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利用蛋白质组学模式进行癌症诊断。

Cancer diagnosis using proteomic patterns.

作者信息

Conrads Thomas P, Zhou Ming, Petricoin Emmanuel F, Liotta Lance, Veenstra Timothy D

机构信息

Mass Spectrometry Center, Biomedical Proteomics Program, SAIC-Frederick, Inc, National Cancer Institute at Frederick, MD 21702, USA.

出版信息

Expert Rev Mol Diagn. 2003 Jul;3(4):411-20. doi: 10.1586/14737159.3.4.411.

Abstract

The advent of proteomics has brought with it the hope of discovering novel biomarkers that can be used to diagnose diseases, predict susceptibility and monitor progression. Much of this effort has focused upon the mass spectral identification of the thousands of proteins that populate complex biosystems such as serum and tissues. A revolutionary approach in proteomic pattern analysis has emerged as an effective method for the early diagnosis of diseases such as ovarian cancer. Proteomic pattern analysis relies on the pattern of proteins observed and does not rely on the identification of a traceable biomarker. Hundreds of clinical samples per day can be analyzed utilizing this technology, which has the potential to be a novel, highly sensitive diagnostic tool for the early detection of cancer.

摘要

蛋白质组学的出现带来了发现新型生物标志物的希望,这些生物标志物可用于疾病诊断、预测易感性和监测病情进展。这项工作大多集中在对血清和组织等复杂生物系统中数千种蛋白质的质谱鉴定上。蛋白质组学模式分析中的一种革命性方法已成为卵巢癌等疾病早期诊断的有效手段。蛋白质组学模式分析依赖于所观察到的蛋白质模式,而不依赖于可溯源生物标志物的鉴定。利用这项技术每天可分析数百份临床样本,它有可能成为一种用于癌症早期检测的新型、高灵敏度诊断工具。

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