An approach for assessing estrogen receptor-mediated interactions in mixtures of three chemicals: A pilot study

Most studies investigating interactions among endocrine-active chemicals have been limited to binary mixtures. This study reports on the preliminary evaluation an in vitro MCF-7 cell ER- reporter gene system, coupled with a statistical methodology adapted for assessing interactions within ternary (3-chemical) mixtures. Two mixtures were initially chosen for assessment of the in vitro system’s ability to detect additivity (mixture A) as well as greater-than-additive (mixture B) responses. Mixture A was composed of 17-estradiol (E2), ethinyl estradiol, and diethylstilbestrol and served as a control for additivity, whereas mixture B (E2, epidermal growth factor, insulin-like growth factor-I) was selected to model greater-than-additive interactions based on previous in vitro studies. After generating complete dose–response curves for each chemical, ternary mixtures were then tested in a full factorial design (4 concentrations per chemical, 64 treatment groups). A response surface was estimated using a nonlinear mixed model, and the observed responses were statistically analyzed for departures from the responses expected under the assumption of additivity. Mixture A exhibited additivity in vitro when the chemicals were present at concentrations in the linear range of their individual dose-response curves. For mixture B, in vitro analysis resulted in the additivity hypothesis being rejected (p < 0.001) because of a greater-than-additive interaction, as expected. A limited in vivo evaluation of mixture A was performed in the immature mouse uterotrophic assay (27 treatment groups), which agreed with the in vitro assessment of no significant departure from additivity (p 0.903). These findings demonstrate the ability of this in vitro methodology to detect additive, greater-than-additive, and less-than-additive interactions within ternary mixtures, which now allows for the assessment of environmentally relevant mixtures.