(1)H-NMR urinary metabolomic profiling for diagnosis of gastric cancer.

ABSTRACT

BACKGROUND: Metabolomics has shown promise in gastric cancer (GC) detection. This research sought to identify whether GC has a unique urinary metabolomic profile compared with benign gastric disease (BN) and healthy (HE) patients. METHODS: Urine from 43 GC, 40 BN, and 40 matched HE patients was analysed using (1)H nuclear magnetic resonance ((1)H-NMR) spectroscopy, generating 77 reproducible metabolites (QC-RSD <25%). Univariate and multivariate (MVA) statistics were employed. A parsimonious biomarker profile of GC vs HE was investigated using LASSO regularised logistic regression (LASSO-LR). Model performance was assessed using Receiver Operating Characteristic (ROC) curves. RESULTS: GC displayed a clear discriminatory biomarker profile; the BN profile overlapped with GC and HE. LASSO-LR identified three discriminatory metabolites 2-hydroxyisobutyrate, 3-indoxylsulfate, and alanine, which produced a discriminatory model with an area under the ROC of 0.95. CONCLUSIONS: GC patients have a distinct urinary metabolite profile. This study shows clinical potential for metabolic profiling for early GC diagnosis.