designer, Alireza Gerami, for his kind cooperation.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animal performed by any of the authors.


  1. 1.
    S. Vaccarella, S. Franceschi, F. Bray, C.P. Wild, M. Plummer, L. Dal Maso, Worldwide thyroid-cancer epidemic? the increasing impact of overdiagnosis. N. Engl. J. Med. 375, 614 (2016)CrossRefPubMedGoogle Scholar
  2. 2.
    L.Z.K. Enewold, E. Ron, A.J. Marrogi, A. Stojadinovic, G.E. Peoples, S.S. Devesa, Rising thyroid cancer incidence in the United States by demographic and tumor characteristics. Cancer Epidemiol. Biomarkers. Prev. 18, 784–779 (2009)CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    L.G. Morris, D. Myssiorek, Improved detection does not fully explain the rising incidence of well-differentiated thyroid cancer: a population-based analysis. Am. J. Surg. 200, 454–461; (2010)
  4. 4.
    F. Bray, J. Ferlay, I. Soerjomataram, R.L. Siegel, L.A. Torre, A. Jemal, Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: Cancer J. Clin. 68, 394–424 (2018)Google Scholar
  5. 5.
    G.D. Braunstein, Thyroid Cnacer. In: Melmed, editor. Endocrine Updates. Vol. 32 (Springer, NY, USA, 2012)Google Scholar
  6. 6.
    N.R.M.E. Lemoine, F.S. Wyllie, C.J. Farr, D. Hughes, R.A. Padua et al., Activated ras oncogenes in human thyroid cancers. Cancer Res. 48, 4459–4463 (1998)Google Scholar
  7. 7.
    D. Sarne, SA, External radiation and thyroid neoplasia. Endocrinol. Metab. Clin. North. Am. 25, 181–195 (1996)CrossRefPubMedGoogle Scholar
  8. 8.
    H.N.I. Yamashita, S. Noguchi, N. Murakami, A. Moriuchi, S. Yokoyama et al., Thyroid carcinoma in benign thyroid diseases:an analysis from minute carcinoma. Acta Pathol. Jpn. 35, 781–788 (1985)PubMedGoogle Scholar
  9. 9.
    American Thyroid Association (ATA) Guidelines Taskforce on Thyroid Nodules and Differentiated Thyroid Cancer CD, G.M. Doherty, B.R. Haugen, R.T. Kloos, S.L. Lee, S.J. Mandel, E.L. Mazzaferri, B. McIver, F. Pacini, M. Schlumberger, S.I. Sherman, D.L. Steward, R.M. Tuttle, Revised American Thyroid Association management guidelines for patients with thyroid nodules and differentiated thyroid cancer. Thyroid. 19, 1167–1214 (2009)CrossRefGoogle Scholar
  10. 10.
    E.S.A.S. Cibas, The Bethesda system for reporting thyroid cytopathology. Thyroid. 19, 1159–1165 (2009)CrossRefPubMedGoogle Scholar
  11. 11.
    J. Yang, V. Schnadig, R. Logrono, P.G. Wasserman, Fine-needle aspiration of thyroid nodules: a study of 4703 patients with histologic and clinical correlations. Cancer 25 111, 306–315 (2007)CrossRefGoogle Scholar
  12. 12.
    L. Yassa, E.S. Cibas, C.B. Benson, M.C. Frates, P.M. Doubilet, A.A. Gawande, F.D. Moore Jr, B.W. Kim, V. Nosé, E. Marqusee, Long‐term assessment of a multidisciplinary approach to thyroid nodule diagnostic evaluation. Cancer Cytopathol.: Interdisciplinary International Journal of the American Cancer Society 111, 508–516 (2007)CrossRefGoogle Scholar
  13. 13.
    F. Pacini, M. Schlumberger, H. Dralle, R. Elisei, J.W. Smit, W. Wiersinga, Erratum: European consensus for the management of patients with differentiated thyroid carcinoma of the follicular epithelium. Eur. J. Endocrinol. 155, 385 (2006)CrossRefGoogle Scholar
  14. 14.
    M. Bongiovanni, A. Spitale, W.C. Faquin, L. Mazzucchelli, Z.W. Baloch, The Bethesda system for reporting thyroid cytopathology: a meta-analysis. Acta Cytol. 56, 333–339 (2012)CrossRefPubMedGoogle Scholar
  15. 15.
    A.S. Ho, E.E. Sarti, K.S. Jain, H. Wang, I.J. Nixon, A.R. Shaha, J.P. Shah, D.H. Kraus, R. Ghossein, S.A. Fish, Malignancy rate in thyroid nodules classified as Bethesda category III (AUS/FLUS). Thyroid. 24, 832–839 (2014)CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    X. Su, X. Jiang, X. Xu, W. Wang, X. Teng, A. Shao, L. Teng, Diagnostic value of BRAFV600E-mutation analysis in fine-needle aspiration of thyroid nodules: a meta-analysis. Onco. Targets Ther. 9, 2495 (2016)CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    W. Clinkscales, A. Ong, S. Nguyen, E.E. Harruff, M.B. Gillespie, Diagnostic value of RAS mutations in indeterminate thyroid nodules: systematic review and meta-analysis. Otolaryngology–Head and Neck Surgery 156, 472–479 (2017)CrossRefPubMedGoogle Scholar
  18. 18.
    M. Eszlinger, A. Krogdahl, S. Münz, C. Rehfeld, E.M. Precht Jensen, C. Ferraz, E. Bösenberg, N. Drieschner, M. Scholz, L. Hegedüs, Impact of molecular screening for point mutations and rearrangements in routine air-dried fine-needle aspiration samples of thyroid nodules. Thyroid. 24, 305–313 (2014)CrossRefPubMedGoogle Scholar
  19. 19.
    S. Yu, Y. Liu, J. Wang, Z. Guo, Q. Zhang, F. Yu, Y. Zhang, K. Huang, Y. Li, E. Song, Circulating microRNA profiles as potential biomarkers for diagnosis of papillary thyroid carcinoma. The Journal of Clinical Endocrinology & Metabolism 97, 2084–2092 (2012)CrossRefGoogle Scholar
  20. 20.
    S. Fischer, S.L. Asa, Application of immunohistochemistry to thyroid neoplasms. Arch. Pathol. Lab. Med. 132, 359–372 (2008)PubMedGoogle Scholar
  21. 21.
    S. Serra, S.L. Asa, Controversies in thyroid pathology: the diagnosis of follicular neoplasms. Endocr. Pathol. 19, 156–165 (2008)CrossRefPubMedGoogle Scholar
  22. 22.
    J.K. Nicholson, J.C. Lindon, E. Holmes, ‘Metabonomics’: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica 29, 1181–1189 (1999)CrossRefGoogle Scholar
  23. 23.
    W.M. Claudino, P.H. Goncalves, A. di Leo, P.A. Philip, F.H. Sarkar, Metabolomics in cancer: a bench-to-bedside intersection. Crit. Rev. Oncol. Hematol. 84, 1–7 (2012)CrossRefPubMedGoogle Scholar
  24. 24.
    A. Shevchenko, K. Simons, Lipidomics: coming to grips with lipid diversity. Nat. Rev. Mol. Cell Biol. 11, 593 (2010)CrossRefPubMedGoogle Scholar
  25. 25.
    M.R. Wenk, The emerging field of lipidomics. Nat. Rev. Drug. Discov. 4, 594 (2005)CrossRefPubMedGoogle Scholar
  26. 26.
    R. Bandu, H.J. Mok, K.P. Kim, Phospholipids as cancer biomarkers: mass spectrometry‐based analysis. Mass. Spectrom. Rev. 37, 107–138 (2018)CrossRefPubMedGoogle Scholar
  27. 27.
    P. Miccoli, L. Torregrossa, L. Shintu, A. Magalhaes, J. Chandran, A. Tintaru, C. Ugolini, M.N. Minuto, M. Miccoli, F. Basolo, Metabolomics approach to thyroid nodules: A high-resolution magic-angle spinning nuclear magnetic resonance–based study. Surgery 152, 1118–1124 (2012)CrossRefPubMedGoogle Scholar
  28. 28.
    A. Wojakowska, M. Chekan, P. Widlak, M. Pietrowska, Application of metabolomics in thyroid cancer research. Int. Jo. Endocrinol 2015, 258763 (2015)Google Scholar
  29. 29.
    R.H. Grogan, E.J. Mitmaker, O.H. Clark, The evolution of biomarkers in thyroid cancer—from mass screening to a personalized biosignature. Cancers 2, 885–912 (2010)CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    L. Guo, C. Wang, C. Chi, X. Wang, S. Liu, W. Zhao, C. Ke, G. Xu, E. Li, Exhaled breath volatile biomarker analysis for thyroid cancer. Translational Research 166, 188–195 (2015)CrossRefPubMedGoogle Scholar
  31. 31.
    X. Shang, X. Zhong, X. Tian, Metabolomics of papillary thyroid carcinoma tissues: potential biomarkers for diagnosis and promising targets for therapy. Tumor Biology 37, 11163–11175 (2016)CrossRefPubMedGoogle Scholar
  32. 32.
    M. Chen, M. Shen, Y. Li, C. Liu, K. Zhou, W. Hu, B. Xu, Y. Xia, W. Tang, GC-MS-based metabolomic analysis of human papillary thyroid carcinoma tissue. Int. J. Mol. Med. 36, 1607–1614 (2015)CrossRefPubMedGoogle Scholar
  33. 33.
    G.N. Gowda, S. Zhang, H. Gu, V. Asiago, N. Shanaiah, D. Raftery, Metabolomics-based methods for early disease diagnostics. Expert. Rev. Mol. Diagn. 8, 617–633 (2008)CrossRefPubMedGoogle Scholar
  34. 34.
    A. Scalbert, L. Brennan, O. Fiehn, T. Hankemeier, B.S. Kristal, B. van Ommen, E. Pujos-Guillot, E. Verheij, D. Wishart, S. Wopereis, Mass-spectrometry-based metabolomics: limitations and recommendations for future progress with particular focus on nutrition research. Metabolomics. 5, 435 (2009)CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    R. Beger, A review of applications of metabolomics in cancer. Metabolites 3, 552–574 (2013)CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    L. Brennan, NMR-based metabolomics: from sample preparation to applications in nutrition research. Prog. Nucl. Magn. Reson. Spectros. 83, 42–49 (2014)CrossRefGoogle Scholar
  37. 37.
    J.L. Griffin, R.A. Kauppinen, Tumour metabolomics in animal models of human cancer. J. Proteome. Res. 6, 498–505 (2007)CrossRefPubMedGoogle Scholar
  38. 38.
    I.C. Felli, B. Brutscher, Recent advances in solution NMR: fast methods and heteronuclear direct detection. Chemphyschem 10, 1356–1368 (2009)CrossRefPubMedGoogle Scholar
  39. 39.
    P. Russell, C.L. Lean, L. Delbridge, G.L. May, S. Dowd, C.E. Mountford, Proton magnetic resonance and human thyroid neoplasia I: discrimination between benign and malignant neoplasms. Am. J. Med. 96, 383–388 (1994)CrossRefPubMedGoogle Scholar
  40. 40.
    W.B. Mackinnon, L. Delbridge, P. Russell, C.L. Lean, G.L. May, S. Doran, S. Dowd, C.E. Mountford, Two-dimensional proton magnetic resonance spectroscopy for tissue characterization of thyroid neoplasms. World J. Surg. 20, 841–847 (1996)CrossRefPubMedGoogle Scholar
  41. 41.
    Y. Yoshioka, J. Sasaki, M. Yamamoto, K. Saitoh, S. Nakaya, M. Kubokawa, Quantitation by 1H‐NMR of dolichol, cholesterol and choline‐containing lipids in extracts of normal and phathological thyroid tissue. NMR. Biomed. 13, 377–383 (2000)CrossRefPubMedGoogle Scholar
  42. 42.
    A.D. King, D.K. Yeung, A.T. Ahuja, M. Gary, A.B. Chan, S.S. Lam, A.C. van Hasselt, In vivo 1H MR spectroscopy of thyroid carcinoma. Eur. J. Radiol. 54, 112–117 (2005)CrossRefPubMedGoogle Scholar
  43. 43.
    K.W. Jordan, C.B. Adkins, L.L. Cheng, W.C. Faquin, Application of magnetic-resonance-spectroscopy-based metabolomics to the fine-needle aspiration diagnosis of papillary thyroid carcinoma. Acta Cytol. 55, 584–589 (2011)CrossRefPubMedPubMedCentralGoogle Scholar
  44. 44.
    L. Torregrossa, L. Shintu, J. Nambiath Chandran, A. Tintaru, C. Ugolini, Magalhães Ar, F. Basolo, P. Miccoli, S. Caldarelli, Toward the reliable diagnosis of indeterminate thyroid lesions: a HRMAS NMR-based metabolomics case of study. J. Proteome. Res. 11, 3317–3325 (2012)CrossRefPubMedGoogle Scholar
  45. 45.
    S. Deja, T. Dawiskiba, W. Balcerzak, M. Orczyk-Pawiłowicz, M. Głód, D. Pawełka, P. Młynarz, Follicular adenomas exhibit a unique metabolic profile. 1H NMR studies of thyroid lesions. PLoS ONE. 8, e84637 (2013)CrossRefPubMedPubMedCentralGoogle Scholar
  46. 46.
    Y. Tian, X. Nie, S. Xu, Y. Li, T. Huang, H. Tang, Y. Wang, Integrative metabonomics as potential method for diagnosis of thyroid malignancy. Sci. Rep. 5, 14869 (2015)CrossRefPubMedPubMedCentralGoogle Scholar
  47. 47.
    I. Ryoo, H. Kwon, S.C. Kim, S.C. Jung, J.A. Yeom, H.S. Shin, H.R. Cho, T.J. Yun, S.H. Choi, C.-H. Sohn, Metabolomic analysis of percutaneous fine-needle aspiration specimens of thyroid nodules: potential application for the preoperative diagnosis of thyroid cancer. Sci. Rep. 6, 30075 (2016)CrossRefPubMedPubMedCentralGoogle Scholar
  48. 48.
    J. Lu, S. Hu, P. Miccoli, Q. Zeng, S. Liu, L. Ran, C. Hu, Non-invasive diagnosis of papillary thyroid microcarcinoma: a NMR-based metabolomics approach. Oncotarget 7, 81768 (2016)PubMedPubMedCentralGoogle Scholar
  49. 49.
    W. Wojtowicz, A. Zabek, S. Deja, T. Dawiskiba, D. Pawelka, M. Glod, W. Balcerzak, P. Mlynarz, Serum and urine 1 H NMR-based metabolomics in the diagnosis of selected thyroid diseases. Sci. Rep. 7, 9108 (2017)CrossRefPubMedPubMedCentralGoogle Scholar
  50. 50.
    J.W. Seo, K. Han, J. Lee, E.-K. Kim, H.J. Moon, J.H. Yoon, V.Y. Park, H.-M. Baek, J.Y. Kwak, Application of metabolomics in prediction of lymph node metastasis in papillary thyroid carcinoma. PLoS ONE. 13, e0193883 (2018)CrossRefPubMedPubMedCentralGoogle Scholar
  51. 51.
    Y. Gu, T. Chen, S. Fu, X. Sun, L. Wang, J. Wang, Y. Lu, S. Ding, G. Ruan, L. Teng, Perioperative dynamics and significance of amino acid profiles in patients with cancer. J. Transl. Med. 13, 35 (2015)CrossRefPubMedPubMedCentralGoogle Scholar
  52. 52.
    Z. Yao, P. Yin, D. Su, Z. Peng, L. Zhou, L. Ma, W. Guo, L. Ma, G. Xu, J. Shi, Serum metabolic profiling and features of papillary thyroid carcinoma and nodular goiter. Mol. Biosyst. 7, 2608–2614 (2011)CrossRefPubMedGoogle Scholar
  53. 53.
    A. Wojakowska, M. Chekan, Ł. Marczak, K. Polanski, D. Lange, M. Pietrowska, P. Widlak, Detection of metabolites discriminating subtypes of thyroid cancer: molecular profiling of FFPE samples using the GC/MS approach. Mol. Cell. Endocrinol. 417, 149–157 (2015)CrossRefPubMedGoogle Scholar
  54. 54.
    Y. Xu, X. Zheng, Y. Qiu, W. Jia, J. Wang, S. Yin, Distinct metabolomic profiles of papillary thyroid carcinoma and benign thyroid adenoma. J. Proteome. Res. 14, 3315–3321 (2015)CrossRefPubMedGoogle Scholar
  55. 55.
    S. Shimma, Y. Sugiura, T. Hayasaka, N. Zaima, M. Matsumoto, M. Setou, Mass imaging and identification of biomolecules with MALDI-QIT-TOF-based system. Anal. Chem. 80, 878–885 (2008)CrossRefPubMedGoogle Scholar
  56. 56.
    S. Ishikawa, I. Tateya, T. Hayasaka, N. Masaki, Y. Takizawa, S. Ohno, T. Kojima, Y. Kitani, M. Kitamura, S. Hirano, Increased expression of phosphatidylcholine (16: 0/18: 1) and (16: 0/18: 2) in thyroid papillary cancer. PLoS ONE. 7, e48873 (2012)CrossRefPubMedPubMedCentralGoogle Scholar
  57. 57.
    S. Guo, Y. Wang, D. Zhou, Z. Li, Significantly increased monounsaturated lipids relative to polyunsaturated lipids in six types of cancer microenvironment are observed by mass spectrometry imaging. Sci. Rep. 4, 5959 (2014)CrossRefPubMedPubMedCentralGoogle Scholar
  58. 58.
    S. Guo, L. Qiu, Y. Wang, X. Qin, H. Liu, M. He, Y. Zhang, Z. Li, X. Chen, Tissue imaging and serum lipidomic profiling for screening potential biomarkers of thyroid tumors by matrix-assisted laser desorption/ionization-Fourier transform ion cyclotron resonance mass spectrometry. Anal. Bioanal. Chem. 406, 4357–4370 (2014)CrossRefPubMedGoogle Scholar
  59. 59.
    A. Wojakowska, L. Cole, M. Chekan, K. Bednarczyk, M. Maksymiak, M. Oczko-Wojciechowska, B. Jarzab, M. Clench, J. Polańska, M. Pietrowska, Discrimination of papillary thyroid cancer from non-cancerous thyroid tissue based on lipid profiling by MALDI-MSI. Endokrynologia Polska 69, 2–8 (2015)CrossRefGoogle Scholar
  60. 60.
    O. Warburg, S. Minami, Versuche an überlebendem carcinom-gewebe. J. Mol. Med. 2, 776–777 (1923)Google Scholar
  61. 61.
    S. Weinhouse, O. Warburg, D. Burk, A.L.Schade, On Respiratory Impairment in Cancer Cells. Science 124, 267–272 (1956).
  62. 62.
    D.C. Ngo, K. Ververis, S.M. Tortorella, T.C. Karagiannis, Introduction to the molecular basis of cancer metabolism and the Warburg effect. Mol. Biol. Rep. 42, 819–823 (2015)CrossRefPubMedGoogle Scholar
  63. 63.
    R.J. DeBerardinis, J.J. Lum, G. Hatzivassiliou, C.B. Thompson, The biology of cancer: metabolic reprogramming fuels cell growth and proliferation. Cell. Metab. 7, 11–20 (2008)CrossRefPubMedGoogle Scholar
  64. 64.
    Y. Asgari, Z. Zabihinpour, A. Salehzadeh-Yazdi, F. Schreiber, A. Masoudi-Nejad, Alterations in cancer cell metabolism: the Warburg effect and metabolic adaptation. Genomics 105, 275–281 (2015)CrossRefPubMedGoogle Scholar
  65. 65.
    R.G. Coelho, Jd.M. Cazarin, C. de Albuquerque, J.P. Albuquerque, B.M. de Andrade, D.P. Carvalho, Differential glycolytic profile and Warburg effect in papillary thyroid carcinoma cell lines. Oncol. Rep. 36, 3673–3681 (2016)CrossRefPubMedGoogle Scholar
  66. 66.
    S.S. Sabharwal, P.T. Schumacker, Mitochondrial ROS in cancer: initiators, amplifiers or an Achilles’ heel? Nat. Rev. Cancer 14, 709 (2014)CrossRefPubMedPubMedCentralGoogle Scholar
  67. 67.
    U. Weyemi, B. Caillou, M. Talbot, R. Ameziane-El-Hassani, L. Lacroix, O. Lagent-Chevallier, A. Al Ghuzlan, D. Roos, J.-M. Bidart, A. Virion, Intracellular expression of reactive oxygen species-generating NADPH oxidase NOX4 in normal and cancer thyroid tissues. Endocr. Relat. Cancer 17, 27–37 (2010)CrossRefPubMedGoogle Scholar
  68. 68.
    U. Weyemi, O. Lagente-Chevallier, M. Boufraqech, F. Prenois, F. Courtin, B. Caillou, M. Talbot, M. Dardalhon, A. Al Ghuzlan, J. Bidart, ROS-generating NADPH oxidase NOX4 is a critical mediator in oncogenic H-Ras-induced DNA damage and subsequent senescence. Oncogene 31, 1117 (2012)CrossRefPubMedGoogle Scholar
  69. 69.
    N. Azouzi, J. Cailloux, J.M. Cazarin, J.A. Knauf, J. Cracchiolo, A. Al Ghuzlan, D. Hartl, M. Polak, A. Carré, M. El Mzibri, NADPH oxidase NOX4 is a critical mediator of BRAFV600E-induced downregulation of the sodium/iodide symporter in papillary thyroid carcinomas. Antioxid. Redox. Signal. 26, 864–877 (2017)CrossRefPubMedPubMedCentralGoogle Scholar
  70. 70.
    I. Moroni, L. D’incerti, E. Maccagnano, M. Bugiani, M. Rimoldi, G. Broggi, G. Uziel, L-2-hydroxyglutaric aciduria and brain malignant tumors. J. Inherit. Metab. Dis. 25, 59 (2002)Google Scholar
  71. 71.
    A.M. Intlekofer, R.G. Dematteo, S. Venneti, L.W. Finley, C. Lu, A.R. Judkins, A.S. Rustenburg, P.B. Grinaway, J.D. Chodera, J.R. Cross, Hypoxia induces production of L-2-hydroxyglutarate. Cell. Metab. 22, 304–311 (2015)CrossRefPubMedPubMedCentralGoogle Scholar
  72. 72.
    F.E. Bleeker, S. Lamba, S. Leenstra, D. Troost, T. Hulsebos, W.P. Vandertop, M. Frattini, F. Molinari, M. Knowles, A. Cerrato, IDH1 mutations at residue p. R132 (IDH1R132) occur frequently in high‐grade gliomas but not in other solid tumors. Hum. Mutat. 30, 7–11 (2009)CrossRefPubMedGoogle Scholar
  73. 73.
    A.K. Murugan, E. Bojdani, M. Xing, Identification and functional characterization of isocitrate dehydrogenase 1 (IDH1) mutations in thyroid cancer. Biochem. Biophys. Res. Commun. 393, 555–559 (2010)CrossRefPubMedPubMedCentralGoogle Scholar
  74. 74.
    R.S. Haber, K.R. Weiser, A. Pritsker, I. Reder, D.E. Burstein, GLUT1 glucose transporter expression in benign and malignant thyroid nodules. Thyroid. 7, 363–367 (1997)CrossRefPubMedGoogle Scholar
  75. 75.
    K. Matsuzu, F. Segade, U. Matsuzu, A. Carter, D.W. Bowden, N.D. Perrier, Differential expression of glucose transporters in normal and pathologic thyroid tissue. Thyroid. 14, 806–812 (2004)CrossRefPubMedGoogle Scholar
  76. 76.
    J.H. Nahm, H.M. Kim, J.S. Koo, Glycolysis-related protein expression in thyroid cancer. Tumor Biology 39, 1010428317695922 (2017)CrossRefPubMedGoogle Scholar
  77. 77.
    J.E. Wilson, Isozymes of mammalian hexokinase: structure, subcellular localization and metabolic function. J. Exp. Biol. 206, 2049–2057 (2003)CrossRefPubMedGoogle Scholar
  78. 78.
    Paweł. Lis, Mariusz Dyl ag, Katarzyna Nied´zwiecka, YoungH. Ko, PeterL. Pedersen AG, S. Ułaszewski, The HK2 dependent “Warburg Effect” and mitochondrial oxidative phosphorylation in cancer: targets for effective therapy with 3-bromopyruvate. Molecules 21, 1730 (2016)CrossRefPubMedCentralGoogle Scholar
  79. 79.
    G. Rijksen, R. Oskam, C.F. Molthoff, S.-J.L. On, M. Streefkerk, G.E. Staal, Hexokinase isoenzymes from anaplastic and differentiated medullary thyroid carcinoma in the rat. Eur. J. Cancer 20, 967–973 (1984)CrossRefGoogle Scholar
  80. 80.
    L. Hooft, A. Van der Veldt, P. Van Diest, O. Hoekstra, J. Berkhof, G. Teule, C. Molthoff, [18F] fluorodeoxyglucose uptake in recurrent thyroid cancer is related to hexokinase I expression in the primary tumor. J. Clin. Endocrinol. Metab. 90, 328–334 (2005)CrossRefPubMedGoogle Scholar
  81. 81.
    L. Hooft, A. Van Der Veldt, O. Hoekstra, M. Boers, C. Molthoff, P. Van Diest, Hexokinase III, cyclin A and galectin‐3 are overexpressed in malignant follicular thyroid nodules. Clin. Endocrinol. (Oxf). 68, 252–257 (2008)CrossRefPubMedGoogle Scholar
  82. 82.
    K. Imamura, T. TANAKA, Multimolecular forms of pyruvate kinase from rat and other mammalian tissues. J. Biochem. 71, 1043–1051 (1972)CrossRefPubMedGoogle Scholar
  83. 83.
    H.R. Christofk, M.G. Vander Heiden, M.H. Harris, A. Ramanathan, R.E. Gerszten, R. Wei, M.D. Fleming, S.L. Schreiber, L.C. Cantley, The M2 splice isoform of pyruvate kinase is important for cancer metabolism and tumour growth. Nature 452, 230 (2008)CrossRefPubMedGoogle Scholar
  84. 84.
    M.I. Koukourakis, A. Giatromanolaki, E. Sivridis, Lactate dehydrogenase isoenzymes 1 and 5: differential expression by neoplastic and stromal cells in non-small cell lung cancer and other epithelial malignant tumors. Tumor Biol. 24, 199–202 (2003)CrossRefGoogle Scholar
  85. 85.
    C. Feng, Y. Gao, C. Wang, X. Yu, W. Zhang, H. Guan, Z. Shan, W. Teng, Aberrant overexpression of pyruvate kinase M2 is associated with aggressive tumor features and the BRAF mutation in papillary thyroid cancer. J. Clin. Endocrinol. Metab. 98, E1524–E1533 (2013)CrossRefPubMedGoogle Scholar
  86. 86.
    V.R. Fantin, J. St-Pierre, P. Leder, Attenuation of LDH-A expression uncovers a link between glycolysis, mitochondrial physiology, and tumor maintenance. Cancer Cell. 9, 425–434 (2006)CrossRefPubMedGoogle Scholar
  87. 87.
    D. Mirebeau-Prunier, S. Le Pennec, C. Jacques, J.-F. Fontaine, N. Gueguen, N. Boutet-Bouzamondo, A. Donnart, Y. Malthièry, F. Savagner, Estrogen-related receptor alpha modulates lactate dehydrogenase activity in thyroid tumors. PLoS ONE. 8, e58683 (2013)CrossRefPubMedPubMedCentralGoogle Scholar
  88. 88.
    P. Kachel, B. Trojanowicz, C. Sekulla, H. Prenzel, H. Dralle, C. Hoang-Vu, Phosphorylation of pyruvate kinase M2 and lactate dehydrogenase A by fibroblast growth factor receptor 1 in benign and malignant thyroid tissue. BMC. Cancer 15, 140 (2015)CrossRefPubMedPubMedCentralGoogle Scholar
  89. 89.
    A.P. Halestrap, The SLC16 gene family–structure, role and regulation in health and disease. Mol. Aspects. Med. 34, 337–349 (2013)CrossRefPubMedGoogle Scholar
  90. 90.
    A.P. Halestrap, M.C. Wilson, The monocarboxylate transporter family—role and regulation. IUBMB Life 64, 109–119 (2012)CrossRefPubMedGoogle Scholar
  91. 91.
    C. Pinheiro, A. Longatto-Filho, J. Azevedo-Silva, M. Casal, F.C. Schmitt, F. Baltazar, Role of monocarboxylate transporters in human cancers: state of the art. J. Bioenerg. Biomembr. 44, 127–139 (2012)CrossRefPubMedGoogle Scholar
  92. 92.
    J.M. Johnson, S.Y. Lai, P. Cotzia, D. Cognetti, A. Luginbuhl, E.A. Pribitkin, T. Zhan, M. Mollaee, M. Domingo-Vidal, Y. Chen, Mitochondrial Metabolism as a Treatment Target in Anaplastic Thyroid Cancer. Semin Oncol. 42, 915–922 (2015)CrossRefPubMedPubMedCentralGoogle Scholar
  93. 93.
    J.M. Curry, P. Tassone, P. Cotzia, J. Sprandio, A. Luginbuhl, D.M. Cognetti, M. Mollaee, M. Domingo‐Vidal, E.A. Pribitkin, W.M. Keane, Multicompartment metabolism in papillary thyroid cancer. Laryngoscope 126, 2410–2418 (2016)CrossRefPubMedGoogle Scholar
  94. 94.
    R.J. DeBerardinis, T. Cheng, Q’s next: the diverse functions of glutamine in metabolism, cell biology and cancer. Oncogene 29, 313 (2010)CrossRefPubMedGoogle Scholar
  95. 95.
    C.L. Collins, M. Wasa, W.W. Souba, S.F. Abcouwer, Regulation of glutamine synthetase in human breast carcinoma cells and experimental tumors. Surgery 122, 451–464 (1997)CrossRefPubMedGoogle Scholar
  96. 96.
    E. Friday, R. Oliver, T. Welbourne, F. Turturro, Glutaminolysis and glycolysis regulation by troglitazone in breast cancer cells: Relationship to mitochondrial membrane potential. J. Cell. Physiol. 226, 511–519 (2011)CrossRefPubMedGoogle Scholar
  97. 97.
    H.M. Kim, Y.K. Lee, J.S. Koo, Expression of glutamine metabolism-related proteins in thyroid cancer. Oncotarget 7, 53628 (2016)PubMedPubMedCentralGoogle Scholar
  98. 98.
    Y. Yu, X. Yu, C. Fan, H. Wang, R. Wang, C. Feng, H. Guan, Targeting glutaminase-mediated glutamine dependence in papillary thyroid cancer. J. Mol. Med. 96, 777–790 (2018)CrossRefPubMedGoogle Scholar
  99. 99.
    J.-w Kim, P. Gao, Y.-C. Liu, G.L. Semenza, C.V. Dang, Hypoxia-inducible factor 1 and dysregulated c-Myc cooperatively induce vascular endothelial growth factor and metabolic switches hexokinase 2 and pyruvate dehydrogenase kinase 1. Mol. Cell. Biol. 27, 7381–7393 (2007)CrossRefPubMedPubMedCentralGoogle Scholar
  100. 100.
    H. Shim, C. Dolde, B.C. Lewis, C.-S. Wu, G. Dang, R.A. Jungmann, R. Dalla-Favera, C.V. Dang, c-Myc transactivation of LDH-A: implications for tumor metabolism and growth. Proc. Natl. Acad. Sci. 94, 6658–6663 (1997)CrossRefPubMedGoogle Scholar
  101. 101.
    Y. Qu, Q. Yang, J. Liu, B. Shi, M. Ji, G. Li, P. Hou, c-Myc is required for BRAFV600E-induced epigenetic silencing by H3K27me3 in tumorigenesis. Theranostics 7, 2092 (2017)CrossRefPubMedPubMedCentralGoogle Scholar
  102. 102.
    J.-w Kim, I. Tchernyshyov, G.L. Semenza, C.V. Dang, HIF-1-mediated expression of pyruvate dehydrogenase kinase: a metabolic switch required for cellular adaptation to hypoxia. Cell Metab. 3, 177–185 (2006)CrossRefPubMedGoogle Scholar
  103. 103.
    J. Pouysségur, F. Dayan, N.M. Mazure, Hypoxia signalling in cancer and approaches to enforce tumour regression. Nature 441, 437 (2006)CrossRefPubMedGoogle Scholar
  104. 104.
    C.V. Dang, Kim J-w, P. Gao, J. Yustein, The interplay between MYC and HIF in cancer. Nat. Rev. Cancer 8, 51 (2008)CrossRefPubMedGoogle Scholar
  105. 105.
    J.D. Gordan, C.B. Thompson, M.C. Simon, HIF and c-Myc: sibling rivals for control of cancer cell metabolism and proliferation. Cancer Cell. 12, 108–113 (2007)CrossRefPubMedPubMedCentralGoogle Scholar
  106. 106.
    O. Koperek, E. Akin, R. Asari, B. Niederle, N. Neuhold, Expression of hypoxia-inducible factor 1 alpha in papillary thyroid carcinoma is associated with desmoplastic stromal reaction and lymph node metastasis. Virchows. Arch. 463, 795–802 (2013)CrossRefPubMedGoogle Scholar
  107. 107.
    A. Klaus, O. Fathi, T.-W. Tatjana, N. Bruno, K. Oskar, Expression of hypoxia-associated protein HIF-1α in follicular thyroid cancer is associated with distant metastasis. Pathol. Oncol. Res. 24, 289–296 (2018)CrossRefPubMedGoogle Scholar
  108. 108.
    L. Lodewijk, P. van Diest, P. van der Groep, N. ter Hoeve, A. Schepers, J. Morreau, J. Bonenkamp, A. van Engen-van Grunsven, S. Kruijff, B. van Hemel, Expression of HIF-1α in medullary thyroid cancer identifies a subgroup with poor prognosis. Oncotarget 8, 28650 (2017)CrossRefPubMedPubMedCentralGoogle Scholar
  109. 109.
    Y. Lv, Y. Sun, T. Shi, C. Shi, H. Qin, Z. Li, Pigment epithelium-derived factor has a role in the progression of papillary thyroid carcinoma by affecting the HIF1α-VEGF signaling pathway. Oncol. Lett. 12, 5217–5222 (2016)CrossRefPubMedPubMedCentralGoogle Scholar
  110. 110.
    İ. Bingül, P. Vural, S. Doğru‐Abbasoğlu, E. Çil, M. Uysal, Vascular endothelial growth factor G + 405C polymorphism may contribute to the risk of developing papillary thyroid carcinoma. J. Clin. Lab. Anal. 31, e22110 (2017)CrossRefGoogle Scholar
  111. 111.
    O. Baris, Fdr Savagner, Vr Nasser, Ba Loriod, S. Granjeaud, S. Guyetant, B. Franc, P. Rodien, V. Rohmer, Fo Bertucci, Transcriptional profiling reveals coordinated up-regulation of oxidative metabolism genes in thyroid oncocytic tumors. J. Clin. Endocrinol. Metab. 89, 994–1005 (2004)CrossRefPubMedGoogle Scholar
  112. 112.
    E. Currie, A. Schulze, R. Zechner, T.C. Walther, R.V. Farese Jr, Cellular fatty acid metabolism and cancer. Cell Metab. 18, 153–161 (2013)CrossRefPubMedPubMedCentralGoogle Scholar
  113. 113.
    C.R. Santos, A. Schulze, Lipid metabolism in cancer. FEBS. J. 279, 2610–2623 (2012)CrossRefPubMedGoogle Scholar
  114. 114.
    C.A. Von Roemeling, L.A. Marlow, A.B. Pinkerton, A. Crist, J. Miller, H.W. Tun, R.C. Smallridge, J.A. Copland, Aberrant lipid metabolism in anaplastic thyroid carcinoma reveals stearoyl CoA desaturase 1 as a novel therapeutic target. J. Clin. Endocrinol. Metab. 100, E697–E709 (2015)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Raziyeh Abooshahab
    • 1
  • Morteza Gholami
    • 1
    • 2
  • Maryam Sanoie
    • 1
  • Fereidoun Azizi
    • 3
  • Mehdi Hedayati
    • 1
    Email author
  1. 1.Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine SciencesShahid Beheshti University of Medical SciencesTehranIran
  2. 2.Department of Chemistry, Faculty of ScienceGolestan UniversityGorganIran
  3. 3.Endocrine Research Center, Research Institute for Endocrine SciencesShahid Beheshti University of Medical SciencesTehranIran

Personalised recommendations