Plasma metabolites analysis of patients with papillary thyroid cancer : A preliminary untargeted 1H NMR-based metabolomics
Copyright © 2024 Elsevier B.V. All rights reserved..
Metabolomics plays a crucial role in identifying molecular biomarkers that can differentiate pathological conditions. In the case of thyroid cancer, it is essential to accurately diagnose malignancy from benignity to avoid unnecessary surgeries. The objective of this research was to apply untargeted NMR-based metabolomics in order to identify metabolic biomarkers that can distinguish between plasma samples of patients with papillary thyroid cancer (PTC) and multinodular goiter (MNG), as well as PTC and healthy individuals. The study included a cohort of 55 patients who were divided into three groups: PTC (n=20), MNG (n=16), and healthy (n=19). Plasma samples were collected from all participants and subjected to 1H NMR spectroscopy. Differential metabolites were identified using chemometric pattern recognition algorithms. The obtained metabolic profile had the potential to differentiate PTC from healthy plasma, but not from MNG. In patients diagnosed with PTC, a total of 18 compounds were discovered, revealing elevated levels of leucine, lysine, and 4-acetamidobutyric acid, while acetate, proline, acetoacetate, 3-hydroxybutyrate, glutamate, pyruvate, cystine, glutathione, asparagine, ethanolamine, histidine, tyrosine, myo-inositol, and glycerol along with a lipid compound were found to be lower in comparison to those of healthy individuals. According to the area under the curve (AUC) of the receiver operating characteristic curve, this particular profile exhibited an impressive capability of 85% to discern PTC from healthy subjects (AUC=0.853, sensitivity=78.95, specificity=84.21). The utilization of the 1H NMR-based metabolomics approach revealed considerable promise in the identification of PTC from healthy plasma specimens. The modifications noticed in the plasma metabolites have the potential to act as practical biomarkers that are non-invasive and could suggest transformations in the metabolic profile of thyroid tumors.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:241 |
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| Enthalten in: |
Journal of pharmaceutical and biomedical analysis - 241(2024) vom: 15. Feb., Seite 115946 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Razavi, S Adeleh [VerfasserIn] |
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| Links: |
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| Themen: |
Biomarkers, Tumor |
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| Anmerkungen: |
Date Completed 21.02.2024 Date Revised 21.02.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.jpba.2023.115946 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 100 | 1 | |a Razavi, S Adeleh |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Plasma metabolites analysis of patients with papillary thyroid cancer |b A preliminary untargeted 1H NMR-based metabolomics |
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| 520 | |a Copyright © 2024 Elsevier B.V. All rights reserved. | ||
| 520 | |a Metabolomics plays a crucial role in identifying molecular biomarkers that can differentiate pathological conditions. In the case of thyroid cancer, it is essential to accurately diagnose malignancy from benignity to avoid unnecessary surgeries. The objective of this research was to apply untargeted NMR-based metabolomics in order to identify metabolic biomarkers that can distinguish between plasma samples of patients with papillary thyroid cancer (PTC) and multinodular goiter (MNG), as well as PTC and healthy individuals. The study included a cohort of 55 patients who were divided into three groups: PTC (n=20), MNG (n=16), and healthy (n=19). Plasma samples were collected from all participants and subjected to 1H NMR spectroscopy. Differential metabolites were identified using chemometric pattern recognition algorithms. The obtained metabolic profile had the potential to differentiate PTC from healthy plasma, but not from MNG. In patients diagnosed with PTC, a total of 18 compounds were discovered, revealing elevated levels of leucine, lysine, and 4-acetamidobutyric acid, while acetate, proline, acetoacetate, 3-hydroxybutyrate, glutamate, pyruvate, cystine, glutathione, asparagine, ethanolamine, histidine, tyrosine, myo-inositol, and glycerol along with a lipid compound were found to be lower in comparison to those of healthy individuals. According to the area under the curve (AUC) of the receiver operating characteristic curve, this particular profile exhibited an impressive capability of 85% to discern PTC from healthy subjects (AUC=0.853, sensitivity=78.95, specificity=84.21). The utilization of the 1H NMR-based metabolomics approach revealed considerable promise in the identification of PTC from healthy plasma specimens. The modifications noticed in the plasma metabolites have the potential to act as practical biomarkers that are non-invasive and could suggest transformations in the metabolic profile of thyroid tumors | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Diagnosis | |
| 650 | 4 | |a Metabolic reprogramming | |
| 650 | 4 | |a Metabolite profiling | |
| 650 | 4 | |a Papillary thyroid carcinoma | |
| 650 | 4 | |a Thyroid neoplasms | |
| 650 | 7 | |a Biomarkers, Tumor |2 NLM | |
| 700 | 1 | |a Mahmanzar, Mohammadamin |e verfasserin |4 aut | |
| 700 | 1 | |a Nobakht M Gh, B Fatemeh |e verfasserin |4 aut | |
| 700 | 1 | |a Zamani, Zahra |e verfasserin |4 aut | |
| 700 | 1 | |a Nasiri, Shirzad |e verfasserin |4 aut | |
| 700 | 1 | |a Hedayati, Mehdi |e verfasserin |4 aut | |
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