Published online Jul 7, 2019. doi: 10.3748/wjg.v25.i25.3218
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
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.
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.
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.
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.
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.
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.
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.