Department of Medicine, University of Chicago, Chicago, Illinois 60637, USA.
Pharmacol Rev. 2009 Dec;61(4):413-29. doi: 10.1124/pr.109.001461.
Quantitative variation in response to drugs in human populations is multifactorial; genetic factors probably contribute to a significant extent. Identification of the genetic contribution to drug response typically comes from clinical observations and use of classic genetic tools. These clinical studies are limited by our inability to control environmental factors in vivo and the difficulty of manipulating the in vivo system to evaluate biological changes. Recent progress in dissecting genetic contribution to natural variation in drug response through the use of cell lines has been made and is the focus of this review. A general overview of current cell-based models used in pharmacogenomic discovery and validation is included. Discussion includes the current approach to translate findings generated from these cell-based models into the clinical arena and the use of cell lines for functional studies. Specific emphasis is given to recent advances emerging from cell line panels, including the International HapMap Project and the NCI60 cell panel. These panels provide a key resource of publicly available genotypic, expression, and phenotypic data while allowing researchers to generate their own data related to drug treatment to identify genetic variation of interest. Interindividual and interpopulation differences can be evaluated because human lymphoblastoid cell lines are available from major world populations of European, African, Chinese, and Japanese ancestry. The primary focus is recent progress in the pharmacogenomic discovery area through ex vivo models.
人群对药物反应的定量差异是多因素的；遗传因素可能在很大程度上起作用。鉴定药物反应的遗传贡献通常来自临床观察和经典遗传工具的使用。这些临床研究受到限制，因为我们无法在体内控制环境因素，并且难以操纵体内系统来评估生物变化。最近通过使用细胞系来剖析遗传对药物反应自然变异的贡献方面取得了进展，这是本综述的重点。本文包括了当前在药物基因组学发现和验证中使用的基于细胞的模型的概述。讨论包括将这些基于细胞的模型产生的研究结果转化到临床领域的当前方法，以及使用细胞系进行功能研究。特别强调了来自细胞系面板的最新进展，包括国际人类基因组单体型图计划和 NCI60 细胞面板。这些面板提供了公开可用的基因型、表达和表型数据的重要资源，同时允许研究人员生成与药物治疗相关的自己的数据，以确定感兴趣的遗传变异。可以评估个体间和人群间的差异，因为可从欧洲、非洲、中国和日本主要世界人群中获得人淋巴母细胞系。主要重点是通过体外模型在药物基因组学发现领域的最新进展。
