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临床癌症标本的激酶组分析。

Kinome profiling of clinical cancer specimens.

机构信息

University Medical Center Groningen, A. Deusinglaan 1, Groningen, 9713 AV, the Netherlands.

出版信息

Cancer Res. 2010 Apr 1;70(7):2575-8. doi: 10.1158/0008-5472.CAN-09-3989. Epub 2010 Mar 23.

Abstract

Over the past years novel technologies have emerged to enable the determination of the transcriptome and proteome of clinical samples. These data sets will prove to be of significant value to our elucidation of the mechanisms that govern pathophysiology and may provide biological markers for future guidance in personalized medicine. However, an equally important goal is to define those proteins that participate in signaling pathways during the disease manifestation itself or those pathways that are made active during successful clinical treatment of the disease: the main challenge now is the generation of large-scale data sets that will allow us to define kinome profiles with predictive properties on the outcome-of-disease and to obtain insight into tissue-specific analysis of kinase activity. This review describes the current techniques available to generate kinome profiles of clinical tissue samples and discusses the future strategies necessary to achieve new insights into disease mechanisms and treatment targets.

摘要

在过去的几年中,出现了一些新技术,能够确定临床样本的转录组和蛋白质组。这些数据集将被证明对我们阐明控制病理生理学的机制具有重要价值,并可能为未来个性化医学的指导提供生物标志物。然而,同样重要的目标是确定在疾病表现过程中参与信号通路的那些蛋白质,或者在疾病成功临床治疗过程中被激活的那些通路:目前的主要挑战是生成大规模数据集,这些数据集将使我们能够定义具有疾病预后预测特性的激酶组谱,并深入了解组织特异性激酶活性分析。这篇综述描述了目前可用于生成临床组织样本激酶组谱的技术,并讨论了实现对疾病机制和治疗靶点的新见解所需的未来策略。

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