In vitro observations and in silico predictions of xenoestrogen mixture effects in T47D-based receptor transactivation and proliferation assays

Toxicol In Vitro. 2017 Dec;45(Pt 1):146-157. doi: 10.1016/j.tiv.2017.08.017. Epub 2017 Aug 30.

Abstract

Within endocrine disruptor research, evaluation and interpretation of mixture effects and the predictive value for downstream responses still warrant more in-depth investigations. We used an estrogen receptor (ER)-mediated reporter gene assay (ER-CALUX®) and a cell proliferation assay (WST-1 assay), both based on the T47D breast cancer cell line, to test mixtures of heterogeneous xenoestrogens. Observed concentration-response curves were compared to those predicted by the concepts of concentration addition (CA), generalized concentration addition (GCA), and a novel full logistic model (FLM). CA performed better regarding mixture potency (EC50 values), whereas GCA was superior in predicting mixture efficacy (maximal response). In comparison, FLM proved to be highly suitable for in silico mixture effect prediction, combining advantages of both CA and GCA. The inter-assay comparison revealed that ER activation is not necessarily predictive for induction of cell proliferation. The results support the use of models like CA, GCA, or FLM in mixture effect evaluation. However, we conclude that reliable estimations regarding the disruptive potential of mixtures of endocrine active substances require an integrative approach considering more than one assay/endpoint to avoid misinterpretations. The formazan-based WST-1 proliferation assay might be a possible alternative to commonly used proliferation assays in endocrine disrupter research.

Keywords: CALUX® assay; Concentration addition; Endocrine disruptors; Full logistic model; Xenoestrogens.

MeSH terms

  • Cell Line
  • Cell Proliferation / drug effects*
  • Computer Simulation*
  • Environmental Pollutants / toxicity
  • Estrogens / toxicity*
  • Humans
  • Transcriptional Activation / drug effects*

Substances

  • Environmental Pollutants
  • Estrogens