Finding transcriptomics biomarkers for in vivo identification of (non-)genotoxic carcinogens using wild-type and Xpa/p53 mutant mouse models
| Autor: | Maarten van Iterson, Harry Vrieling, Martijs J. Jonker, Mirjam M. Schaap, Harry van Steeg, Tessa V. van der Hoeven, Annemieke de Vries, Oskar Bruning, Mirjam Luijten, Timo M. Breit, Rudolf B. Beems |
|---|---|
| Přispěvatelé: | RNA Biology & Applied Bioinformatics (SILS, FNWI), Other departments |
| Rok vydání: | 2009 |
| Předmět: |
Genetic Markers
Cancer Research DNA Repair Genotype Transcription Genetic Mutant Computational biology Biology medicine.disease_cause Transcriptome Mice In vivo medicine Animals Bioassay Animal testing Carcinogen Mice Knockout Genetics Gene Expression Profiling General Medicine Xeroderma Pigmentosum Group A Protein Gene Expression Regulation Neoplastic Mice Inbred C57BL Carcinogens RNA Tumor Suppressor Protein p53 Toxicogenomics Genotoxicity Mutagens |
| Zdroj: | Carcinogenesis, 30(10), 1805-1812. Oxford University Press |
| ISSN: | 1460-2180 0143-3334 |
| DOI: | 10.1093/carcin/bgp190 |
| Popis: | The carcinogenic potential of chemicals and pharmaceuticals is traditionally tested in the chronic, 2 year rodent bioassay. This assay is not only time consuming, expensive and often with a limited sensitivity and specificity but it also causes major distress to the experimental animals. A major improvement in carcinogenicity testing, especially regarding reduction and refinement of animal experimentation, could be the application of toxicogenomics. The ultimate aim of this study is to demonstrate a proof-of-principle for transcriptomics biomarkers in various tissues for identification of (subclasses of) carcinogenic compounds after short-term in vivo exposure studies. Both wild-type and DNA repair-deficient Xpa(-/-)/p53(+/-) (Xpa/p53) mice were exposed up to 14 days to compounds of three distinct classes: genotoxic carcinogens (GTXC), non-genotoxic carcinogens (NGTXC) and non-carcinogens. Subsequently, extensive transcriptomics analyses were performed on several tissues, and transcriptomics data were screened for potential biomarkers using advanced statistical learning techniques. For all tissues analyzed, we identified multigene gene-expression signatures that are, with a high confidence, predictive for GTXC and NGTXC exposures in both mouse genotypes. Xpa/p53 mice did not perform better in the short-term bioassay. We were able to achieve a proof-of-principle for the identification and use of transcriptomics biomarkers for GTXC or NGTXC. This supports the view that toxicogenomics with short-term in vivo exposure provides a viable tool for classifying (geno)toxic compounds. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|