Early detection of gastric cancer (GC) is critical for improving prognosis, yet conventional biomarkers lack sensitivity and specificity, necessitating non-invasive, high-performance diagnostic tools. This study integrated untargeted metabolomics and machine learning to develop a plasma metabolite panel for GC diagnosis and mechanistic insights. Plasma and tissue samples from two cohorts (nâ=â597) were analyzed using ultra-performance liquid chromatography-mass spectrometry (UPLC-MS). A six-metabolite panel was identified and validated, demonstrating excellent diagnostic performance (area under the curve: 0.947-0.982 in discovery; 0.920-0.951 in validation) and superior sensitivity (0.900-0.940) compared to conventional markers (0.020-0.240). Isovalerylcarnitine (C5), a key component, was consistently downregulated in both plasma and tissue samples. Mendelian randomization supported a causal relationship between isovalerylcarnitine (C5) and GC risk. Proteomic analyses revealed inverse correlations between C5 and cadherin/MMP family proteins. Functional assays confirmed that isovalerylcarnitine (C5) inhibited GC cell migration and invasion via calpain-mediated cleavage of VE-cadherin and MMP2. This study identifies a robust diagnostic metabolite panel for GC detection and highlights a novel mechanistic role of isovalerylcarnitine (C5) in GC progression, supporting its utility as both a biomarker and therapeutic target.
Metabolic signatures for gastric cancer diagnosis and mechanistic insights: a multicenter study.
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作者:Zhu Juan, Huang Yida, Li Xue, Liu Bin, Yuan Li, Wang Le, Qian Kun, Mao Yingying, Xu Yongjie, Du Lingbin, Cheng Xiangdong
| 期刊: | EMBO Molecular Medicine | 影响因子: | 8.300 |
| 时间: | 2025 | 起止号: | 2025 Dec;17(12):3355-3376 |
| doi: | 10.1038/s44321-025-00325-0 | ||
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