A feasibility study: Can information collected to classify for mutagenicity be informative in predicting carcinogenicity?

• Published in: Regulatory toxicology and pharmacology Vol. 72; no. 1; pp. 17 - 25
• Main Authors: Petkov, Petko I., Patlewicz, Grace, Schultz, Terry W., Honma, Masamitsu, Todorov, Milen, Kotov, Stefan, Dimitrov, Sabcho D., Donner, E. Maria, Mekenyan, Ovanes G.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Inc 01.06.2015
• Subjects: (Q)SAR; Adverse Outcome Pathway (AOP); Animals; Carcinogenicity classification; Carcinogenicity Tests - methods; Carcinogens - toxicity; DNA - drug effects; DNA Damage - drug effects; False Positive Reactions; Feasibility Studies; Integrated Approaches to Testing and Assessment (IATA); Mutagenicity Tests - methods; Mutagens - toxicity; Proteins - drug effects; Risk Assessment - methods; Carcinogenicity classification; Adverse Outcome Pathway (AOP); Integrated Approaches to Testing and Assessment (IATA); (Q)SAR
• ISSN: 0273-2300; 1096-0295; 1096-0295
• DOI: 10.1016/j.yrtph.2015.03.003

•An in vitro–in vivo extrapolation workflow was adapted to mimic a mechanistic IATA.•Disconcordant outcomes could be mechanistically reasoned.•The IATA was used to predict mutagenicity categories.•A high sensitivity and low rate of false positives was achieved. Carcinogenicity is a complex endpoint of high concern yet the rodent bioassay still used is costly to run in terms of time, money and animals. Therefore carcinogenicity has been the subject of many different efforts to both develop short-term tests and non-testing approaches capable of predicting genotoxic carcinogenic potential. In our previous publication (Mekenyan et al., 2012) we presented an in vitro–in vivo extrapolation workflow to help investigate the differences between in vitro and in vivo genotoxicity tests. The outcomes facilitated the development of new (Q)SAR models and for directing testing. Here we have refined this workflow by grouping specific tests together on the basis of their ability to detect DNA and/or protein damage at different levels of biological organization. This revised workflow, akin to an Integrated Approach to Testing and Assessment (IATA) informed by mechanistic understanding was helpful in rationalizing inconsistent study outcomes and categorizing a test set of carcinogens with mutagenicity data on the basis of regulatory mutagenicity classifications. Rodent genotoxic carcinogens were found to be correctly predicted with a high sensitivity (90–100%) and a low rate of false positives (3–10%). The insights derived are useful to consider when developing future (non-)testing approaches to address regulatory purposes.