Verma M, Wright G L, Hanash S M, Gopal-Srivastava R, Srivastava S
Cancer Biomarkers Research Group, Division of Cancer Prevention, National Cancer Institute, Bethesda, Maryland, USA.
Ann N Y Acad Sci. 2001 Sep;945:103-15. doi: 10.1111/j.1749-6632.2001.tb03870.x.
In the postgenome era, proteomics provides a powerful approach for the analysis of normal and transformed cell functions, for the identification of disease-specific targets, and for uncovering novel endpoints for the evaluation of chemoprevention agents and drug toxicity. Unfortunately, the genomic information that has greatly expounded the genetic basis of cancer does not allow an accurate prediction of what is actually occurring at the protein level within a given cell type at any given time. The gene expression program of a given cell is affected by numerous factors in the in vivo environment resulting from tissue complexity and organ system orchestration, with cells acting in concert with each other and responding to changes in their microenvironment. Repositories of genomic information can be considered master "inventory lists" of genes and their maps, which need to be supplemented with protein-derived information. The National Cancer Institute's Early Detection Research Network is employing proteomics, or "protein walking", in the discovery and evaluation of biomarkers for cancer detection and for the identification of high-risk subjects. Armed with microdissection techniques, including the use of Laser Capture Microdissection (LCM) to procure pure populations of cells directly from human tissue, the Network is facilitating the development of technologies that can overcome the problem of tissue heterogeneity and address the need to identify markers in easily accessible biological fluids. Proteomic approaches complement plasma-based assays of circulating DNA for cancer detection and risk assessment. LCM, coupled with downstream proteomics applications, such as two-dimensional polyacrylamide gel electrophoresis and SELDI (surface enhanced laser desorption ionization) separation followed by mass spectrometry (MS) analysis, may greatly facilitate the characterization and identification of protein expression changes that track normal and disease phenotypes. We highlight recent work from Network investigators to demonstrate the potential of proteomics to identify proteins present in cancer tissues and body fluids that are relevant for cancer screening.
在后基因组时代,蛋白质组学为分析正常和转化细胞功能、鉴定疾病特异性靶点以及揭示用于评估化学预防剂和药物毒性的新终点提供了强有力的方法。不幸的是,尽管基因组信息极大地阐明了癌症的遗传基础,但它无法准确预测在任何给定时间给定细胞类型内蛋白质水平上实际发生的情况。给定细胞的基因表达程序受到体内环境中众多因素的影响,这些因素源于组织复杂性和器官系统的协调,细胞彼此协同作用并对其微环境的变化做出反应。基因组信息库可被视为基因及其图谱的主要“清单”,还需要补充蛋白质衍生的信息。美国国立癌症研究所的早期检测研究网络正在采用蛋白质组学,即“蛋白质探寻”,来发现和评估用于癌症检测的生物标志物以及识别高危人群。借助显微切割技术,包括使用激光捕获显微切割(LCM)直接从人体组织中获取纯净的细胞群体,该网络正在推动能够克服组织异质性问题并满足在易于获取的生物流体中识别标志物需求的技术发展。蛋白质组学方法可补充基于血浆的循环DNA检测,用于癌症检测和风险评估。LCM与下游蛋白质组学应用相结合,如二维聚丙烯酰胺凝胶电泳和表面增强激光解吸电离(SELDI)分离后进行质谱(MS)分析,可能极大地促进对追踪正常和疾病表型的蛋白质表达变化的表征和鉴定。我们重点介绍了该网络研究人员最近的工作,以展示蛋白质组学在识别癌症组织和体液中与癌症筛查相关的蛋白质方面的潜力。