Helmholtz Centre for Environmental Research - UFZ, Division Health Science, Permoserstr. 15, 04318 Leipzig, Germany.
Toxicol Appl Pharmacol. 2010 May 1;244(3):336-43. doi: 10.1016/j.taap.2010.01.012. Epub 2010 Feb 2.
The interaction of drugs and non-therapeutic xenobiotics constitutes a central role in human health risk assessment. Still, available data are rare. Two different models have been established to predict mixture toxicity from single dose data, namely, the concentration addition (CA) and independent action (IA) model. However, chemicals can also act synergistic or antagonistic or in dose level deviation, or in a dose ratio dependent deviation. In the present study we used the MIXTOX model (EU project ENV4-CT97-0507), which incorporates these algorithms, to assess effects of the binary mixtures in the human hepatoma cell line HepG2. These cells possess a liver-like enzyme pattern and a variety of xenobiotic-metabolizing enzymes (phases I and II). We tested binary mixtures of the metal nickel, the anti-inflammatory drug diclofenac, and the antibiotic agent irgasan and compared the experimental data to the mathematical models. Cell viability was determined by three different methods the MTT-, AlamarBlue(R) and NRU assay. The compounds were tested separately and in combinations. We could show that the metal nickel is the dominant component in the mixture, affecting an antagonism at low-dose levels and a synergism at high-dose levels in combination with diclofenac or irgasan, when using the NRU and the AlamarBlue assay. The dose-response surface of irgasan and diclofenac indicated a concentration addition. The experimental data could be described by the algorithms with a regression of up to 90%, revealing the HepG2 cell line and the MIXTOX model as valuable tool for risk assessment of binary mixtures for cytotoxic endpoints. However the model failed to predict a specific mode of action, the CYP1A1 enzyme activity.
药物和非治疗性异生物质的相互作用是人类健康风险评估的核心。然而，可用的数据很少。已经建立了两种不同的模型来从单剂量数据预测混合物毒性，即浓度加和（CA）和独立作用（IA）模型。然而，化学物质也可以协同、拮抗或在剂量水平偏差，或剂量比依赖性偏差下作用。在本研究中，我们使用了包含这些算法的 MIXTOX 模型（欧盟项目 ENV4-CT97-0507）来评估二元混合物对人肝癌细胞系 HepG2 的影响。这些细胞具有类似肝脏的酶模式和多种异生物质代谢酶（I 相和 II 相）。我们测试了金属镍、抗炎药双氯芬酸和抗生素 Irgasan 的二元混合物，并将实验数据与数学模型进行了比较。细胞活力通过三种不同的方法——MTT、AlamarBlue（R）和 NRU 测定来确定。这些化合物分别进行了测试，并进行了组合测试。我们可以证明，金属镍是混合物中的主要成分，当与双氯芬酸或 Irgasan 组合使用时，在低剂量水平下表现出拮抗作用，在高剂量水平下表现出协同作用，使用 NRU 和 AlamarBlue 测定时。Irgasan 和双氯芬酸的剂量反应曲面表明浓度加和。实验数据可以用高达 90%的回归来描述算法，这表明 HepG2 细胞系和 MIXTOX 模型是用于评估二元混合物对细胞毒性终点的风险的有价值的工具。然而，该模型未能预测特定的作用模式，即 CYP1A1 酶活性。
