Synergistic drug–cytokine induction of hepatocellular death as an in vitro approach for the study of inflammation-associated idiosyncratic drug hepatotoxicity☆
Introduction
Idiosyncratic drug hepatotoxicity is defined as drug-induced liver injury that occurs in a very small fraction of human patients, is unrelated to the pharmacologic target of the drug, and is host dependent (Ganey et al., 2004, Kaplowitz, 2005, Uetrecht, 2007). Idiosyncratic drug hepatotoxicity is poorly predicted by standard preclinical cell culture and animal models as well as in clinical trials, and, consequently, most idiosyncratic drug hepatotoxicities are not evident until after approval for human use. Due to the inability to predict idiosyncratic hepatotoxicities in the drug development process, idiosyncratic drug hepatotoxicity frequently leads to drug withdrawal or “black box” warnings and accounts for more than 10% of acute liver failure cases (Uetrecht, 2003, Kaplowitz, 2005). Multiple hypotheses have been suggested to explain the mechanisms underlying idiosyncratic drug hepatotoxicity. These include (i) variations in drug metabolism, particularly associated with alterations in the expression and/or activities of the cytochrome P450 family enzymes, due to variable environmental conditions and/or genetic polymorphisms in the human population (Uetrecht, 2008); and (ii) a relationship with concomitant liver inflammation associated with viral or bacterial infection or liver or inflammatory disease (Ganey et al., 2004). Moreover, it is likely that multiple factors – both genetic and environmental – contribute, at relative degrees which are not predictable at the present time, to a drug's hepatotoxicity idiosyncrasies (Peters, 2005).
A number of preclinical models have been developed in attempts to predict idiosyncratic drug hepatotoxicity, including the assessment of reactive metabolites through glutathione (GSH) conjugation assays and the evaluation of animals models by toxicogenomic and metabolonomic approaches to identify common idiosyncratic hepatotoxicity-associated biomarkers, with little overall predictive success (Kaplowitz, 2005, Peters, 2005, Obach et al., 2008). Rodent models administered with bacterial lipopolysaccharide (LPS) have been recently developed to assess inflammation-associated idiosyncratic drug hepatotoxicity. In these rodent models, LPS exposure induces a mild inflammatory response that has been demonstrated to synergistically induce hepatotoxicity in the presence of a number of idiosyncratic hepatotoxic drugs, including diclonfenac, sulindac, trovafloxacin, ranitidine, chlorpromazine, but not non- or less-toxic control drugs (Buchweitz et al., 2002, Luyendyk et al., 2003, Deng et al., 2006, Shaw et al., 2007). In rats, LPS administration upregulates plasma concentrations of the cytokines tumor necrosis factor-α (TNF), interferon-γ (IFNγ), interleukin-1α and -1β (IL-1α/β), interleukin-6 (IL-6), and the chemokine interleukin-10 (IL-10) (Bergheim et al., 2006). Of these, TNF, IFNγ, IL-1α/β, IL-6, and LPS itself all stimulate hepatocyte signaling responses through the activation of a diversity of intracellular signal transduction pathways, including the IKK–NF-κB, p38, and JNK pathways (associated with TNF, IL-1α/β, and LPS signaling) and the STAT1 and STAT3 pathways (associated with IFNγ and IL-6 signaling, respectively), which all are implicated in hepatocellular death in liver diseases and injuries (reviewed in Luedde and Trautwein, 2006, Schwabe and Brenner, 2006, Malhi and Gores, 2008, Tacke et al., 2009). In LPS-administered rat models, synergistic induction of hepatocellular death in the presence of the idiosyncratic hepatotoxicants ranitidine and trovafloxacin has been reported to be dependent on TNF signaling (Shaw et al., 2007, Shaw et al., 2009, Tukov et al., 2007). The observations in LPS-administered rodent models suggest that idiosyncratic drug hepatotoxicity can arise when mild drug-induced hepatocellular stresses synergize with LPS-induced inflammatory cytokine signaling to elicit acute hepatocellular death (Ganey et al., 2004, Kaplowitz, 2005). These stresses may be idiosyncratic in nature in human patients due variations in drug metabolism, exposure, and/or clearance. The sensitizing role of hepatocellular stress is supported by the fact that drug-induced depletion of glutathione is known to sensitize hepatocytes to TNF-induced apoptosis (Mari et al., 2008). Furthermore, both LPS and inflammatory cytokine signaling can alter hepatocyte expression of cytochrome P450 enzymes and thus lead to dysregulated drug metabolism and clearance in conditions of LPS-induced liver inflammation (Warren et al., 1999, Zolfaghari et al., 2007). Although they offer promise for improved predictability of idiosyncratic hepatotoxicity in preclinical screening, LPS-administered rodent models lack sufficient throughput for preclinical screening of candidate pharmaceuticals. Moreover, it has been shown that animal models are in general not highly predictive of human drug hepatotoxicity, as combined preclinical testing in rodents, dogs, and monkeys can only identify ∼ 50% of known human hepatotoxicants (Olson et al., 2000).
Recent advances in the maintenance and characterization of in vitro hepatocyte culture systems offer substantial promise for their more wide-spread utilization in high-throughput preclinical screening approaches for the prediction of both non-idiosyncratic and idiosyncratic drug hepatotoxicity in humans. Amongst hepatocyte culture systems that are commonly employed for high-throughput preclinical studies, primary human hepatocytes are considered the “gold standard” for evaluating drug metabolism, transport, and toxicity (LeCluyse et al., 2005, Hewitt et al., 2007). In comparison, primary rat hepatocytes, while more readily available and similarly capable of maintaining differentiated hepatic function in time-scales of a few days in vitro, do not reproduce some aspects of human drug metabolism (Xu et al., 2004, Sivaraman et al., 2005). Immortalized and transformed human cell lines (e.g. HepG2 cells) are also frequently employed but have poor maintenance of liver-specific functions and are relatively insensitive to human hepatotoxicants in simple cytotoxicity assays (Xu et al., 2004, O'Brien and Haskins, 2007). A small number of hepatocyte cell culture models have been recently developed to assess idiosyncratic drug hepatotoxicity. Of note, Xu et al. utilized human hepatocyte cell culture models to assay four sub-lethal hepatotoxicity injuries with high-throughput live-cell microscopy for over 300 drugs, including many that cause idiosyncratic liver toxicity in humans (Xu et al., 2008). Using a well-calibrated random forest prediction model of the imaging data, they were able to predict drug hepatotoxicity with a ∼ 50% true-positive rate and ∼ 5% false-positive rate. A rat hepatocyte-Kupffer cell co-culture model has been developed and shown to successfully predict chlorpromazine idiosyncratic hepatotoxicity through its synergistic induction of hepatocellular death following LPS treatment (Tukov et al., 2006). The further development and validation of hepatocyte cell culture models would provide much-needed tools for the preclinical evaluation of idiosyncratic drug hepatotoxicity and could offer greater predictive ability and higher throughput than LPS-administered animal models.
Here, we describe a model of inflammatory cytokine-associated idiosyncratic drug hepatotoxicity in three standard hepatocyte cell culture systems amenable to high-throughput preclinical screening — primary rat and human hepatocytes and the HepG2 human hepatoblastoma cell line. We initially validate this model to demonstrate that a number of idiosyncratic hepatotoxic drugs (ranitidine, trovafloxacin, nefazodone, nimesulide, clarithromycin) synergistically induce hepatocellular death in vitro when co-administered with a cytokine mix containing the LPS-upregulated cytokines TNF, IFNγ, and IL-1α, and LPS itself. We then collect a hepatotoxicity data compendium comprised of combinations of drug and cytokine mix co-treatments covering ∼ 1500 experimental conditions and analyze it to identify informative cytokine mix treatments and hepatocyte cell systems for predicting inflammation-associated idiosyncratic drug hepatotoxicity. Using this data compendium, we show that in vitro drug–cytokine synergies are predominantly potentiated by TNF, IL-1α, and LPS within the context of multi-cytokine mixes and that patterns of drug–cytokine mix synergies across a landscape of multi-cytokine environments can be shown to correlate to drug-induced sub-lethal hepatocyte injury signatures. Then, we demonstrate the screening utility of this drug–cytokine mix co-treatment model by assaying a set of 90 drugs in human hepatocytes and show that a significantly larger fraction of idiosyncratic hepatotoxicants synergize with a single cytokine mix at physiologically relevant dosing concentrations than do non-toxic drugs. Lastly, we also employ an information theoretic technique to identify subsets of cytokine co-treatment conditions that maintain the information contained across the full set of cytokine conditions in the compendium. We show that these informative condition sets can be transferred across cell systems and act as better trainings sets for predicting drug- and cytokine-induced hepatotoxicities in primary human hepatocytes. Our results indicate promise for employing our approach for efficient in vitro investigation of inflammation-associated idiosyncratic drug hepatotoxicity.
Section snippets
Drugs and cytokines
Most drugs were obtained from Sigma (St. Louis, MO) or Sequoia Research Products (Pangbourne, UK). Trovafloxacin was obtained from Pfizer's chemical sample bank (Groton, CT). Unless otherwise noted, the following drug concentrations were used: 450 μM ranitidine, 450 μM trovafloxacin, 70 μM nefazodone, 450 μM nimesulide, 175 μM clarithromycin, and 175 μM telithromycin. These drug concentrations were selected from initial dosing studies based on the criteria that the drug concentration (i) elicit
Several idiosyncratic hepatotoxic drugs, but not their control-paired compounds, exhibit drug–cytokine mix hepatotoxicity synergies in vitro
We developed an in vitro model of inflammation-associated idiosyncratic drug hepatotoxicity by co-administering drug compounds with known idiosyncratic hepatotoxicities in humans with a variety of inflammatory cytokines mixtures (comprised of the cytokines TNF, IFNγ, IL-1α, and IL-6, along with LPS) in multiple hepatocellular cell culture systems (primary human and rat hepatocytes and HepG2 human hepatoblastoma cells). In developing this model, we investigated drug–cytokine mix hepatotoxicity
Discussion
Hepatotoxicity is a major cause of failures in both the clinical and post-approval stages of drug development and thus represents a major challenge for the pharmaceutical industry (Kaplowitz, 2001, Lee, 2003). Furthermore, drug hepatotoxicity represents a serious public health problem, as it is the leading cause of acute liver failure in the United States (Ostapowicz et al., 2002). Idiosyncratic drug hepatotoxicity – a hepatotoxicity subset that occurs in a very small fraction of human patients
Conflict of interest statement
B.S.H. is employed by and holds stock in Pfizer. J.J.X. was a past employee of Pfizer, is employed by Merck & Co., and owns stock in Pfizer, Merck & Co., and other biopharmaceutical companies.
Acknowledgments
The authors thank Arthur Smith and Margaret Dunn for assistance in conducting hepatotoxicity imaging assays and David de Graaf, Steve Tannenbaum, Ajit Dash, Walker Inman, Justin Pritchard, and Brian Joughin for helpful discussions. The authors acknowledge funding support from Pfizer Inc., the MIT Center for Cell Decision Processes (NIH grant P50-GM68762; D.A.L., P.K.S.), the MIT Biotechnology Process Engineering Center (L.G.G.), the MIT Center for Environmental Health Sciences (NIH grant
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Animal experimentation statement: All animals received humane care according to the criteria outlined in the “Guide for the Care and Use of Laboratory Animals” prepared by the National Academy of Sciences and published by the National Institutes of Health (NIH publication 86-23).
- 1
Current address: Yale School of Medicine, New Haven, CT, USA.
- 2
Current address: Department of Mechanical Engineering, National Technical University of Athens, Athens, Greece.
- 3
Current address: Department of Life and Health Sciences, University of Nicosia, Nicosia, Cyprus.
- 4
Current address: Department of Automated Biotechnology, Merck & Co., North Wales, PA, USA.