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基于蛋白质组学的激酶组学分析及其对精准肿瘤学的影响。

Proteomics-based interrogation of the kinome and its implications for precision oncology.

机构信息

Cancer Program and Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.

出版信息

Proteomics. 2021 Sep;21(17-18):e2000161. doi: 10.1002/pmic.202000161. Epub 2021 Mar 8.

Abstract

The identification of specific protein kinases as oncogenic drivers in a variety of cancer types, coupled with the clinical success of particular kinase-directed targeted therapies, has cemented the human kinome as an attractive source of "actionable" targets for cancer therapy. However, "mining" of the human kinome for precision oncology applications has yet to yield its full potential. This reflects a variety of issues, including oncogenic kinase dysregulation at levels not detectable by genomic sequencing and the uncharacterized nature of a considerable fraction of the kinome. In addition, selective therapeutic targeting of specific kinases requires efficient mapping of total kinome space impacted by candidate small molecule drugs. Fortunately, recent developments in proteomics techniques, particularly in mass spectrometry-based phosphoproteomics and kinomics, provide the necessary technology platforms to address these impediments. Moreover, initiatives such as the Clinical Proteomic Tumour Analysis Consortium have enabled the generation, deposition and integration of genomic, transcriptomic and (phospho)proteomic data for many cancer types, providing unprecedented insights into oncogenic kinases and cancer cell signalling generally. These multi-omic data are identifying novel therapeutic targets, highlighting opportunities for drug re-purposing, and helping assign optimal therapies to specific tumour subtypes, heralding a new era of "enhanced" precision oncology.

摘要

特定蛋白激酶在多种癌症类型中被鉴定为致癌驱动因子,加上特定激酶导向的靶向治疗的临床成功,使人类激酶组成为癌症治疗中“可操作”靶点的有吸引力的来源。然而,为精准肿瘤学应用而对人类激酶组进行“挖掘”尚未发挥其全部潜力。这反映了各种问题,包括基因组测序无法检测到的致癌激酶失调,以及激酶组相当一部分的未知性质。此外,对特定激酶的选择性治疗靶向需要有效地映射候选小分子药物所影响的整个激酶组空间。幸运的是,蛋白质组学技术的最新进展,特别是基于质谱的磷酸化蛋白质组学和激酶组学,提供了必要的技术平台来解决这些障碍。此外,临床蛋白质组肿瘤分析联盟等倡议已经能够为许多癌症类型生成、存储和整合基因组、转录组和(磷酸化)蛋白质组数据,为致癌激酶和癌症细胞信号转导提供了前所未有的见解。这些多组学数据正在确定新的治疗靶点,突出了药物再利用的机会,并有助于为特定肿瘤亚型分配最佳治疗方法,预示着“增强”精准肿瘤学的新时代的到来。

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