Musumarra G, Condorelli D F, Costa A S, Fichera M
Dipartimento di Scienze Chimiche, Università di Catania, Italy.
J Comput Aided Mol Des. 2001 Mar;15(3):219-34. doi: 10.1023/a:1008171426412.
A multivariate insight into the in vitro antitumour screen database of the NCI by means of the SIMCA package allows to propose hypotheses on the mechanism of action of novel anticancer compounds. As an example, the application of multivariate analysis to the NCI standard database provided clues to the classification of drugs whose mechanism is either unknown or controversial. Moreover, the influence of intrinsic biochemical cell line properties (molecular targets) on the sensitivity to drug treatment could be evaluated simultaneously for classes of compounds which act by the same mechanism. Interestingly, the present approach can also provide a correlation between the molecular targets and the therapeutical fingerprint of novel active compounds thus suggesting specific biochemical studies for the investigation of new mechanisms of drug action and resistance. The statistical approach reported here represents a valuable tool for handling theenormous data sets deriving from recent genome-wide investigations of gene expression in the NCI cell lines.
借助SIMCA软件包对美国国立癌症研究所（NCI）的体外抗肿瘤筛选数据库进行多变量分析，有助于对新型抗癌化合物的作用机制提出假设。例如，将多变量分析应用于NCI标准数据库，为作用机制不明或有争议的药物分类提供了线索。此外，对于通过相同机制起作用的化合物类别，可以同时评估内在生化细胞系特性（分子靶点）对药物治疗敏感性的影响。有趣的是，目前的方法还可以提供分子靶点与新型活性化合物治疗指纹之间的相关性，从而为研究药物作用和耐药性的新机制提出具体的生化研究方向。本文报道的统计方法是处理来自NCI细胞系近期全基因组基因表达研究产生的大量数据集的宝贵工具。
