Basic Study
Copyright ©The Author(s) 2019. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Jul 7, 2019; 25(25): 3218-3230
Published online Jul 7, 2019. doi: 10.3748/wjg.v25.i25.3218
Nuclear magnetic resonance-based metabolomics and metabolic pathway networks from patient-matched esophageal carcinoma, adjacent noncancerous tissues and urine
Jia-Hao Liang, Yan Lin, Ting Ouyang, Wan Tang, Yao Huang, Wei Ye, Jia-Yun Zhao, Zhe-Ning Wang, Chang-Chun Ma
Jia-Hao Liang, Yan Lin, Ting Ouyang, Wan Tang, Yao Huang, Wei Ye, Jia-Yun Zhao, Zhe-Ning Wang, Department of Radiology, Second Affiliated Hospital, Shantou University Medical College, Shantou 515041, Guangdong Province, China
Chang-Chun Ma, Department of Radiation Oncology, Affiliated Tumor Hospital, Shantou University Medical College, Shantou 515041, Guangdong Province, China
Author contributions: Lin Y conceived and designed the experiments; Liang JH and Lin Y contributed to NMR data acquisition; Liang JH, Ouyang T, Tang W and Huang Y analyzed the data; Lin Y wrote the paper; Ye W, Zhao JY and Wang ZN contributed to sample preparation; all authors approved the final version of the manuscript for publication.
Supported by the National Natural Science Foundation of China, No. 81471729 and No. 81101102; the Science and Technology and Planning Project of Guangdong Province, No. 2016A020216025; the Research Award Fund for Outstanding Young Teachers in Higher Education Institutions, Guangdong Province, No. YQ2015245; the National Natural Science Foundation of Guangdong Province, No. S2011010004973; the Department of Education of Guangdong Province, No. 2017KTSCX071.
Institutional review board statement: This study was reviewed and approved by the Second Affiliated Hospital, Shantou University Medical College Review Board (2018-44).
Informed consent statement: Informed consent was obtained from each subject prior to participation in this study.
Conflict-of-interest statement: The authors declare that they have no competing interests related to this study.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Yan Lin, PhD, Chief Doctor, Department of Radiology, Second Affiliated Hospital, Shantou University Medical College, No. 69. Dongshabei Road, Shantou 515041, Guangdong Province, China. 994809889@qq.com
Telephone: +86-13502958156
Received: January 25, 2019
Peer-review started: January 25, 2019
First decision: February 26, 2019
Revised: May 13, 2019
Accepted: May 31, 2019
Article in press: June 1, 2019
Published online: July 7, 2019
ARTICLE HIGHLIGHTS
Research background

A large number of studies have revealed changes of urinary metabolites between esophageal cancer (EC) and healthy controls (HCs), and some studies have demonstrated a correlation between EC and perturbed urinary metabolomic profiles.

Research motivation

However, none of the previous studies has described the correlation between urine metabolite profiles and those of the tumor and adjacent colonic mucosa in the same patient. Our study revealed a significant number of altered metabolites and metabolic pathway networks in EC patient urine and tumor tissues compared with HCs.

Research objectives

Our work is the first parallel investigation of esophageal tumor tissues and adjacent normal mucosal tissues alongside patient-matched urine samples to investigate how urinary metabolic phenotypes were linked to changes in the biochemical landscape of esophageal tumors.

Research methods

All samples were detected by a Bruker AVII 400 MHz nuclear magnetic resonance spectrometer, and all spectral data were applied to pattern recognition analysis and cross-validation by SIMCA-P software. Then, statistical significance was assessed using the Mann-Whitney U test and receiver operating characteristic analysis to calculate biomarker metabolites. Finally, we employed Pearson Correlation Analysis to assess the associations of biomarker candidates between urine and tumor tissues of EC patients.

Research results

Our study revealed metabolite changes that overlapped across both metrics, including glucose, glutamate, citrate, glycine, creatinine and taurine, indicating the networks for metabolic pathway perturbations in EC. Additionally, changes in most urinary biomarkers were correlated with changes in biomarker candidates in EC tissues.

Research conclusions

Our research is the first parallel investigation to investigate how urinary metabolic phenotypes were linked to the changes in the biochemical landscape of esophageal tumors. Our study showed significant metabolic alterations in both urine and tumor tissues of EC patients compared to their respective HCs. Our research revealed a few distinct and overlapping discri-minatory metabolites, suggesting that EC is associated with the following dysregulated metabolic pathway perturbations. Furthermore, the metabolic profiling correlations between esophageal tissues and urine showed that most urine potential biomarkers were correlated with most of the discriminating metabolites in EC tissues, indicating that changes in the urine metabolic signature could reflect reprogramming of metabolic pathways in tumor tissue, high-lighting the significance of the distinct urinary metabolic profiles as potential novel and noni-nvasive indicators for EC detection.

Research perspectives

With experiences in our study, we realized that many metabolites have associations in samples of cancer patients. In our same group, we are now investigating the serum samples of EC pa-tients to see whether the same pattern of serum levels of amino acids can be found in EC patients.