蛋白质组学
计算生物学
蛋白质组
基因表达谱
生物
仿形(计算机编程)
癌变
癌细胞
生物信息学
基因表达
癌症
基因
遗传学
计算机科学
操作系统
作者
Daniel K. Nomura,Melissa M. Dix,Benjamin F. Cravatt
出处
期刊:Nature Reviews Cancer
[Springer Nature]
日期:2010-08-12
卷期号:10 (9): 630-638
被引量:316
摘要
This Review focuses on activity-based protein profiling, which enables the discovery of cancer-relevant enzymes and selective pharmacological probes to perturb and characterize these proteins in tumour cells. When ABPP is integrated with other large-scale profiling methods, it can provide insight into the metabolic and signalling pathways that support cancer pathogenesis and indicate new strategies for treatment. Large-scale profiling methods have uncovered numerous gene and protein expression changes that correlate with tumorigenesis. However, determining the relevance of these expression changes and which biochemical pathways they affect has been hindered by our incomplete understanding of the proteome and its myriad functions and modes of regulation. Activity-based profiling platforms enable both the discovery of cancer-relevant enzymes and selective pharmacological probes to perturb and characterize these proteins in tumour cells. When integrated with other large-scale profiling methods, activity-based proteomics can provide insight into the metabolic and signalling pathways that support cancer pathogenesis and illuminate new strategies for disease diagnosis and treatment.
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