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Big data in healthcare can enable unprecedented understanding of diseases and their treatment, particularly in oncology. These data may include electronic health records, medical imaging, genomic sequencing, payor records, and data from pharmaceutical research, wearables, and medical devices. The ability to combine datasets and use data across many analyses is critical to the successful use of big data and is a concern for those who generate and use the data. Interoperability and data quality continue to be major challenges when working with different healthcare datasets. Mapping terminology across datasets, missing and incorrect data, and varying data structures make combining data an onerous and largely manual undertaking. Data privacy is another concern addressed by the Health Insurance Portability and Accountability Act, the Common Rule, and the General Data Protection Regulation. The use of big data is now included in the planning and activities of the FDA and the European Medicines Agency. The willingness of organizations to share data in a precompetitive fashion, agreements on data quality standards, and institution of universal and practical tenets on data privacy will be crucial to fully realizing the potential for big data in medicine., (©2023 The Authors; Published by the American Association for Cancer Research.)

The analysis of big healthcare data has enormous potential as a tool for advancing oncology drug development and patient treatment, particularly in the context of precision medicine. However, there are challenges in organizing, sharing, integrating, and making these data readily accessible to the research community. This review presents five case studies illustrating various successful approaches to addressing such challenges. These efforts are CancerLinQ, the American Association for Cancer Research Project GENIE, Project Data Sphere, the National Cancer Institute Genomic Data Commons, and the Veterans Health Administration Clinical Data Initiative. Critical factors in the development of these systems include attention to the use of robust pipelines for data aggregation, common data models, data deidentification to enable multiple uses, integration of data collection into physician workflows, terminology standardization and attention to interoperability, extensive quality assurance and quality control activity, incorporation of multiple data types, and understanding how data resources can be best applied. By describing some of the emerging resources, we hope to inspire consideration of the secondary use of such data at the earliest possible step to ensure the proper sharing of data in order to generate insights that advance the understanding and the treatment of cancer., (©2023 The Authors; Published by the American Association for Cancer Research.)

Mapping network analysis in cells and tissues can provide insights into metabolic adaptations to changes in external environment, pathological conditions, and nutrient deprivation. Here, we reconstructed a genome-scale metabolic network of the rat liver that will allow for exploration of systems-level physiology. The resulting in silico model (iRatLiver) contains 1,882 reactions, 1,448 metabolites, and 994 metabolic genes. We then used this model to characterize the response of the liver's energy metabolism to a controlled perturbation in diet. Transcriptomics data were collected from the livers of Sprague Dawley rats at 4 or 14 days of being subjected to 15%, 30%, or 60% diet restriction. These data were integrated with the iRatLiver model to generate condition-specific metabolic models, allowing us to explore network differences under each condition. We observed different pathway usage between early and late time points. Network analysis identified several highly connected "hub" genes (Pklr, Hadha, Tkt, Pgm1, Tpi1, and Eno3) that showed differing trends between early and late time points. Taken together, our results suggest that the liver's response varied with short- and long-term diet restriction. More broadly, we anticipate that the iRatLiver model can be exploited further to study metabolic changes in the liver under other conditions such as drug treatment, infection, and disease.

Safety pharmacology screening against a wide range of unintended vital targets using in vitro assays is crucial to understand off-target interactions with drug candidates. With the increasing demand for in vitro assays, ligand- and structure-based virtual screening approaches have been evaluated for potential utilization in safety profiling. Although ligand based approaches have been actively applied in retrospective analysis or prospectively within well-defined chemical space during the early discovery stage (i.e., HTS screening and lead optimization), virtual screening is rarely implemented in later stage of drug discovery (i.e., safety). Here we present a case study to evaluate ligand-based 3D QSAR models built based on in vitro antagonistic activity data against adenosine receptor 2A (A2A). The resulting models, obtained from 268 chemically diverse compounds, were used to test a set of 1,897 chemically distinct drugs, simulating the real-world challenge of safety screening when presented with novel chemistry and a limited training set. Due to the unique requirements of safety screening versus discovery screening, the limitations of 3D QSAR methods (i.e., chemotypes, dependence on large training set, and prone to false positives) are less critical than early discovery screen. We demonstrated that 3D QSAR modeling can be effectively applied in safety assessment prior to in vitro assays, even with chemotypes that are drastically different from training compounds. It is also worth noting that our model is able to adequately make the mechanistic distinction between agonists and antagonists, which is important to inform subsequent in vivo studies. Overall, we present an in-depth analysis of the appropriate utilization and interpretation of pharmacophore-based 3D QSAR models for safety screening., Competing Interests: The authors declare the following competing interests: Amgen Inc. provided support in the form of salaries for authors FF, DTW, HDH, RTD; and at the initial planning stage of the presented study, DTW was an employee for Schrodinger Inc. This does not alter our adherence to PLOS ONE policies on sharing data and materials. There are no patents, products in development or marketed products associated with this research to declare.

Mitochondrial perturbation has been recognized as a contributing factor to various drug-induced organ toxicities. To address this issue, we developed a high-throughput flow cytometry-based mitochondrial signaling assay to systematically investigate mitochondrial/cellular parameters known to be directly impacted by mitochondrial dysfunction: mitochondrial membrane potential (MMP), mitochondrial reactive oxygen species (ROS), intracellular reduced glutathione (GSH) level, and cell viability. Modulation of these parameters by a training set of compounds, comprised of established mitochondrial poisons and 60 marketed drugs (30 nM to 1mM), was tested in HL-60 cells (a human pro-myelocytic leukemia cell line) cultured in either glucose-supplemented (GSM) or glucose-free (containing galactose/glutamine; GFM) RPMI-1640 media. Post-hoc bio-informatic analyses of IC50 or EC50 values for all parameters tested revealed that MMP depolarization in HL-60 cells cultured in GSM was the most reliable parameter for determining mitochondrial dysfunction in these cells. Disruptors of mitochondrial function depolarized MMP at concentrations lower than those that caused loss of cell viability, especially in cells cultured in GSM; cellular GSH levels correlated more closely to loss of viability in vitro. Some mitochondrial respiratory chain inhibitors increased mitochondrial ROS generation; however, measuring an increase in ROS alone was not sufficient to identify mitochondrial disruptors. Furthermore, hierarchical cluster analysis of all measured parameters provided confirmation that MMP depletion, without loss of cell viability, was the key signature for identifying mitochondrial disruptors. Subsequent classification of compounds based on ratios of IC50s of cell viability:MMP determined that this parameter is the most critical indicator of mitochondrial health in cells and provides a powerful tool to predict whether novel small molecule entities possess this liability., (© The Author 2014. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Gene expression profiling is a tool to gain mechanistic understanding of adverse effects in response to compound exposure. However, little is known about how the common handling procedures of experimental animals during a preclinical study alter baseline gene expression. We report gene expression changes in the livers of female Sprague-Dawley rats following common handling procedures. Baseline gene expression changes identified in this study provide insight on how these changes may affect interpretation of gene expression profiles following compound exposure. Rats were divided into three groups. One group was not subjected to handling procedures and served as controls for both handled groups. Animals in the other two groups were weighed, subjected to restraint in Broome restrainers, and administered water via oral gavage daily for 1 or 4 days with tail vein blood collections at 1, 2, 4, and 8 hours postdose on days 1 and 4. Significantly altered genes were identified in livers of animals following 1 or 4 days of handling when compared to the unhandled animals. Gene changes in animals handled for 4 days were similar to those handled for 1 day, suggesting a lack of habituation. The altered genes were primarily immune function related genes. These findings, along with a correlating increase in corticosterone levels suggest that common handling procedures may cause a minor immune system perturbance.

We recently reported results that erythropoiesis-stimulating agent (ESA)-related thrombotic toxicities in preclinical species were not solely dependent on a high hematocrit (HCT) but also associated with increased ESA dose level, dose frequency, and dosing duration. In this article, we conclude that sequelae of an increased magnitude of ESA-stimulated erythropoiesis potentially contributed to thrombosis in the highest ESA dose groups. The results were obtained from two investigative studies we conducted in Sprague-Dawley rats administered a low (no thrombotic toxicities) or high (with thrombotic toxicities) dose level of a hyperglycosylated analog of recombinant human erythropoietin (AMG 114), 3 times weekly for up to 9 days or for 1 month. Despite similarly increased HCT at both dose levels, animals in the high-dose group had an increased magnitude of erythropoiesis measured by spleen weights, splenic erythropoiesis, and circulating reticulocytes. Resulting prothrombotic risk factors identified predominantly or uniquely in the high-dose group were higher numbers of immature reticulocytes and nucleated red blood cells in circulation, severe functional iron deficiency, and increased intravascular destruction of iron-deficient reticulocyte/red blood cells. No thrombotic events were detected in rats dosed up to 9 days suggesting a sustained high HCT is a requisite cofactor for development of ESA-related thrombotic toxicities.

We previously reported an increased incidence of thrombotic toxicities in Sprague-Dawley rats administered the highest dose level of a hyperglycosylated analog of recombinant human erythropoietin (AMG 114) for 1 month as not solely dependent on high hematocrit (HCT). Thereafter, we identified increased erythropoiesis as a prothrombotic risk factor increased in the AMG 114 high-dose group with thrombotic toxicities, compared to a low-dose group with no toxicities but similar HCT. Here, we identified pleiotropic cytokines as prothrombotic factors associated with AMG 114 dose level. Before a high HCT was achieved, rats in the AMG 114 high, but not the low-dose group, had imbalanced hemostasis (increased von Willebrand factor and prothrombin time, decreased antithrombin III) coexistent with cytokines implicated in thrombosis: monocyte chemotactic protein 1 (MCP-1), MCP-3, tissue inhibitor of metalloproteinases 1, macrophage inhibitory protein-2, oncostatin M, T-cell-specific protein, stem cell factor, vascular endothelial growth factor, and interleukin-11. While no unique pathway to erythropoiesis stimulating agent-related thrombosis was identified, cytokines associated with increased erythropoiesis contributed to a prothrombotic intravascular environment in the AMG 114 high-dose group, but not in lower dose groups with a similar high HCT.

The bile salt export pump (BSEP) is expressed at the canalicular domain of hepatocytes, where it serves as the primary route of elimination for monovalent bile acids (BAs) into the bile canaliculi. The most compelling evidence linking dysfunction in BA transport with liver injury in humans is found with carriers of mutations that render BSEP nonfunctional. Based on mounting evidence, there appears to be a strong association between drug-induced BSEP interference and liver injury in humans; however, causality has not been established. For this reason, drug-induced BSEP interference is best considered a susceptibility factor for liver injury as other host- or drug-related properties may contribute to the development of hepatotoxicity. To better understand the association between BSEP interference and liver injury in humans, over 600 marketed or withdrawn drugs were evaluated in BSEP expressing membrane vesicles. The example of a compound that failed during phase 1 human trials is also described, AMG 009. AMG 009 showed evidence of liver injury in humans that was not predicted by preclinical safety studies, and BSEP inhibition was implicated. For 109 of the drugs with some effect on in vitro BSEP function, clinical use, associations with hepatotoxicity, pharmacokinetic data, and other information were annotated. A steady state concentration (C(ss)) for each of these annotated drugs was estimated, and a ratio between this value and measured IC₅₀ potency values were calculated in an attempt to relate exposure to in vitro potencies. When factoring for exposure, 95% of the annotated compounds with a C(ss)/BSEP IC₅₀ ratio ≥ 0.1 were associated with some form of liver injury. We then investigated the relationship between clinical evidence of liver injury and effects to multidrug resistance-associated proteins (MRPs) believed to play a role in BA homeostasis. The effect of 600+ drugs on MRP2, MRP3, and MRP4 function was also evaluated in membrane vesicle assays. Drugs with a C(ss)/BSEP IC₅₀ ratio ≥ 0.1 and a C(ss)/MRP IC₅₀ ratio ≥ 0.1 had almost a 100% correlation with some evidence of liver injury in humans. These data suggest that integration of exposure data, and knowledge of an effect to not only BSEP but also one or more of the MRPs, is a useful tool for informing the potential for liver injury due to altered BA transport.

The use of plasma membrane vesicles that overexpress the bile salt export pump (BSEP) or multidrug resistance-associated protein 2, 3, or 4 (MRP2-4) with an in vitro vacuum filtration system offers a rapid and reliable means for screening drug candidates for their effects on transporter function in hepatocytes and thus their potential for causing drug-induced liver injury (DILI). Comparison of transporter activity in the presence and absence of ATP allows for determination of a specific assay window for each transporter. This window is used to determine the degree to which each test compound inhibits transporter activity. This assay battery is helpful for prioritizing and rank-ordering compounds within a chemical series with respect to each other and in the context of known inhibitors of transporter activity and/or liver injury. This model can be used to influence the drug development process at an early stage and provide rapid feedback regarding the selection of compounds for advancement to in vivo safety evaluations. A detailed protocol for the high-throughput assessment of ABC transporter function is provided, including specific recommendations for curve-fitting to help ensure consistent results.

Anti-cancer therapy based on anthracyclines (DNA intercalating Topoisomerase II inhibitors) is limited by adverse effects of these compounds on the cardiovascular system, ultimately causing heart failure. Despite extensive investigations into the effects of doxorubicin on the cardiovascular system, the molecular mechanisms of toxicity remain largely unknown. MicroRNAs are endogenously transcribed non-coding 22 nucleotide long RNAs that regulate gene expression by decreasing mRNA stability and translation and play key roles in cardiac physiology and pathologies. Increasing doses of doxorubicin, but not etoposide (a Topoisomerase II inhibitor devoid of cardiovascular toxicity), specifically induced the up-regulation of miR-208b, miR-216b, miR-215, miR-34c and miR-367 in rat hearts. Furthermore, the lowest dosing regime (1 mg/kg/week for 2 weeks) led to a detectable increase of miR-216b in the absence of histopathological findings or alteration of classical cardiac stress biomarkers. In silico microRNA target predictions suggested that a number of doxorubicin-responsive microRNAs may regulate mRNAs involved in cardiac tissue remodeling. In particular miR-34c was able to mediate the DOX-induced changes of Sipa1 mRNA (a mitogen-induced Rap/Ran GTPase activating protein) at the post-transcriptional level and in a seed sequence dependent manner. Our results show that integrated heart tissue microRNA and mRNA profiling can provide valuable early genomic biomarkers of drug-induced cardiac injury as well as novel mechanistic insight into the underlying molecular pathways.

As one reflects back through the past 50 years of scientific research, a significant accomplishment was the advance into the genomic era. Basic research scientists have uncovered the genetic code and the foundation of the most fundamental building blocks for the molecular activity that supports biological structure and function. Accompanying these structural and functional discoveries is the advance of techniques and technologies to probe molecular events, in time, across environmental and chemical exposures, within individuals, and across species. The field of toxicology has kept pace with advances in molecular study, and the past 50 years recognizes significant growth and explosive understanding of the impact of the compounds and environment to basic cellular and molecular machinery. The advancement of molecular techniques applied in a whole-genomic capacity to the study of toxicant effects, toxicogenomics, is no doubt a significant milestone for toxicological research. Toxicogenomics has also provided an avenue for advancing a joining of multidisciplinary sciences including engineering and informatics in traditional toxicological research. This review will cover the evolution of the field of toxicogenomics in the context of informatics integration its current promise, and limitations.

Genome-wide gene expression profiling has become standard for assessing potential liabilities as well as for elucidating mechanisms of toxicity of drug candidates under development. Analysis of microarray data is often challenging due to the lack of a statistical model that is amenable to biological variation in a small number of samples. Here we present a novel non-parametric algorithm that requires minimal assumptions about the data distribution. Our method for determining differential expression consists of two steps: 1) We apply a nominal threshold on fold change and platform p-value to designate whether a gene is differentially expressed in each treated and control sample relative to the averaged control pool, and 2) We compared the number of samples satisfying criteria in step 1 between the treated and control groups to estimate the statistical significance based on a null distribution established by sample permutations. The method captures group effect without being too sensitive to anomalies as it allows tolerance for potential non-responders in the treatment group and outliers in the control group. Performance and results of this method were compared with the Significant Analysis of Microarrays (SAM) method. These two methods were applied to investigate hepatic transcriptional responses of wild-type (PXR(+/+)) and pregnane X receptor-knockout (PXR(-/-)) mice after 96 h exposure to CMP013, an inhibitor of β-secretase (β-site of amyloid precursor protein cleaving enzyme 1 or BACE1). Our results showed that CMP013 led to transcriptional changes in hallmark PXR-regulated genes and induced a cascade of gene expression changes that explained the hepatomegaly observed only in PXR(+/+) animals. Comparison of concordant expression changes between PXR(+/+) and PXR(-/-) mice also suggested a PXR-independent association between CMP013 and perturbations to cellular stress, lipid metabolism, and biliary transport.

The bile salt export pump (BSEP) is an efflux transporter, driving the elimination of endobiotic and xenobiotic substrates from hepatocytes into the bile. More specifically, it is responsible for the elimination of monovalent, conjugated bile salts, with little or no assistance from other apical transporters. Disruption of BSEP activity through genetic disorders is known to manifest in clinical liver injury such as progressive familial intrahepatic cholestasis type 2. Drug-induced disruption of BSEP is hypothesized to play a role in the development of liver injury for several marketed or withdrawn therapeutics. Unfortunately, preclinical animal models have been poor predictors of the liver injury associated with BSEP interference observed for humans, possibly because of interspecies differences in bile acid composition, differences in hepatobiliary transporter modulation or constitutive expression, as well as other mechanisms. Thus, a BSEP-mediated liver liability may go undetected until the later stages of drug development, such as during clinical trials or even postlicensing. In the absence of a relevant preclinical test system for BSEP-mediated liver injury, the toxicological relevance of available in vitro models to human health rely on the use of benchmark compounds with known clinical outcomes, such as marketed or withdrawn drugs. In this study, membrane vesicles harvested from BSEP-transfected insect cells were used to assess the activity of more than 200 benchmark compounds to thoroughly investigate the relationship between interference with BSEP function and liver injury. The data suggest a relatively strong association between the pharmacological interference with BSEP function and human hepatotoxicity. Although the most accurate translation of risk would incorporate pharmacological potency, pharmacokinetics, clearance mechanisms, tissue distribution, physicochemical properties, indication, and other drug attributes, the additional understanding of a compound's potency for BSEP interference should help to limit or avoid BSEP-related liver liabilities in humans that are not often detected by standard preclinical animal models.

The key to the discovery of new pharmaceuticals is to develop molecules that interact with the intended target and minimize interaction with unintended molecular targets, therefore minimizing toxicity. This is aided by the use of various in vitro selectivity assays that are used to select agents most potent for the desired target. Typically, molecules from similar chemical series, with similar in vitro potencies, are expected to yield comparable in vivo pharmacological and toxicological profiles, predictive of target effects. However, in this study, we investigated the in vivo effects of two analogue compounds that similarly inhibit several receptor tyrosine kinases such as vascular endothelial growth factor receptor 1 (VEGFR/Flt1), vascular endothelial growth factor 2 (VEGFR2/kinase domain receptor/Flk-1), vascular endothelial growth factor receptor 3 (VEGFR3/Flt4), platelet-derived growth factor receptor (PDGFR), and Kit receptors, which bear similar chemical structures, have comparable potencies, but differ markedly in their rodent toxicity profiles. Global gene expression data were used to generate hypotheses regarding the existence of toxicity triggers that would reflect the perturbation of signaling in multiple organs such as the liver, adrenal glands, and the pancreas in response to compound treatment. We concluded that differences in pharmacokinetic properties of the two analogues, such as volume of distribution, half-life, and organ concentrations, resulted in marked differences in the chemical burden on target organs and may have contributed to the vast differences in toxicity profiles observed with the two otherwise similar molecules. We propose including select toxicokinetic parameters such as V(ss), T(1/2), and T(max) as additional criteria that could be used to rank order compounds from the same pharmacological series to possibly minimize organ toxicity. Assessment of toxicokinetics is not an atypical activity on toxicology studies, even in early screening studies; however, these data may not always be used in decision making for selecting or eliminating one compound over another. Finally, we illustrate that in vivo gene expression profiles can serve as a complementary assessor of this activity and simultaneously help provide an assessment of on or off-target biological activity.

The comparability and reliability of data generated using microarray technology would be enhanced by use of a common set of standards that allow accuracy, reproducibility and dynamic range assessments on multiple formats. We designed and tested a complex biological reagent for performance measurements on three commercial oligonucleotide array formats that differ in probe design and signal measurement methodology. The reagent is a set of two mixtures with different proportions of RNA for each of four rat tissues (brain, liver, kidney and testes). The design provides four known ratio measurements of >200 reference probes, which were chosen for their tissue-selectivity, dynamic range coverage and alignment to the same exemplar transcript sequence across all three platforms. The data generated from testing three biological replicates of the reagent at eight laboratories on three array formats provides a benchmark set for both laboratory and data processing performance assessments. Close agreement with target ratios adjusted for sample complexity was achieved on all platforms and low variance was observed among platforms, replicates and sites. The mixed tissue design produces a reagent with known gene expression changes within a complex sample and can serve as a paradigm for performance standards for microarrays that target other species.

Molecular techniques, such as cDNA microarrays, are being used to aid in the elucidation of the mechanisms of toxicity of a variety of compounds. In this study, we evaluate the molecular effects of furan in the rat liver. Sprague-Dawley rats were exposed to 4 or 40 mg/kg furan for up to 14 days. Furan induced an initial degenerative and necrotic phenotype that was followed by inflammation and fibrosis, consistent with previous observations for this compound. RNA was harvested from each lobe of the liver at several time points to observe whether lobe-specific gene expression effects occurred. Similar gene expression changes were observed in all lobes, however the magnitude of gene expression change was more pronounced in the right lobe. Finally, to help determine the correlation between gene expression changes and liver pathology, we applied traditional microarray visualization tools to the assessment of clinical chemistry and pathology parameters.

Consistency and coherence of gene expression data across multiple sites depends on several factors such as platform (oligo, cDNA, etc.), environmental conditions at each laboratory, and data quality. The Hepatotoxicity Working Group of the International Life Sciences Institute Health and Environmental Sciences Institute consortium on the application of genomics to mechanism-based risk assessment is investigating these factors by comparing high-density gene expression data sets generated on two sets of RNA from methapyrilene (MP) experiments conducted at Abbott Laboratories and Boehringer-Ingelheim Pharmaceuticals, Inc. using a single platform (Affymetrix Rat Genome U34A GeneChip) at seven different sites. This article focuses on the evaluation of data quality and statistical models that facilitate the comparison of such data sets at the probe level. We present methods for exploring and quantitatively assessing differences in the data, with the principal goal being the generation of lists of site-insensitive genes responsive to low and high doses of MP. A combination of numerical and graphical techniques reveals important patterns and partitions of variability in the data, including the magnitude of the site effects. Although the site effects are significantly large in the analysis results, they appear to be primarily additive and therefore can be adjusted in the statistical calculations in a way that does not bias conclusions regarding treatment differences.

This study, designed and conducted as part of the International Life Sciences Institute working group on the Application of Genomics and Proteomics, examined the changes in the expression profile of genes associated with the administration of three different nephrotoxicants--cisplatin, gentamicin, and puromycin--to assess the usefulness of microarrays in the understanding of mechanism(s) of nephrotoxicity. Male Sprague-Dawley rats were treated with daily doses of puromycin (5-20 mg/kg/day for 21 days), gentamicin (2-240 mg/kg/day for 7 days), or a single dose of cisplatin (0.1-5 mg/kg). Groups of rats were sacrificed at various times after administration of these compounds for standard clinical chemistry, urine analysis, and histological evaluation of the kidney. RNA was extracted from the kidney for microarray analysis. Principal component analysis and gene expression-based clustering of compound effects confirmed sample separation based on dose, time, and degree of renal toxicity. In addition, analysis of the profile components revealed some novel changes in the expression of genes that appeared to be associated with injury in specific portions of the nephron and reflected the mechanism of action of these various nephrotoxicants. For example, although puromycin is thought to specifically promote injury of the podocytes in the glomerulus, the changes in gene expression after chronic exposure of this compound suggested a pattern similar to the known proximal tubular nephrotoxicants cisplatin and gentamicin; this prediction was confirmed histologically. We conclude that renal gene expression profiling coupled with analysis of classical end points affords promising opportunities to reveal potential new mechanistic markers of renal toxicity.

Assessment of the impact of xenobiotic exposure on human health and disease progression is complex. Knowledge of mode(s) of action, including mechanism(s) contributing to toxicity and disease progression, is valuable for evaluating compounds. Toxicogenomics, the subdiscipline which merges genomics with toxicology, holds the promise to contributing significantly toward the goal of elucidating mechanism(s) by studying genome-wide effects of xenobiotics. Global gene expression profiling, revolutionized by microarray technology and a crucial aspect of a toxicogenomic study, allows measuring transcriptional modulation of thousands of genes following exposure to a xenobiotic. We use our results from previous studies on compounds representing two different classes of xenobiotics (barbiturate and peroxisome proliferator) to discuss the application of computational approaches for analyzing microarray data to elucidate mechanism(s) underlying cellular responses to toxicants. In particular, our laboratory demonstrated that chemical-specific patterns of gene expression can be revealed using cDNA microarrays. Transcript profiling provides discrimination between classes of toxicants, as well as, genome-wide insight into mechanism(s) of toxicity and disease progression. Ultimately, the expectation is that novel approaches for predicting xenobiotic toxicity in humans will emerge from such information.

Human exposure to arsenic, a ubiquitous and toxic environmental pollutant, is associated with an increased incidence of skin cancer. However, the mechanism(s) associated with AsIII-mediated toxicity and carcinogenesis at low levels of exposure remains elusive. Aberrations in cell proliferation, oxidative damage, and DNA-repair fidelity have been implicated in sodium arsenite (AsIII)-mediated carcinogenicity and toxicity, but these events have been examined in isolation in the majority of biological models of arsenic exposure. We hypothesized that the simultaneous interaction of these effects may be important in arsenic-mediated neoplasia in the skin. To evaluate this, normal human epidermal keratinocytes (NHEK) were exposed to nontoxic doses (0.005-5 micro M) of AsIII and monitored for several physiological endpoints at the times when cells were harvested for gene expression measurements (1-24 h). Two-fluor cDNA microarray analyses indicated that AsIII treatment decreased the expression of genes associated with DNA repair (e.g., p53 and Damage-specific DNA-binding protein 2) and increased the expression of genes indicative of the cellular response to oxidative stress (e.g., Superoxide dismutase 1, NAD(P)H quinone oxidoreductase, and Serine/threonine kinase 25). AsIII also modulated the expression of certain transcripts associated with increased cell proliferation (e.g., Cyclin G1, Protein kinase C delta), oncogenes, and genes associated with cellular transformation (e.g., Gro-1 and V-yes). These observations correlated with measurements of cell proliferation and mitotic measurements as AsIII treatment resulted in a dose-dependent increase in cellular mitoses at 24 h and an increase in cell proliferation at 48 h of exposure. Data in this manuscript demonstrates that AsIII exposure simultaneously modulates DNA repair, cell proliferation, and redox-related gene expression in nontransformed, normal NHEK. It is anticipated that data in this report will serve as a foundation for furthering our knowledge of AsIII-regulated gene expression in skin and other tissues and contribute to a better understanding of arsenic toxicity and carcinogenesis.

Skin is a major target of oxidative stress due to reactive oxygen species (ROS) that originate in the environment and in the skin itself. ROS are generated during normal metabolism, are an integral part of normal cellular function, and are usually of little harm because of intracellular mechanisms that reduce their damaging effects. Antioxidants attenuate the damaging effects of ROS and can impair and/or reverse many of the events that contribute to epidermal toxicity and disease. However, increased or prolonged free radical action can overwhelm ROS defense mechanisms, contributing to the development of cutaneous diseases and disorders. Although ROS play a role in diseases such as skin cancer, their biological targets and pathogenic mode of action are still not fully understood. In addition, strategies useful in the therapeutic management of ROS action in human skin are still lacking. This review is intended to give investigators an introduction to ROS, antioxidants, two skin disorders influenced by ROS action (skin cancer and psoriasis), and relevant model systems used to study ROS action.

Methapyrilene (MP) exposure of animals can result in an array of adverse pathological responses including hepatotoxicity. This study investigates gene expression and histopathological alterations in response to MP treatment in order to 1) utilize computational approaches to classify samples derived from livers of MP treated rats based on severity of toxicity incurred in the corresponding tissue, 2) to phenotypically anchor gene expression pattems, and 3) to gain insight into mechanism(s) of methapyrilene hepatotoxicity. Large-scale differential gene expression levels associated with the exposure of male Sprague-Dawley rats to the rodent hepatic carcinogen MP for 1, 3, or 7 days after daily dosage with 10 or 100 mg/kg/day were monitored. Hierarchical clustering and principal component analysis were successful in classifying samples in agreement with microscopic observations and revealed low-dose effects that were not observed histopathologically. Data from cDNA microarray analysis corroborated observed histopathological alterations such as hepatocellular necrosis, bile duct hyperplasia, microvesicular vacuolization, and portal inflammation observed in the livers of MP exposed rats and provided insight into the role of specific genes in the studied toxicological processes.

In this investigation we used statistical methods to select genes with expression profiles that partition classes and subclasses of biological samples. Gene expression data corresponding to liver samples from rats treated for 24 h with an enzyme inducer (phenobarbital) or a peroxisome proliferator (clofibrate, gemfibrozil or Wyeth 14,643) were subjected to a modified Z-score test to identify gene outliers and a binomial distribution to reduce the probability of detecting genes as differentially expressed by chance. Hierarchical clustering of 238 statistically valid differentially expressed genes partitioned class-specific gene expression signatures into groups that clustered samples exposed to the enzyme inducer or to peroxisome proliferators. Using analysis of variance (ANOVA) and linear discriminant analysis methods we identified single genes as well as coupled gene expression profiles that separated the phenobarbital from the peroxisome proliferator treated samples and discerned the fibrate (gemfibrozil and clofibrate) subclass of peroxisome proliferators. A comparison of genes ranked by ANOVA with genes assessed as significant by mixedlinear models analysis [J. Comput. Biol. 8 (2001) 625] or ranked by information gain revealed good congruence with the top 10 genes from each statistical method in the contrast between phenobarbital and peroxisome proliferators expression profiles. We propose building upon a classification regimen comprised of analysis of replicate data, outlier diagnostics and gene selection procedures to utilize cDNA microarray data to categorize subclasses of samples exposed to pharmacologic agents.

DNA microarrays, used to measure the gene expression of thousands of genes simultaneously, hold promise for future application in efficient screening of therapeutic drugs. This will be aided by the development and population of a database with gene expression profiles corresponding to biological responses to exposures to known compounds whose toxicological and pathological endpoints are well characterized. Such databases could then be interrogated, using profiles corresponding to biological responses to drugs after developmental or environmental exposures. A positive correlation with an archived profile could lead to some knowledge regarding the potential effects of the tested compound or exposure. We have previously shown that cDNA microarrays can be used to generate chemical-specific gene expression profiles that can be distinguished across and within compound classes, using clustering, simple correlation, or principal component analyses. In this report, we test the hypothesis that knowledge can be gained regarding the nature of blinded samples, using an initial training set comprised of gene expression profiles derived from rat liver exposed to clofibrate, Wyeth 14,643, gemfibrozil, or phenobarbital for 24 h or 2 weeks of exposure. Highly discriminant genes were derived from our database training set using approaches including linear discriminant analysis (LDA) and genetic algorithm/K-nearest neighbors (GA/KNN). Using these genes in the analysis of coded liver RNA samples derived from 24-h, 3-day, or 2-week exposures to phenytoin, diethylhexylpthalate, or hexobarbital led to successful prediction of whether these samples were derived from livers of rats exposed to enzyme inducers or to peroxisome proliferators. This validates our initial hypothesis and lends credibility to the concept that the further development of a gene expression database for chemical effects will greatly enhance the hazard identification processes.

The application of gene expression profiling technology to examine multiple genes and signaling pathways simultaneously promises a significant advance in understanding toxic mechanisms to ultimately aid in protection of public health. Public and private efforts in the new field of toxicogenomics are focused on populating databases with gene expression profiles of compounds where toxicological and pathological endpoints are well characterized. The validity and utility of a toxicogenomics is dependent on whether gene expression profiles that correspond to different chemicals can be distinguished. The principal hypothesis underlying a toxicogenomic or pharmacogenomic strategy is that chemical-specific patterns of altered gene expression will be revealed using high-density microarray analysis of tissues from exposed organisms. Analyses of these patterns should allow classification of toxicants and provide important mechanistic insights. This report provides a verification of this hypothesis. Patterns of gene expression corresponding to liver tissue derived from chemically exposed rats revealed similarity in gene expression profiles between animals treated with different agents from a common class of compounds, peroxisome proliferators [clofibrate (ethyl-p-chlorophenoxyisobutyrate), Wyeth 14,643 ([4-chloro-6(2,3-xylidino)-2-pyrimidinylthio]acetic acid), and gemfibrozil (5-2[2,5-dimethylphenoxy]2-2-dimethylpentanoic acid)], but a very distinct gene expression profile was produced using a compound from another class, enzyme inducers (phenobarbital).

Toxicogenomics is a rapidly developing discipline that promises to aid scientists in understanding the molecular and cellular effects of chemicals in biological systems. This field encompasses global assessment of biological effects using technologies such as DNA microarrays or high throughput NMR and protein expression analysis. This review provides an overview of advancing multiple approaches (genomic, proteomic, metabonomic) that may extend our understanding of toxicology and highlights the importance of coupling such approaches with classical toxicity studies.

The use of DNA microarrays has spanned numerous disciplines of life science research. Despite the volume of studies utilizing this technology, no consensus exists on basic issues such as the determination of significantly altered genes in a given experiment, often leading to either false-negative or false-positive data. In this report, we study the effect of dilution of biological alterations on the detection level of gene expression differences using cDNA microarrays. We propose that subtle alterations in transcript levels of genes below the 2-fold level should be considered when replicate hybridizations are performed, because these subtle gene expression changes may be due to a robust response in few cells. We measured the effect of dilution of gene expression and found that differences in gene expression between the two cell lines assayed (HaCaT and MCF-7) were detected even after a 20-fold dilution factor. These results better our understanding of biological alterations that comprise a relatively small percentage of an assayed organ and help in the interpretation of gene expression data.

Phenobarbital (PB) induces various gene encoding drug/steroid-metabolizing enzymes such as cytochromes P450 (P450s) and transferases. Although the nuclear orphan constitutive active receptor (CAR) has been identified as a key transcription factor that regulates the induction of CYP2B, the full scope of CAR-regulated genes still remains a major question. To this end, reverse transcriptase-polymerase chain reaction and cDNA microarray techniques were employed to examine gene expression in wild-type and CAR-null mice. The results show that a total of 138 genes were detected to be either induced or repressed in response to PB treatment, of which about half were under CAR regulation. Including CYP2B10, CYP3A11, and NADPH-CYP reductase, CAR regulated a group of the PB-induced drug/steroid-metabolizing enzymes. Enzymes such as amino levulinate synthase 1 and squalene epoxidase displayed CAR-independent induction by PB. Cyp4a10 and Cyp4a14 represented the group of genes induced by PB only in CAR-null mice, indicating that CAR may be a transcription blocker that prevents these genes from being induced by PB. Additionally, the group of genes encoding enzymes and proteins involved in basic biological processes such as energy metabolism underwent the CAR-dependent repression by PB. Thus, CAR seems to have diverse roles, both as a positive and negative regulator, in the regulation of hepatic genes in response to PB beyond drug/steroid metabolism.

Microarray technology has been applied to a variety of different fields to address fundamental research questions. The use of microarrays, or DNA chips, to study the gene expression profiles of biologic samples began in 1995. Since that time, the fundamental concepts behind the chip, the technology required for making and using these chips, and the multitude of statistical tools for analyzing the data have been extensively reviewed. For this reason, the focus of this review will be not on the technology itself but on the application of microarrays as a research tool and the future challenges of the field.

Toxicogenomics is a term that represents the merging of toxicology with novel genomics techniques. Data generated in the new-age era of toxicology is relatively complex, requires new bioinformatics tools for adequate interpretation, and allows for the rapid generation of testable hypotheses. Hazard identification and risk assessment processes will advance from the use of genomics techniques, which will lead to greater understanding of mechanism(s) of action of toxicants, development of novel biomarkers of exposure and effect, and better identification of sensitive subpopulations., (Copyright 2001 John Wiley & Sons, Inc. *This article is a US Government work and, as such, is in the public domain in the United States of America.)

The antitumor protein p53 plays a critical role in DNA repair. Inorganic arsenic exposure is associated with a wide variety of human tumors, particularly of the skin. To investigate how inorganic arsenic might interfere with DNA repair and lead to greater incidence of hyperkeratosis and skin tumors, we exposed human keratinocytes (HaCaT) to environmentally relevant concentrations of arsenite for 14 days. Arsenite reduced p53 levels while concomitantly increasing the p53 regulatory protein mdm2 levels in a dose- and time-dependent manner. We propose the disruption of the p53-mdm2 loop regulating cell cycle arrest as a model for arsenic-related skin carcinogenesis and it may be important in tumors with elevated mdm2 levels., (Copyright 1999 Academic Press.)

Arsenic is a ubiquitous contaminant of drinking water and food. The mechanisms of the toxic action of inorganic arsenic are unknown. We report the isolation of proteins having a high affinity for arsenic in the +3 oxidation state that are induced by arsenite (AsIII) in human lymphoblastoid cells. The arsenic-binding proteins were isolated using a p-aminophenylarsine oxide affinity column. At least four proteins of 50, 42, 38.5 and 19.5 kDa were isolated by elution with 10 or 100 mM 2-mercaptoethanol. Two proteins were tentatively identified as tubulin and actin on the basis of their molecular weights and previously reported affinity for the arsenic column. The identities of the remaining proteins are unknown. Heme oxygenase 1 was induced by AsIII but did not bind to the arsenic affinity column. We conclude that AsIII induces multiple proteins that have variable affinities for arsenic in the +3 state as judged by the concentration of 2-mercaptoethanol required for their elution. The arsenic binding motif of these proteins may involve three thiol groups arranged 3-6 A apart by the tertiary structure of the protein as suggested by others. These proteins may serve as high affinity binding sites for AsIII and may be involved in the biological action of AsIII.