Proteomic patterns as a diagnostic tool for early-stage cancer: a review of its progress to a clinically relevant tool.
Proteomic patterns as a diagnostic tool for early-stage cancer: a review of its progress to a clinically relevant tool.
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DOI：
10.2165/00066982-200408020-00001
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发表时间：
2004-01-01
期刊：
影响因子：
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通讯作者：
Veenstra, Timothy D
中科院分区：
文献类型：
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作者：
Conrads, Thomas P;Hood, Brian L;Veenstra, Timothy D
有望改善疾病早期诊断的新技术的发展速度确实令人印象深刻。这场革命最前沿的一项技术就是质谱法。质谱分析的新功能为蛋白质组学的发展提供了手段，人们正在寻找创新的方法来应用这种强大的技术来解决临床医学面临的问题。过去几年备受关注的一个领域是使用质谱模式进行癌症诊断。使用这些所谓的“蛋白质组模式”进行疾病诊断从根本上依赖于在质谱内观察到的信号模式，而不是更传统的生物标志物识别和定量，例如癌症抗原125或前列腺特异性抗原。蛋白质组模式技术的固有通量能够每天分析数百个临床样本。目前，获得蛋白质组图谱的主要方法有两种：表面增强激光解吸/电离 (SELDI) 和电喷雾电离 (ESI) 方法，该方法已以 OvaCheck 的名称普及。在这篇综述中，描述了用于诊断早期癌症的蛋白质组学模式的发展的历史观点。此外，对整体技术进行了严格评估，重点是使蛋白质组模式分析成为诊断早期癌症的可行临床工具所需的步骤。
The pace of development in novel technologies that promise improvements in the early diagnosis of disease is truly impressive. One such technology at the forefront of this revolution is mass spectrometry. New capabilities in mass spectrometry have provided the means for the development of proteomics, and the race is on to find innovative ways to apply this powerful technology to solving the problems faced in clinical medicine. One area that has garnered much attention over the past few years is the use of mass spectral patterns for cancer diagnostics. The use of these so-called 'proteomic patterns' for disease diagnosis relies fundamentally on the pattern of signals observed within a mass spectrum rather than the more conventional identification and quantitation of a biomarker such as in the case of cancer antigen-125- or prostate-specific antigen. The inherent throughput of proteomic pattern technology enables the analysis of hundreds of clinical samples per day. Currently, there are two primary means by which proteomic patterns can be acquired, surface-enhanced laser desorption/ionization (SELDI) and an electrospray ionization (ESI) method that has been popularized under the name, OvaCheck. In this review, an historical perspective on the development of proteomic patterns for the diagnosis of early-stage cancers is described. In addition, a critical assessment of the overall technology is presented with an emphasis on the steps required to enable proteomic pattern analysis to become a viable clinical tool for diagnosing early-stage cancers.