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Carcinogenesis Advance Access published online on February 12, 2004

Carcinogenesis, doi:10.1093/carcin/bgh108
© 2004 by Oxford University Press
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© 2004 Oxford University Press

CARCINOGENESIS

Discrimination of genotoxic from non-genotoxic carcinogens by gene expression profiling

J. H. M. van Delft 1*, E. van Agen 1, S. G. J. van Breda 1, M. H. Herwijnen 1, Y. C. M. Staal 1, and J. C. S. Kleinjans 1

1 Department of Health Risk Analysis and Toxicology, Maastricht University, P.O. Box 616, 6200 MD Maastricht, Netherlands

* Corresponding author. E-mail: j.vandelft{at}grat.unimaas.nl.

Received 30 October 2003 ; revised 28 January 2004 ; accepted 1 February 2004

Abstract

Two general mechanisms are implicated in chemical carcinogenesis. The first involves direct damage to DNA, referred to as genotoxic, to which the cell responds by repair of the damages, arrest of the cell cycle or induction of apoptosis. The second is non-DNA damaging, nongenotoxic, in which a wide variety of cellular processes may be involved. Therefore, it can be hypothesised that modulation of the underlying gene expression patterns is profoundly distinct between genotoxic and non-genotoxic carcinogens, and thus that expression profiling is applicable for classification of chemical carcinogens as genotoxic or non-genotoxic. We investigated this hypothesis by analysing modulation of gene expression profiles induced by 20 chemical carcinogens in HepG2 cells with application of cDNA microarrays that contain 597 toxicologically relevant genes. In total 22 treatments were included, divided in 2 sets. The training set consisted of 16 treatments (9 genotoxins and 7 non-genotoxins) and the validation set of 6 treatments (3 and 3). Class discrimination models based on Pearson correlation analyses for the 20 most discriminating genes were developed with data from the training set, where after the models were tested with all data. Using all data, the correctness for classification of the carcinogens from the training set was clearly better than that for the validation set, namely 81 and 33% respectively. Exclusion of the treatments that had only marginal effects on the expression profiles, improved the discrimination for the training and validation sets to 92% and 100% correctness, respectively. Exclusion of the gene expression signals that were hardly altered also improved classification, namely to 94% and 80%. Therefore, our study proofs the principle that gene expression profiling can discriminate carcinogens with major differences in their mode of actions, namely genotoxins versus non-genotoxins.


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