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.

A novel analytical approach for the targeted profiling of bile acids (BAs) in human serum/plasma based on liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) is presented. Reversed-phase chromatography enabled the baseline separation of 15 human BA species which could be readily detected by accurate mass analysis in negative ion mode. Blood proteins were removed by methanol precipitation in the presence of deuterium-labeled internal standards which allowed BA quantification in 50 μl plasma/serum. The assay was validated according to FDA guidance achieving quantification limits from 7.8 to 156 nM. Calibration curves prepared in charcoal-stripped serum/plasma showed excellent regression coefficients (R (2) > 0.997) and covered quantities from 7.8 to 10,000 nM depending on the analyzed species. Intra- and inter-day accuracy and precision were below 15 % for all analytes. Apparent extraction recoveries were above 97 %, and ion suppression rates were between 4 and 53 %. Mean BA level in serum/plasma from healthy volunteers ranged from 11 ± 4 nM (tauroursodeoxycholic acid) to 1321 ± 1442 nM (glycochenodeoxycholic acid). As a proof of concept, the assay was applied to plasma samples derived from a clinical phase I study of myrcludex B, a novel first-in-class virus entry inhibitor for the treatment of chronic hepatitis B and D. The results demonstrate that myrcludex-induced inhibition of the hepatic BA transporter Na(+)-taurocholate cotransporting polypeptide (NTCP) significantly affects plasma BA level. These observations provide novel insights into drug-induced metabolic responses and will be indispensable for the assessment of side effects and dose-finding processes during future clinical trials.

Tissue analysis represents a powerful tool for the investigation of disease pathophysiology. However, the heterogeneous nature of tissue samples, in particular of neoplastic, may affect the outcome of such analysis and hence obscure interpretation of results. Thus, comprehensive isolation and extraction of transcripts and metabolites from an identical tissue specimen would minimize variations and enable the economic use of biopsy material which is usually available in limited amounts. Here we demonstrate a fast and simple protocol for combined transcriptomics and metabolomics analysis in homogenates prepared from one single tissue sample. Metabolites were recovered by protein precipitation from lysates originally prepared for RNA isolation and were analyzed by LC-QTOF-MS after HILIC and RPLC separation, respectively. Strikingly, although ion suppression was observed, over 80% of the 2885 detected metabolic features could be extracted and analyzed with high reproducibility (CV ≤ 20%). Moreover fold changes of different tumor and nontumor kidney tissues were correlated to an established metabolomics protocol and revealed a strong correlation ( r ≥ 0.75). In order to demonstrate the feasibility of the combined analysis of RNA and metabolites, the protocol was applied to kidney tissue of metformin treated mice to investigate drug induced alterations.

Background The metabolic enzyme nicotinamide‐N‐methyltransferase (NNMT) is highly expressed in various cancer entities, suggesting tumour‐promoting functions. We systematically investigated NNMT expression and its metabolic interactions in clear cell renal cell carcinoma (ccRCC), a prominent RCC subtype with metabolic alterations, to elucidate its role as a drug target. Methods NNMT expression was assessed in primary ccRCC (n = 134), non‐tumour tissue and ccRCC‐derived metastases (n = 145) by microarray analysis and/or immunohistochemistry. Findings were validated in The Cancer Genome Atlas (kidney renal clear cell carcinoma [KIRC], n = 452) and by single‐cell analysis. Expression was correlated with clinicopathological data and survival. Metabolic alterations in NNMT‐depleted cells were assessed by nontargeted/targeted metabolomics and extracellular flux analysis. The NNMT inhibitor (NNMTi) alone and in combination with the inhibitor 2‐deoxy‐D‐glucose for glycolysis and BPTES (bis‐2‐(5‐phenylacetamido‐1,3,4‐thiadiazol‐2‐yl)ethyl‐sulfide) for glutamine metabolism was investigated in RCC cell lines (786‐O, A498) and in two 2D ccRCC‐derived primary cultures and three 3D ccRCC air–liquid interface models. Results NNMT protein was overexpressed in primary ccRCC (p = 1.32 × 10–16) and ccRCC‐derived metastases (p = 3.92 × 10–20), irrespective of metastatic location, versus non‐tumour tissue. Single‐cell data showed predominant NNMT expression in ccRCC and not in the tumour microenvironment. High NNMT expression in primary ccRCC correlated with worse survival in independent cohorts (primary RCC—hazard ratio [HR] = 4.3, 95% confidence interval [CI]: 1.5–12.4; KIRC—HR = 3.3, 95% CI: 2.0–5.4). NNMT depletion leads to intracellular glutamine accumulation, with negative effects on mitochondrial function and cell survival, while not affecting glycolysis or glutathione metabolism. At the gene level, NNMT‐depleted cells upregulate glycolysis, oxidative phosphorylation and apoptosis pathways. NNMTi alone or in combination with 2‐deoxy‐D‐glucose and BPTES resulted in inhibition of cell viability in ccRCC cell lines and primary tumour and metastasis‐derived models. In two out of three patient‐derived ccRCC air–liquid interface models, NNMTi treatment induced cytotoxicity. Conclusions Since efficient glutamine utilisation, which is essential for ccRCC tumours, depends on NNMT, small‐molecule NNMT inhibitors provide a novel therapeutic strategy for ccRCC and act as sensitizers for combination therapies.

Therapy of molybdenum cofactor (Moco) deficiency has received US Food and Drug Administration (FDA) approval in 2021. Whereas urothione, the urinary excreted catabolite of Moco, is used as diagnostic biomarker for Mocodeficiency, its catabolic pathway remains unknown. Here, we identified the urothione-synthesizing methyltransferase using mouse liver tissue by anion exchange/size exclusion chromatography and peptide mass fingerprinting. We show that the catabolic Moco S-methylating enzyme corresponds to thiopurine S-methyltransferase (TPMT), a highly polymorphic drug-metabolizing enzyme associated with drug-related hematotoxicity but unknown physiological role. Urothione synthesis was investigated in vitro using recombinantly expressed human TPMT protein, liver lysates from Tpmt wild-type and knock-out (Tpmt −/− ) mice as well as human liver cytosol. Urothione levels were quantified by liquid-chromatography tandem mass spectrometry in the kidneys and urine of mice. TPMT-genotype/phenotype and excretion levels of urothione were investigated in human samples and validated in an independent population-based study. As Moco provides a physiological substrate (thiopterin) of TPMT, thiopterin-methylating activity was associated with TPMT activity determined with its drug substrate (6-thioguanin) in mice and humans. Urothione concentration was extremely low in the kidneys and urine of Tpmt −/− mice. Urinary urothione concentration in TPMT-deficient patients depends on common TPMT polymorphisms, with extremely low levels in homozygous variant carriers (TPMT*3A/*3A) but normal levels in compound heterozygous carriers (TPMT*3A/*3C) as validated in the populationbased study. Our work newly identified an endogenous substrate for TPMT and shows an unprecedented link between Moco catabolism and drug metabolism. Moreover, the TPMT example indicates that phenotypic consequences of genetic polymorphisms may differ between drug-and endogenous substrates.

No abstract