Literature DB >> 19720165

Metabonomics study of liver cancer based on ultra performance liquid chromatography coupled to mass spectrometry with HILIC and RPLC separations.

Jing Chen1, Wenzhao Wang, Shen Lv, Peiyuan Yin, Xinjie Zhao, Xin Lu, Fengxia Zhang, Guowang Xu.   

Abstract

In this study, urinary metabolites from liver cancer patients and healthy volunteers were studied by a metabonomic method based on ultra performance liquid chromatography coupled to mass spectrometry. Both hydrophilic interaction chromatography (HILIC) and reversed-phase liquid chromatography (RPLC) were used to separate the urinary metabolites. Principle component analysis (PCA) and partial least squares to latent structure-discriminant analysis (PLS-DA) models were built to separate the healthy volunteers from the liver cancer patients and to find compounds that are expressed in significantly different amounts between the two populations. 21 metabolite ions were considered as potential biomarkers according to the Variable importance in the Project (VIP) value and S-plot. Compared with RPLC, a more sensitive and stable response can be recorded in HILIC mode due to the high content of organic solvent used. Moreover, the liver cancer group and the healthy volunteers can be better separated based on the data from the HILIC separation, which indicates that HILIC is suitable for urinary metabonomic analysis. In HILIC mode, several polar compounds related to arginine and proline metabolism, alanine and aspartate metabolism, lysine degradation, nicotinate and nicotinamide metabolism were found to be significantly changed in the concentrations of the two different populations: healthy and cancer. In contrast, in RPLC mode, these changed compounds are related to fatty acids oxidation.

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Year:  2009        PMID: 19720165     DOI: 10.1016/j.aca.2009.03.039

Source DB:  PubMed          Journal:  Anal Chim Acta        ISSN: 0003-2670            Impact factor:   6.558


  50 in total

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10.  Optimization of harvesting, extraction, and analytical protocols for UPLC-ESI-MS-based metabolomic analysis of adherent mammalian cancer cells.

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