Document Type

Journal Article

Publisher

Nature Publishing Group

School

School of Science

RAS ID

21055

Funders

Edmonton Civic Employees Charitable Assistance Fund

Alberta Innovates Technology Futures Graduate Student Scholarship

Dr D Schiller Academic Enrichment Fund

Queen Elizabeth II Graduate Scholarship

Canada Research Chair from Government of Canada

Alberta Heritage Foundation for Medical Research (AHFMR)

Population Health Investigator Award from Alberta Innovates Health Solutions (AIHS)

Comments

Chan, A. W., Mercier, P., Schiller, D., Bailey, R., Robbins, S., Eurich, D. T., ... & Broadhurst, D. (2016). 1H-NMR urinary metabolomic profiling for diagnosis of gastric cancer. British journal of cancer, 114(1), 59-62. https://doi.org/10.1038/bjc.2015.414

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 1H nuclear magnetic resonance (1H-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.

DOI

10.1038/bjc.2015.414

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
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