Estimation of Acceptable Daily Intake Values based on Modeling and In Vivo Mutagenicity of NDSRIs of Fluoxetine, Duloxetine and Atomoxetine.

Nitrosamine drug substance related impurities or NDSRIs can be formed if an active pharmaceutical ingredient (API) has an intrinsic secondary amine that can undergo nitrosation. This is a concern as 1) nitrosamines are potentially highly potent carcinogens, 2) secondary amines in API are common, and 3) NDSRIs that might form from such secondary amines will be of unknown carcinogenic potency. Approaches for evaluating NDSRIs include read across, quantum mechanical modeling of reactivity, in vitro mutation data, and transgenic in vivo mutation data. These approaches were used here to assess NDSRIs that could potentially form from the drugs fluoxetine, duloxetine and atomoxetine. Based on a read across informed by modeling of physicochemical properties and mechanistic activation from quantum mechanical modeling, NDSRIs of fluoxetine, duloxetine, and atomoxetine were 10-100-fold less potent compared with highly potent nitrosamines such as NDMA or NDEA. While the NDSRIs were all confirmed to be mutagenic in vitro (Ames assay) and in vivo (TGR) studies, the latter data indicated that the potency of the mutation response was > 4400 ng/day for all compounds- an order of magnitude higher than published regulatory limits for these NDSRIs. The approaches described herein can be used qualitatively to better categorize NDSRIs with respect to potency and inform whether they are in the ICH M7R2-designated Cohort of Concern.

Quantum Mechanical Assessment of Nitrosamine Potency.

Nitrosamines are in the cohort of concern (CoC) as determined by regulatory guidance. CoC compounds are considered highly potent carcinogens that need to be limited below the threshold of toxicological concern, 1.5 µg/day. Nitrosamines like NDMA and NDEA require strict control, while novel nitrosamine drug substance-related impurities (NDSRIs) may or may not be characterized as potent carcinogens. A risk assessment based on the structural features of NDSRIs is important in order to predict potency because they lack substance-specific carcinogenicity. Herein, we present a quantum mechanical (QM)-based analysis on structurally diverse sets of nitrosamines to better understand how structure influences the reactivity that could result in carcinogenicity. We describe the potency trend through activation energies corresponding to α-hydroxylation, aldehyde formation, diazonium intermediate formation, reaction with DNA base, and hydrolysis reactions, and other probable metabolic pathways associated with the carcinogenicity of nitrosamines. We evaluated activation energies for selected cases such as N-nitroso pyrrolidines, N-nitroso piperidines, N-nitroso piperazines, N-nitroso morpholines, N-nitroso thiomorpholine, N-methyl nitroso aromatic, fluorine-substituted nitrosamines, and substituted aliphatic nitrosamines. We compare these results to the recent framework of the carcinogenic potency characterization approach (CPCA) proposed by health authorities which is meant to give guidance on acceptable intakes (AI) for NDSRIs lacking substance-specific carcinogenicity data. We show examples where QM modeling and CPCA are aligned and examples where CPCA both underestimates and overestimates the AI. In cases where CPCA predicts high potency for NDSRIs, QM modeling can help better estimate an AI. Our results suggest that a combined mechanistic understanding of α-hydroxylation, aldehyde formation, hydrolysis, and reaction with DNA bases could help identify the structural features that underpin the potency of nitrosamines. We anticipate this work will be a valuable addition to the CPCA and provide a more analytical way to estimate AI for novel NDSRIs.

Setting impurity limits for endogenous substances: Recommendations for a harmonized procedure and an example using fatty acids.

Endogenous substances, such as fatty, amino, and nucleic acids, are often purposefully used in parenterally pharmaceuticals, but may be present as impurities. Currently, no consensus guidance exists on setting impurity limits for these substances. Specific procedures are needed, as the amount and types of toxicity data available for endogenous substances are typically far less than those for other chemical impurities. Additionally, the parenteral route of administration of these substances is inherently non-physiological, resulting in potentially different or increased severity of toxicity. Risk Assessment Process Maps (RAPMAPs) are proposed as a model to facilitate the development of health-based exposure limits (HBELs) for endogenous substances. This yielded a framework that was applied to derive HBELs for several fatty acids commonly used in parenteral pharmaceuticals. This approach was used to derive HBELs with further vetting based on anticipated perturbations in physiological serum levels, impacts of dose-rate, and consideration of intermittent dosing. Parenteral HBELs of 100-500 mg/day were generated for several fatty acids, and a proposed class-based limit of 50 mg/day to be used in the absence of chemical-specific data. This default limit is consistent with the low toxicity of this chemical class and ICH Q3C value for Class 3 solvents.

In Vivo Mutagenicity Testing of Arylboronic Acids and Esters.

Arylboronic acids and esters (referred to collectively as arylboronic compounds) are commonly used intermediates in the synthesis of pharmaceuticals but pose a challenge for chemical syntheses because they are often positive for bacterial mutagenicity in vitro. As such, arylboronic compounds are then typically controlled to levels that are acceptable for mutagenic impurities, that is, the threshold of toxicological concern (TTC). This study used ICH M7 guidance to design and conduct a testing strategy to investigate the in vivo relevance of the in vitro positive findings of arylboronic compounds. Eight arylboronic compounds representing a variety of chemical scaffolds were tested in Sprague Dawley and/or Wistar rats in the in vivo Pig-a (peripheral blood reticulocytes and mature red blood cells) and/or comet assays (duodenum and/or liver). Five of the eight compounds were also tested in the micronucleus (peripheral blood) assay. The arylboronic compounds tested orally demonstrated high systemic exposure; thus the blood and bone marrow were adequately exposed to test article. One compound was administered intravenously due to formulation stability issues. This investigation showed that arylboronic compounds that were mutagenic in vitro were not found to be mutagenic in the corresponding in vivo assays. Therefore, arylboronic compounds similar to the scaffolds tested in this article may be considered non-mutagenic and managed in accordance with the ICH Q3A/Q3B guidelines. Environ. Mol. Mutagen. 2019. © 2019 Wiley Periodicals, Inc.

A harmonization effort for acceptable daily exposure application to pharmaceutical manufacturing - Operational considerations.

A European Union (EU) regulatory guideline came into effect for all new pharmaceutical products on June 1st, 2015, and for all existing pharmaceutical products on December 1st, 2015. This guideline centers around the use of the Acceptable Daily Exposure (ADE) [synonymous with the Permitted Daily Exposure (PDE)] and operational considerations associated with implementation are outlined here. The EU guidance states that all active pharmaceutical ingredients (API) require an ADE; however, other substances such as starting materials, process intermediates, and cleaning agents may benefit from an ADE. Problems in setting ADEs for these additional substances typically relate to toxicological data limitations precluding the ability to establish a formal ADE. Established methodologies such as occupational exposure limits or bands (OELs or OEBs) and the threshold of toxicological concern (TTC) can be used or adjusted for use as interim ADEs when only limited data are available and until a more formal ADE can be established. Once formal ADEs are derived, it is important that the documents are routinely updated and that these updates are communicated to appropriate stakeholders. Another key operational consideration related to data-poor substances includes the use of maximum daily dose (MDD) in setting cross-contamination limits. The MDD is an important part of the maximum allowable/safe concentration (MAC/MSC) calculation and there are important considerations for its use and definition. Finally, other considerations discussed include operational aspects of setting ADEs for pediatrics, considerations for large molecules, and risk management in shared facilities.

Issues and approaches for ensuring effective communication on acceptable daily exposure (ADE) values applied to pharmaceutical cleaning.

This manuscript centers on communication with key stakeholders of the concepts and program goals involved in the application of health-based pharmaceutical cleaning limits. Implementation of health-based cleaning limits, as distinct from other standards such as 1/1000th of the lowest clinical dose, is a concept recently introduced into regulatory domains. While there is a great deal of technical detail in the written framework underpinning the use of Acceptable Daily Exposures (ADEs) in cleaning (for example ISPE, 2010; Sargent et al., 2013), little is available to explain how to practically create a program which meets regulatory needs while also fulfilling good manufacturing practice (GMP) and other expectations. The lack of a harmonized approach for program implementation and communication across stakeholders can ultimately foster inappropriate application of these concepts. Thus, this period in time (2014-2017) could be considered transitional with respect to influencing best practice related to establishing health-based cleaning limits. Suggestions offered in this manuscript are intended to encourage full and accurate communication regarding both scientific and administrative elements of health-based ADE values used in pharmaceutical cleaning practice. This is a large and complex effort that requires: 1) clearly explaining key terms and definitions, 2) identification of stakeholders, 3) assessment of stakeholders' subject matter knowledge, 4) formulation of key messages fit to stakeholder needs, 5) identification of effective and timely means for communication, and 6) allocation of time, energy, and motivation for initiating and carrying through with communications.

Assessing Concordance of Drug-Induced Transcriptional Response in Rodent Liver and Cultured Hepatocytes.

The effect of drugs, disease and other perturbations on mRNA levels are studied using gene expression microarrays or RNA-seq, with the goal of understanding molecular effects arising from the perturbation. Previous comparisons of reproducibility across laboratories have been limited in scale and focused on a single model. The use of model systems, such as cultured primary cells or cancer cell lines, assumes that mechanistic insights derived from the models would have been observed via in vivo studies. We examined the concordance of compound-induced transcriptional changes using data from several sources: rat liver and rat primary hepatocytes (RPH) from Drug Matrix (DM) and open TG-GATEs (TG), human primary hepatocytes (HPH) from TG, and mouse liver/HepG2 results from the Gene Expression Omnibus (GEO) repository. Gene expression changes for treatments were normalized to controls and analyzed with three methods: 1) gene level for 9071 high expression genes in rat liver, 2) gene set analysis (GSA) using canonical pathways and gene ontology sets, 3) weighted gene co-expression network analysis (WGCNA). Co-expression networks performed better than genes or GSA when comparing treatment effects within rat liver and rat vs. mouse liver. Genes and modules performed similarly at Connectivity Map-style analyses, where success at identifying similar treatments among a collection of reference profiles is the goal. Comparisons between rat liver and RPH, and those between RPH, HPH and HepG2 cells reveal lower concordance for all methods. We observe that the baseline state of untreated cultured cells relative to untreated rat liver shows striking similarity with toxicant-exposed cells in vivo, indicating that gross systems level perturbation in the underlying networks in culture may contribute to the low concordance.

Predictive Power Estimation Algorithm (PPEA)--a new algorithm to reduce overfitting for genomic biomarker discovery.

Toxicogenomics promises to aid in predicting adverse effects, understanding the mechanisms of drug action or toxicity, and uncovering unexpected or secondary pharmacology. However, modeling adverse effects using high dimensional and high noise genomic data is prone to over-fitting. Models constructed from such data sets often consist of a large number of genes with no obvious functional relevance to the biological effect the model intends to predict that can make it challenging to interpret the modeling results. To address these issues, we developed a novel algorithm, Predictive Power Estimation Algorithm (PPEA), which estimates the predictive power of each individual transcript through an iterative two-way bootstrapping procedure. By repeatedly enforcing that the sample number is larger than the transcript number, in each iteration of modeling and testing, PPEA reduces the potential risk of overfitting. We show with three different cases studies that: (1) PPEA can quickly derive a reliable rank order of predictive power of individual transcripts in a relatively small number of iterations, (2) the top ranked transcripts tend to be functionally related to the phenotype they are intended to predict, (3) using only the most predictive top ranked transcripts greatly facilitates development of multiplex assay such as qRT-PCR as a biomarker, and (4) more importantly, we were able to demonstrate that a small number of genes identified from the top-ranked transcripts are highly predictive of phenotype as their expression changes distinguished adverse from nonadverse effects of compounds in completely independent tests. Thus, we believe that the PPEA model effectively addresses the over-fitting problem and can be used to facilitate genomic biomarker discovery for predictive toxicology and drug responses.

Toxicogenomics and cancer risk assessment: a framework for key event analysis and dose-response assessment for nongenotoxic carcinogens.

In order to determine a threshold for nongenotoxic carcinogens, the traditional risk assessment approach has been to identify a mode of action (MOA) with a nonlinear dose-response. The dose-response for one or more key event(s) linked to the MOA for carcinogenicity allows a point of departure (POD) to be selected from the most sensitive effect dose or no-effect dose. However, this can be challenging because multiple MOAs and key events may exist for carcinogenicity and oftentimes extensive research is required to elucidate the MOA. In the present study, a microarray analysis was conducted to determine if a POD could be identified following short-term oral rat exposure with two nongenotoxic rodent carcinogens, fenofibrate and methapyrilene, using a benchmark dose analysis of genes aggregated in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and Gene Ontology (GO) biological processes, which likely encompass key event(s) for carcinogenicity. The gene expression response for fenofibrate given to rats for 2days was consistent with its MOA and known key events linked to PPARα activation. The temporal response from daily dosing with methapyrilene demonstrated biological complexity with waves of pathways/biological processes occurring over 1, 3, and 7days; nonetheless, the benchmark dose values were consistent over time. When comparing the dose-response of toxicogenomic data to tumorigenesis or precursor events, the toxicogenomics POD was slightly below any effect level. Our results suggest that toxicogenomic analysis using short-term studies can be used to identify a threshold for nongenotoxic carcinogens based on evaluation of potential key event(s) which then can be used within a risk assessment framework.

Kainic acid-induced F-344 rat model of mesial temporal lobe epilepsy: gene expression and canonical pathways.

Mesial temporal lobe epilepsy (MTLE) is a severe neurological condition of unknown pathogenesis for which several animal models have been developed. To obtain a better understanding of the underlying molecular mechanisms and identify potential biomarkers of lesion progression, we used a rat kainic acid (KA) treatment model of MTLE coupled with global gene expression analysis to examine temporal (four hours, days 3, 14, or 28) gene regulation relative to hippocampal histopathological changes. The authors recommend reviewing the companion histopathology paper (Sharma et al. 2008) to get a better understanding of the work presented here. Analysis of filtered gene expression data using Ingenuity Pathways Analysis (Ingenuity Systems, http://www.ingenuity.com) revealed that a number of genes pertaining to neuronal plasticity (RhoA, Rac1, Cdc42, BDNF, and Trk), neurodegeneration (Caspase3, Calpain 1, Bax, a Cytochrome c, and Smac/Diablo), and inflammation/immune-response pathways (TNF-alpha, CCL2, Cox2) were modulated in a temporal fashion after KA treatment. Expression changes for selected genes known to have a role in neuronal plasticity were subsequently validated by quantitative polymerase chain reaction (qPCR). Notably, canonical pathway analysis revealed that a number of genes within the axon guidance signaling canonical pathway were up-regulated from Days 3 to 28, which correlated with aberrant mossy fiber (MF) sprouting observed histologically beginning at Day 6. Importantly, analysis of the gene expression data also identified potential biomarkers for monitoring neurodegeneration (Cox2) and neuronal/synaptic plasticity (Kalrn).

Underlying mechanisms of pharmacology and toxicity of a novel PPAR agonist revealed using rodent and canine hepatocytes.

Marked species-specific responses to agonists of the peroxisome proliferator-activated alpha receptor (PPAR alpha) have been observed in rats and dogs, two species typically used to assess the potential human risk of pharmaceuticals in development. In this study, we used primary cultured rat and dog hepatocytes to investigate the underlying mechanisms of a novel PPAR alpha and -gamma coagonist, LY465608, relative to fenofibrate, a prototypical PPAR alpha agonist. As expected, rat hepatocytes incubated with these two agonists demonstrated an increase in peroxisome number as evaluated by electron microscopy, whereas the peroxisome number remained unchanged in dog hepatocytes. Biochemical analysis showed that rat hepatocytes responded to PPAR agonists with an induction of both peroxisomal and mitochondrial beta-oxidation (PBox and MBox) activities. Dog hepatocytes treated with both PPAR agonists, however, did not show increased PBox activity but did demonstrate increased MBox activity. Analysis of peroxisomal beta-oxidation gene expression markers by quantitative real-time PCR confirmed that PPAR agonists induced the peroxisomal enzymes, acyl-coenzyme A (CoA) oxidase (Acox), enoyl-CoA hydratase/L-3-hydroxyacyl-CoA dehydrogenase (Ehhadh), and 3-ketoacyl-CoA thiolase (Acaa1) at the transcriptional level in rat hepatocytes, but not dog hepatocytes. Expression of mRNA for the mitochondrial beta-oxidation gene hydroxyacyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase (Hadhb), however, increased in both rat and dog hepatocytes, consistent with biochemical measurements of peroxisomal and mitochondrial beta-oxidation. Repeat-dose nonclinical safety studies of LY465608 revealed abnormities in mitochondrial morphology and evidence of single-cell necrosis following 30 days of dosing exclusively in dogs, but not in rats. Microarray analysis indicated that dog hepatocytes, but not rat hepatocytes, treated with LY465608 had an expression profile consistent with abnormalities in the regulation of cell renewal and death, oxidative stress, and mitochondrial bioenergetics, which may explain the canine-specific toxicity observed in vivo with this compound. This increased sensitivity to mitochondrial toxicity of canine hepatocytes relative to rat hepatocytes identified using gene expression was confirmed using the fluorescent indicator tetramethylrhodamine ethyl ester (TMRE) and flow cytometry. At doses of 0.1 microM LY465608, canine hepatocytes showed a greater shift in fluorescence indicative of mitochondrial damage than observed with rat hepatocytes treated at 10 microM. In summary, using rat and dog primary hepatocytes, we replicated the pharmacologic and toxicologic effects of LY465608 observed in vivo during preclinical development and propose an underlying mechanism for these species-specific effects.

Pooling samples within microarray studies: a comparative analysis of rat liver transcription response to prototypical toxicants.

Combining or pooling individual samples when carrying out transcript profiling using microarrays is a fairly common means to reduce both the cost and complexity of data analysis. However, pooling does not allow for statistical comparison of changes between samples and can result in a loss of information. Because a rigorous comparison of the identified expression changes from the two approaches has not been reported, we compared the results for hepatic transcript profiles from pooled vs. individual samples. Hepatic transcript profiles from a single-dose time-course rat study in response to the prototypical toxicants clofibrate, diethylhexylphthalate, and valproic acid were evaluated. Approximately 50% more transcript expression changes were observed in the individual (statistical) analysis compared with the pooled analysis. While the majority of these changes were less than twofold in magnitude ( approximately 80%), a substantial number were greater than twofold (approximately 20%). Transcript changes unique to the individual analysis were confirmed by quantitative RT-PCR, while all the changes unique to the pooled analysis did not confirm. The individual analysis identified more hits per biological pathway than the pooled approach. Many of the transcripts identified by the individual analysis were novel findings and may contribute to a better understanding of molecular mechanisms of these compounds. Furthermore, having individual animal data provided the opportunity to correlate changes in transcript expression to phenotypes (i.e., histology) observed in toxicology studies. The two approaches were similar when clustering methods were used despite the large difference in the absolute number of transcripts changed. In summary, pooling reduced resource requirements substantially, but the individual approach enabled statistical analysis that identified more gene expression changes to evaluate mechanisms of toxicity. An individual animal approach becomes more valuable when the overall expression response is subtle and/or when associating expression data to variable phenotypic responses.

The role of transcriptome analysis in pre-clinical toxicology.

A major benefit of the genomics revolution in biomedical research has been the establishment of transcriptome analysis as an enabling technology in the drug development process. Nowhere in the realm of drug development has the expectation of the impact of transcriptome analysis been greater than in the area of pre-clinical toxicology. Transcriptome analysis, along with other new high-content data generating technologies, has the potential to radically improve the drug safety assessment process by allowing drug development teams to identify potential toxicity liabilities earlier, and thus proceed only with those molecules that have both efficacy at the target and a low potential for toxicity in the human population. In this review we will briefly describe the major ways in which transcriptome analysis is being applied in the pre-clinical safety assessment process, focusing primarily on four areas where transcriptome analysis has already begun to have impact. These include using transcriptome analysis to: 1) understand mechanisms of toxicity: 2) predict toxicity: 3) develop in vivo and in vitro surrogate models and screens; and, 4) develop toxicity biomarkers. We will close by briefly addressing future trends and needs in the application of transcriptome analysis to drug safety assessment.

Microvesicular steatosis induced by a short chain fatty acid: effects on mitochondrial function and correlation with gene expression.

Hepatotoxicity characterized by microvesicular steatosis (MVS) is characterized by an abnormal accumulation of numerous small cytoplasmic lipid droplets in hepatocytes. Fulminant or progressive cases of microvesicular steatosis may lead to liver failure and death. Experimentally, short-chain carboxylic acids are known to induce microvesicular steatosis. The identification of gene changes that correlate with MVS concomitant with biochemical and histological indices could provide a better understanding of how this toxicity occurs as well as biomarkers that could be used to avoid this toxicity in the future. Sprague-Dawley rats were dosed days with cyclopropane carboxylic acid (CPCA) a short-chain fatty acid that can induce microvesicular steatosis, and with butyrate, a short chain fatty acid that served as a negative control. CPCA initiated microvesicular steatosis while butyrate did not. In addition, CPCA inhibited beta-oxidation in a concentration-dependent manner in vitro and caused a reduction in mitochondrial respiration ex vivo; no inhibition was evident with butyrate. Microarray results showed that gene expression changes with CPCA resulted in regulation of genes involved in beta-oxidation, as well as other genes associated with mitochondrial function. Overall, these results support altered hepatic mitochondrial function as a mechanism of the toxicity induced by a short-chain fatty acid and may provide potential biomarkers for this toxicity.

Clofibrate-induced gene expression changes in rat liver: a cross-laboratory analysis using membrane cDNA arrays.

Microarrays have the potential to significantly impact our ability to identify toxic hazards by the identification of mechanistically relevant markers of toxicity. To be useful for risk assessment, however, microarray data must be challenged to determine reliability and interlaboratory reproducibility. As part of a series of studies conducted by the International Life Sciences Institute Health and Environmental Science Institute Technical Committee on the Application of Genomics to Mechanism-Based Risk Assessment, the biological response in rats to the hepatotoxin clofibrate was investigated. Animals were treated with high (250 mg/kg/day) or low (25 mg/kg/day) doses for 1, 3, or 7 days in two laboratories. Clinical chemistry parameters were measured, livers removed for histopathological assessment, and gene expression analysis was conducted using cDNA arrays. Expression changes in genes involved in fatty acid metabolism (e.g., acyl-CoA oxidase), cell proliferation (e.g., topoisomerase II-Alpha), and fatty acid oxidation (e.g., cytochrome P450 4A1), consistent with the mechanism of clofibrate hepatotoxicity, were detected. Observed differences in gene expression levels correlated with the level of biological response induced in the two in vivo studies. Generally, there was a high level of concordance between the gene expression profiles generated from pooled and individual RNA samples. Quantitative real-time polymerase chain reaction was used to confirm modulations for a number of peroxisome proliferator marker genes. Though the results indicate some variability in the quantitative nature of the microarray data, this appears due largely to differences in experimental and data analysis procedures used within each laboratory. In summary, this study demonstrates the potential for gene expression profiling to identify toxic hazards by the identification of mechanistically relevant markers of toxicity.

Isolated human hepatocytes in culture display markedly different gene expression patterns depending on attachment status.

In vitro human hepatocyte cultures are a key tool in the investigation of xenobiotic toxicity and metabolism. In most in vitro hepatocyte studies, the cells are allowed to adhere to an extracellular matrix, such as collagen. Unfortunately, the ability of freshly isolated hepatocytes to adhere to collagen varies from donor to donor. We used microarray analysis to determine what gene expression differences exist between hepatocytes in suspension and hepatocytes attached to collagen. Results from different donors showed a considerable difference in gene expression patterns between the two hepatocyte populations. In addition, we also compared the gene expression profiles of hepatocytes in culture with liver tissue. The results showed that both hepatocytes in suspension and hepatocytes attached to collagen display significant gene expression differences compared with liver tissue. Finally, we show that both populations of hepatocytes are responsive to dexamethasone and regulate some of the same genes. Overall, our results suggest that either significant gene expression changes occur in isolated hepatocytes or that suspended and attached cells represent different populations of hepatocytes found in intact livers.

PTP1B antisense-treated mice show regulation of genes involved in lipogenesis in liver and fat.

Protein tyrosine phosphatases are important regulators of insulin signal transduction. Our studies have shown that in insulin resistant and diabetic ob/ob and db/db mice, reducing the levels of protein tyrosine phosphatase 1B (PTP1B) protein by treatment with a PTP1B antisense oligonucleotide resulted in improved insulin sensitivity and normalized plasma glucose levels. The mechanism by which PTP1B inhibition improves insulin sensitivity is not fully understood. We have used microarray analysis to compare gene expression changes in adipose tissue, liver and muscle of PTP1B antisense-treated ob/ob mice. Our results show that treatment with PTP1B antisense resulted in the downregulation of genes involved in lipogenesis in both fat and liver, and a downregulation of genes involved in adipocyte differentiation in fat, suggesting that PTP1B antisense acts through a different mechanism than thiazolidinedione (TZD) treatment. In summary, microarray results suggest that reduction of PTP1B may alleviate hyperglycemia and enhance insulin sensitivity by a different mechanism than TZD treatment.

Development of a DNA microarray for toxicology based on hepatotoxin-regulated sequences.

Toxicogenomics is an emerging field combining genomics and bioinformatics to identify and characterize mechanisms of toxicity of compounds. One of the main tools used in toxicogenomics is DNA microarrays. We have used a novel strategy to create a library highly enriched for genes expressed in the liver under hepatotoxic conditions. Using this library, we have created a new oligonucleotide microarray dedicated to the study of rat liver function. Oligonucleotide probes for these genes were designed and used in experimental hybridization studies to deduce the correct sequence orientation and to determine those sequences exhibiting differential regulation under a variety of toxicity-related treatments and conditions. The final array was benchmarked on treatments with 3-methylcholanthrene, Aroclor 1254, and cyclopropane carboxylic acid. Our results showed that the subtractive hybridization greatly enriched for genes regulated during a hepatotoxic response. Overall, our strategy for design of a new rat toxicology microarray can be applied to other systems as well and should aid greatly in the development of microarrays targeted for specific scientific areas.