Laura Suter

Renal biomarker qualification submission: a dialog between the FDA-EMEA and Predictive Safety Testing Consortium

The first formal qualification of safety biomarkers for regulatory decision making marks a milestone in the application of biomarkers to drug development. Following submission of drug toxicity studies and analyses of biomarker performance to the Food and Drug Administration (FDA) and European Medicines Agency (EMEA) by the Predictive Safety Testing Consortiums (PSTC) Nephrotoxicity Working Group, seven renal safety biomarkers have been qualified for limited use in nonclinical and clinical drug development to help guide safety assessments. This was a pilot process, and the experience gained will both facilitate better understanding of how the qualification process will probably evolve and clarify the minimal requirements necessary to evaluate the performance of biomarkers of organ injury within specific contexts.

A long-term three dimensional liver co-culture system for improved prediction of clinically relevant drug-induced hepatotoxicity.

Drug-induced liver injury (DILI) is the major cause for liver failure and post-marketing drug withdrawals. Due to species-specific differences in hepatocellular function, animal experiments to assess potential liabilities of drug candidates can predict hepatotoxicity in humans only to a certain extent. In addition to animal experimentation, primary hepatocytes from rat or human are widely used for pre-clinical safety assessment. However, as many toxic responses in vivo are mediated by a complex interplay among different cell types and often require chronic drug exposures, the predictive performance of hepatocytes is very limited. Here, we established and characterized human and rat in vitro three-dimensional (3D) liver co-culture systems containing primary parenchymal and non-parenchymal hepatic cells. Our data demonstrate that cells cultured on a 3D scaffold have a preserved composition of hepatocytes, stellate, Kupffer and endothelial cells and maintain liver function for up to 3months, as measured by the production of albumin, fibrinogen, transferrin and urea. Additionally, 3D liver co-cultures maintain cytochrome P450 inducibility, form bile canaliculi-like structures and respond to inflammatory stimuli. Upon incubation with selected hepatotoxicants including drugs which have been shown to induce idiosyncratic toxicity, we demonstrated that this model better detected in vivo drug-induced toxicity, including species-specific drug effects, when compared to monolayer hepatocyte cultures. In conclusion, our results underline the importance of more complex and long lasting in vitro cell culture models that contain all liver cell types and allow repeated drug-treatments for detection of in vivo-relevant adverse drug effects.

Biomarker Discovery by Imaging Mass Spectrometry Transthyretin is a Biomarker for Gentamicin-induced Nephrotoxicity in Rat

Adverse drug effects are often associated with pathological changes in tissue. An accurate depiction of the undesired affected area, possibly supported by mechanistic data, is important to classify the effects with regard to relevance for human patients. MALDI imaging MS represents a new analytical tool to directly provide the spatial distribution and the relative abundance of proteins in tissue. Here we evaluate this technique to investigate potential toxicity biomarkers in kidneys of rats that were administered gentamicin, a well known nephrotoxicant. Differential analysis of the mass spectrum profiles revealed a spectral feature at 12,959 Da that strongly correlates with histopathology alterations of the kidney. We unambiguously identified this spectral feature as transthyretin (Ser28–Gln146) using an innovative combination of tissue microextraction and fractionation by reverse-phase liquid chromatography followed by a top-down tandem mass spectrometric approach. Our findings clearly demonstrate the emerging role of imaging MS in the discovery of toxicity biomarkers and in obtaining mechanistic insights concerning toxicity mechanisms.

Discriminating different classes of toxicants by transcript profiling

Male rats were treated with various model compounds or the appropriate vehicle controls. Most substances were either well-known hepatotoxicants or showed hepatotoxicity during preclinical testing. The aim of the present study was to determine if biological samples from rats treated with various compounds can be classified based on gene expression profiles. In addition to gene expression analysis using microarrays, a complete serum chemistry profile and liver and kidney histopathology were performed. We analyzed hepatic gene expression profiles using a supervised learning method (support vector machines; SVMs) to generate classification rules and combined this with recursive feature elimination to improve classification performance and to identify a compact subset of probe sets with potential use as biomarkers. Two different SVM algorithms were tested, and the models obtained were validated with a compound-based external cross-validation approach. Our predictive models were able to discriminate between hepatotoxic and nonhepatotoxic compounds. Furthermore, they predicted the correct class of hepatotoxicant in most cases. We provide an example showing that a predictive model built on transcript profiles from one rat strain can successfully classify profiles from another rat strain. In addition, we demonstrate that the predictive models identify nonresponders and are able to discriminate between gene changes related to pharmacology and toxicity. This work confirms the hypothesis that compound classification based on gene expression data is feasible.

Two-dimensional database of mouse liver proteins: Changes in hepatic protein levels following treatment with acetaminophen or its nontoxic regioisomer 3-acetamidophenol

Overdose of acetaminophen (APAP) causes acute hepatotoxicity in rodents and man. The mechanism underlying APAP‐induced liver injury remains unclear, but experimental evidence strongly suggests that activation of APAP and subsequent formation of protein adducts are involved in hepatotoxicity. Using proteomics technologies, we constructed a two‐dimensional protein database for mouse liver, comprising 256 different gene products and investigated the proteins affected after APAP‐induced hepatotoxicity. Adult male mice received a single dose of APAP (100 or 300 mg/kg) or its nontoxic regioisomer 3‐acetamidophenol (AMAP, 300 mg/kg). The extent of liver damage was assessed 8 h after administration by increased liver enzyme release and histopathology. Changes in the protein level were studied by comparison of the intensities of the corresponding spots on two‐dimensional (2‐D) gels. The expression level of about 35 of the identified proteins was modified due to treatment with APAP or AMAP. The observed changes were usually in the order of 10—50% of the control value and were more marked in the high‐ than in the low‐dose of APAP‐treated animals. Most of the changes caused by AMAP occurred in a subset of the proteins modified by APAP. Many of the proteins showing changed expression levels are either known targets for covalent modification by N‐acetyl‐p‐benzoquinoneimine (NAPQI) or involved in the regulation of mechanisms that are believed to drive APAP‐induced hepatotoxicity.

The rat liver mitochondrial proteins.

Subcellular fractionation increases the probability of detection of low‐abundance proteins. We prepared a fraction highly enriched in mitochondrial proteins from rat liver. The proteins were analyzed by two‐dimensional (2‐D) electrophoresis using broad‐and narrow‐range immobilized pH gradient strips, and identified by matrix assisted laser desorption/ionization‐mass spectrometry (MALDI‐MS). 192 different gene products were detected, of which approximately 70% were enzymes with a broad spectrum of catalytic activities. Most of the identified proteins were detected in other rat protein samples as well, which were analyzed in our laboratory. Eight gene products were detected for the first time. These were represented by one spot each, whereas most of the frequently detected proteins were represented by multiple spots. In average, approximately 10–15 spots corresponded to one gene product.

Proteomic analysis of the rat liver.

Rat is a useful, widely used animal model for biological and toxicity studies. We analyzed total and cytosolic rat liver proteins by applying proteomics technologies. The proteins were separated by two-dimensional electrophoresis employing broad and narrow range immobilized pH gradient strips, followed by MALDI-MS analysis of the tryptic digests. Two hundred and seventy-three different gene products were identified, of which approximately 60% were enzymes with a broad spectrum of catalytic activities. Most of the identified proteins were detected in other rat protein samples as well, which were analyzed in our laboratory. Fifteen gene products were detected for the first time. These were represented by one spot each, whereas most of the frequently detected proteins were represented by multiple spots. In average, approximately five to 10 spots corresponded to one gene product. The database includes a large number of proteins known to be involved in toxicology-relevant pathways and may be useful in toxicity prediction studies.

Bioengineered 3D Human Kidney Tissue, a Platform for the Determination of Nephrotoxicity

The staggering cost of bringing a drug to market coupled with the extremely high failure rate of prospective compounds in early phase clinical trials due to unexpected human toxicity makes it imperative that more relevant human models be developed to better predict drug toxicity. Drug–induced nephrotoxicity remains especially difficult to predict in both pre-clinical and clinical settings and is often undetected until patient hospitalization. Current pre-clinical methods of determining renal toxicity include 2D cell cultures and animal models, both of which are incapable of fully recapitulating the in vivo human response to drugs, contributing to the high failure rate upon clinical trials. We have bioengineered a 3D kidney tissue model using immortalized human renal cortical epithelial cells with kidney functions similar to that found in vivo. These 3D tissues were compared to 2D cells in terms of both acute (3 days) and chronic (2 weeks) toxicity induced by Cisplatin, Gentamicin, and Doxorubicin using both traditional LDH secretion and the pre-clinical biomarkers Kim-1 and NGAL as assessments of toxicity. The 3D tissues were more sensitive to drug-induced toxicity and, unlike the 2D cells, were capable of being used to monitor chronic toxicity due to repeat dosing. The inclusion of this tissue model in drug testing prior to the initiation of phase I clinical trials would allow for better prediction of the nephrotoxic effects of new drugs.

A label-free, impedance-based real time assay to identify drug-induced toxicities and differentiate cytostatic from cytotoxic effects.

Cell-based assays are key tools in drug safety assessment. However, they usually provide only limited information about time-kinetics of a toxic effect and implementing multiple measurements is often complex. To overcome these issues we established an impedance-based approach which is able to differentiate cytostatic from cytotoxic drugs by recording time-kinetics of compound-effects on cells. NIH 3T3 fibroblasts were seeded on xCELLigence® E-plates and impedance was continuously measured over 5 days. The obtained results reflected cytotoxicity and cell proliferation, as confirmed by neutral red uptake in vitro. Based on known toxicants, we established an algorithm able to discriminate cytostatic, cytotoxic and non-toxic compounds based on the shape of the impedance curves. Analyzing impedance curve patterns of additional 37 compounds allowed the identification and differentiation of these distinct effects as results correlated well with previous in vivo findings. We show that impedance-based real-time cell analysis is a convenient tool to characterize and discriminate effects of compounds on cells in a time-dependent and label-free manner. The presented impedance assay could be used to further characterize toxicities observed in vivo or in vitro. Due to the ease of performance it may also be a suitable screening tool.

Preclinical evidence for nitrogen-containing bisphosphonate inhibition of farnesyl diphosphate (FPP) synthase in the kidney : Implications for renal safety

Bisphosphonates are potent inhibitors of osteoclast-mediated bone resorption and play an important role in the treatment of osteoporosis, metastatic bone disease, and Paget disease. However, nephrotoxicity has been reported with some bisphosphonates. Nitrogen-containing bisphosphonates directly inhibit farnesyl diphosphate (FPP) synthase activity (mevalonate pathway) and reduce protein prenylation leading to osteoclast cell death. The aim here was to elucidate if this inhibition also occurs in kidney cells and may directly account for nephrotoxicity. In an exploratory study in rats receiving zoledronate or ibandronate an approximate 2-fold increase in FPP synthase mRNA levels was observed in the kidney. The involvement of the mevalonate pathway was confirmed in subsequent in vitro studies with zoledronate, ibandronate, and pamidronate, using the non-nitrogen containing bisphosphonate clodronate as a comparator. In vitro changes in FPP synthase mRNA expression, enzyme activity, and levels of prenylated proteins were assessed. Using two cell lines (a rat normal kidney cell line, NRK-52E, and a human kidney proximal tubule cell line, HK-2), ibandronate and zoledronate were identified as most cytotoxic (EC50: 23/>1000 microM and 16/82 microM, respectively) and as the most potent inhibitors of FPP synthase (IC50; 1.6/7.4 microM and 0.5/0.7 microM, respectively). In both cell lines, inhibition of FPP synthase activity occurred prior to a decrease in levels of prenylated proteins followed by cytotoxicity. This further supports that the mechanism responsible for osteoclast inhibition (therapeutic effect) might also underlie the mechanism of nephrotoxicity.