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[New effect biomarkers].

The major research goals for researchers developing biomarkers of effect are the development and validation of biomarkers that permit the prediction of the risk of disease in individuals and groups. One important objective is to prevent human cancer. This article reviews the most recent analytical methodologies, validation studies and field trials together with auditing and quality assessment of the necessary data based on scientific grounds. Consideration is given to new developments in the relatively young field of toxicogenomics, possibly leading to the identification of early changes that may lead to both cancer and non-cancer end points. Although the creation and development of reliable databases integrating information from genomic and proteomic research programmes should offer a contribution to the prediction of risks and prevention of diseases related to chemical exposure, the most promising future application of these technologies lies in the molecular diagnosis of diseases whose nosography will probably be redefined.

Biomarkers↗
PubMed2004

Genomic and proteomic profiling for biomarkers and signature profiles of toxicity.

Toxicity profiling measures and compares all gene expression changes among biological samples after toxicant exposure. Toxicity profiling with DNA microarrays to measure all mRNA transcripts (transcriptomics), or by global separation and identification of proteins (proteomics), has led to the discovery of better descriptors of toxicity, toxicant classification and exposure monitoring than current indicators. A shared goal in transcript and proteomic profiling is the development of biomarkers and signatures of chemical toxicity. In this review, biomarkers and signature profiles are described for specific chemical toxicants that affect target organs such as liver, kidney, neural tissues, gastrointestinal tract and skeletal muscle, for specific disease models such as cancer and inflammation, and for unique chemical-protein adducts underlying cell injury. The recent introduction of toxicogenomics databases support researchers in sharing, analyzing, visualizing and mining expression data, assist the integration of transcriptomics, proteomics and toxicology datasets, and eventually will permit in silico biomarker and signature pattern discovery.

Animals↗
PubMed2004

Gels and more gels: probing toxicity.

Two-dimensional electrophoresis (2-DE) remains an important technology in the study of protein expression. In many applications, 2-DE has been supplanted by liquid chromatographic and mass spectrometric approaches that overcome some of its limitations and labor intensiveness. Nevertheless, 2-DE has exceptional relevance in toxicology and, despite the challenges, its implementation continues to support toxicologists in understanding the biological effects of chemical exposures in living systems. This review will address the use of 2-DE-based proteomics in toxicology and recent developments in this strategy, considering the unique nature of toxicity testing and the issues of dynamic range and reproducibility that have previously limited the overall utility of 2-DE in this field.

Animals↗
PubMed2005

In vivo zebrafish assays for toxicity testing.

Toxicity, due to complications of in vivo adsorption, distribution, metabolism and excretion (ADME), is a major cause of failure during drug development; many drugs shown to be safe in cell culture prove toxic in animal studies. Effective in vivo toxicity screening early in the development process can reduce the number of compounds that progress to laborious and costly late-stage animal testing. The transparent zebrafish provides accessibility to internal organs, tissues and even cells, and has emerged as an invaluable model organism for toxicity testing and drug discovery. Straightforward in vivo zebrafish assays can serve as an intermediate step between cell-based and mammalian testing, thus streamlining the drug development time-line.

Animals↗
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↗
PubMed2005

Health and employment practices: ethical, legal, and social implications of advances in toxicogenomics.

Advances in toxicogenomics research may allow the identification of individuals who may be hyper-susceptible to occupational exposures and could create a shift from population to individual-based risk assessment in occupational health. Although many states have passed legislation to prevent the misuse of genetic information in employment, there is no general federal protection from the use of genetic information after a conditional offer of employment. Occupational health professionals have a crucial role in shaping future guidelines governing the use of genetic information in employment.

Confidentiality↗
PubMed2006

Computational toxicology: heading toward more relevance in drug discovery and development.

Computational tools for predicting toxicity have been envisioned to have the potential to broadly impact the attrition rate of compounds in early research and development, and prove successful in predicting adverse drug reactions (ADRs) in patients enrolled in clinical trials, and particularly prior to the marketing of drugs. The impact of such tools to date, however, has been modest and relatively narrow in scope. It is important to note that advances within medical science and newer approaches in clinical development will require predictive toxicology applications to be viable, and therefore efforts must be directed into making these tools relevant to the goal of preventing undesired toxicity in patients. In this Editorial Opinion, the current status of computational toxicology within industry is reviewed and areas in which advances can be made are highlighted. While predicting the potential of a compound to induce specific ADRs continues to be a formidable task, the field of computational biology is now heading in a direction more relevant to human disease and adverse outcomes.

Animals↗
PubMed2006

The state-of-the-art in predictive toxicogenomics.

Predictive toxicogenomics, ie, the acquisition of advanced knowledge of the safety profile of a compound using genomic biomarkers, is a technology that provides much optimism for improving early drug discovery decisions. Toxicogenomics creates an opportunity to shift attrition to earlier stages in drug development to a point where course-corrective action can be taken with relatively lower financial costs, thus improving the efficiency of the drug development process. This review will survey the current state-of-the-art in toxicogenomics for predicting toxicity, both in vivo and in vitro, with emphasis on the use of classification algorithms and the importance of toxicogenomic databases for biomarker discovery and validation.

Algorithms↗