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Comprehensive Metabolomic and Lipidomic Profiling of Human Kidney Tissue: A Platform Comparison.
- Source :
-
Journal of proteome research [J Proteome Res] 2017 Feb 03; Vol. 16 (2), pp. 933-944. Date of Electronic Publication: 2017 Jan 12. - Publication Year :
- 2017
-
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 (CV < 30%) 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.
- Subjects :
- Animals
Carcinoma, Renal Cell diagnosis
Carcinoma, Renal Cell pathology
Chromatography, Liquid methods
Humans
Kidney Neoplasms diagnosis
Kidney Neoplasms pathology
Metabolomics instrumentation
Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
Swine
Carcinoma, Renal Cell chemistry
Kidney chemistry
Kidney Neoplasms chemistry
Lipids isolation & purification
Metabolome
Metabolomics methods
Subjects
Details
- Language :
- English
- ISSN :
- 1535-3907
- Volume :
- 16
- Issue :
- 2
- Database :
- MEDLINE
- Journal :
- Journal of proteome research
- Publication Type :
- Academic Journal
- Accession number :
- 27992229
- Full Text :
- https://doi.org/10.1021/acs.jproteome.6b00875