1. Comprehensive Metabolomic and Lipidomic Profiling of Human Kidney Tissue: A Platform Comparison
- Author
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Ute Hofmann, Judith Wahrheit, Elke Schaeffeler, Jörg Hennenlotter, Florian Büttner, Thomas E. Mürdter, Denise Sonntag, Matthias Schwab, Falko Fend, Jens Bedke, Mathias Haag, Steffen Rausch, Stefan Winter, and Patrick Leuthold
- Subjects
0301 basic medicine ,Swine ,Biology ,Kidney ,Biochemistry ,03 medical and health sciences ,Metabolomics ,Liquid chromatography–mass spectrometry ,Lipidomics ,Animals ,Humans ,Carcinoma, Renal Cell ,Chromatography ,Hydrophilic interaction chromatography ,Human kidney ,General Chemistry ,Lipids ,Kidney Neoplasms ,Chromatographic separation ,030104 developmental biology ,Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization ,Metabolite profiling ,Metabolome ,METABOLIC FEATURES ,Chromatography, Liquid - Abstract
Metabolite profiling of tissue samples is a promising approach for the characterization of cancer pathways and tumor classification based on metabolic features. Here, we present an analytical method for nontargeted metabolomics of kidney tissue. Capitalizing on different chemical properties of metabolites allowed us to extract a broad range of molecules covering small polar molecules and less polar lipid classes that were analyzed by LC-QTOF-MS after HILIC and RP chromatographic separation, respectively. More than 1000 features could be reproducibly extracted and analyzed (CV30%) in porcine and human kidney tissue, which were used as surrogate matrices for method development. To further assess assay performance, cross-validation of the nontargeted metabolomics platform to a targeted metabolomics approach was carried out. Strikingly, from 102 metabolites that could be detected on both platforms, the majority (90%) revealed Spearman's correlation coefficients ≥0.3, indicating that quantitative results from the nontargeted assay are largely comparable to data derived from classical targeted assays. Finally, as proof of concept, the method was applied to human kidney tissue where a clear differentiation between kidney cancer and nontumorous material could be demonstrated on the basis of unsupervised statistical analysis.
- Published
- 2017
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