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Identifying potential metabolic tissue biomarkers for papillary thyroid cancer in different iodine nutrient regions

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Abstract

Purpose

To investigate the applicability of metabolomics to select thyroid cancer-associated biomarkers and discover the effects of iodine on metabolic changes in thyroid cancer.

Methods

In this study, a total of 33 papillary thyroid cancer (PTC) patients from areas with iodine excess and 32 PTC patients from areas with adequate iodine were recruited, and their cancerous tissue and paracancerous tissue were collected. These specimens were analyzed by ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC/QTOF/MS) in conjunction with multivariate statistical analysis.

Results

Good separations were obtained for PTC tissue vs. paracancerous tissue, and 15 metabolites, including L-octanoylcarnitine, N-arachidonoylglycine, and others were found to be disturbed in PTC tissue. Moreover, the metabolic profile presented considerable separation between PTC tissue from different iodine areas, and 15 metabolomic biomarkers were found to be differentially expressed. Among them, 10 metabolites, including arachidonoylcarnitine and LysoPCs, were related to thyroid cancer and excess iodine. These biomarkers play a role in arachidonic acid metabolism pathways and others. In addition, biomarkers such as 3,5-tetradecadiencarnitine and oxidized glutathione were significantly correlated with thyroid function, and biomarkers such as L-octanoylcarnitine and arachidonic acid were significantly correlated with the clinical characteristics of PTC.

Conclusions

Distinct differences in metabolic profiles were found to exist between PTCs from areas with different levels of iodine nutrition. The identified biomarkers have significant potential for diagnosing PTC and investigating its underlying mechanisms.

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References

  1. C.M. Kitahara, J.A. Sosa, The changing incidence of thyroid cancer. Nat. Rev. Endocrinol. 12(11), 646–653 (2016)

    Article  PubMed  Google Scholar 

  2. M. Pusztaszeri, M. Auger, Update on the cytologic features of papillary thyroid carcinoma variants. Diagn. Cytopathol. 45(8), 714–730 (2017)

    Article  PubMed  Google Scholar 

  3. M. Akıncı, S.P. Bulut, F. Erözgen et al. Predictive value of fine needle aspiration biopsy of axillary lymph nodes in preoperative breast cancer staging. Ulus. Cerrahi Derg. 32(3), 191–6 (2016)

    PubMed  PubMed Central  Google Scholar 

  4. J.H. An, K.H. Song, S.K. Kim et al. RAS mutations in indeterminate thyroid nodules are predictive of the follicular variant of papillary thyroid carcinoma. Clin. Endocrinol. 82(5), 760–6 (2015)

    Article  CAS  Google Scholar 

  5. J. Li, J. Liu, X. Yu, X. Bao, L. Qian, BRAFv600e mutation combined with thyroglobulin and fine-needle aspiration in diagnosis of lymph node metastasis of papillary thyroid carcinoma. Pathol. Res. Pract. 214(11), 1892–1897 (2018)

    Article  CAS  PubMed  Google Scholar 

  6. E.G. Armitage, M. Ciborowski, Applications of metabolomics in cancer studies. Adv. Exp. Med. Biol. 965, 209–234 (2017)

    Article  CAS  PubMed  Google Scholar 

  7. A.K. Kaushik, R.J. DeBerardinis, Applications of metabolomics to study cancer metabolism. Biochim. Biophys. Acta Rev. Cancer 1870(1), 2–14 (2018)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. G. Hoang, S. Udupa, A. Le, Application of metabolomics technologies toward cancer prognosis and therapy. Int. Rev. Cell Mol. Biol. 347, 191–223 (2019)

    Article  CAS  PubMed  Google Scholar 

  9. X. Shang, X. Zhong, X. Tian, Metabolomics of papillary thyroid carcinoma tissues: potential biomarkers for diagnosis and promising targets for therapy. Tumour Biol. 37(8), 11163–75 (2016)

    Article  CAS  PubMed  Google Scholar 

  10. J. Chen, Q. Hu, H. Hou et al. Metabolite analysis-aided diagnosis of papillary thyroid cancer. Endocr. Relat. Cancer 26(12), 829–841 (2019)

    Article  CAS  PubMed  Google Scholar 

  11. C.T. Shen, Y. Zhang, Y.M. Liu et al. A distinct serum metabolic signature of distant metastatic papillary thyroid carcinoma. Clin. Endocrinol. 87(6), 844–852 (2017)

    Article  CAS  Google Scholar 

  12. Y. Li, M. Chen, C. Liu et al. Metabolic changes associated with papillary thyroid carcinoma: a nuclear magnetic resonance-based metabolomics study. Int. J. Mol. Med. 41(5), 3006–3014 (2018)

    CAS  PubMed  Google Scholar 

  13. M.B. Zimmermann, K. Boelaert, Iodine deficiency and thyroid disorders. Lancet Diabetes Endocrinol. 3(4), 286–95 (2015)

    Article  CAS  PubMed  Google Scholar 

  14. P. Laurberg, S.B. Nøhr, K.M. Pedersen et al. Thyroid disorders in mild iodine deficiency. Thyroid 10(11), 951–63 (2000)

    Article  CAS  PubMed  Google Scholar 

  15. F. Delange, H. Bürgi, Iodine deficiency disorders in Europe. Bull. World Health Organ 67(3), 317–25 (1989)

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Y. Guo, J. Zynat, Z. Xu et al. Iodine nutrition status and thyroid disorders: a cross-sectional study from the Xinjiang Autonomous Region of China. Eur. J. Clin. Nutr. 70(11), 1332–1336 (2016)

    Article  CAS  PubMed  Google Scholar 

  17. O. Ali, Iodine deficiency disorders: a public health challenge in developing countries. Nutrition 11(5 Suppl), 517–20 (1995)

    CAS  PubMed  Google Scholar 

  18. Q.J. Yang, J.R. Zhao, J. Hao et al. Serum and urine metabolomics study reveals a distinct diagnostic model for cancer cachexia. J. Cachexia Sarcopenia Muscle 9(1), 71–85 (2018)

    Article  PubMed  Google Scholar 

  19. T. Chen, P. He, Y. Tan, D. Xu, Biomarker identification and pathway analysis of preeclampsia based on serum metabolomics. Biochem. Biophys. Res. Commun. 485(1), 119–125 (2017)

    Article  CAS  PubMed  Google Scholar 

  20. M. Chen, M. Shen, Y. Li et al. GC-MS-based metabolomic analysis of human papillary thyroid carcinoma tissue. Int. J. Mol. Med. 36(6), 1607–14 (2015)

    Article  PubMed  Google Scholar 

  21. K.M. Kim, B.H. Jung, D.S. Lho, W.Y. Chung, K.J. Paeng, B.C. Chung, Alteration of urinary profiles of endogenous steroids and polyunsaturated fatty acids in thyroid cancer. Cancer Lett. 202(2), 173–9 (2003)

    Article  CAS  PubMed  Google Scholar 

  22. Z.H. Wen, Y.C. Su, P.L. Lai et al. Critical role of arachidonic acid-activated mTOR signaling in breast carcinogenesis and angiogenesis. Oncogene 32(2), 160–70 (2013)

    Article  CAS  PubMed  Google Scholar 

  23. S. Wang, J. Xie, H. Li, K. Yang, Differences of polyunsaturated fatty acid in patients with colorectal cancer and healthy people. J. Cancer Res. Ther. 11(2), 459–63 (2015)

    Article  CAS  PubMed  Google Scholar 

  24. D.K. Nomura, J.Z. Long, S. Niessen, H.S. Hoover, S.W. Ng, B.F. Cravatt, Monoacylglycerol lipase regulates a fatty acid network that promotes cancer pathogenesis. Cell 140(1), 49–61 (2010)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. W.C. Chang, J. Nakao, H. Orimo, S. Murota, Effects of reduced glutathione on the 12-lipoxygenase pathways in rat platelets. Biochem J. 202(3), 771–6 (1982)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Y.S. Lin, Y.C. Shen, C.Y. Wu et al. Danshen improves survival of patients with breast cancer and dihydroisotanshinone i induces ferroptosis and apoptosis of breast cancer cells. Front. Pharm. 10, 1226 (2019)

    Article  CAS  Google Scholar 

  27. J. Liu, M. Liu, H. Zhang et al. Exploring cysteine regulation in cancer cell survival with a highly specific “Lock and Key” fluorescent probe for cysteine. Chem. Sci. 10(43), 10065–10071 (2019)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. E.S. Pizer, C. Jackisch, F.D. Wood, G.R. Pasternack, N.E. Davidson, F.P. Kuhajda, Inhibition of fatty acid synthesis induces programmed cell death in human breast cancer cells. Cancer Res. 56(12), 2745–7 (1996)

    CAS  PubMed  Google Scholar 

  29. S. Qiao, P. Pennanen, N. Nazarova, Y.R. Lou, P. Tuohimaa, Inhibition of fatty acid synthase expression by 1alpha,25-dihydroxyvitamin D3 in prostate cancer cells. J. Steroid Biochem. Mol. Biol. 85(1), 1–8 (2003)

    Article  CAS  PubMed  Google Scholar 

  30. M. Crous-Bou, G. Rennert, R. Salazar et al. Genetic polymorphisms in fatty acid metabolism genes and colorectal cancer. Mutagenesis 27(2), 169–76 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. N. Khan, P.P. Shah, D. Ban et al. Solution structure and functional investigation of human guanylate kinase reveals allosteric networking and a crucial role for the enzyme in cancer. J. Biol. Chem. 294(31), 11920–11933 (2019)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. H.I. Wettersten, A.A. Hakimi, D. Morin, C. Bianchi, M.E. Johnstone, D.R. Donohoe, J.F. Trott, O.A. Aboud, S. Stirdivant, B. Neri, R. Wolfert, B. Stewart, R. Perego, J.J. Hsieh, R.H. Weiss, Grade-dependent metabolic reprogramming in kidney cancer revealed by combined proteomics and metabolomics analysis. Cancer Res. 75(12), 2541–2552 (2015)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. S. Ganti, S.L. Taylor, K. Kim, C.L. Hoppel, L. Guo, J. Yang, C. Evans, R.H. Weiss, Urinary acylcarnitines are altered in human kidney cancer. Int. J. Cancer 130(12), 2791–2800 (2012)

    Article  CAS  PubMed  Google Scholar 

  34. A. Al-Bakheit, M. Traka, S. Saha, R. Mithen, A. Melchini, Accumulation of palmitoylcarnitine and its effect on pro-inflammatory pathways and calcium influx in prostate cancer. Prostate 76(14), 1326–37 (2016)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. S. Wahl, Z. Yu, M. Kleber, P. Singmann, C. Holzapfel, Y. He, K. Mittelstrass, A. Polonikov, C. Prehn, W. Römisch-Margl, J. Adamski, K. Suhre, H. Grallert, T. Illig, R. Wang-Sattler, T. Reinehr, Childhood obesity is associated with changes in the serum metabolite profile. Obes. Facts 5(5), 660–70 (2012)

    Article  CAS  PubMed  Google Scholar 

  36. M. Kang, H.J. Yoo, M. Kim, M. Kim, J.H. Lee, Metabolomics identifies increases in the acylcarnitine profiles in the plasma of overweight subjects in response to mild weight loss: a randomized, controlled design study. Lipids Health Dis. 17(1), 237 (2018)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. F.Q. Huang, J. Li, L. Jiang et al. Serum-plasma matched metabolomics for comprehensive characterization of benign thyroid nodule and papillary thyroid carcinoma. Int. J. Cancer 144(4), 868–876 (2019)

    Article  CAS  PubMed  Google Scholar 

  38. J.L. Rabinowitz, C.J. Tavares, Iodinated phospholipids and the in vitro iodination of proteins of dog thyroid gland. Biochem. J. 168(2), 155–60 (1977)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. N.G. Psihogios, I.F. Gazi, M.S. Elisaf, K.I. Seferiadis, E.T. Bairaktari, Gender-related and age-related urinalysis of1 healthy subjects by NMR-based metabonomics. NMR Biomed. 21(3), 195–207 (2008)

    Article  CAS  PubMed  Google Scholar 

  40. D. Chen, L. Fang, H. Li, C. Jin, The effects of acetaldehyde exposure on histone modifications and chromatin structure in human lung bronchial epithelial cells. Environ. Mol. Mutagen 59(5), 375–385 (2018)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Y.S. Lin, Y.C. Shen, C.Y. Wu et al. Danshen improves survival of patients with breast cancer and dihydroisotanshinone I induces ferroptosis and apoptosis of breast cancer cells. Front. Pharmacol. 10, 1226 (2019)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Yu. J, Shan. Z, Chong. W, et al. Vitamin E ameliorates iodine-induced cytotoxicity in thyroid. J. Endocrinol. 209(3), 299–306 (2011).

    Article  Google Scholar 

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Acknowledgements

The authors gratefully thank the General Surgery Department of the People’s Hospital of Chengwu County and the Department of Head and Neck Oncology in the Third Affiliated Hospital of Harbin Medical University for technical assistance.

Author contributions

Q.S. was the principal investigator of this paper. Q.S., L.F., J.S., and D.S. developed the hypothesis and study design and supervised the study. All authors contributed to the study concept and design, analysis, and interpretation of data, and drafted or critically revised the paper for important intellectual content. All authors approved the final paper for submission.

Funding

The study was supported by a grant from the National Natural Science Foundation of China (NSFC 81602808 and NSFC 81830098) and the Natural Science Foundation of Heilongjiang Province of China (H2016017).

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Authors and Affiliations

  1. Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention, Harbin Medical University, Harbin, Heilongjiang, China

    Qihao Sun, Zhiyong Liu, Qiushi Tian, Lijun Fan & Dianjun Sun

  2. General Surgery Department, People’s Hospital of Chengwu County, Heze, Shandong, China

    Hongjian Zhao

  3. Public Health College, Harbin Medical University, Harbin, Heilongjiang, China

    Fengqian Wang

  4. Shandong First Medical University, Tai’an, Shandong, China

    Qian He

  5. Department of Head and Neck Oncology, The Third Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China

    Cheng Xiu, Lunhua Guo & Ji Sun

  6. School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA

    Lijun Fan

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  1. Qihao Sun
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Correspondence to Lijun Fan, Ji Sun or Dianjun Sun.

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The study was approved by the ethics committee of Harbin Medical University.

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Sun, Q., Zhao, H., Liu, Z. et al. Identifying potential metabolic tissue biomarkers for papillary thyroid cancer in different iodine nutrient regions. Endocrine 74, 582–591 (2021). https://doi.org/10.1007/s12020-021-02773-3

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  • DOI: https://doi.org/10.1007/s12020-021-02773-3

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