Case Control Study
Copyright ©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Oncol. Jul 24, 2025; 16(7): 108967
Published online Jul 24, 2025. doi: 10.5306/wjco.v16.i7.108967
Untargeted metabolomics analysis of serum metabolic signatures as novel biomarkers for gastric carcinoma
Le Ren, Jun Liu, Ya-Yun Xu, Zhen-Wang Shi
Le Ren, Zhen-Wang Shi, Department of Gastroenterology, The Second People’s Hospital of Hefei, Hefei 230011, Anhui Province, China
Jun Liu, Department of Ophthalmology, The Third People’s Hospital of Hefei, Hefei 230011, Anhui Province, China
Ya-Yun Xu, Department of Pharmacy, Hefei Fourth People’s Hospital, Hefei 2300000, Anhui Province, China
Co-first authors: Le Ren and Jun Liu.
Author contributions: Ren L, Liu J, Xu YY, and Shi ZW were involved in the conception and design of the study; Ren L and Liu J they contributed equally to this article, they are the co-first authors of this manuscript; Ren L and Xu YY constructed a draft of the manuscript; Shi ZW has provided relevant feedback and critical revisions of the manuscript; and all authors read and approved the final manuscript.
Institutional review board statement: This study was approved by the Medical Ethics Committee of The Second People’s Hospital of Hefei, approval No. 2023-keyan-123.
Informed consent statement: All participants in the study provided informed written consent prior to their involvement.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
STROBE statement: The authors have read the STROBE Statement-checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
Data sharing statement: No additional data are available.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (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: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Zhen-Wang Shi, Professor, Department of Gastroenterology, The Second People’s Hospital of Hefei, Heping Road, Hefei 230011, Anhui Province, China. shiyitao99@163.com
Received: April 27, 2025
Revised: May 14, 2025
Accepted: June 26, 2025
Published online: July 24, 2025
Processing time: 87 Days and 1.3 Hours
Abstract
BACKGROUND

In recent years, metabolomics has emerged as a novel platform for biomarker discovery. However, the metabolic profiles associated with gastric carcinoma (GC) remain insufficiently explored.

AIM

To examine the differences in metabolites between patients with GC and healthy controls, with the objective of identifying potential serum biomarkers for GC diagnosis through a non-targeted metabolomics approach.

METHODS

An untargeted metabolic analysis was conducted on serum samples from 6 patients with GC and 6 healthy controls. Subsequently, the differential metabolites identified were further validated in serum samples from an expanded cohort of 50 patients with GC and 50 healthy controls. The discriminative capacity of differential metabolites in distinguishing patients with GC from healthy controls was assessed utilizing the receiver operating characteristic curve analysis. The association between the serum levels of differential metabolites and the disease severity, as determined by the tumor-node-metastasis staging system, was evaluated using Spearman’s rank correlation coefficient.

RESULTS

Our findings revealed a significant alteration in the metabolic profile, characterized by 111 up-regulated and 55 down-regulated metabolites in patients with GC compared to healthy controls. Among the top 10 up-regulated metabolites, the serum concentrations of eight metabolites including fenpiclonil, methyclothiazide, 5-hydroxyindoleacetate, 3-pyridinecarboxylic acid, guanabenz, 2,2-dichloro-N-(3-chloro-1,4-dioxo-2-naphthyl) acetamide, epigallocatechin gallate, and dimethenamid, were further validated to be significantly elevated in a cohort of 50 patients diagnosed with GC compared to 50 healthy control subjects (P < 0.001). With the exception of 3-pyridinecarboxylic acid, the area under the curve values for the remaining seven metabolites exceeded 0.7, suggesting that these metabolites possess substantial diagnostic potential for distinguishing patients with GC from healthy individuals. Additionally, the serum concentrations of methyclothiazide (r = 0.615, P < 0.001), epigallocatechin gallate (r = 0.482, P = 0.004), and dimethenamid (r = 0.634, P < 0.001) demonstrated a significant positive correlation with the T stage in patients with GC. The serum concentrations of methyclothiazide (r = 0.438, P = 0.008) and epigallocatechin gallate (r = 0.383, P = 0.023) exhibited a significant positive correlation with the N stage in these patients.

CONCLUSION

This study provides insights into the metabolic alterations associated with GC, and the identification of these biomarkers may enhance the clinical detection and management of the disease.

Keywords: Gastric carcinoma; Untargeted metabolomics; Serum; Biomarker; Diagnosis

Core Tip: We applied untargeted metabolomics to explore serum metabolic profile changes to identify potential serum biomarkers for the diagnosis of gastric carcinoma (GC). Firstly, a substantial alteration in the metabolic profile was observed. Secondly, the serum concentrations of eight metabolites were significantly elevated in 50 GC patients compared to 50 healthy controls. Thirdly, the area under the curve values for eight metabolites exceeded 0.7, indicating their effectiveness in distinguishing GC patients. Fourthly, the serum concentrations of methyclothiazide and epigallocatechin gallate demonstrated a positive correlation with T and N stage, while the serum concentrations of dimethenamid showed a positive correlation with T stage in GC patients.