Spatial evaluation of long-term metabolic changes induced by cisplatin nephrotoxicity.

Cisplatin is a widely used chemotherapeutic agent. However, it is causing nephrotoxic side effects including a reduced glomerular filtration rate and acute kidney injury. Although kidneys can recover to an extent from the treatment, long-term damage is possible. While a lot of research is focusing on short-term effects, little is known about adverse metabolic effects in the process of recovery. In this study, male Han Wistar rats were dosed with a single intraperitoneal injection of 3 mg/kg cisplatin. Urine and kidney samples were harvested 3, 8 and 26 days after administration. Tubular injury was demonstrated through urinary biomarkers. Complementing this, mass spectrometry imaging gives insight on molecular alterations on a spatial level, thus making it well suited to analyze short- and long-term disturbances. Various metabolic pathways seem to be affected, as changes in a wide range of metabolites were observed between treated and control animals. Besides previously reported early changes in kidney metabolism, unprecedented long-term effects were detected including deviation in nucleotides, antioxidants, and phospholipids.

Mass spectrometry imaging reveals lipid upregulation and bile acid changes indicating amitriptyline induced steatosis in a rat model.

As a consequence of the detoxification process, drugs and drug related metabolites can accumulate in the liver, resulting in drug induced liver injury (DILI), which is the major cause for dose limitation. Amitriptyline, a commonly used tricyclic anti-depressant, is known to cause DILI. The mechanism of Amitriptyline induced liver injury is not yet completely understood. However, as it undergoes extensive hepatic metabolism, unraveling the molecular changes in the liver upon Amitriptyline treatment can help understand Amitriptyline's mode of toxicity. In this study, Amitriptyline treated male rat liver tissue was analyzed using Matrix Assisted Laser Desorption/Ionization-Mass Spectrometry Imaging (MALDI-MSI) to investigate the spatial abundances of Amitriptyline, lipids, and bile acids. The metabolism of Amitriptyline in liver tissue was successfully demonstrated, as the spatial distribution of Amitriptyline and its metabolites localize throughout treatment group liver samples. Several lipids appear upregulated, from which nine were identified as distinct phosphatidylcholine (PC) species. The detected bile acids were found to be lower in Amitriptyline treatment group. The combined results from histological findings, Oil Red O staining, and lipid zonation by MSI revealed lipid upregulation in the periportal area indicating drug induced macrovesicular steatosis (DIS).

Quantitative targeted bile acid profiling as new markers for DILI in a model of methapyrilene-induced liver injury in rats.

Recently, bile acids (BAs) were reported as promising markers for drug-induced liver injury (DILI). BAs have been suggested to correlate with hepatocellular and hepatobiliary damage; however a clear connection of BA patterns with different types of DILI remains to be established. To investigate if BAs can improve the assessment of liver injury, 20 specific BAs were quantitatively profiled via LC-MS/MS in plasma and liver tissue in a model of methapyrilene-induced liver injury in rats. Methapyrilene, a known hepatotoxin was dosed daily over 14-days at doses of 30 and 80mg/kg, followed by a recovery phase of 10days. Conventional preclinical safety endpoints were related to BA perturbations and to hepatic gene expression profiling for a mechanistic interpretation of effects. Histopathological signs of hepatocellular and hepatobiliary damage with significant changes of clinical chemistry markers were accompanied by significantly increased levels of indivdual BAs in plasma and liver tissue. BA perturbations were already evident at the earliest time point after 30mg/kg treatment, and thereby indicating better sensitivity than clinical chemistry parameters. Furthermore, the latter markers suggested recovery of liver injury, whereas BA levels in plasma and liver remained significantly elevated during the recovery phase, in line with persistent histopathological findings of bile duct hyperplasia (BDH) and bile pigment deposition. Gene expression profiling revealed downregulation of genes involved in BA synthesis (AMACR, BAAT, ACOX2) and hepatocellular uptake (NTCP, OATs), and upregulation for efflux transporters (MRP2, MRP4), suggesting an adaptive hepatocellular protection mechanism against cytotoxic bile acid accumulation. In summary, our data suggests that specific BAs with high reliability such as cholic acid (CA) and chenodeoxycholic acid (CDCA) followed by glycocholic acid (GCA), taurocholic acid (TCA) and deoxycholic acid (DCA) can serve as additional biomarkers for hepatocellular/hepatobiliary damage in the liver in rat toxicity studies.

Metabolomics in toxicology and preclinical research.

Metabolomics, the comprehensive analysis of metabolites in a biological system, provides detailed information about the biochemical/physiological status of a biological system, and about the changes caused by chemicals. Metabolomics analysis is used in many fields, ranging from the analysis of the physiological status of genetically modified organisms in safety science to the evaluation of human health conditions. In toxicology, metabolomics is the -omics discipline that is most closely related to classical knowledge of disturbed biochemical pathways. It allows rapid identification of the potential targets of a hazardous compound. It can give information on target organs and often can help to improve our understanding regarding the mode-of-action of a given compound. Such insights aid the discovery of biomarkers that either indicate pathophysiological conditions or help the monitoring of the efficacy of drug therapies. The first toxicological applications of metabolomics were for mechanistic research, but different ways to use the technology in a regulatory context are being explored. Ideally, further progress in that direction will position the metabolomics approach to address the challenges of toxicology of the 21st century. To address these issues, scientists from academia, industry, and regulatory bodies came together in a workshop to discuss the current status of applied metabolomics and its potential in the safety assessment of compounds. We report here on the conclusions of three working groups addressing questions regarding 1) metabolomics for in vitro studies 2) the appropriate use of metabolomics in systems toxicology, and 3) use of metabolomics in a regulatory context.

Biological qualification of biomarkers of chemical-induced renal toxicity in two strains of male rat.

This study reports the evaluation of four urinary biomarkers of renal toxicity, α-glutathione-S-transferase (α-GST), µ-GST, clusterin, and renal papillary antigen-1 (RPA-1), in male Sprague-Dawley and Han-Wistar rats given cisplatin, gentamicin, or N-phenylanthranilic acid (NPAA). Kidney injury was diagnosed histopathologically, according to site/nature of renal injury, and graded for severity. The area under the receiver operating characteristic (ROC) curve was used to compare the diagnostic accuracy of each exploratory renal biomarker with traditional indicators of renal function and injury (blood urea nitrogen [BUN], serum creatinine [sCr] as well as urinary N-acetyl-ß-D-glucosaminidase [NAG] and protein). These analyses showed that increased urinary α-GST was superior to BUN, sCr, and NAG for diagnosis of proximal tubular (PT) degeneration/necrosis. Paradoxically, urinary α-GST was decreased in the presence of collecting duct (CD) injury without PT injury (NPAA administration). RPA-1 demonstrated high specificity for CD injury, superior to all of the reference biomarkers. The clusterin response correlated well with tubular injury, whatever the location, particularly when regeneration was present (superior to all of the reference markers for cortical tubular regeneration). There was no conclusive evidence for the diagnostic utility of µ-GST. The data were submitted for qualification review by the European Medicines Agency and the US Food and Drug Administration. Both agencies concluded that the data justified the qualification of RPA-1 and increased the level of evidence for, and clarified the context of use of, the previously qualified clusterin for use in male rats. These biomarkers can be used in conjunction with traditional clinical chemistry markers and histopathology in Good Laboratory Practice rodent toxicology studies used to support renal safety studies in clinical trials. Qualification of α-GST must await further explanation of the differences in response to PT and CD injury.

A comparative integrated transcript analysis and functional characterization of differential mechanisms for induction of liver hypertrophy in the rat.

The main goal of the present work was to better understand the molecular mechanisms underlying liver hypertrophy (LH), a recurrent finding observed following acute or repeated drug administration to animals, using transcriptomic technologies together with the results from conventional toxicology methods. Administration of 5 terminated proprietary drug candidates from participating companies involved in the EU Innomed PredTox Project or the reference hepatotoxicant troglitazone to rats for up to a 14-day duration induced LH as the main liver phenotypic toxicity outcome. The integrated analysis of transcriptomic liver expression data across studies turned out to be the most informative approach for the generation of mechanistic models of LH. In response to a xenobiotic stimulus, a marked increase in the expression of xenobiotic metabolizing enzymes (XME) was observed in a subset of 4 studies. Accumulation of these newly-synthesized proteins within the smooth endoplasmic reticulum (SER) would suggest proliferation of this organelle, which most likely is the main molecular process underlying the LH observed in XME studies. In another subset of 2 studies (including troglitazone), a marked up-regulation of genes involved in peroxisomal fatty acid ß-oxidation was noted, associated with induction of genes involved in peroxisome proliferation. Therefore, an increase in peroxisome abundance would be the main mechanism underlying LH noted in this second study subset. Together, the use of transcript profiling provides a means to generate putative mechanistic models underlying the pathogenesis of liver hypertrophy, to distinguish between subtle variations in subcellular organelle proliferation and creates opportunities for improved mechanism-based risk assessment.

Cross-study and cross-omics comparisons of three nephrotoxic compounds reveal mechanistic insights and new candidate biomarkers.

The European InnoMed-PredTox project was a collaborative effort between 15 pharmaceutical companies, 2 small and mid-sized enterprises, and 3 universities with the goal of delivering deeper insights into the molecular mechanisms of kidney and liver toxicity and to identify mechanism-linked diagnostic or prognostic safety biomarker candidates by combining conventional toxicological parameters with "omics" data. Mechanistic toxicity studies with 16 different compounds, 2 dose levels, and 3 time points were performed in male Crl: WI(Han) rats. Three of the 16 investigated compounds, BI-3 (FP007SE), Gentamicin (FP009SF), and IMM125 (FP013NO), induced kidney proximal tubule damage (PTD). In addition to histopathology and clinical chemistry, transcriptomics microarray and proteomics 2D-DIGE analysis were performed. Data from the three PTD studies were combined for a cross-study and cross-omics meta-analysis of the target organ. The mechanistic interpretation of kidney PTD-associated deregulated transcripts revealed, in addition to previously described kidney damage transcript biomarkers such as KIM-1, CLU and TIMP-1, a number of additional deregulated pathways congruent with histopathology observations on a single animal basis, including a specific effect on the complement system. The identification of new, more specific biomarker candidates for PTD was most successful when transcriptomics data were used. Combining transcriptomics data with proteomics data added extra value.