The utility of proteomic patterns for the diagnosis of cancer.

Thomas P Conrads, Timothy D Veenstra
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引用次数: 12

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 on the mass spectral identification of the thousands of proteins that populate complex biosystems such as serum and tissues. A revolutionary approach termed proteomic pattern analysis has emerged as an effective method for the early diagnosis of diseases such as ovarian, breast, and prostate cancer. Proteomic pattern analysis relies on the pattern of proteins observed and does not rely on the identification of a traceable biomarker. Utilizing this technology, hundreds of clinical samples per day can be analyzed with the potential to be a novel, highly sensitive diagnostic tool for the early detection of diseases or as a predictor of response to therapy.

蛋白质组学模式在癌症诊断中的应用。
蛋白质组学的出现为发现新的生物标记物带来了希望,这些生物标记物可用于诊断疾病、预测易感性和监测疾病进展。这方面的工作主要集中在质谱鉴定上,以鉴定血清和组织等复杂生物系统中的数千种蛋白质。一种被称为蛋白质组模式分析的革命性方法已经成为卵巢癌、乳腺癌和前列腺癌等疾病早期诊断的有效方法。蛋白质组学模式分析依赖于观察到的蛋白质模式,而不依赖于可追溯生物标志物的鉴定。利用这项技术,每天可以分析数百个临床样本,有可能成为一种新的、高度敏感的诊断工具,用于疾病的早期检测或作为对治疗反应的预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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