The environmental risks of environmental estrogens (EEs) are often assessed via the same mode of action in the concentration addition (CA) model, neglecting the complex combined mechanisms at the genetic level. In this study, the cell proliferation effects of estrone, 17α-ethinylestradiol, 17β-estradiol, estriol, diethylstilbestrol, estradiol valerate, bisphenol A, 4-tert-octylphenol and 4-nonylphenol were determined individually using the CCK-8 method, and the proliferation effects of a multicomponent mixture of estrogenic chemicals mixed at equipotent concentrations using a fixed-ratio design were studied using estrogen-sensitive MCF-7 cells. Furthermore, transcription factors related to cell proliferation were analyzed using RT-PCR assays to explore the potential molecular mechanisms related to the estrogenic proliferative effects. The results showed that the estrogenic chemicals act together in an additive mode, and the combined proliferative effects could be predicted more accurately by the response addition model than the CA model with regard to their adverse outcomes. Furthermore, different signaling pathways were involved depending on the different mixtures. The RT-PCR analyses showed that different estrogens have distinct avidities and preferences for different estrogen receptors at the gene level. Furthermore, the results indicated that estrogenic mixtures increased ERα, PIK3CA, GPER, and PTEN levels and reduced Akt1 level to display combined estrogenicity. These findings indicated that the potential combined environmental risks were greater than those found in some specific assessment procedures based on a similar mode of action due to the diversity of environmental pollutions and their multiple unknown modes of action. Thus, more efforts are needed for mode-of-action-driven analyses at the molecular level. Furthermore, to more accurately predict and assess the individual responses in vivo from the cellular effects in vitro, more parameters and correction factors should be taken into consideration in the addition model.

环境雌激素 (EE) 的环境风险通常通过以下方式进行评估：浓度加成 (CA) 模型中的相同作用模式，忽略了遗传水平上复杂的组合机制。本研究采用 CCK-8 法分别测定了雌酮、17α-炔雌醇、17β-雌二醇、雌三醇、己烯雌酚、戊酸雌二醇、双酚 A、4-叔辛基苯酚和 4-壬基苯酚对细胞增殖的影响，使用雌激素敏感的 MCF-7 细胞研究了使用固定比例设计以等效浓度混合的雌激素化学物质的多组分混合物的增殖效应。此外，使用 RT-PCR 测定分析与细胞增殖相关的转录因子，以探索与雌激素增殖作用相关的潜在分子机制。结果表明雌激素化学物质以加性方式共同作用，与 CA 模型相比，响应加法模型可以更准确地预测组合增殖效应的不利结果。此外，根据不同的混合物，涉及不同的信号通路。RT-PCR 分析表明，不同的雌激素在基因水平上对不同的雌激素受体具有不同的亲和力和偏好。此外，结果表明雌激素混合物增加 ERα、PIK3CA、GPER 和 PTEN 水平并降低 Akt1 水平以显示组合雌激素。这些发现表明，由于环境污染的多样性及其多种未知的作用方式，潜在的综合环境风险大于基于类似作用方式的某些特定评估程序中发现的风险。因此，需要更多的努力在分子水平上进行作用模式驱动的分析。此外，为了更准确地预测和评估个体反应in vivo从体外细胞效应来看，加法模型需要考虑更多的参数和校正因子。