Literature DB >> 27992229

Comprehensive Metabolomic and Lipidomic Profiling of Human Kidney Tissue: A Platform Comparison.

Patrick Leuthold1,2, Elke Schaeffeler1,2, Stefan Winter1,2, Florian Büttner1,2, Ute Hofmann1,2, Thomas E Mürdter1,2, Steffen Rausch1,2,3, Denise Sonntag4, Judith Wahrheit4, Falko Fend5, Jörg Hennenlotter3, Jens Bedke3, Matthias Schwab1,2,6,7, Mathias Haag1,2.   

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.

Entities:  

Keywords:  LC−MS; Q-TOF; clear cell renal cell carcinoma (ccRCC); kidney cancer; lipidomics; metabolomics; nontargeted metabolomics; platform comparison; targeted metabolomics; tissue metabolomics

Mesh:

Substances:

Year:  2017        PMID: 27992229     DOI: 10.1021/acs.jproteome.6b00875

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  11 in total

1.  Nicotinamide-N-methyltransferase is a promising metabolic drug target for primary and metastatic clear cell renal cell carcinoma.

Authors:  Anna Reustle; Lena-Sophie Menig; Patrick Leuthold; Ute Hofmann; Viktoria Stühler; Christian Schmees; Michael Becker; Mathias Haag; Verena Klumpp; Stefan Winter; Florian A Büttner; Steffen Rausch; Jörg Hennenlotter; Falko Fend; Marcus Scharpf; Arnulf Stenzl; Jens Bedke; Matthias Schwab; Elke Schaeffeler
Journal:  Clin Transl Med       Date:  2022-06

2.  Hepatic Expression of the Na+-Taurocholate Cotransporting Polypeptide Is Independent from Genetic Variation.

Authors:  Roman Tremmel; Anne T Nies; Barbara A C van Eijck; Niklas Handin; Mathias Haag; Stefan Winter; Florian A Büttner; Charlotte Kölz; Franziska Klein; Pascale Mazzola; Ute Hofmann; Kathrin Klein; Per Hoffmann; Markus M Nöthen; Fabienne Z Gaugaz; Per Artursson; Matthias Schwab; Elke Schaeffeler
Journal:  Int J Mol Sci       Date:  2022-07-05       Impact factor: 6.208

3.  Optimized GC-MS metabolomics for the analysis of kidney tissue metabolites.

Authors:  Biswapriya B Misra; Ram P Upadhayay; Laura A Cox; Michael Olivier
Journal:  Metabolomics       Date:  2018-05-25       Impact factor: 4.290

Review 4.  Clinical and Functional Relevance of the Monocarboxylate Transporter Family in Disease Pathophysiology and Drug Therapy.

Authors:  Pascale Fisel; Elke Schaeffeler; Matthias Schwab
Journal:  Clin Transl Sci       Date:  2018-04-16       Impact factor: 4.689

5.  Cross-Platform Comparison of Untargeted and Targeted Lipidomics Approaches on Aging Mouse Plasma.

Authors:  Kévin Contrepois; Salah Mahmoudi; Baljit K Ubhi; Katharina Papsdorf; Daniel Hornburg; Anne Brunet; Michael Snyder
Journal:  Sci Rep       Date:  2018-12-10       Impact factor: 4.379

6.  WZ66, a novel acetyl-CoA carboxylase inhibitor, alleviates nonalcoholic steatohepatitis (NASH) in mice.

Authors:  Ying-Sheng Gao; Min-Yi Qian; Qiang-Qiang Wei; Xu-Bin Duan; Shi-Lei Wang; Hai-Yang Hu; Jun Liu; Chu-Yue Pan; Shuo-Quan Zhang; Lian-Wen Qi; Jin-Pei Zhou; Hui-Bin Zhang; Li-Rui Wang
Journal:  Acta Pharmacol Sin       Date:  2019-10-23       Impact factor: 6.150

Review 7.  New Advances in Tissue Metabolomics: A Review.

Authors:  Michelle Saoi; Philip Britz-McKibbin
Journal:  Metabolites       Date:  2021-09-30

8.  Molecular signature of renal cell carcinoma by means of a multiplatform metabolomics analysis.

Authors:  Marta Kordalewska; Renata Wawrzyniak; Julia Jacyna; Joanna Godzień; Ángeles López Gonzálves; Joanna Raczak-Gutknecht; Marcin Markuszewski; Piotr Gutknecht; Marcin Matuszewski; Janusz Siebert; Coral Barbas; Michał J Markuszewski
Journal:  Biochem Biophys Rep       Date:  2022-08-04

Review 9.  Integration of genomics and metabolomics for prioritization of rare disease variants: a 2018 literature review.

Authors:  Emma Graham; Jessica Lee; Magda Price; Maja Tarailo-Graovac; Allison Matthews; Udo Engelke; Jeffrey Tang; Leo A J Kluijtmans; Ron A Wevers; Wyeth W Wasserman; Clara D M van Karnebeek; Sara Mostafavi
Journal:  J Inherit Metab Dis       Date:  2018-05-02       Impact factor: 4.982

10.  Integrative -omics and HLA-ligandomics analysis to identify novel drug targets for ccRCC immunotherapy.

Authors:  Anna Reustle; Moreno Di Marco; Carolin Meyerhoff; Annika Nelde; Juliane S Walz; Stefan Winter; Siahei Kandabarau; Florian Büttner; Mathias Haag; Linus Backert; Daniel J Kowalewski; Steffen Rausch; Jörg Hennenlotter; Viktoria Stühler; Marcus Scharpf; Falko Fend; Arnulf Stenzl; Hans-Georg Rammensee; Jens Bedke; Stefan Stevanović; Matthias Schwab; Elke Schaeffeler
Journal:  Genome Med       Date:  2020-03-30       Impact factor: 11.117

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