We investigated a potential mechanism for the estrogenic properties of three chloro-s-triazine herbicides and six metabolites in vitro in several cell systems. We determined effects on human aromatase (CYP19), the enzyme that converts androgens to estrogens, in H295R (adrenocortical carcinoma), JEG-3 (placental choriocarcinoma), and MCF-7 (breast cancer) cells; we determined effects on estrogen receptor-mediated induction of vitellogenin in primary hepatocyte cultures of adult male carp (Cyprinus carpio). In addition to atrazine, simazine, and propazine, two metabolites-atrazine-desethyl and atrazine-desisopropyl-induced aromatase activity in H295R cells concentration-dependently (0.3-30 µM) and with potencies similar to those of the parent triazines. After a 24-hr exposure to 30 µM of the triazines, an apparent maximum induction of about 2-to 2.5-fold was achieved. The induction responses were confirmed by similar increases in CYP19 mRNA levels, determined by reverse-transcriptase polymerase chain reaction. In JEG-3 cells, where basal aromatase expression is about 15-fold greater than in H295R cells, the induction responses were similar but less pronounced; aromatase expression in MCF-7 cells was neither detectable nor inducible under our culture conditions. The fully dealkylated metabolite atrazinedesethyl-desisopropyl and the three hydroxylated metabolites (2-OH-atrazine-desethyl,-desisopropyl, and-desethyl-desisopropyl) did not induce aromatase activity. None of the triazine herbicides nor their metabolites induced vitellogenin production in male carp hepatocytes; nor did they antagonize the induction of vitellogenin by 100 nM (EC 50) 17β-estradiol. These findings together with other reports indicate that the estrogenic effects associated with the triazine herbicides in vivo are not estrogen receptor-mediated, but may be explained partly by their ability to induce aromatase in vitro.

SummaryThe role that in vitro systems can play in toxicological risk assessment is determined by the appropriateness of the chosen methods, with respect to the way in which in vitro data can be extrapolated to the in vivo situation. This report presents the results of a workshop aimed at better defining the use of in vitro-derived biomarkers of toxicity (BoT) and determining the place these data can have in human risk assessment. As a result, a conceptual framework is presented for the incorporation of in vitro-derived toxicity data into the risk assessment process. The selection of BoT takes into account that they need to distinguish adverse and adaptive changes in cells. The framework defines the place of in vitro systems in the context of data on exposure, structural and physico-chemical properties, and toxicodynamic and biokinetic modeling. It outlines the determination of a proper point-of-departure (PoD) for in vitro-in vivo extrapolation, allowing implementation in risk assessment procedures. A BoT will need to take into account both the dynamics and the kinetics of the compound in the in vitro systems. For the implementation of the proposed framework it will be necessary to collect and collate data from existing literature and new in vitro test systems, as well as to categorize biomarkers of toxicity and their relation to pathways-of-toxicity. Moreover, data selection and integration need to be driven by their usefulness in a quantitative in vitro-in vivo extrapolation (QIVIVE). Keywords: biomarker of toxicity, integrated testing strategies, quantitative in vitro-in vivo extrapolations

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Background: The Cefic Mixtures Industry Ad-hoc Team (MIAT) has investigated how risks from combined exposures can be effectively identified and managed using concepts proposed in recent regulatory guidance, new advances in risk assessment, and lessons learned from a Cefic-sponsored case study of mixture exposures. Results: A series of tools were created that include: a decision tree, a system for grouping exposures, and a graphical tool (the MCR-HI plot). The decision tree allows the division of combined exposures into different groups, exposures where one or more individual components are a concern, exposures that are of low concern, and exposures that are a concern for combined effects but not for the effects of individual chemicals. These tools efficiently use available data, identify critical data gaps for combined assessments, and prioritize which chemicals require detailed toxicity information. The tools can be used to address multiple human health endpoints and ecological effects.