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PubMed2006

DNA microarray technology in toxicogenomics of aquatic models: methods and applications.

Toxicogenomics represents the merging of toxicology with genomics and bioinformatics to investigate biological functions of genome in response to environmental contaminants. Aquatic species have traditionally been used as models in toxicology to characterize the actions of environmental stresses. Recent completion of the DNA sequencing for several fish species has spurred the development of DNA microarrays allowing investigators access to toxicogenomic approaches. However, since microarray technology is thus far limited to only a few aquatic species and derivation of biological meaning from microarray data is highly dependent on statistical arguments, the full potential of microarray in aquatic species research has yet to be realized. Herein we review some of the issues related to construction, probe design, statistical and bioinformatical data analyses, and current applications of DNA microarrays. As a model a recently developed medaka (Oryzias latipes) oligonucleotide microarray was described to highlight some of the issues related to array technology and its application in aquatic species exposed to hypoxia. Although there are known non-biological variations present in microarray data, it remains unquestionable that array technology will have a great impact on aquatic toxicology. Microarray applications in aquatic toxicogenomics will range from the discovery of diagnostic biomarkers, to establishment of stress-specific signatures and molecular pathways hallmarking the adaptation to new environmental conditions.

Animals↗

PubMed2004

Development of public toxicogenomics software for microarray data management and analysis.

A robust bioinformatics capability is widely acknowledged as central to realizing the promises of toxicogenomics. Successful application of toxicogenomic approaches, such as DNA microarray, inextricably relies on appropriate data management, the ability to extract knowledge from massive amounts of data and the availability of functional information for data interpretation. At the FDA's National Center for Toxicological Research (NCTR), we are developing a public microarray data management and analysis software, called ArrayTrack. ArrayTrack is Minimum Information About a Microarray Experiment (MIAME) supportive for storing both microarray data and experiment parameters associated with a toxicogenomics study. A quality control mechanism is implemented to assure the fidelity of entered expression data. ArrayTrack also provides a rich collection of functional information about genes, proteins and pathways drawn from various public biological databases for facilitating data interpretation. In addition, several data analysis and visualization tools are available with ArrayTrack, and more tools will be available in the next released version. Importantly, gene expression data, functional information and analysis methods are fully integrated so that the data analysis and interpretation process is simplified and enhanced. ArrayTrack is publicly available online and the prospective user can also request a local installation version by contacting the authors.

Databases, Genetic↗

PubMed2005

Toxicogenomics in the pharmaceutical industry: hollow promises or real benefit?

Almost 10 years ago, microarray technology was established as a new powerful tool for large-scale analysis of gene expression. Soon thereafter the new technology was discovered by toxicologists for the purpose of deciphering the molecular events underlying toxicity, and the term "Toxicogenomics" appeared in scientific literature. Ever since, the toxicology community was fascinated by the multiplicity of sophisticated possibilities toxicogenomics seems to offer: genome-wide analysis of toxicant-induced expression profiles may provide a means for prediction of toxicity prior to classical toxicological endpoints such as histopathology or clinical chemistry. Some researchers even speculated of the classical methods being superfluous before long. It was assumed that by using toxicogenomics it would be possible to classify compounds early in drug development and consequently save animals, time, and money in pre-clinical toxicity studies. Moreover, it seemed within reach to unravel the molecular mechanisms underlying toxicity. The feasibility of bridging data derived from in vitro and in vivo systems, identifying new biomarkers, and comparing toxicological responses "across-species" was also excessively praised. After several years of intensive application of microarray technology in the field of toxicology, not only by the pharmaceutical industry, it is now time to survey its achievements and to question how many of these wishes and promises have really come true.

Animals↗

PubMedDate not supplied

Mapping molecular responses to xenoestrogens through Gene Ontology and pathway analysis of toxicogenomic data.

The recent sequencing of mammalian genomes has driven the development of genomic technologies, including microarray-based gene expression profiling, that allow simultaneous measurement of the expression levels of thousands of genes. Gene expression profiling applied to toxicology (toxicogenomics) has the potential to reveal, holistically, the molecular pathways and cellular processes that mediate the adverse responses to a toxicant. However, the initial output of a toxicogenomics experiment consists of a list of genes whose expression is altered upon toxicant exposure. In order to interpret these data in a biological context, new bioinformatic methods must be developed to place gene expression changes in the context of the underlying pathways and processes affected. One emerging approach is the application of Gene Ontology (GO) mapping and pathway analysis to gene expression profiling data. The utility of this in mechanistic toxicology will be illustrated using examples in which GO mapping of toxicogenomic data has provided novel insights into the molecular mechanisms induced by exposure to xenoestrogens.

Animals↗

PubMed2005

Toxicogenomic analysis methods for predictive toxicology.

Toxicogenomics, the application of genomic data to elucidate or predict an organism's response to a toxicant, can inform the drug development process in important ways. It is apparent that standardized approaches to many types of toxicogenomic questions are still being formulated. Specifically, a significant body of proof of principle studies has emerged that demonstrates a range of statistical methodologies applied to predictive toxicology. These studies rely on class prediction methods--mathematical models generated using the gene expression profiles of known toxins from representative toxicological classes--to predict the toxicological effect of a compound based on the similarities between its gene expression profile and the profiles of a given toxicological class. Class prediction methods hold promise for increasing the rate at which compounds can be evaluated for toxicity early in the drug discovery process, while at the same time reducing the length of toxicological studies and their associated costs. Class prediction methods are informed by class comparison and class discovery steps, which inform, respectively, the selection of genes whose response can be used to distinguish among the toxicological classes and the number of classes distinguishable using the response of these genes. Together these steps use a variety of complementary statistical techniques to achieve a successful class prediction model. This report attempts to review some of the themes that appear to be emerging in the application of these techniques to predictive toxicology methods over toxicogenomics' short history.

Animals↗

PubMedDate not supplied

Toxicogenomics in drug development.

Toxicogenomics represents the merging of toxicology with technologies that have been developed, together with bioinformatics, to identify and quantify global gene expression changes. It represents a new paradigm in drug development and risk assessment, which promises to generate a wealth of information towards an increased understanding of the molecular mechanisms that lead to drug toxicity and efficacy, and of DNA polymorphisms responsible for individual susceptibility to toxicity. Gene expression profiling, through the use of DNA microarray and proteomic technologies will aid in establishing links between expression profiles, mode of action and traditional toxic endpoints. Such patterns of gene expression, or 'molecular fingerprints' could be used as diagnostic or predictive markers of exposure, that is characteristic of a specific mechanism of induction of that toxic or efficacious effect. It is anticipated that toxicogenomics will be increasingly integrated into all phases of the drug development process particularly in mechanistic and predictive toxicology, and biomarker discovery. This review provides an overview of the expression profiling technologies applied in toxicogenomics. and discusses the promises as well as the future challenges of applying this discipline to the drug development process.

Animals↗

PubMed2000

Toxicogenomics-based discrimination of toxic mechanism in HepG2 human hepatoma cells.

The rapid discovery of sequence information from the Human Genome Project has exponentially increased the amount of data that can be retrieved from biomedical experiments. Gene expression profiling, through the use of microarray technology, is rapidly contributing to an improved understanding of global, coordinated cellular events in a variety of paradigms. In the field of toxicology, the potential application of toxicogenomics to indicate the toxicity of unknown compounds has been suggested but remains largely unsubstantiated to date. A major supposition of toxicogenomics is that global changes in the expression of individual mRNAs (i.e., the transcriptional responses of cells to toxicants) will be sufficiently distinct, robust, and reproducible to allow discrimination of toxicants from different classes. Definitive demonstration is still lacking for such specific "genetic fingerprints," as opposed to nonspecific general stress responses that may be indistinguishable between compounds and therefore not suitable as probes of toxic mechanisms. The present studies demonstrate a general application of toxicogenomics that distinguishes two mechanistically unrelated classes of toxicants (cytotoxic anti-inflammatory drugs and DNA-damaging agents) based solely upon a cluster-type analysis of genes differentially induced or repressed in cultured cells during exposure to these compounds. Initial comparisons of the expression patterns for 100 toxic compounds, using all approximately 250 genes on a DNA microarray ( approximately 2.5 million data points), failed to discriminate between toxicant classes. A major obstacle encountered in these studies was the lack of reproducible gene responses, presumably due to biological variability and technological limitations. Thus multiple replicate observations for the prototypical DNA damaging agent, cisplatin, and the non-steroidal anti-inflammatory drugs (NSAIDs) diflunisal and flufenamic acid were made, and a subset of genes yielding reproducible inductions/repressions was selected for comparison. Many of the "fingerprint genes" identified in these studies were consistent with previous observations reported in the literature (e. g., the well-characterized induction by cisplatin of p53-regulated transcripts such as p21(waf1/cip1) and PCNA [proliferating cell nuclear antigen]). These gene subsets not only discriminated among the three compounds in the learning set but also showed predictive value for the rest of the database ( approximately 100 compounds of various toxic mechanisms). Further refinement of the clustering strategy, using a computer-based optimization algorithm, yielded even better results and demonstrated that genes that ultimately best discriminated between DNA damage and NSAIDs were involved in such diverse processes as DNA repair, xenobiotic metabolism, transcriptional activation, structural maintenance, cell cycle control, signal transduction, and apoptosis. The determination of genes whose responses appropriately group and dissociate anti-inflammatory versus DNA-damaging agents provides an initial paradigm upon which to build for future, higher throughput-based identification of toxic compounds using gene expression patterns alone.

Algorithms↗

PubMed2005

Toxicogenomics: regulatory perspective on current position.

Published studies on the utility of toxicogenomic approaches (transcriptomics, proteomics and metabonomics) in screening for toxicological mechanisms and evaluation of dose response effects have been reviewed. The information supports the use of transcriptomics to screen for specific toxicological mechanisms for which there is an a priori hypothesis, although in some areas such as mutagenicity testing, toxicogenomics appear to have limited value for identifying mutagens. Data from such screening approaches cannot be used to exclude the possibility of toxicity. Targeted transcriptomics might be valuable for screening for specific mechanisms of toxicity considered to be irrelevant for assessing risk to humans, which would help to reduce the need for detailed testing of some chemicals. An integrated approach is suggested where data from more than one toxicogenomic approach could be used as an adjunct to conventional toxicology to assess dose-response in toxicological tests. An outline preliminary proposal for use by regulators is suggested although it is noted that more data are required before this could be formally used in a decision-making process.

Animals↗

PubMed2002

Application of toxicogenomics to drug development.

The application of advanced modern biomedical and chemical research technologies in the pharmaceutical industry has led to a significant increase in the number of potential drug targets and lead candidates. Whereas the drug discovery process is enhanced significantly, the failure rate of new compounds due to toxicity remains very high. The pharmaceutical industry is setting high hopes on the new discipline of toxicogenomics to revolutionize the process of drug toxicity assessment by reducing the bottleneck of new drug candidates and minimizing late-stage developmental failures. Toxicogenomics is expected to facilitate the efficient screening of new compounds at an early stage, resulting in significant savings of time and cost associated with new drug development. In this review, a general description of the new discipline of toxicogenomics and its potential impact on the safety assessment of new drugs in the pharmaceutical industry is provided. An overview of the key issues and questions that are confronting investigators in this field today is also given as well as a prospective view of the future of this new discipline.

Drug Design↗

PubMed2003

Informatics and multivariate analysis of toxicogenomics data.

The application of genomics methods to toxicology holds great promise. Toxicogenomics data mapping gene expression to predict toxicity and understand mechanisms are emerging, with data suggesting the possibility to classify, and eventually predict, toxic responses. The overall process of informatics analysis of microarray data is summarized. The relationship between the bioinformatics of gene expression and toxicogenomics is discussed, with reference to emerging themes that may be important as the field of toxicogenomics evolves. Emerging themes include the choice and validation of statistical methods, the use of gene annotation and the impact of genome sequence projects.

Animals↗

PubMed2002

[Toxicogenomics--a new paradigm of toxicology and birth of reverse toxicology].

Toxicogenomics is, similar to other genome science fields, based on DNA microarray and/or DNA chip technologies, which has enabled a large number of gene expressions, thus, have been applied to such functional genomics as pharmacogenomics, oncogenomics, proteomics, metabonomics, etc. Toxicogenomics has advantages such as deducing the number of test animals and the test period, and adopts simpler techniques using new biomarkers. What toxicogenomics can offer to conventional toxicology is given herein.

Computational Biology↗

PubMed2003

Application of toxicogenomic analysis to risk assessment of delayed long-term effects of multiple chemicals, including endocrine disruptors in human fetuses.

Our previous studies analyzing umbilical cords show that human fetuses in Japan are exposed to multiple chemicals. Because of these findings, we believe it is necessary to establish a new strategy for examining the possible delayed long-term effects caused by prenatal exposure to multiple chemical combinations and evaluating the health risk to human fetuses. In this commentary we describe our attempts to apply toxicogenomic analysis of umbilical cords, using DNA microarray for future risk assessment. Because the umbilical cord is part of the fetal tissue, it is possible to estimate the effects of chemicals on the fetus by analyzing alteration of the gene expression. This type of toxicogenomic analysis could be a powerful and effective tool for developing a new risk assessment strategy to help investigators understand and possibly prevent long-term effects caused by fetal exposure to multiple chemicals. Worldwide cooperation is needed to establish a new stragegy for risk assessment using toxicogenomic analysis that focuses on the human fetus.

Animals↗

PubMed2004

[Toxicogenomics. New perspectives for the molecular toxicology].

Gene expression in the cellular genome is subject to changes caused by internal and external factors. Due to different expression of gene sets (polymorphism), cells show different morphological and functional characteristics. Environmental and occupational toxic agents may influence cells at the level of transcription and translation. The functional toxicogenomics attempts to explain those influences. Due to recent developments in molecular biology and bioinformatics, it has become possible to analyze protein transcript (toxicogenomics) and profile (toxicoproteomics). This work reports new opportunities to study gene sequencing and expression by means of the DNA chip technique (rapid analysis of the genetic polymorphism) and the microarrays technique (simultaneous analysis of hundreds or thousands of genes). The authors report examples of some practical applications of toxicogenomics in the assessment of the effects of pathological exposures to environmental and occupational toxic (carcinogenic, hepatotoxic and/or neurotoxic) agents, due to the development of new groups of biomarkers, such as biomarkers of individual susceptibility, biomarkers of toxic effects combined with the assay of the relationship between a toxic agent and its dose, and the effect measured at the level of the cellular genome and results of histopathological and biochemical tests.

Carcinogens, Environmental↗

PubMed2004

Construction of a data dependent analysis (DDA) yeast cDNA microarray experiment for use in toxicogenomics.

DNA microarrays are becoming increasingly popular in toxicogenomic studies. It is common knowledge that multiple repeats of microarray experiments have to be performed with multiple samples to get reliable data, due to experimental variations (both technical and biological) contained in microarray experiments. However, the use of multiple samples and replicate experiments is not practical in the field of environmental toxicology, since environmental samples are limited and microarray experiments are expensive. Thus it is desirable to obtain reliable data from a minimum number of repeats of microarray experiments. To further establish and extend gene expression profiling for toxicogenomics using microarrays, it is necessary to establish an analytical method of microarrays for toxicogenomics. In this study, we attempted to construct a "Data Dependent Analysis (DDA)" yeast cDNA microarray experiment from 100 microarray datasets in order to get reliable data from one microarray experiment.

Carbocyanines↗

PubMed2005

The use of toxicogenomic data in risk assessment: a regulatory perspective.

Recent advances in genomic research have provided new insights into mechanisms of toxicity evoked by drugs or xenobiotics. Several governmental and commercial organizations are at present actively building up databases containing large amounts of toxicogenomics information. With promises to improve our ability to characterize hazard, scientists are facing the challenge as to how to link patterns of gene expression and gene clustering to specific adverse effects of toxicants or classes of toxicants. The future of toxicogenomics lies in the robustness of the databases generated. Regulators are working together with institutes and industry in exploring the potential use of these databases in regulatory purposes. It is, however, anticipated that regulatory use of the toxicogenomic databases as supportive information in the assessment procedure of new drug applications will be on a case-by-case basis until the predictive value of the databases is firmly established.

Biomarkers↗

PubMed2025

BMDx2: A Tool for Integrating Toxicogenomics-Based Dose-Dependency Analysis and AOP-Based Mechanistic Insights.

Despite the advent of mechanistic toxicology using omics data to link molecular perturbations with systemic outcomes, regulatory toxicology still lacks the application of mechanism-anchored metrics from such data. This is partially because traditional gene-centric analysis often falls short of linking molecular changes to adverse outcomes. To address this gap, BMDx2, an open-source tool that transforms multi-dose toxicogenomics datasets into quantitative, mechanistic evidence for human chemical safety assessment is developed. BMDx2 couples benchmark-dose modeling with Adverse Outcome Pathway (AOP) enrichment to derive transcriptomic-based points of departure, enabling potency ranking, chemical prioritization, and mechanistically anchored explanations of the effect of chemical exposures. BMDx2 can process a broad range of data, including DNA microarray and RNA sequencing studies. Here, case studies are used to illustrate the versatility of BMDx2 in characterizing the mechanism of action of chemicals. An initial case study on carbon nanotubes exposure applies integrative analysis of transcriptomics and genome-wide DNA methylation data, uncovering cellular reprogramming processes underlying fibrosis. A second case study on bleomycin exposure demonstrate how transcriptomic data alone can be mapped to fibrosis-related AOPs in a standardized, regulatory appropriate manner. Together, these examples show how BMDx2 supports the regulatory application of toxicogenomics and accelerates mechanism-based chemical safety evaluation.

Toxicogenetics↗

PubMed2006

Toxicogenomics in drug discovery and drug development: potential applications and future challenges.

Despite the massive investments made by pharmaceutical companies on drug research and development, the number of new drug approvals has remained stagnant in the past decades. It is well known that developing safe and effective new drugs is a long, difficult, and expensive process. While the cost of developing new drugs is increasing rapidly, withdrawals of drugs from the marketplace due to adverse drug reactions (ADR) and/or toxicity is increasing concurrently. The recent advent of high-throughput in silico (computer softwares) and in vitro (cell cultures) screenings have somewhat alleviated some, but not all, of these challenges by providing an efficient and effective way for developing safer and better drugs. This emerging technology, known as toxicogenomics, has great potential to facilitate the development of methodologies that could predict the long-term toxic effects of compounds using relatively short-term bioassays. This review is aimed at discussing the potential applications and future challenges of toxicogenomics in drug discovery and drug development.

Animals↗

PubMed2004

Long-term alteration of gene expression without morphological change in testis after neonatal exposure to genistein in mice: toxicogenomic analysis using cDNA microarray.

In this study, we carried out toxicogenomic analysis using in-house cDNA microarray to ascertain the long-term effects of neonatal exposure to genistein, also known as phytoestrogen, on testicular gene expression in mice. Male ICR mice, 1 day after birth, were exposed for 5 days to genistein (1000 microg/mouse/day) or diethylstilbestrol (DES) (50 microg/mouse/day), used as an example of a potent estrogen, and their testes were used when they were 12 weeks old. Since exposure to DES was been reported to induce morphological changes and alteration of gene expression in reproductive organs, DES was used as a positive control. Genistein-treated mice did not show any histological abnormalities or increased apoptotic cells in testes, but these abnormalities and increases were found in DES-treated mice. On the other hand, mRNA expression analysis using in-house cDNA microarray revealed that 2 down-regulated genes (GeneBank accession No. W49392 and AI430907) were detected in genistein-treated mouse testes. Moreover, real-time PCR analysis revealed that mRNAs of the W49392 gene, estrogen receptor alpha (ERalpha) and androgen receptor (AR), were down-regulated in the testes of both genistein-treated and DES-treated mice. In our present study using toxicogenomic analysis, long-term alteration in testicular mRNA expression, without morphological change in testes, was detected after neonatal treatment with genistein, indicating that the W49392 gene, in addition to ERalpha and AR, might be useful as a biological marker for predicting the effects of neonatal exposure to DES and genistein.

Animals↗