Linked Life Data

19696161

Source:http://linkedlifedata.com/resource/pubmed/id/19696161

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
10
pubmed:dateCreated
2009-10-6
pubmed:abstractText
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.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
1460-2180
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
30
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1805-12
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Finding transcriptomics biomarkers for in vivo identification of (non-)genotoxic carcinogens using wild-type and Xpa/p53 mutant mouse models.
pubmed:affiliation
MicroArray Department and Integrative Bioinformatics Unit, Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, Amsterdam, The Netherlands.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't