Systematic review of current evidence on metabolites associated with gastric cancer
A partir d'une revue systématique de la littérature publiée entre 2004 et 2025 (52 études), cette étude examine l'association entre des métabolites et le cancer de l'estomac
Background : Gastric cancer (GC) is often diagnosed at advanced stages, contributing to poor prognosis. Circulating metabolites have emerged as potential biomarkers for GC risk stratification or early detection. We conducted a systematic review of studies investigating the association between metabolites and GC, including both precancerous and cancerous gastric lesions.
Methods : We comprehensively searched PubMed, Embase, and Web of Science for articles published from 2004 to 2025. Eligible studies assessed endogenous metabolites using mass spectrometry- or nuclear magnetic resonance-based platforms in relation to precancerous gastric lesions, GC or GC subtypes. Data were extracted on study design, biospecimen type, analytical approaches, Helicobacter pylori infection, identified metabolites, and model performance.
Results : A total of 52 studies were included, comprising 12 case-only, 31 case-control, five nested case-control, and four cohort studies. Across studies, metabolites reported to differ between GC and non-GC groups and across stages of gastric lesion progression were primarily involved in metabolism of glucose, lipids, amino acids, nucleic acids, and vitamins. Several studies evaluated metabolite-based classification or prediction models, reporting a wide range of performance metrics for distinguishing GC from non-GC conditions and for classifying disease stages. Considerable heterogeneity was observed across studies, limiting direct comparability of findings.
Conclusions : Previous studies have reported associations between metabolites and GC, as well as progression of precancerous lesions, providing insights into gastric carcinogenesis. However, substantial heterogeneity across studies highlights the need for standardized methodological approaches and adjustment for key confounders followed by independent validation and replication in large, well-designed, multi-population studies.
Journal of the National Cancer Institute , résumé, 2026