Journal
JOURNAL OF PROTEOME RESEARCH
Volume 16, Issue 2, Pages 933-944Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.6b00875
Keywords
metabolomics; lipidomics; kidney cancer; clear cell renal cell carcinoma (ccRCC); Q-TOF; tissue metabolomics; LC-MS; targeted metabolomics; nontargeted metabolomics; platform comparison
Categories
Funding
- Robert Bosch Stiftung, Stuttgart
- Bosch-Forschungsstiftung, Stuttgart
- ICEPHA Graduate School Tubingen-Stuttgart, Germany
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available