Plasma metabolome identifies potential biomarkers of gastric precancerous lesions and gastric cancer risk.

Metabolomics

Department of Nutrition and Food Hygiene, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China.

Published: August 2023

AI Article Synopsis

  • There is a lack of practical metabolic biomarkers for diagnosing gastric cancer (GC) and gastric precancerous lesions (GPL), prompting research into patients' plasma metabolic profiles.
  • A targeted analysis of plasma samples from patients with non-atrophic gastritis, GPL, and GC revealed distinct metabolic profiles, with specific metabolites showing significant elevation in GPL and GC groups compared to controls.
  • The study identified 9 metabolites as potential biomarkers for detecting high-risk individuals for GPL and GC, with Trimethylamine N-oxide demonstrating particularly strong diagnostic performance, especially when paired with Rhamnose.

Article Abstract

Objectives: Currently, metabolic biomarkers with great practicability of gastric cancer (GC) and gastric precancerous lesions (GPL) are scarce. Thus, we are devoted to determining the plasma metabolic profiles of patients with GPL or GC and validate candidate biomarkers for disease diagnosis.

Methods: In this hospital-based case-control study, 68 plasma samples from 27 non-atrophic gastritis (NAG, control), 31 GPL, and 10 GC patients were collected for targeted metabolomics analysis. Univariate and multivariate analyses were used for selecting the differential metabolites. A receiver operating characteristic curve combined with binary logistic regression analysis was performed to test the diagnostic performance of the differential metabolites. Dietary data were obtained using a semiquantitative food frequency questionnaire.

Results: Distinct metabolomic profiles were noted for NAG, GPL, and GC. Compared to the NAG patients, the levels of 5 metabolites in the GPL group and 4 metabolites in the GC group were found to significantly elevate. Compared with the model involving 9 traditional risk factors (AUC: 0.89, 95%CI: 0.78-1.00), Trimethylamine N-oxide, the most significant metabolite (P = 2.00 × 10, FDR = 0.003, FC > 2, VIP > 2), showed a good diagnostic performance for the patients with GC (AUC: 0.90, 95%CI: 0.78-1.00), and its diagnostic performance has been further improved with the integration of Rhamnose (AUC: 0.96, 95%CI: 0.89-1.00).

Conclusion: In our study, 9 defined metabolites might serve as meaningful biomarkers for identifying the high-risk population of GPL and GC, possibly enhancing the prevention and control of GPL and GC.

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Source
http://dx.doi.org/10.1007/s11306-023-02037-3DOI Listing

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