Erschienen in:
02.06.2021 | Original Article
Identifying potential metabolic tissue biomarkers for papillary thyroid cancer in different iodine nutrient regions
verfasst von:
Qihao Sun, Hongjian Zhao, Zhiyong Liu, Fengqian Wang, Qian He, Cheng Xiu, Lunhua Guo, Qiushi Tian, Lijun Fan, Ji Sun, Dianjun Sun
Erschienen in:
Endocrine
|
Ausgabe 3/2021
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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.