MetaboLights

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molecular weights and secondary mass spectrometry information were used, in conjunction with the databases mzCloud (THERMO Fisher Scientific), mzVault (THERMO Fisher Scientific, and ChemSpider (www.chemspider.com), and the Human Metabolome Database (Human Metabolome Database (hmdb.ca)), to identify the structures associated with characteristic peaks.MetaboLightsPublicLiquid Chromatography MS - positive - hilicLiquid Chromatography MS - negative - hilicA Phenomenex HILIC chromatographic column (2.6 μm, 3.0 mm internal diameter x 100 mm) was employed, using acetonitrile as mobile phase A. In positive mode, mobile phase B consisted of a solution of 10 mM ammonium acetate in 0.1% formic acid, and in negative mode, mobile phase B was a solution of 10 mM ammonium acetate. The gradient elution was performed as follows: 0? min 2% B, 1?6 min 2%?0% B, 16?8 min 50% B, 18?8.5 min 50%?% B, 18.5?1 min 2% B. The column temperature was 40 °C and the flow rate was 0.4 mL/min.Metabolomic biomarkers discovery across chronic gastritis to gastric cancer progression. 10.1038/s41598-025-19005-7. PMID:41023363Hebei Medical UniversityLe Yangblood plasmamass spectrometry assaySerum samples collected from the Control, CNAG, CAG and GC groups were pooled in equal volumes to prepare quality control (QC) samples. In total 100-μL samples of serum were aspirated, mixed with 300-μL acetonitrile, vigorously vortexed for 1 min, then centrifuged at 14,000 rpm for 10 min at 4 °C. A 100-μL aliquot of each supernatant was transferred to an injection vial, and 3-μL volumes were analyzed.Homo sapienshttps://www.ebi.ac.uk/metabolights/MTBLS12186Yang Le. Hebei medical university. Hebei medical university. yangle@stu.hebmu.edu.cn.Compound Discoverer 3.2.0.421 software (THERMO Fisher Scientific) was used to process the data collected during the non-targeted metabolomic study.Genderyangle@stu.hebmu.edu.cnSerum samples were collected from the participants as part of a National Administration of Traditional Chinese Medicine Science and Technology Project. Metabolomicsgastric canceruntargeted metabolitestargeted metabolitesgastric canceruntargeted metabolitestargeted metabolitesFor MS, we used an electrospray ionization source (ESI) with a spray voltage of 3.5 kV / 3.2 kV (+/-, an ion source temperature of 350 °C and a capillary temperature of 320 °C The sheath gas flow rate was 40 arb and the auxiliary gas flow rate was 10 arb. Scanning was conducted separately for positive and negative ions using full scan/ddMS2 mode, covering a mass range of 100-1000 m/z. The scan resolution of the primary mass spectrum (MS1) and the secondary mass spectrum (MS2) were 70,000 FWHM and 17,500 FWHM, respectively. The collision energies for the secondary scan were set at 20, 40 and 60 eV, with an S-lens value of 60.Gastric cancer (GC) is a severe malignancy characterized by late diagnosis, poor prognosis, and low survival rates. Its progression is often linked to chronic non-atrophic gastritis (CNAG) and chronic atrophic gastritis (CAG), which show atypical symptoms. Identifying biomarkers for CNAG, CAG, and GC progression is crucial for earlier diagnosis and prevention. This study conducted non-targeted metabolomics on 81 clinical samples (17 controls; 23, 23, and 18 from CNAG, CAG, and GC patients, respectively) using ultra-high-performance Liquid chromatography and high-resolution mass spectrometry. A total of 763 metabolites were identified, of which eight metabolic pathways were in dysregulation at different disease stages. Disease progression showed pronounced disruptions in amino acid, Lipid, and microbial metabolism. Targeted metabolomics identified 56 metabolites, with significant differences in O-(4,8-dimethylnonanoyl) carnitine and dehydroepiandrosterone sulfate (DHEAS). DHEAS and L-threonic acid (L-TA) were validated as biomarkers, with detection methods developed and applied to confirm their clinical significance. These findings enhance understanding of CNAG, CAG, and GC progression and provide validated biomarkers for potential clinical application in GC diagnosis and treatment.Metabolomic biomarkers discovery across chronic gastritis to gastric cancer progression.Yang Le L, Wang Jie J, Li Peng P, Guo Yuxi Y, Li Siyuan S, Liu Shuangyu S, Lou Yingying Y, Qi Jinlong J, Yang Qian QfalseIdentification of Biomarkers Using Metabolomics: From Chronic Non-Atrophic Gastritis and Chronic Atrophic Gastritis to Gastric CancerGastric cancer (GC) is a severe malignancy characterized by late diagnosis, poor prognosis and low survival rates. Its progression is often linked to chronic non-atrophic gastritis (CNAG) and chronic atrophic gastritis (CAG), which show atypical symptoms. Identifying biomarkers for CNAG, CAG and GC progression is crucial for earlier diagnosis and prevention. This study conducted non-targeted metabolomics on 81 clinical samples (17 controls; 23, 23 and 18 from CNAG, CAG and GC patients, respectively) using ultra-high-performance liquid chromatography and high-resolution mass spectrometry. 63 metabolites were identified, with 18 consistently dysregulated across disease stages. Disease progression showed pronounced disruptions in amino acid, lipid and microbial metabolism. Targeted metabolomics identified 46 metabolites, with significant differences in O-(4,8-dimethylnonanoyl) carnitine and dehydroepiandrosterone sulfate (DHEAS). DHEAS and L-threonic acid (L-TA) were validated as biomarkers, with detection methods developed and applied to confirm their clinical significance. These findings enhance understanding of CNAG, CAG and GC progression and provide validated biomarkers for potential clinical application in GC diagnosis and treatment.2026-09-292025-01-22MTBLS1218641023363