In vitro mammalian cytogenetic tests detect chromosomal aberrations and are used for testing the genotoxicity of compounds. This study aimed to identify a supportive genomic biomarker could minimize the risk of misjudgments and aid appropriate decision making in genotoxicity testing. Human lymphoblastoid TK6 cells were treated with each of six DNA damage-inducing genotoxins (clastogens) or two genotoxins that do not cause DNA damage. Cells were exposed to each compound for 4 h, and gene expression was comprehensively examined using Affymetrix U133A microarrays. Toxicogenomic analysis revealed characteristic alterations in the expression of genes included in cyclin-dependent kinase inhibitor 1A (CDKN1A/p21)-centered network. The majority of genes included in this network were upregulated on treatment with DNA damage-inducing clastogens. The network, however, also included kinesin family member 20A (KIF20A) downregulated by treatment with all the DNA damage-inducing clastogens. Downregulation of KIF20A expression was successfully confirmed using additional DNA damage-inducing clastogens. Our analysis also demonstrated that nucleic acid constituents falsely downregulated the expression of KIF20A, possibly via p16 activation, independently of the CDKN1A signaling pathway. Our results indicate the potential of KIF20A as a supportive biomarker for clastogenicity judgment and possible mechanisms involved in KIF20A downregulation in DNA damage and non-DNA damage signaling networks.
The genotoxic potential of drugs is a serious problem, and its evaluation is one of the most critical processes of drug development. Although the comet assay of compound-exposed tissue is a frequently used genotoxicity test, its high false-positive rate is a major complication, and we consistently obtained false-positive results using the comet assay of mouse liver for nine hepatotoxic non-genotoxins (NGTXs). To identify novel genotoxin (GTX)-specific biomarkers, we screened the expression of 750 microRNAs (miRNAs) in the livers of mice treated with GTXs or NGTXs. Three miRNAs, miR-22-3p, miR-409-3p, and miR-543-3p, were significantly down-regulated in GTX-treated mouse liver. In contrast, these three miRNAs were significantly up-regulated in plasma. A discrimination model based on the expression levels of these biomarkers successfully identified GTXs and NGTXs. This novel biomarker expression-based discrimination model analysis using both liver and plasma is effective for detecting genotoxicity with high sensitivity and reliability to support drug development.
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