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Identification of potential biomarkers of genotoxicity and carcinogenicity in L5178Y mouse lymphoma cells by cDNA
Ji-Young Kim1, Jung Kwon, Ja Eun Kim
1Korea Institute of Toxicology, Korea Research Institute of Chemical Technology, Daejeon, South Korea.
Abstract:
In the present study, cDNA microarray analyses were performed with mouse cDNA chips in order to evaluate similarities and differences in the gene expression profiles for compounds differing in their genotoxic and carcinogenic potential. Eight test substances were evaluated, two each from four classes of compounds: genotoxic carcinogens (1,2-dibromoethane and glycidol), genotoxic noncarcinogens (8-hydroxyquinoline and emodin), nongenotoxic carcinogens (methyl carbamate and o-nitrotoluene), and nongenotoxic noncarcinogens (D-mannitol and 1,2-dichlorobenzene). Quadruplicate hybridization experiments were performed in order to identify a set of genes with significant expression changes for these four classes of substances. Twelve genes were consistently altered more than twofold by the genotoxic noncarcinogens while four genes were consistently regulated by the nongenotoxic carcinogens. One gene (Trp63) was identified whose expression was upregulated by all four genotoxic substances regardless of the presence or absence of carcinogenicity; this finding, however, was not confirmed by quantitative real-time RT-PCR. RT-PCR did confirm the change in expression of 9 of 15 genes (60%) identified by microarray analysis. Interestingly, the downregulated genes were least likely to be validated by real-time RT-PCR. Those genes showing more than a twofold change in expression level in response to at least one substance were further analyzed with hierarchical clustering after category assignment of each gene according to its main cellular function. Clustering revealed differences in the gene expression profiles between the genotoxic and nongenotoxic substances for genes involved in cell cycle control, the stress response, and the immune response. However, no clustering specific to all four carcinogenic substances was observed in any of the functional categories. Taken together, these results suggest that gene expression profiling in mouse lymphoma cells can provide valuable information for the evaluation of potential genotoxicity but may have limitations in predicting carcinogenicity.
Insights
Gene expression profiling in mouse lymphoma cells effectively identifies genotoxicity but shows limitations in predicting carcinogenicity. Microarray analysis revealed distinct gene expression patterns for genotoxic versus nongenotoxic compounds.
Area of Science:
- Toxicogenomics
- Molecular Toxicology
- Biomarker Discovery
Background:
- Assessing chemical genotoxicity and carcinogenicity is crucial for risk assessment.
- Gene expression profiling offers a potential method to understand compound mechanisms of action.
- Distinguishing genotoxic from nongenotoxic and carcinogenic from noncarcinogenic compounds requires robust methodologies.
Purpose of the Study:
- To evaluate gene expression profiles using cDNA microarray analysis.
- To compare gene expression patterns of compounds with varying genotoxic and carcinogenic potentials.
- To determine the utility of gene expression profiling for predicting genotoxicity and carcinogenicity.
Main Methods:
- Utilized mouse cDNA chips for gene expression analysis.
- Tested eight substances across four classes: genotoxic carcinogens, genotoxic noncarcinogens, nongenotoxic carcinogens, and nongenotoxic noncarcinogens.
- Performed quadruplicate hybridizations and validated findings with quantitative real-time RT-PCR.
Main Results:
- Identified 12 genes consistently altered by genotoxic noncarcinogens and 4 by nongenotoxic carcinogens.
- Hierarchical clustering revealed distinct gene expression profiles for genotoxic versus nongenotoxic substances.
- Gene expression profiling showed promise for genotoxicity assessment but limitations in predicting carcinogenicity.
Conclusions:
- Gene expression profiling in mouse lymphoma cells can aid in evaluating potential genotoxicity.
- The study highlights limitations in predicting carcinogenicity solely based on gene expression profiles.
- Further research may refine gene expression-based methods for chemical safety assessment.
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