NMR-based metabolomics to select a surgical method for treating papillary thyroid carcinoma

OBJECTIVE: This study aims to investigate differences in the metabolomic profiles of patients who received different surgeries for papillary thyroid carcinoma (PTC). METHODS: Two surgical methods, i.e., unilateral and total thyroidectomy, were employed according to different disease conditions. Sera from patients who were treated with levothyroxine sodium tablets before and after surgery was analyzed with a Bruker 500 Hz nuclear magnetic resonance (NMR) spectrometer. Data were analyzed via principal component analysis (PCA) and partial least squares discriminate analysis (PLS-DA) with SIMCA-P+ 11.0 software, and metabolites were obtained and compared. The first and second principal components were selected from PCA, PLS-DA, and orthogonal partial least squares discriminate analysis (OPLS-DA). A p-value less than 0.05 was considered statistically significant. RESULTS: There were significant differences in serum metabolomics before and after surgery. Compared with unilateral thyroidectomy, total thyroidectomy reversed some highly increased metabolite levels (e.g., taurine and betaine). More significant variations in abnormal metabolites were noted after total thyroidectomy than after unilateral thyroidectomy (e.g., alanine, choline, hippurate, and formic acid). CONCLUSIONS: The choice of surgical method for PTC patients should be based not only on the tumor condition but also on the potential consequences of metabolic variations. Total thyroidectomy reversed some increased metabolite levels but led to accumulation of some other metabolites due to the loss of thyroid function; thus, metabolic disturbances caused by thyroid hormone deficiency should be prevented in advance.

Bibliographic Details

Main Authors:	Wang,Bo, Zhang,Li-Yong, Wang,Si-Si, Yang,Ying-Hong, Zhao,Wen-Xin
Format:	Digital revista
Language:	English
Published:	Faculdade de Medicina / USP 2018
Online Access:	http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1807-59322018000100283
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