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Performance of HepaRG and HepG2 cells in the high-throughput micronucleus assay for in vitro genotoxicity assessment.

Xiaoqing GuoJi-Eun SeoDayton PetiboneVolodymyr TryndyakUn Jung LeeTong ZhouTimothy W RobisonNan Mei
Published in: Journal of toxicology and environmental health. Part A (2020)
The micronucleus (MN) assay is a core test used to evaluate genotoxic potential of xenobiotics. The traditional in vitro MN assay is usually conducted in cells lacking metabolic competency or by supplementing cultures with an exogenous rat S9 metabolic system, which creates a significant assay limitation for detecting genotoxic metabolites. Our previous study demonstrated that compared to HepG2, HepaRG cells exhibited a significantly higher level of CYP450 enzyme activities and detected a greater portion of genotoxic carcinogens requiring metabolic activation using the Comet assay. The aim of this study was to assess the performance of HepaRG cells in the flow cytometry-based MN assay by testing 28 compounds with known genotoxic or carcinogenic modes of action (MoA). HepaRG cells exhibited higher sensitivity (83%) than HepG2 cells (67%) in detecting 12 indirect-acting genotoxicants or carcinogens. The HepaRG MN assay was 100% specific and 93% accurate in detecting genotoxic potential of the 28 compounds. Quantitative comparison of the MN concentration-response data using benchmark dose analysis showed that most of the tested compounds induced higher % MN in HepaRG than HepG2 cells. In addition, HepaRG cells were compatible with the Multiflow DNA damage assay, which predicts the genotoxic MoA of compounds tested. These results suggest that high-throughput flow cytometry-based MN assay may be adapted using HepaRG cells for genotoxicity assessment, and that HepaRG cells appear to be more sensitive than HepG2 cells in detecting genotoxicants or carcinogens that require metabolic activation.
Keyphrases
  • high throughput
  • induced apoptosis
  • cell cycle arrest
  • flow cytometry
  • oxidative stress
  • cell death
  • room temperature
  • electronic health record
  • cell proliferation
  • transition metal
  • artificial intelligence