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源自具有抗肿瘤细胞活性的中药和天然药物的天然产物的植物化学与药物基因组学。

Phytochemistry and pharmacogenomics of natural products derived from traditional Chinese medicine and Chinese materia medica with activity against tumor cells.

作者信息

Efferth Thomas, Kahl Stefan, Paulus Kerstin, Adams Michael, Rauh Rolf, Boechzelt Herbert, Hao Xiaojiang, Kaina Bernd, Bauer Rudolf

机构信息

German Cancer Research Centre, Pharmaceutical Biology (C015), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.

出版信息

Mol Cancer Ther. 2008 Jan;7(1):152-61. doi: 10.1158/1535-7163.MCT-07-0073.

Abstract

The cure from cancer is still not a reality for all patients, which is mainly due to the limitations of chemotherapy (e.g., drug resistance and toxicity). Apart from the high-throughput screening of synthetic chemical libraries, natural products represent attractive alternatives for drug development. We have done a systematic bioactivity-based screening of natural products derived from medicinal plants used in traditional Chinese medicine. Plant extracts with growth-inhibitory activity against tumor cells have been fractionated by chromatographic techniques. We have isolated the bioactive compounds and elucidated the chemical structures by nuclear magnetic resonance and mass spectrometry. By this strategy, we identified 25-O-acetyl-23,24-dihydro-cucurbitacin F as a cytotoxic constituent of Quisqualis indica. Another promising compound identified by this approach was miltirone from Salvia miltiorrhiza. The IC50 values for miltirone of 60 National Cancer Institute cell lines were associated with the microarray-based expression of 9,706 genes. By COMPARE and hierarchical cluster analyses, candidate genes were identified, which significantly predicted sensitivity or resistance of cell lines to miltirone.

摘要

对所有癌症患者来说,治愈癌症仍不现实,这主要归因于化疗的局限性(如耐药性和毒性)。除了对合成化学文库进行高通量筛选外,天然产物是药物研发的有吸引力的替代选择。我们对源自中药的药用植物的天然产物进行了基于生物活性的系统筛选。对具有抑制肿瘤细胞生长活性的植物提取物进行了色谱技术分离。我们分离出了生物活性化合物,并通过核磁共振和质谱阐明了其化学结构。通过这种策略,我们鉴定出25 - O - 乙酰基 - 23,24 - 二氢 - 葫芦素F是使君子的一种细胞毒性成分。通过这种方法鉴定出的另一种有前景的化合物是丹参中的丹参酮。60种美国国立癌症研究所细胞系对丹参酮的半数抑制浓度(IC50)值与基于微阵列的9706个基因的表达相关。通过比较分析和层次聚类分析,鉴定出了候选基因,这些基因显著预测了细胞系对丹参酮的敏感性或耐药性。

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