Metabolic changes associated with papillary thyroid carcinoma: A nuclear magnetic resonance-based metabolomics study

Li,Yanyun; Chen,Minjian; Liu,Cuiping; Xia,Yankai; Xu,Bo; Hu,Yanhui; Chen,Ting; Shen,Meiping; Tang,Wei

doi:10.3892/ijmm.2018.3494

Metabolic changes associated with papillary thyroid carcinoma: A nuclear magnetic resonance-based metabolomics study

Authors:
- Yanyun Li
- Minjian Chen
- Cuiping Liu
- Yankai Xia
- Bo Xu
- Yanhui Hu
- Ting Chen
- Meiping Shen
- Wei Tang
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Affiliations: Department of Endocrinology, Jiangyin People's Hospital, School of Medicine, Southeast University, Jiangyin, Jiangsu 214400, P.R. China, State Key Laboratory of Reproductive Medicine, Institute of Toxicology, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, P.R. China, Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210036, P.R. China, Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, P.R. China, Department of Science and Education Section, Maternity and Child Care Hospital of Nanjing, Nanjing, Jiangsu 210004, P.R. China
Published online on: February 16, 2018 https://doi.org/10.3892/ijmm.2018.3494
Pages: 3006-3014

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Abstract

Papillary thyroid carcinoma (PTC) is the most common thyroid cancer. Nuclear magnetic resonance (NMR)‑based metabolomic technique is the gold standard in metabolite structural elucidation, and can provide different coverage of information compared with other metabolomic techniques. Here, we firstly conducted NMR based metabolomics study regarding detailed metabolic changes especially metabolic pathway changes related to PTC pathogenesis. 1H NMR-based metabolomic technique was adopted in conjunction with multivariate analysis to analyze matched tumor and normal thyroid tissues obtained from 16 patients. The results were further annotated with Kyoto Encyclopedia of Genes and Genomes (KEGG), and Human Metabolome Database, and then were analyzed using modules of pathway analysis and enrichment analysis of MetaboAnalyst 3.0. Based on the analytical techniques, we established the models of principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and orthogonal partial least-squares discriminant analysis (OPLS‑DA) which could discriminate PTC from normal thyroid tissue, and found 15 robust differentiated metabolites from two OPLS-DA models. We identified 8 KEGG pathways and 3 pathways of small molecular pathway database which were significantly related to PTC by using pathway analysis and enrichment analysis, respectively, through which we identified metabolisms related to PTC including branched chain amino acid metabolism (leucine and valine), other amino acid metabolism (glycine and taurine), glycolysis (lactate), tricarboxylic acid cycle (citrate), choline metabolism (choline, ethanolamine and glycerolphosphocholine) and lipid metabolism (very-low‑density lipoprotein and low-density lipoprotein). In conclusion, the PTC was characterized with increased glycolysis and inhibited tricarboxylic acid cycle, increased oncogenic amino acids as well as abnormal choline and lipid metabolism. The findings in this study provide new insights into detailed metabolic changes of PTC, and hold great potential in the treatment of PTC.

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