Tan Aik-Choon, Vyse Simon, Huang Paul H
Translational Bioinformatics and Cancer Systems Biology Laboratory, Division of Medical Oncology, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Division of Cancer Biology, The Institute of Cancer Research, London SW3 6JB, UK.
Drug Discov Today. 2017 Jan;22(1):72-84. doi: 10.1016/j.drudis.2016.07.010. Epub 2016 Jul 21.
Studies over the past decade have shown that many cancers have evolved receptor tyrosine kinase (RTK) co-activation as a mechanism to drive tumour progression and limit the lethal effects of therapy. This review summarises the general principles of RTK co-activation and discusses approaches to exploit this phenomenon in cancer therapy and drug discovery. Computational strategies to predict kinase co-dependencies by integrating drug screening data and kinase inhibitor selectivity profiles will also be described. We offer a perspective on the implications of RTK co-activation on tumour heterogeneity and cancer evolution and conclude by surveying emerging computational and experimental approaches that will provide insights into RTK co-activation biology and deliver new developments in effective cancer therapies.
过去十年的研究表明,许多癌症已经进化出受体酪氨酸激酶(RTK)共激活机制,以此作为驱动肿瘤进展和限制治疗致死效应的一种方式。本综述总结了RTK共激活的一般原则,并讨论了在癌症治疗和药物发现中利用这一现象的方法。还将描述通过整合药物筛选数据和激酶抑制剂选择性概况来预测激酶共依赖性的计算策略。我们对RTK共激活对肿瘤异质性和癌症进化的影响提出了一种观点,并通过概述新兴的计算和实验方法来结束本文,这些方法将为RTK共激活生物学提供见解,并在有效的癌症治疗方面带来新进展。