Dataset Information

Plasma sample based analysis of gastric cancer progression using targeted metabolomics.

ABSTRACT: Gastric carcinogenesis is a multifactorial process described as a stepwise progression from non-active gastritis (NAG), chronic active gastritis (CAG), precursor lesions of gastric cancer (PLGC) and gastric adenocarcinoma. Gastric cancer (GC) 5-year survival rate is highly dependent upon stage of disease at diagnosis, which is based on endoscopy, biopsy and pathological examinations. Non-invasive GC biomarkers would facilitate its diagnosis at early stages leading to improved GC prognosis. We analyzed plasma samples collected from 80 patients diagnosed with NAG without H. pylori infection (NAG-), CAG with H. pylori infection (CAG+), PLGC and GC. A panel of 208 metabolites including acylcarnitines, amino acids and biogenic amines, sphingolipids, glycerophospholipids, hexoses, and tryptophan and phenylalanine metabolites were quantified using two complementary quantitative approaches: Biocrates AbsoluteIDQ®p180 kit and a LC-MS method designed for the analysis of 29 tryptophan pathway and phenylalanine metabolites. Significantly altered metabolic profiles were found in GC patients that allowing discrimination from NAG-, CAG+ and PLGC patients. Pathway analysis showed significantly altered tryptophan and nitrogen metabolic pathways (FDR P?

SUBMITTER: Lario S

PROVIDER: S-EPMC5736578 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Plasma sample based analysis of gastric cancer progression using targeted metabolomics.

Lario Sergio S Ramírez-Lázaro Maria José MJ Sanjuan-Herráez Daniel D Brunet-Vega Anna A Pericay Carles C Gombau Lourdes L Junquera Félix F Quintás Guillermo G Calvet Xavier X

Scientific reports 20171219 1

Gastric carcinogenesis is a multifactorial process described as a stepwise progression from non-active gastritis (NAG), chronic active gastritis (CAG), precursor lesions of gastric cancer (PLGC) and gastric adenocarcinoma. Gastric cancer (GC) 5-year survival rate is highly dependent upon stage of disease at diagnosis, which is based on endoscopy, biopsy and pathological examinations. Non-invasive GC biomarkers would facilitate its diagnosis at early stages leading to improved GC prognosis. We an ...[more]

PMID: 29259332

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Project description:Rationale: Gastric cancer (GC) is preceded by a stepwise progression of precancerous gastric lesions. Distinguishing individuals with precancerous gastric lesions that have progression potential to GC is an important need. Perturbated lipid metabolism, particularly the dysregulation of de novo lipogenesis, is involved in gastric carcinogenesis. We conducted the first prospective lipidomics study exploring lipidomic signatures for the risk of gastric lesion progression and early GC. Methods: Our two-stage study of targeted lipidomics enrolled 400 subjects from the National Upper Gastrointestinal Cancer Early Detection Program in China, including 200 subjects of GC and different gastric lesions in the discovery and validation stages. Of validation stage, 152 cases with gastric lesions were prospectively followed for the progression of gastric lesions for a median follow-up of 580 days (interquartile range 390-806 days). We examined the lipidomic signatures associated with the risk of advanced gastric lesions and their progression to GC. Our published tissue proteomic data were referred to further investigate highlighted lipids with their biologically related protein expression in gastric mucosa. Results: We identified 11 plasma lipids significantly inversely associated with the risk of gastric lesion progression and GC occurrence. These lipids were integrated as latent profiles to identify 5 clusters of lipid expression that had distinct risk of gastric lesion progression. The latent profiles significantly improved the ability to predict the progression potential of gastric lesions (AUC: 0.82 vs 0.68, Delong's P = 4.6×10-4) and risk of early GC (AUC: 0.81 vs 0.55, P = 6.3×10-5). Significant associations were found between highlighted lipids, their biologically correlated proteins and the risk of GC, supporting the role of the pathways involving monocarboxylic acid metabolism and lipid transport and catabolic process in GC. Conclusions: Our study revealed the lipidomic signatures associated with the risk of gastric lesion progression and GC occurrence, exhibiting translational implications for GC prevention.

Dataset Information

Plasma sample based analysis of gastric cancer progression using targeted metabolomics.

Publications

Plasma sample based analysis of gastric cancer progression using targeted metabolomics.

Similar Datasets

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