Suppr超能文献

用于即时检测和监测癌症的生物标志物蛋白的测量。

Measurement of biomarker proteins for point-of-care early detection and monitoring of cancer.

机构信息

Department of Chemistry, University of Connecticut, 55 North Eagleville Road, Storrs, Connecticut 06269, USA.

出版信息

Analyst. 2010 Oct;135(10):2496-511. doi: 10.1039/c0an00204f. Epub 2010 Jul 8.

Abstract

This critical review evaluates progress toward viable point-of-care protein biomarker measurements for cancer detection and diagnostics. The ability to measure panels of specific, selective cancer biomarker proteins in physicians' surgeries and clinics has the potential to revolutionize cancer detection, monitoring, and therapy. The dream envisions reliable, cheap, automated, technically undemanding devices that can analyze a patient's serum or saliva in a clinical setting, allowing on-the-spot diagnosis. Existing commercial products for protein assays are reliable in laboratory settings, but have limitations for point-of-care applications. A number of ultrasensitive immunosensors and some arrays have been developed, many based on nanotechnology. Multilabel detection coupled with high capture molecule density in immunosensors and arrays seems to be capable of detecting a wide range of protein concentrations with sensitivity ranging into the sub pg mL(-1) level. Multilabel arrays can be designed to detect both high and ultralow abundance proteins in the same sample. However, only a few of the newer ultrasensitive methods have been evaluated with real patient samples, which is key to establishing clinical sensitivity and selectivity.

摘要

这篇评论性文章评估了在癌症检测和诊断方面实现可行的即时护理蛋白质生物标志物测量的进展。在医生的手术和诊所中测量特定、选择性癌症生物标志物蛋白质的能力有可能彻底改变癌症的检测、监测和治疗。人们梦想着能够制造出可靠、廉价、自动化且技术要求不高的设备,这些设备可以在临床环境下分析患者的血清或唾液,从而实现现场诊断。现有的蛋白质分析商业产品在实验室环境中是可靠的,但在即时护理应用方面存在局限性。已经开发出许多超灵敏免疫传感器和一些阵列,其中许多基于纳米技术。多标签检测加上免疫传感器和阵列中高捕获分子密度似乎能够以亚 pg mL(-1) 级别的灵敏度检测广泛的蛋白质浓度。多标签阵列可以设计为在同一样品中同时检测高丰度和超低丰度蛋白质。然而,只有少数较新的超灵敏方法已经用真实的患者样本进行了评估,这对于建立临床敏感性和选择性至关重要。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验