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Application of generalized concentration addition to predict mixture effects of glucocorticoid receptor ligands.

ABSTRACT: Environmental exposures often occur in complex mixtures and at low concentrations. Generalized concentration addition (GCA) is a method used to estimate the joint effect of receptor ligands that vary in efficacy. GCA models have been successfully applied to mixtures of aryl hydrocarbon receptor (AhR) and peroxisome proliferator-activated receptor gamma (PPARγ) ligands, each of which can be modeled as a receptor with a single binding site. Here, we evaluated whether GCA could be applied to homodimer nuclear receptors, which have two binding sites, to predict the combined effect of full glucocorticoid receptor (GR) agonists with partial agonists. We measured transcriptional activation of GR using a cell-based bioassay. Individual concentration-response curves for dexamethasone (full agonist), prednisolone (full agonist), and medroxyprogesterone 17-acetate (partial agonist) were generated and applied in three additivity models, GCA, effect summation (ES), and relative potency factor (RPF), to generate response surfaces. GCA and RPF yielded adequate predictions of the experimental data for two full agonists. However, GCA fit experimental data significantly better than ES and RPF for all other binary mixtures. This work extends the application of GCA to homodimer nuclear receptors and improves prediction accuracy of mixture effects of GR agonists.

SUBMITTER: de la Rosa R

PROVIDER: S-EPMC7594746 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Humans are concomitantly exposed to numerous chemicals. An infinite number of combinations and doses thereof can be imagined. For toxicological risk assessment the mathematical prediction of mixture effects, using knowledge on single chemicals, is therefore desirable. We investigated pros and cons of the concentration addition (CA), independent action (IA) and generalized concentration addition (GCA) models. First we measured effects of single chemicals and mixtures thereof on steroid synthesis in H295R cells. Then single chemical data were applied to the models; predictions of mixture effects were calculated and compared to the experimental mixture data. Mixture 1 contained environmental chemicals adjusted in ratio according to human exposure levels. Mixture 2 was a potency adjusted mixture containing five pesticides. Prediction of testosterone effects coincided with the experimental Mixture 1 data. In contrast, antagonism was observed for effects of Mixture 2 on this hormone. The mixtures contained chemicals exerting only limited maximal effects. This hampered prediction by the CA and IA models, whereas the GCA model could be used to predict a full dose response curve. Regarding effects on progesterone and estradiol, some chemicals were having stimulatory effects whereas others had inhibitory effects. The three models were not applicable in this situation and no predictions could be performed. Finally, the expected contributions of single chemicals to the mixture effects were calculated. Prochloraz was the predominant but not sole driver of the mixtures, suggesting that one chemical alone was not responsible for the mixture effects. In conclusion, the GCA model seemed to be superior to the CA and IA models for the prediction of testosterone effects. A situation with chemicals exerting opposing effects, for which the models could not be applied, was identified. In addition, the data indicate that in non-potency adjusted mixtures the effects cannot always be accounted for by single chemicals.

Project description:Glucocorticoids exert rapid nongenomic effects by several mechanisms including the activation of a membrane-bound glucocorticoid receptor (mGR). Here, we report the first proteomic study on the effects of mGR activation by BSA-conjugated cortisol (Cort-BSA). A subset of target proteins in the proteomic data set was validated by Western blot and we found them responding to mGR activation by BSA-conjugated cortisol in three additional cell lines, indicating a conserved effect in cells originating from different tissues. Changes in the proteome of BSA-conjugated cortisol treated CCRF-CEM leukemia cells were associated with early and rapid pro-apoptotic, immune-modulatory and metabolic effects aligning with and possibly "priming" classical activities of the cytosolic glucocorticoid receptor (cGR). PCR arrays investigating target genes of the major signaling pathways indicated that the mGR does not exert its effects through the transcriptional activity of any of the most common kinases in these leukemic cells, but RhoA signaling emerged from our pathway analysis. All cell lines tested displayed very low levels of mGR on their surface. Highly sensitive and specific in situ proximity ligation assay visualized low numbers of mGR even in cells previously thought to be mGR negative. We obtained similar results when using three distinct anti-GR monoclonal antibodies directed against the N-terminal half of the cGR. This strongly suggests that the mGR and the cGR have a high sequence homology and most probably originate from the same gene. Furthermore, the mGR appears to reside in caveolae and its association with caveolin-1 (Cav-1) was clearly detected in two of the four cell lines investigated using double recognition proximity ligation assay. Our results indicate however that Cav-1 is not necessary for membrane localization of the GR since CCRF-CEM and Jurkat cells have a functional mGR, but did not express this caveolar protein. However, if expressed, this membrane protein dimerizes with the mGR modulating its function.

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Application of generalized concentration addition to predict mixture effects of glucocorticoid receptor ligands.

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