Abstract 281: Plasma metabolomic profiling identifies novel biomarkers for gastric cancer diagnosis and prognosis

Abstract Gastric cancer (GC) remains a significant global health challenge, representing the fifth leading cause of cancer-related mortality. Altered metabolism plays a crucial role in GC development and progression. This study aimed to identify plasma metabolic biomarkers for improved GC diagnosis and prognosis prediction. We performed untargeted metabolomic profiling of plasma samples from 105 GC patients and 120 healthy controls using ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS). Following rigorous quality control, orthogonal partial least squares discriminant analysis (OPLS-DA) identified 562 differentially abundant metabolites between groups. Pathway enrichment analysis revealed significant alterations in metabolic pathways associated with amino acid metabolism, lipid metabolism, and hormone signaling. Machine learning algorithms were employed to develop diagnostic and prognostic models based on these differentially abundant metabolites. A four-metabolite diagnostic model achieved high sensitivity (0.86) and specificity (0.95) in an independent validation cohort, significantly outperforming conventional protein-based diagnostic markers. Furthermore, our prognostic model demonstrated superior performance compared to established clinical parameters, effectively stratifying patients into distinct risk groups for personalized therapeutic strategies. This comprehensive metabolomic analysis provides novel insights into the metabolic landscape of GC and identifies promising biomarkers for improved clinical management. Citation Format: Zun Li, Xiangnan Zhang, Yanxin Yao, Yubei Huang, Zhangyan Lv, Hongji Dai, Kexin Chen, Ben Liu. Plasma metabolomic profiling identifies novel biomarkers for gastric cancer diagnosis and prognosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 281.