The GARD™skin assay: Investigation of the applicability domain for metals.

New approach methodologies (NAMs) for hazard identification of skin sensitizing chemicals were adopted as test guidelines by the OECD during the last decade. These alternatives to animal models align to individual key events (KE) in the adverse outcome pathway (AOP) for skin sensitization for which the molecular initiating event (MIE) is covalent binding to proteins. As it currently stands, the AOP does not include mechanistic events of sensitization by metals, and limited information is available on whether NAMs accurately predict the sensitization potential of such molecules, which have been proposed to act via alternative mechanisms to organic chemicals. Methods for assessing the sensitization potential of metals would be valuable tools to support risk management within, e.g., occupational settings during production of new metal salts or within the medical device industry to evaluate leachables from metal alloys. This paper describes a systematic evaluation of the applicability domain of the GARD™skin assay for the assessment of metals. Hazard classifications were supplemented with an extended analysis of gene expression profiles induced by metal sensitizers to compare the induction of toxicity pathways between metals and organic sensitizers. Based on the results of this study, the accuracy, sensitivity, and specificity of GAR­D™skin for the prediction of skin sensitizing hazard were 92% (12/13), 100% (7/7), and 83% (5/6), respectively. Thus, the performance of GARD™skin for the assessment of metals was found to be similar to that observed for conventional organic substances, providing support for inclusion of metals within the applicability domain of the test method.

Joint effects of heterogeneous estrogenic chemicals in the E-screen--exploring the applicability of concentration addition.

In the last few years, significant advances have been made toward understanding the joint action of endocrine disrupting chemicals (EDCs). A number of studies have demonstrated that the combined effects of different types of EDCs (e.g., estrogenic, antiandrogenic, or thyroid-disrupting agents) can be predicted by the model of concentration addition (CA). However, there is still limited information on the effects of mixtures of large numbers of chemicals with varied structural features, which are more representative of realistic human exposure scenarios. The work presented here aims at filling this gap. Using a breast cancer cell proliferation assay (E-Screen), we assessed the joint effects of five mixtures, containing between 3 and 16 estrogenic agents, including compounds as diverse as steroidal hormones (endogenous and synthetic), pesticides, cosmetic additives, and phytoestrogens. CA was employed to predict mixture effects, which were then compared with experimental outcomes. The effects of two of the mixtures tested were additive, being accurately predicted by CA. However, for the three other mixtures, CA slightly overestimated the experimental observations. In view of these results, we hypothesized that the deviations were due to increased metabolism of steroidal estrogens in the mixture setting. We investigated this by testing the impact of two such mixtures on the activation and expression of steroidal estrogen metabolizing enzymes, such as cytochrome P450 (CYP) 1A1, CYP 1B1, and CYP 3A4. Activation of CYP 1B1 and, consequently, a reduction in the levels of steroidal estrogens in the mixture could contribute to the shortfall from the additivity prediction that we observed.

Detection of DNA strand breaks and oxidized DNA bases at the single-cell level resulting from exposure to estradiol and hydroxylated metabolites.

Long-term exposure to steroidal estrogens is a key factor contributing to increases in the risk of developing breast cancer. Proposed mechanisms include receptor-activated increases in the rate of cell proliferation leading to the accumulation of genetic damage resulting from reading errors, and the production of DNA damage by species arising from metabolism of 17beta-estradiol (E2) resulting in mutations. In support of the second mechanism, catechol metabolites of E2 induce DNA damage in vitro. In the present study, utilizing the single-cell gel electrophoresis (Comet) assay, we observed increases in the number of single-strand breaks in estrogen receptor alpha-positive (MCF-7) and -negative (MDA-MB-231) breast cancer cells exposed to E2 (for 24 hr) or 4-hydroxy-17beta-estradiol (4-OH-E2; for 2 hr). The concentrations of 4-OH-E2 sufficient to induce these effects were approximately 100 nM, substantially lower than reported previously. The catechol 2-hydroxy-17beta-estradiol (2-OH-E2) also induced strand breaks. 2-OH-E2, often referred to as an improbable carcinogen in humans, is not a major metabolite of E2 in the breast; however, our findings show that it is as DNA-damaging as 4-OH-E2. Formamidopyrimidine glycosylase posttreatment of E2-, 4-OH-E2-, and 2-OH-E2-exposed MCF-7 cells led to an up to sixfold increase in mean tail moment, suggesting that oxidative DNA damage was formed. Comet formation could be partially attenuated by coincubation with dimethylsulfoxide, attributing a small DNA-damaging role to oxyradicals emanating from catechol redox cycling. Similar findings were obtained with MDA-MB-231 cells, indicating that estrogen receptor status is not relevant to these effects. Our observations show that exposure to E2 adds to the oxidative load of cells, and this may contribute to genomic instability.

Deviation from additivity with estrogenic mixtures containing 4-nonylphenol and 4-tert-octylphenol detected in the E-SCREEN assay.

An intriguing deviation from expected additivity is reported with mixtures containing 17beta-estradiol, 17alpha-ethinylestradiol, genistein, bisphenol A, 4-nonylphenol, and 4-tert-octylphenol. The effect of these chemicals on the proliferation of estrogen-dependent MCF-7 human breast cancer cells (the E-SCREEN) was measured. Data variance-component analyses, carried out to optimize the assay for mixture studies, showed that between-experiment variability was the dominant source of data variation. Adoption of a data-normalization procedure reduced the impact of this variability and allowed the pooling of historical E-SCREEN data. Concentration-response relationships for all six chemicals were recorded and utilized to calculate predictions of their joint effects by employing the model of concentration addition. Surprisingly, the observed combination effects of the mixture fell short of the additivity expectations, indicating weak antagonism. Experimental or prediction errors were ruled out as possible explanations for this deviation, which suggested that it might be the result of interactions between mixture components. With the aim of identifying the responsible components, mixtures were designed by excluding one or more of the chemicals from the original six-component mixture, and the resulting combination effects were assessed. These permutation studies allowed us to conclude thatthe presence of 4-nonylphenol and 4-tert-octylphenol is associated with the antagonisms observed with the six-component mixture and thus negatively affected the predictability of mixture effects. Future mixture studies utilizing the E-SCREEN with endocrine disrupters that also exhibit toxicity or growth-inhibitory effects will have to take account of the possibility that such interactions might compromise the predictability of estrogenic combination effects.

Combining xenoestrogens at levels below individual no-observed-effect concentrations dramatically enhances steroid hormone action.

The low potency of many man-made estrogenic chemicals, so-called xenoestrogens, has been used to suggest that risks arising from exposure to individual chemicals are negligible. Another argument used to dismiss concerns of health effects is that endogenous steroidal estrogens are too potent for xenoestrogens to contribute significantly to estrogenic effects. Using a yeast reporter gene assay with the human estrogen receptoralpha, we tested these ideas experimentally by assessing the ability of a combination of 11 xenoestrogens to affect the actions of 17ss-estradiol. Significantly, each xenoestrogen was present at a level well below its no-observed-effect concentration (NOEC). To derive accurate descriptions of low effects, we recorded concentration-response relationships for each xenoestrogen and for 17ss-estradiol. We used these data to predict entire concentration-response curves of mixtures of xenoestrogens with 17ss-estradiol, assuming additive combination effects. Over a large range of concentrations, the experimentally observed responses decisively confirmed the model predictions. The combined additive effect of the 11 xenoestrogens led to a dramatic enhancement of the hormone's action, even when each single agent was present below its NOEC. Our results show that not even sub-NOEC levels of xenoestrogens can be considered to be without effect on potent steroidal estrogens when they act in concert with a large number of similarly acting chemicals. It remains to be seen to what degree these effects can be neutralized by environmental chemicals with antiestrogenic activity. Nevertheless, potential human and wildlife responses induced by additive combination effects of xenoestrogens deserve serious consideration.

Something from "nothing"--eight weak estrogenic chemicals combined at concentrations below NOECs produce significant mixture effects.

We tested whether multicomponent mixtures of xenoestrogens would produce significant effects when each component was combined at concentrations below its individual NOEC or EC01 level. The estrogenic effects of eight chemicals of environmental relevance, including hydroxylated PCBs, benzophenones, parabenes, bisphenol A, and genistein, were recorded using a recombinant yeast estrogen screen (YES). To ensure that no chemical contributed disproportionately to the overall combination effect, a mixture was prepared at a mixture ratio proportional to the potency of each individual component. The performance of four approaches for the calculation of additive combination effects (concentration addition, toxicity equivalency factors, effect summation, and independent action) was compared. Experimental testing of the predictions revealed that concentration addition and its application, the toxicity equivalency factor approach, were valid methods for the calculation of additive mixture effects. There was excellent agreement between prediction and observation. In contrast, independent action and effect summation led to clear underestimations of the experimentally observed responses. Crucially, there were substantial mixture effects even though each chemical was present at levels well below its NOEC and EC01. We conclude that estrogenic agents are able to act together to produce significant effects when combined at concentrations below their NOECs. Our results highlight the limitations of the traditional focus on the effects of single agents. Hazard assessments that ignore the possibility of joint action of estrogenic chemicals will almost certainly lead to significant underestimations of risk.