Suchergebnisse

One of the main challenges of toxicology is the accurate prediction of compound carcinogenicity. The default test model for assessing chemical carcinogenicity, the 2 year rodent cancer bioassay, is currently criticized because of its limited specificity. With increased societal attention and new legislation against animal testing, toxicologists urgently need an alternative to the current rodent bioassays for chemical cancer risk assessment. Toxicogenomics approaches propose to use global high-throughput technologies (transcriptomics, proteomics and metabolomics) to study the toxic effect of compounds on a biological system. Here, we demonstrate the improvement of transcriptomics assay consisting of primary human hepatocytes to predict the putative liver carcinogenicity of several compounds by applying the connectivity map methodology. Our analyses underline that connectivity mapping is useful for predicting compound carcinogenicity by connecting in vivo expression profiles from human cancer tissue samples with in vitro toxicogenomics data sets. Furthermore, the importance of time and dose effect on carcinogenicity prediction is demonstrated, showing best prediction for low dose and 24 h exposure of potential carcinogens.

MOTIVATION: The field of toxicogenomics (the application of '-omics' technologies to risk assessment of compound toxicities) has expanded in the last decade, partly driven by new legislation, aimed at reducing animal testing in chemical risk assessment but mainly as a result of a paradigm change in toxicology towards the use and integration of genome wide data. Many research groups worldwide have generated large amounts of such toxicogenomics data. However, there is no centralized repository for archiving and making these data and associated tools for their analysis easily available. RESULTS: The Data Infrastructure for Chemical Safety Assessment (diXa) is a robust and sustainable infrastructure storing toxicogenomics data. A central data warehouse is connected to a portal with links to chemical information and molecular and phenotype data. diXa is publicly available through a user-friendly web interface. New data can be readily deposited into diXa using guidelines and templates available online. Analysis descriptions and tools for interrogating the data are available via the diXa portal. Availability: http://www.dixa-fp7.eu CONTACT: d.hendrickx@maastrichtuniversity.nl ; info@dixa-fp7.eu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.