模拟体内微环境筛选与肿瘤细胞作用的中药活性成分

利用三维(3D)细胞反应器模拟体内微环境,建立了一种与肿瘤细胞作用的活性分子的筛选和分析方法.利用药物与三维细胞反应器中活肿瘤细胞和固化肿瘤细胞分别作用后的HPLC生物指纹谱峰面积之间有无显著性差异,建立了与细胞结合的活性成分的筛选识别模型.已知抗肿瘤药物紫杉醇和白藜声醇的谱峰均具有显著性差异,而非抗肿瘤药物酮洛芬和青霉素G的谱峰均没有显著性差异,证明利用该模型筛选识别与细胞结合的活性成分是可行的.此外,应用该模型从中草药桃儿七提取物中筛选出了7种可作用于Lovo细胞的活性成分.此研究提供了一种模拟体内微环境下与肿瘤细胞作用的活性成分的筛选和分析方法,在药物发现环节,特别是中草药活性成分研究中具有潜在的应用价值.

Affinity screening and analysis of active components interacted with cancer cells at simulating the in vivo micro-environment from traditional Chinese medicines

An affinity screening and analysis method was established by combining three-dimensional cell bioreactor with HPLC/MS for the active components interacted with cancer cells at simulating the in vivo micro-environment. The differences between the biological fingerprinting chromatograms of HPLC after interacting with live and fixed ceils were used to establish a screening recognition model to distinguish bioactive components interacted specifically. Having significant difference （P 〈 0.05） for model anticancer drugs （paclitaxel and resveratrol） and having no significant difference （P 〈 0.05） for model non-anticancer drugs （ketoprofen and penicillin G） with model cancer cells demonstrated the feasibility of this recognition model. The model was used to screen bioactive components from Sinopodophyllum hexandrum （Royle） Ying extract. Seven components interacted with Lovo cells were screened. This paper provides a screening and analysis method, mimicking in vivo micro-environment, for bioactive components interacted with cancer cells. This method has the potential to be used in drug discovery programs especially in bioactive components research from traditional Chinese medicines.