Metabolomics-Based Diagnosis of Medullary Thyroid Cancer: A Plasma 1H NMR Approach
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Abstract
Background: Medullary thyroid cancer (MTC) is a rare neuroendocrine malignancy, accounting for 5-10% of all thyroid cancer cases. The precise molecular processes driving MTC remain largely elusive. We aimed to conduct a pilot study analyzing plasma metabolic profiles of MTC patients to uncover disruptions in metabolic pathways that may contribute to MTC tumorigenesis.
Methods: Proton nuclear magnetic resonance (1H-NMR) spectroscopy was performed to screen metabolic changes in plasma samples from MTC patients (n=16) and healthy subjects (n=12). Multivariate and univariate analyses were applied using MetaboAnalyst and SIMCA software.
Results: A total of 30 compounds were identified, of which three metabolites—glycerol, isobutyric acid, and valine—showed significant differences between MTC patients and the control group (P<0.05).
Conclusion: The findings from this study contribute to the current understanding of MTC metabolism and suggest that the NMR-based metabolomics approach can provide a metabolic pattern of MTC, potentially improving diagnostic procedures.
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16. Iuculano A, Murgia F, Peddes C, et al (2019). Metabolic characterization of amniotic fluids of fetuses with enlarged nuchal translucency. J Perinat Med, 47(3):311-8.
17. Metere A, Graves CE, Chirico M, et al (2020). Metabolomic reprogramming detected by 1H-NMR spectroscopy in human thyroid cancer tissues. Biology (Basel), 9(6):112.
18. Kweon S-S, Shin M-H, Chung I-J, et al (2013). Thyroid cancer is the most common cancer in women, based on the data from population-based cancer registries, South Korea. Jpn J Clin Oncol, 43(10):1039-46.
19. Yu G-P, Li JC-L, Branovan D, et al (2010). Thyroid cancer incidence and survival in the national cancer institute surveillance, epidemiology, and end results race/ethnicity groups.Thyroid, 20(5):465-73.
20. Shabani N, Razaviyan J, Paryan M, et al (2018). Evaluation of miRNAs expression in medullary thyroid carcinoma tissue samples: miR-34a and miR-144 as promising overexpressed markers in MTC.Hum Pathol, 79:212-221.
21. Lu J, Hu S, Miccoli P, et al (2016). Non-invasive diagnosis of papillary thyroid microcarcinoma: a NMR-based metabolomics approach.Oncotarget, 7(49):81768- 81777.
22. Faubert B, Solmonson A, DeBerardinis RJ (2020). Metabolic reprogramming and cancer progression. Science, 368(6487):eaaw5473.
23. Vettore L, Westbrook RL, Tennant DA (2020). New aspects of amino acid metabolism in cancer. Br J Cancer, 122(2):150-6.
24. Chen L, Li Z, Zhang Q, et al (2017). Silencing of AQP3 induces apoptosis of gastric cancer cells via downregulation of glycerol intake and downstream inhibition of lipogenesis and autophagy. Onco Targets Ther, 10:2791-2804.
25. Yde J, Keely SJ, Moeller HB (2021). Expression, regulation and function of Aquaporin-3 in colonic epithelial cells. Biochim Biophys Acta Biomembr,1863(7):183619.
26. Niu D, Kondo T, Nakazawa T, et al (2012). Differential expression of aquaporins and its diagnostic utility in thyroid cancer. PLoS One, 7(7):e40770.
27. Rastelli M, Cani PD, Knauf C (2019). The gut microbiome influences host endocrine functions. Endocr Rev, 40(5):1271-84.
28. Liu Q, Wang C, Yang W, et al (2009). Effects of isobutyrate on rumen fermentation, lactation performance and plasma characteristics in dairy cows. Anim Feed Sci Technol, 154(1-2):58-67.
29. Chalova P, Tazky A, Skultety L, et al (2023). Determination of short-chain fatty acids as putative biomarkers of cancer diseases by modern analytical strategies and tools: a review. Front Oncol, 13:1110235.
30. Wang T, Sun Z, Wang Y, et al (2020). Diagnosis of papillary thyroid carcinoma by 1H NMR spectroscopy-based metabolomic analysis of whole blood. Drug Discov Ther, 14(4):187-196.
2. Zarkesh M, Zadeh-Vakili A, Azizi F, et al (2018). Altered epigenetic mechanisms in thyroid cancer subtypes. Mol Diagn Ther, 22:41-56.
3. Agrawal N, Jiao Y, Sausen M, et al (2013). Exomic sequencing of medullary thyroid cancer reveals dominant and mutually exclusive oncogenic mutations in RET and RAS. J Clin Endocrinol Metab, 98(2):E364-9.
4. Roman S, Lin R, Sosa JA (2006). Prognosis of medullary thyroid carcinoma: demographic, clinical, and pathologic predictors of survival in 1252 cases.Cancer, 107(9):2134-42.
5. Campbell MJ, Seib CD, Gosnell J (2013). Vandetanib and the management of advanced medullary thyroid cancer. Curr Opin Oncol, 25(1):39-43.
6. Kloos RT, Eng C, Evans DB, et al (2009). Medullary thyroid cancer: management guidelines of the American Thyroid Association.Thyroid, 19(6):565-612.
7. Scollo C, Baudin E, Travagli J-P, et al (2003). Rationale for central and bilateral lymph node dissection in sporadic and hereditary medullary thyroid cancer. J Clin Endocrinol Metab, 88(5):2070-5.
8. Ferlito A, Shaha AR, Silver CE, et al (2001). Incidence and sites of distant metastases from head and neck cancer. ORL J Otorhinolaryngol Relat Spec, 63(4):202-7.
9. Hutschenreuther A, Birkenmeier G, Bigl M, et al (2013). Glycerophosphoglycerol, beta-alanine, and pantothenic acid as metabolic companions of glycolytic activity and cell migration in breast cancer cell lines.Metabolites, 3(4):1084-101.
10. Slyshenkov VS, Rakowska M, Moiseenok AG, et al (1995). Pantothenic acid and its derivatives protect Ehrlich ascites tumor cells against lipid peroxidation. Free Radic Biol Med, 19(6):767-72.
11. Botros L, Sakkas D, Seli E (2008). Metabolomics and its application for non-invasive embryo assessment in IVF. Mol Hum Reprod, 14(12):679-90.
12. Williams R, Lenz E, Lowden J, et al (2005). The metabonomics of aging and development in the rat: an investigation into the effect of age on the profile of endogenous metabolites in the urine of male rats using 1H NMR and HPLC-TOF MS. Mol Biosyst, 1(2):166-75.
13. Manish Kumar G, Dev Bukhsh S, Rath S, et al (2012). Metabolic modeling and simulation analysis of thyroid disorder pathway.J Comput Sci Syst Biol, 5:052-61.
14. Deidda M, Piras C, Dessalvi CC, et al (2017). Distinctive metabolomic fingerprint in scleroderma patients with pulmonary arterial hypertension.Int J Cardiol, 241:401-6.
15. Fanos V, Cristina Pintus M, Lussu M, et al (2014). Urinary metabolomics of bronchopulmonary dysplasia (BPD): preliminary data at birth suggest it is a congenital disease. J Matern Fetal Neonatal Med, 27 Suppl 2:39-45.
16. Iuculano A, Murgia F, Peddes C, et al (2019). Metabolic characterization of amniotic fluids of fetuses with enlarged nuchal translucency. J Perinat Med, 47(3):311-8.
17. Metere A, Graves CE, Chirico M, et al (2020). Metabolomic reprogramming detected by 1H-NMR spectroscopy in human thyroid cancer tissues. Biology (Basel), 9(6):112.
18. Kweon S-S, Shin M-H, Chung I-J, et al (2013). Thyroid cancer is the most common cancer in women, based on the data from population-based cancer registries, South Korea. Jpn J Clin Oncol, 43(10):1039-46.
19. Yu G-P, Li JC-L, Branovan D, et al (2010). Thyroid cancer incidence and survival in the national cancer institute surveillance, epidemiology, and end results race/ethnicity groups.Thyroid, 20(5):465-73.
20. Shabani N, Razaviyan J, Paryan M, et al (2018). Evaluation of miRNAs expression in medullary thyroid carcinoma tissue samples: miR-34a and miR-144 as promising overexpressed markers in MTC.Hum Pathol, 79:212-221.
21. Lu J, Hu S, Miccoli P, et al (2016). Non-invasive diagnosis of papillary thyroid microcarcinoma: a NMR-based metabolomics approach.Oncotarget, 7(49):81768- 81777.
22. Faubert B, Solmonson A, DeBerardinis RJ (2020). Metabolic reprogramming and cancer progression. Science, 368(6487):eaaw5473.
23. Vettore L, Westbrook RL, Tennant DA (2020). New aspects of amino acid metabolism in cancer. Br J Cancer, 122(2):150-6.
24. Chen L, Li Z, Zhang Q, et al (2017). Silencing of AQP3 induces apoptosis of gastric cancer cells via downregulation of glycerol intake and downstream inhibition of lipogenesis and autophagy. Onco Targets Ther, 10:2791-2804.
25. Yde J, Keely SJ, Moeller HB (2021). Expression, regulation and function of Aquaporin-3 in colonic epithelial cells. Biochim Biophys Acta Biomembr,1863(7):183619.
26. Niu D, Kondo T, Nakazawa T, et al (2012). Differential expression of aquaporins and its diagnostic utility in thyroid cancer. PLoS One, 7(7):e40770.
27. Rastelli M, Cani PD, Knauf C (2019). The gut microbiome influences host endocrine functions. Endocr Rev, 40(5):1271-84.
28. Liu Q, Wang C, Yang W, et al (2009). Effects of isobutyrate on rumen fermentation, lactation performance and plasma characteristics in dairy cows. Anim Feed Sci Technol, 154(1-2):58-67.
29. Chalova P, Tazky A, Skultety L, et al (2023). Determination of short-chain fatty acids as putative biomarkers of cancer diseases by modern analytical strategies and tools: a review. Front Oncol, 13:1110235.
30. Wang T, Sun Z, Wang Y, et al (2020). Diagnosis of papillary thyroid carcinoma by 1H NMR spectroscopy-based metabolomic analysis of whole blood. Drug Discov Ther, 14(4):187-196.
| Files | ||
| Issue | Vol 54 No 9 (2025) | |
| Section | Original Article(s) | |
| DOI | https://doi.org/10.18502/ijph.v54i9.19867 | |
| Keywords | ||
| Medullary thyroid cancer Metabolomics Diagnosis Metabolic perturbation | ||
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How to Cite
1.
Saeidi K, Hedayati M, Movahedi M, Daneshpour MS. Metabolomics-Based Diagnosis of Medullary Thyroid Cancer: A Plasma 1H NMR Approach. Iran J Public Health. 2025;54(9):2005-2014.
