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Br J Cancer. 2016 Jan 12;114(1):59-62. doi: 10.1038/bjc.2015.414. Epub 2015 Dec 8.

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

Author information

1
Department of Surgery, University of Alberta Hospital, 8440-112 Street, Edmonton, AB T6G 2B7, Canada.
2
Department of Biochemistry, NANUC, University of Alberta, Edmonton, AB T6G 2M8, Canada.
3
Department of Surgery, Royal Alexandra Hospital, 10240 Kingsway Avenue NW, Edmonton, AB T5H 3V9, Canada.
4
Department of Medicine, Division of Gastroenterology, HYS Medical Centre, 310-11010 101 Street NW, Edmonton, AB T5H 4B9, Canada.
5
School of Public Health, 2-040 Li Ka Shing Centre for Health Research Innovation, University of Alberta, Edmonton, AB T6G 2E6, Canada.
6
Department of Oncology, Cross Cancer Institute, 11560 University Avenue, Edmonton, AB T6G 1Z2, Canada.
7
Department of Medicine, 4126A Katz Group Centre for Pharmacy & Health, University of Alberta, Edmonton, AB T6G 2E1, Canada.

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.

PMID:
26645240
PMCID:
PMC4716538
DOI:
10.1038/bjc.2015.414
[Indexed for MEDLINE]
Free PMC Article

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