Chromosomal patterns of gene expression from microarray data: methodology, validation and clinical relevance in gliomas.

BACKGROUND: Expression microarrays represent a powerful technique for the simultaneous investigation of thousands of genes. The evidence that genes are not randomly distributed in the genome and that their coordinated expression depends on their position on chromosomes has highlighted the need for mathematical approaches to exploit this dependency for the analysis of expression data-sets. RESULTS: We have devised a novel mathematical technique (CHROMOWAVE) based on the Haar wavelet transform and applied it to a dataset obtained with the Affymetrix HG-U133_Plus_2 array in 27 gliomas. CHROMOWAVE generated multi-chromosomal pattern featuring low expression in chromosomes 1p, 4, 9q, 13, 18, and 19q. This pattern was not only statistically robust but also clinically relevant as it was predictive of favourable outcome. This finding was replicated on a data-set independently acquired by another laboratory. FISH analysis indicated that monosomy 1p and 19q was a frequent feature of tumours displaying the CHROMOWAVE pattern but that allelic loss on chromosomes 4, 9q, 13 and 18 was much less common. CONCLUSION: The ability to detect expression changes of spatially related genes and to map their position on chromosomes makes CHROMOWAVE a valuable screening method for the identification and display of regional gene expression changes of clinical relevance. In this study, FISH data showed that monosomy was frequently associated with diffuse low gene expression on chromosome 1p and 19q but not on chromosomes 4, 9q, 13 and 18. Comparative genomic hybridisation, allelic polymorphism analysis and methylation studies are in progress in order to identify the various mechanisms involved in this multi-chromosomal expression pattern.

Endocrine activity of mycotoxins and mycotoxin mixtures.

Reporter gene assays incorporating nuclear receptors (estrogen, androgen, thyroid ß and PPARγ2) have been implemented to assess the endocrine activity of 13 mycotoxins and their mixtures. As expected, zearalenone and its metabolites α-zearalenol and ß- zearalenol turned out to have the strongest estrogenic potency (EC50 8,7 10-10 ± 0,8; 3,1 10-11 ± 0,5 and 1,3 10-8 ± 0,3 M respectively). The metabolite of deoxynivalenol, 3-acetyl-deoxynivalenol also had estrogenic activity (EC50 3,8 10-7 ± 1,1 M). Furthermore, most of the mycotoxins (and their mixtures) showed anti-androgenic effects (15-acetyldeoxynivalenol, 3-acetyl-deoxynivalenol and α-zearalenol with potencies within one order of magnitude of that of the reference compound flutamide). In particular, deoxynivalenol and 15-acetyl-deoxynivalenol acted as antagonists for the PPARy2 receptor. When testing mixtures of mycotoxins on the same cell systems, we showed that most of the mixtures reacted as predicted by the concentration addition (CA) theory. Generally, the CA was within the 95% confidence interval of the observed ones, only minor deviations were detected. Although these reporter gene tests cannot be directly extrapolated in vivo, they can be the basis for further research. Especially the additive effects of ZEN and its metabolites are of importance and could have repercussions in vivo.