Centre for Toxicology, School of Pharmacy, University of London, London WC1N1AX, UK.
Toxicol Sci. 2011 Aug;122(2):383-94. doi: 10.1093/toxsci/kfr103. Epub 2011 May 10.
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.
在过去的几年中，人们在理解内分泌干扰化学品（EDCs）的联合作用方面取得了重大进展。许多研究表明，不同类型的 EDCs（例如雌激素、抗雄激素或甲状腺干扰剂）的联合效应可以通过浓度加和（CA）模型来预测。然而，对于具有不同结构特征的大量化学物质混合物的影响，仍然缺乏信息，这些混合物更能代表现实的人类暴露情况。这里介绍的工作旨在填补这一空白。使用乳腺癌细胞增殖测定（E-Screen），我们评估了包含 3 至 16 种雌激素类物质的五种混合物的联合效应，其中包括甾体激素（内源性和合成）、农药、化妆品添加剂和植物雌激素等各种化合物。采用 CA 来预测混合物的效应，然后将其与实验结果进行比较。所测试的两种混合物的效应是相加的，CA 能够准确预测。然而，对于另外三种混合物，CA 略微高估了实验观察结果。鉴于这些结果，我们假设偏差是由于混合物中甾体雌激素代谢增加所致。我们通过测试两种此类混合物对甾体雌激素代谢酶（如细胞色素 P450（CYP）1A1、CYP1B1 和 CYP3A4）的激活和表达的影响来研究这一点。CYP1B1 的激活以及由此导致混合物中甾体雌激素水平的降低可能导致我们观察到的与加和性预测的差距。
