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Carcinogenesis Advance Access originally published online on August 20, 2009
Carcinogenesis 2009 30(10):1805-1812; doi:10.1093/carcin/bgp190
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© The Author 2009. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Finding transcriptomics biomarkers for in vivo identification of (non-)genotoxic carcinogens using wild-type and Xpa/p53 mutant mouse models

Martijs J. Jonker, Oskar Bruning, Maarten van Iterson, Mirjam M. Schaap1, Tessa V. van der Hoeven, Harry Vrieling2, Rudolf B. Beems1, Annemieke de Vries1, Harry van Steeg1,2,*, Timo M. Breit and Mirjam Luijten1

MicroArray Department and Integrative Bioinformatics Unit, Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, The Netherlands
1 Laboratory for Health Protection Research, National Institute for Public Health and the Environment, 3720 BA Bilthoven, The Netherlands
2 Department of Toxicogenetics, Leiden University Medical Center, 2300 RC Leiden, The Netherlands

* To whom correspondence should be addressed. Tel: +31 30 274 2102; Fax: +31 30 274 4446; Email: harry.van.steeg{at}rivm.nl

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.

Abbreviations: 2-AAF, 2-acetylaminofluorene; B[a]P, benzo[a]pyrene; CsA, cyclosporine A; DLDA-BW, diagonal linear discriminant analysis with a between-group to within-group sums of squares-based gene selection; GTXC, genotoxic carcinogens; MLN, mesenteric lymph node; NC, non-carcinogens; NCC-SC, nearest centroid classification with shrunken centroid gene selection; NGTXC, non-GTXC; SVM-RFE, support vector machines with recursive feature elimination; TBTO, tributyltin oxide; WT, wild-type; WY, Wyeth-14,643; Xpa/p53, Xpa–/–/p53+/–

Received April 22, 2009; revised July 27, 2009; accepted July 27, 2009.


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