Comprehensive interpretation of in vitro micronucleus test results for 292 chemicals: from hazard identification to risk assessment application

• Published in: Archives of toxicology Vol. 96; no. 7; pp. 2067 - 2085
• Main Authors: Kuo, Byron, Beal, Marc A., Wills, John W., White, Paul A., Marchetti, Francesco, Nong, Andy, Barton-Maclaren, Tara S., Houck, Keith, Yauk, Carole L.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.07.2022; Springer Nature B.V
• Subjects: Abnormalities; Aneugens - toxicity; Animals; Archives & records; Aroclor 1254; Automation; Biocompatibility; Biological activity; Biomedical and Life Sciences; Biomedicine; Chemicals; Chromosome aberrations; Chromosomes; Clastogenicity; Cytotoxicity; Datasets; Decision trees; Environmental Health; Estimates; Exposure; Genotoxicity; Genotoxicity and Carcinogenicity; Genotoxicity testing; Hazard identification; In vitro methods and tests; In vivo methods and tests; Micronucleus Tests - methods; Mutagenicity Tests - methods; Mutagens - toxicity; Occupational Medicine/Industrial Medicine; PCB; Pharmacology/Toxicology; Polychlorinated biphenyls; Rats; Risk Assessment; Solvents; Toxicity; Toxicology; Toxicokinetics; Micronucleus; Genotoxicity; IVIVE; Point of departure; Benchmark dose
• ISSN: 0340-5761; 1432-0738; 1432-0738
• DOI: 10.1007/s00204-022-03286-2

Risk assessments are increasingly reliant on information from in vitro assays. The in vitro micronucleus test (MNvit) is a genotoxicity test that detects chromosomal abnormalities, including chromosome breakage (clastogenicity) and/or whole chromosome loss (aneugenicity). In this study, MNvit datasets for 292 chemicals, generated by the US EPA’s ToxCast program, were evaluated using a decision tree-based pipeline for hazard identification. Chemicals were tested with 19 concentrations ( n  = 1) up to 200 µM, in the presence and absence of Aroclor 1254-induced rat liver S9. To identify clastogenic chemicals, %MN values at each concentration were compared to a distribution of batch-specific solvent controls; this was followed by cytotoxicity assessment and benchmark concentration (BMC) analyses. The approach classified 157 substances as positives, 25 as negatives, and 110 as inconclusive. Using the approach described in Bryce et al. (Environ Mol Mutagen 52:280–286, 2011), we identified 15 (5%) aneugens. IVIVE (in vitro to in vivo extrapolation) was employed to convert BMCs into administered equivalent doses (AEDs). Where possible, AEDs were compared to points of departure (PODs) for traditional genotoxicity endpoints; AEDs were generally lower than PODs based on in vivo endpoints. To facilitate interpretation of in vitro MN assay concentration–response data for risk assessment, exposure estimates were utilized to calculate bioactivity exposure ratio (BER) values. BERs for 50 clastogens and two aneugens had AEDs that approached exposure estimates (i.e., BER < 100); these chemicals might be considered priorities for additional testing. This work provides a framework for the use of high-throughput in vitro genotoxicity testing for priority setting and chemical risk assessment.