Untargeted metabolomics profiles delineate metabolic alterations in mouse plasma during lung carcinoma development using UPLC-QTOF/MS in MSE mode. Issue 9 (19th September 2018)

• Record Type: Journal Article
• Authors: Wu, Huan; Chen, Yang; Li, Zegeng; Liu, Xianhua
• Is Part Of: Royal Society open science. Volume 5:Issue 9(2018)
• Publication Date: 2018-09-19
• Subjects: untargeted metabolomics -- lung carcinoma -- UPLC-QTOF-MS -- multivariate data analysis -- receiver operating characteristic curve; Science -- Periodicals; 500
• DOI: 10.1098/rsos.181143
• Languages: English
• ISSNs: 2054-5703

Abstract

Abstract : In this work, an untargeted metabolomic method based on ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) in MS E (E represents collision energy) mode was exploited to determine the dynamic metabolic alterations in the plasma of male C57BL/6 mice during the onset and development of lung carcinoma. Plasma samples were collected from control and model mice (male C57BL/6 mice experimentally inoculated with the Lewis lung carcinoma cells) at 7 and 14 days post-inoculation (DPI). As a result, 15 dysregulated metabolites, including cholesterol sulphate, tiglylcarnitine, 1-palmitoylglycerophosphoinositol, 2-stearoylglycerophosphoinositol, stearoylcarnitine, PC(20:2(11Z, 14Z)/16:0), PC(22:4(7Z, 10Z, 13Z, 16Z)/14:0), PC(22:5(7Z, 10Z, 13Z, 16Z, 19Z)/14:0), PC(22:6(4Z, 7Z, 10Z, 13Z, 16Z, 19Z)/16:0), 12, 20-Dioxo-leukotriene B4, sphingosine 1-phosphate(d19:1-P), sphingomyelin(d18:0/16:1(9Z)), lysoPC(16:0), lysoPC(18:0) and lysoPC(20:4(5Z, 8Z, 11Z, 14Z)), were identified in the plasma of model mice with xenografts at both 7 and 14 DPI. All the altered metabolites associated with the onset and development of lung carcinoma were involved in the metabolism of glycerophospholipid, fatty acid, sphingolipid and arachidonic acid. The feasible utility of these endogenous biomarkers as potential diagnostic indicators was validated through receiver operating characteristic curve analysis. Collectively, these findings provide a systematic view of metabolic changes linked to the onset and development of lung carcinoma.