药物发现
药物开发
癌症
临床试验
医学
药品
癌细胞系
计算生物学
计算机科学
生物信息学
重症监护医学
药理学
生物
癌细胞
病理
内科学
作者
Jennifer L. Wilding,Walter F. Bodmer
出处
期刊:Cancer Research
[American Association for Cancer Research]
日期:2014-04-10
卷期号:74 (9): 2377-2384
被引量:396
标识
DOI:10.1158/0008-5472.can-13-2971
摘要
Abstract Despite the millions of dollars spent on target validation and drug optimization in preclinical models, most therapies still fail in phase III clinical trials. Our current model systems, or the way we interpret data from them, clearly do not have sufficient clinical predictive power. Current opinion suggests that this is because the cell lines and xenografts that are commonly used are inadequate models that do not effectively mimic and predict human responses. This has become such a widespread belief that it approaches dogma in the field of drug discovery and optimization and has spurred a surge in studies devoted to the development of more sophisticated animal models such as orthotopic patient-derived xenografts in an attempt to obtain more accurate estimates of whether particular cancers will respond to given treatments. Here, we explore the evidence that has led to the move away from the use of in vitro cell lines and toward various forms of xenograft models for drug screening and development. We review some of the pros and cons of each model and give an overview of ways in which the use of cell lines could be modified to improve the predictive capacity of this well-defined model. Cancer Res; 74(9); 2377–84. ©2014 AACR.
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