Evaluation of felbamate and other antiepileptic drug toxicity potential based on hepatic protein covalent binding and gene expression.

Felbamate is an antiepileptic drug that is associated with minimal toxicity in preclinical species such as rat and dog but has an unacceptable incidence of serious idiosyncratic reactions in man. Idiosyncratic reactions account for over half of toxicity-related drug failures in the marketplace, and improving the preclinical detection of idiosyncratic toxicities is thus of paramount importance to the pharmaceutical industry. The formation of reactive metabolites is common among most drugs associated with idiosyncratic drug reactions and may cause deleterious effects through covalent binding and/or oxidative stress. In the present study, felbamate was compared to several other antiepileptic drugs (valproic acid, carbamazepine, phenobarbital, and phenytoin), using covalent binding of radiolabeled drugs and hepatic gene expression responses to evaluate oxidative stress/reactive metabolite potential. Despite causing only very mild effects on covalent binding parameters, felbamate produced robust effects on a previously established oxidative stress/reactive metabolite gene expression signature. The other antiepileptic drugs and acetaminophen are known hepatotoxicants at high doses in the rat, and all increased covalent binding to liver proteins in vivo and/or to liver microsomes from human and rat. With the exception of acetaminophen, valproic acid exhibited the highest covalent binding in vivo, whereas carbamazepine exhibited the highest levels in vitro. Pronounced effects on oxidative stress/reactive metabolite-responsive gene expression were observed after carbamazepine, phenobarbital, and phenytoin administration. Valproic acid had only minor effects on the oxidative stress/reactive metabolite indicator genes. The relative ease of detection of felbamate based on gene expression results in rat liver as having potential oxidative stressor/reactive metabolites indicates that this approach may be useful in screening for potential idiosyncratic toxicity. Together, measurements of gene expression along with covalent binding should improve the safety assessment of candidate drugs.

Hepatic expression of heme oxygenase-1 and antioxidant response element-mediated genes following administration of ethinyl estradiol to rats.

Heme oxygenase-1 (HO-1) is one of several enzymes induced by hepatotoxicants, and is thought to have an important protective role against cellular stress during liver inflammation and injury. The objective of the present study was to evaluate the role of HO-1 in estradiol-induced liver injury. A single dose of ethinyl estradiol (500 mg/kg, po) resulted in mild liver injury. Repeated administration of ethinyl estradiol (500 mg/kg/day for 4 days, po) resulted in no detectable liver injury or dysfunction. Using RT-PCR analysis, we demonstrate that HO-1 gene expression in whole liver tissue is elevated (>20-fold) after the single dose of ethinyl estradiol. The number and intensity of HO-1 immunoreactive macrophages were increased after the single dose of ethinyl estradiol. HO-1 expression was undetectable in hepatic parenchymal cells from rats receiving Methocel control or a single dose of ethinyl estradiol, however cytosolic HO-1 immunoreactivity in these cells after repeated dosing of ethinyl estradiol was pronounced. The increases in HO-1 mRNA and HO-1 immunoreactivity following administration of a single dose of ethinyl estradiol suggested that this enzyme might be responsible for the observed protection of the liver during repeated dosing. To investigate the effect of HO-1 expression on ethinyl estradiol-induced hepatotoxicity, rats were pretreated with hemin (50 micromol/kg, ip, a substrate and inducer of HO-1), with tin protoporphyrin IX (60 micromol/kg, ip, an HO-1 inhibitor), or with gadolinium chloride (10 mg/kg, iv, an inhibitor/toxin of Kupffer cells) 24 h before ethinyl estradiol treatment. Pretreatment with modulators of HO-1 expression and activity had generally minimal effects on ethinyl estradiol-induced liver injury. These data suggest that HO-1 plays a limited role in antioxidant defense against ethinyl estradiol-induced oxidative stress and hepatotoxicity, and suggests that other coordinately induced enzymes are responsible for protection observed with repeated administration of high doses of this compound.

Predictive toxicogenomics approaches reveal underlying molecular mechanisms of nongenotoxic carcinogenicity.

Toxicogenomics technology defines toxicity gene expression signatures for early predictions and hypotheses generation for mechanistic studies, which are important approaches for evaluating toxicity of drug candidate compounds. A large gene expression database built using cDNA microarrays and liver samples treated with over one hundred paradigm compounds was mined to determine gene expression signatures for nongenotoxic carcinogens (NGTCs). Data were obtained from male rats treated for 24 h. Training/testing sets of 24 NGTCs and 28 noncarcinogens were used to select genes. A semiexhaustive, nonredundant gene selection algorithm yielded six genes (nuclear transport factor 2, NUTF2; progesterone receptor membrane component 1, Pgrmc1; liver uridine diphosphate glucuronyltransferase, phenobarbital-inducible form, UDPGTr2; metallothionein 1A, MT1A; suppressor of lin-12 homolog, Sel1h; and methionine adenosyltransferase 1, alpha, Mat1a), which identified NGTCs with 88.5% prediction accuracy estimated by cross-validation. This six genes signature set also predicted NGTCs with 84% accuracy when samples were hybridized to commercially available CodeLink oligo-based microarrays. To unveil molecular mechanisms of nongenotoxic carcinogenesis, 125 differentially expressed genes (P<0.01) were selected by Student's t-test. These genes appear biologically relevant, of 71 well-annotated genes from these 125 genes, 62 were overrepresented in five biochemical pathway networks (most linked to cancer), and all of these networks were linked by one gene, c-myc. Gene expression profiling at early time points accurately predicts NGTC potential of compounds, and the same data can be mined effectively for other toxicity signatures. Predictive genes confirm prior work and suggest pathways critical for early stages of carcinogenesis.

Class prediction in toxicogenomics.

The intent of this article is to discuss some of the complexities of toxicogenomics data and the statistical design and analysis issues that arise in the course of conducting a toxicogenomics study. We also describe a procedure for classifying compounds into various hepatotoxicity classes based on gene expression data. The methodology involves first classifying a compound as toxic or nontoxic and subsequently classifying the toxic compounds into the hepatotoxicity classes, based on votes by binary classifiers. The binary classifiers are constructed by using genes selected to best elicit differences between the two classes. We show that the gene selection strategy improves the misclassification error rates and also delivers gene pathways that exhibit biological relevance.

A gene expression signature for oxidant stress/reactive metabolites in rat liver.

Formation of free radicals and other reactive molecules is responsible for the adverse effects produced by a number of hepatotoxic compounds. cDNA microarray technology was used to compare transcriptional profiles elicited by training and testing sets of 15 oxidant stressors/reactive metabolite treatments to those produced by approximately 85 other paradigm compounds (mostly hepatotoxicants) to determine a shared signature profile for oxidant stress-associated hepatotoxicity. Initially, 100 genes were chosen that responded significantly different to oxidant stressors/reactive metabolites (OS/RM) compared to other samples in the database, then a 25-gene subset was selected by multivariate analysis. Many of the selected genes (e.g., aflatoxin aldehyde reductase, diaphorase, epoxide hydrolase, heme oxgenase and several glutathione transferases) are well-characterized oxidant stress/Nrf-2-responsive genes. Less than 10 other compounds co-cluster with our training and testing set compounds and these are known to generate OS/RMs as part of their mechanisms of toxicity. Using OS/RM signature gene sets, compounds previously associated with macrophage activation formed a distinct cluster separate from OS/RM and other compounds. A 69-gene set was chosen to maximally separate compounds in control, macrophage activator, peroxisome proliferator and OS/RM classes. The ease with which these 'oxidative stressor' classes can be separated indicates a role for microarray technology in early prediction and classification of hepatotoxicants. The ability to rapidly screen the oxidant stress potential of compounds may aid in avoidance of some idiosyncratic drug reactions as well as overtly toxic compounds.

Inverse gene expression patterns for macrophage activating hepatotoxicants and peroxisome proliferators in rat liver.

Macrophage activation contributes to adverse effects produced by a number of hepatotoxic compounds. Transcriptional profiles elicited by two macrophage activators, LPS and zymosan A, were compared to those produced by 100 paradigm compounds (mostly hepatotoxicants) using cDNA microarrays. Several hepatotoxicants previously reported to activate liver macrophages produced transcriptional responses similar to LPS and zymosan, and these were used to construct a gene signature profile for macrophage activators in the liver. Measurement of cytokine mRNAs in the same liver samples by RT-PCR independently confirmed that these compounds are associated with macrophage activation. In addition to expected effects on acute phase proteins and metabolic pathways that are regulated by LPS and inflammation, a strong induction was observed for many endoplasmic reticulum-associated stress/chaperone proteins. Additionally, many genes in our macrophage activator signature profile were well-characterized PPARalpha-induced genes which were repressed by macrophage activators. A shared gene signature profile for peroxisome proliferators was determined using a training set of clofibrate, WY 14643, diethylhexylphthalate, diisononylphthalate, perfluorodecanoic acid, perfluoroheptanoic acid, and perfluorooctanoic acid. The signature profile included macrophage activator-induced genes that were repressed by peroxisome proliferators. NSAIDs comprised an interesting pharmacological class in that some compounds, notably diflunisal, co-clustered with peroxisome proliferators whereas several others co-clustered with macrophage activators, possibly due to endotoxin exposure secondary to their adverse effects on the gastrointestinal system. While much of these data confirmed findings from the literature, the transcriptional patterns detected using this toxicogenomics approach showed relationships between genes and biological pathways requiring complex analysis to be discerned.