Screening for Early Gastric Cancer Using a Noninvasive Urine Metabolomics Approach
Hyuk Nam Kwon, Hyuk Lee, Ji Won Park, Young‐Ho Kim, Sunghyouk Park, Jae J. Kim · 2020 · 49 citationsRead the paper
The early detection of gastric cancer (GC) could decrease its incidence and mortality. However, there are currently no accurate noninvasive markers for GC screening. Therefore, we developed a noninvasive diagnostic approach, employing urine nuclear magnetic resonance (NMR) metabolomics, to discover putative metabolic markers associated with GC. Changes in urine metabolite levels during oncogenesis were evaluated using samples from 103 patients with GC and 100 age- and sex-matched healthy controls. Approximately 70% of the patients with GC (n = 69) had stage I GC, with the majority (n = 56) having intramucosal cancer. A multivariate statistical analysis of the urine NMR data well discriminated between the patient and control groups and revealed nine metabolites, including alanine, citrate, creatine, creatinine, glycerol, hippurate, phenylalanine, taurine, and 3-hydroxybutyrate, that contributed to the difference. A diagnostic performance test with a separate validation set exhibited a sensitivity and specificity of more than 90%, even with the intramucosal cancer samples only. In conclusion, the NMR-based urine metabolomics approach may have potential as a convenient screening method for the early detection of GC and may facilitate consequent endoscopic examination through risk stratification.
What the full text shows
Working prototype- The NMR-based urine metabolomics model discriminated between GC patients and healthy controls with high accuracy. — 94.1% sensitivity and 93.9% specificity (Validation set of 34 cancer and 33 healthy control samples)
- The model maintained high performance when restricted to the earliest stage of gastric cancer. — 94.7% sensitivity and 97% specificity (Stage IA samples only)
- Nine metabolites were identified as contributors to the difference between groups. — '' (Multivariate statistical analysis of urine NMR data)
- The metabolomics approach outperformed conventional serum tumor markers (CEA, CA19-9, CA72-4). — Significantly better sensitivity (Same patient cohort)
- Opposite trends were observed for creatine and creatinine levels between groups. — '' (Normal controls vs. GC patients)
- Setup
- 103 patients with gastric cancer (69 stage I, including 56 intramucosal) and 100 age- and sex-matched healthy controls.
- How
- Urine samples were analyzed using 500-MHz 1H NMR spectroscopy and processed via OPLS-DA and PLS-DA multivariate statistical models. A separate validation set (one-third of samples) was used to test the prediction model, and MetScape was used to correlate metabolites with microarray gene expression data.
- Limitations
- Could not establish a firm mechanistic link between metabolite changes and GC. · Could not identify a single marker metabolite that explained the difference. · Correlations of individual metabolites with group differences were relatively small.
Summarized by Gemma 4 from the open-access full text · 16 Oct 2026. Read it