Application of metabolomics in prediction of lymph node metastasis in papillary thyroid carcinoma.

PURPOSE:The aim of this study was to find useful metabolites to predict lymph node (LN) metastasis in patients with papillary thyroid cancer (PTC) through a metabolomics approach and investigate the potential role of metabolites as a novel prognostic marker. MATERIALS AND METHODS:Fifty-two consecuti...

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Main Authors: Ji Won Seo, Kyunghwa Han, Jandee Lee, Eun-Kyung Kim, Hee Jung Moon, Jung Hyun Yoon, Vivian Youngjean Park, Hyeon-Man Baek, Jin Young Kwak
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2018-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5839571?pdf=render
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spelling doaj-1483016a83b0428fa0c19f7848718d5f2020-11-24T22:06:49ZengPublic Library of Science (PLoS)PLoS ONE1932-62032018-01-01133e019388310.1371/journal.pone.0193883Application of metabolomics in prediction of lymph node metastasis in papillary thyroid carcinoma.Ji Won SeoKyunghwa HanJandee LeeEun-Kyung KimHee Jung MoonJung Hyun YoonVivian Youngjean ParkHyeon-Man BaekJin Young KwakPURPOSE:The aim of this study was to find useful metabolites to predict lymph node (LN) metastasis in patients with papillary thyroid cancer (PTC) through a metabolomics approach and investigate the potential role of metabolites as a novel prognostic marker. MATERIALS AND METHODS:Fifty-two consecutive patients (median age: 41.5 years, range 15-74 years) were enrolled who underwent total thyroidectomy and central LN dissection with or without lateral LN dissection in Severance Hospital between October 2013 and July 2015. The study specimens were provided by the Severance Hospital Gene Bank, and consisted of PTC from each patient. The specimens were prepared for proton nuclear magnetic resonance (1H-NMR) spectroscopy. Spectral data by 1H-NMR spectroscopy were acquired, processed, and analyzed. Patients were grouped in three ways, according to the presence of LN metastasis, central LN metastasis and lateral LN metastasis. Chi-square test and the student t-test were used to analyze categorical variables and continuous variables, respectively. The Mann-Whitney U test was used for univariate analysis of metabolites. Orthogonal projections to latent structure discriminant analysis (OPLS-DA) was used for multivariate analysis to discriminate metabolic differences between the two groups. RESULTS:Among 52 patients, 32 had central LN metastasis and 19 had lateral LN metastasis. No clinical or histopathological characteristic was significantly different for all comparisons. On univariate analysis, no metabolite showed significant difference for all comparisons. On multivariate analysis, OPLS-DA did not discriminate the presence and absence of LN metastasis. Lactate was found to be the most promising metabolite. CONCLUSIONS:No metabolite could discriminate the presence of LN metastasis. However, lactate was found to be the most promising metabolite for discrimination. Further studies with larger sample sizes are needed to elucidate significant metabolites which can indicate the presence of LN metastasis in patients with PTC.http://europepmc.org/articles/PMC5839571?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Ji Won Seo
Kyunghwa Han
Jandee Lee
Eun-Kyung Kim
Hee Jung Moon
Jung Hyun Yoon
Vivian Youngjean Park
Hyeon-Man Baek
Jin Young Kwak
spellingShingle Ji Won Seo
Kyunghwa Han
Jandee Lee
Eun-Kyung Kim
Hee Jung Moon
Jung Hyun Yoon
Vivian Youngjean Park
Hyeon-Man Baek
Jin Young Kwak
Application of metabolomics in prediction of lymph node metastasis in papillary thyroid carcinoma.
PLoS ONE
author_facet Ji Won Seo
Kyunghwa Han
Jandee Lee
Eun-Kyung Kim
Hee Jung Moon
Jung Hyun Yoon
Vivian Youngjean Park
Hyeon-Man Baek
Jin Young Kwak
author_sort Ji Won Seo
title Application of metabolomics in prediction of lymph node metastasis in papillary thyroid carcinoma.
title_short Application of metabolomics in prediction of lymph node metastasis in papillary thyroid carcinoma.
title_full Application of metabolomics in prediction of lymph node metastasis in papillary thyroid carcinoma.
title_fullStr Application of metabolomics in prediction of lymph node metastasis in papillary thyroid carcinoma.
title_full_unstemmed Application of metabolomics in prediction of lymph node metastasis in papillary thyroid carcinoma.
title_sort application of metabolomics in prediction of lymph node metastasis in papillary thyroid carcinoma.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2018-01-01
description PURPOSE:The aim of this study was to find useful metabolites to predict lymph node (LN) metastasis in patients with papillary thyroid cancer (PTC) through a metabolomics approach and investigate the potential role of metabolites as a novel prognostic marker. MATERIALS AND METHODS:Fifty-two consecutive patients (median age: 41.5 years, range 15-74 years) were enrolled who underwent total thyroidectomy and central LN dissection with or without lateral LN dissection in Severance Hospital between October 2013 and July 2015. The study specimens were provided by the Severance Hospital Gene Bank, and consisted of PTC from each patient. The specimens were prepared for proton nuclear magnetic resonance (1H-NMR) spectroscopy. Spectral data by 1H-NMR spectroscopy were acquired, processed, and analyzed. Patients were grouped in three ways, according to the presence of LN metastasis, central LN metastasis and lateral LN metastasis. Chi-square test and the student t-test were used to analyze categorical variables and continuous variables, respectively. The Mann-Whitney U test was used for univariate analysis of metabolites. Orthogonal projections to latent structure discriminant analysis (OPLS-DA) was used for multivariate analysis to discriminate metabolic differences between the two groups. RESULTS:Among 52 patients, 32 had central LN metastasis and 19 had lateral LN metastasis. No clinical or histopathological characteristic was significantly different for all comparisons. On univariate analysis, no metabolite showed significant difference for all comparisons. On multivariate analysis, OPLS-DA did not discriminate the presence and absence of LN metastasis. Lactate was found to be the most promising metabolite. CONCLUSIONS:No metabolite could discriminate the presence of LN metastasis. However, lactate was found to be the most promising metabolite for discrimination. Further studies with larger sample sizes are needed to elucidate significant metabolites which can indicate the presence of LN metastasis in patients with PTC.
url http://europepmc.org/articles/PMC5839571?pdf=render
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