Genetic toxicity assessment using liver cell models: past, present, and future. (2nd January 2020)

• Record Type: Journal Article
• Authors: Guo, Xiaoqing; Seo, Ji-Eun; Li, Xilin; Mei, Nan
• Is Part Of: Journal of toxicology and environmental health. Volume 23:Number 1(2020)
• Page Start: 27
• Page End: 50
• Publication Date: 2020-01-02
• Subjects: Hepatocytes -- genotoxicity -- mutagenicity -- DNA damage -- micronucleus assay; Toxicology -- Periodicals; Environmental toxicology -- Periodicals; Environmental health -- Periodicals; 615.90205
• DOI: 10.1080/10937404.2019.1692744
• Languages: English
• ISSNs: 1093-7404

Abstract

ABSTRACT: Genotoxic compounds may be detoxified to non-genotoxic metabolites while many pro-carcinogens require metabolic activation to exert their genotoxicity in vivo . Standard genotoxicity assays were developed and utilized for risk assessment for over 40 years. Most of these assays are conducted in metabolically incompetent rodent or human cell lines. Deficient in normal metabolism and relying on exogenous metabolic activation systems, the current in vitro genotoxicity assays often have yielded high false positive rates, which trigger unnecessary and costly in vivo studies. Metabolically active cells such as hepatocytes have been recognized as a promising cell model in predicting genotoxicity of carcinogens in vivo . In recent years, significant advances in tissue culture and biological technologies provided new opportunities for using hepatocytes in genetic toxicology. This review encompasses published studies (both in vitro and in vivo ) using hepatocytes for genotoxicity assessment. Findings from both standard and newly developed genotoxicity assays are summarized. Various liver cell models used for genotoxicity assessment are described, including the potential application of advanced liver cell models such as 3D spheroids, organoids, and engineered hepatocytes. An integrated strategy, that includes the use of human-based cells with enhanced biological relevance and throughput, and applying the quantitative analysis of data, may provide an approach for future genotoxicity risk assessment.