Literature DB >> 12106614

Gene expression profiling of drug metabolism and toxicology markers using a low-density DNA microarray.

Françoise de Longueville1, Dominic Surry, Georgina Meneses-Lorente, Vincent Bertholet, Valérie Talbot, Stephanie Evrard, Nathalie Chandelier, Andrew Pike, Phil Worboys, Jean Paul Rasson, Béatrice Le Bourdellès, José Remacle.   

Abstract

DNA microarrays are useful tools to study changes of gene expression in response to a treatment with drugs. Here, we describe the optimization of conditions for the cDNA synthesis and hybridization protocols to be used for a low-density DNA microarray called 'Rat HepatoChips.' This DNA microarray with 59 carefully selected genes could be used to study changes in gene expression levels due to a treatment with xenobiotic. These 59 genes (including 8 housekeeping genes) have been selected among potential toxic markers involved in basic cellular processes and drug metabolism related genes. Using the optimized conditions, the results were shown to be reproducible, with 6% variation between the duplicated spots and 10% between arrays. Conditions were optimized to allow quantification with a dynamic range of four log units. In order to demonstrate the major advantage of these tool for studying gene expression, samples of control rat liver were compared with those of animals dosed with phenobarbital (PB) or pregnenolone-16 alpha-carbonitrile (PCN), two compounds well known to induce cytochrome P450 isoforms of 2B and 3A subfamilies, respectively. This microarray has shown that other genes apart from the corresponding CYP P450 genes have been changed due to PB and PCN treatment. Apoptosis-related genes have shown to be changed due to PB and PCN treatment, which confirms results from previous work.

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Year:  2002        PMID: 12106614     DOI: 10.1016/s0006-2952(02)01055-9

Source DB:  PubMed          Journal:  Biochem Pharmacol        ISSN: 0006-2952            Impact factor:   5.858


  13 in total

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8.  Recognition of multiple imbalanced cancer types based on DNA microarray data using ensemble classifiers.

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9.  The hepatic transcriptome in human liver disease.

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Journal:  BMC Genomics       Date:  2008-02-11       Impact factor: 3.969

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