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蛋白质裂解物微阵列在分子标志物验证和定量中的应用。

Application of protein lysate microarrays to molecular marker verification and quantification.

作者信息

Ramaswamy Anitha, Lin E, Chen Iou, Mitra Rahul, Morrisett Joel, Coombes Kevin, Ju Zhenlin, Kapoor Mini

机构信息

Department of Molecular Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.

出版信息

Proteome Sci. 2005 Nov 10;3:9. doi: 10.1186/1477-5956-3-9.

Abstract

This study presents the development and application of protein lysate microarray (LMA) technology for verification of presence and quantification of human tissue samples for protein biomarkers. Sub-picogram range sensitivity has been achieved on LMA using a non-enzymatic protein detection methodology. Results from a set of quality control experiments are presented and demonstrate the high sensitivity and reproducibility of the LMA methodology. The optimized LMA methodology has been applied for verification of the presence and quantification of disease markers for atherosclerosis. LMA were used to measure lipoprotein [a] and apolipoprotein B100 in 52 carotid endarterectomy samples. The data generated by LMA were validated by ELISA using the same protein lysates. The correlations of protein amounts estimated by LMA and ELISA were highly significant, with r2 > or = 0.98 (p < or = 0.001) for lipoprotein [a] and with r2 > or = 0.94 (p < or = 0.001) for apolipoprotein B100. This is the first report to compare data generated using proteins microarrays with ELISA, a standard technology for the verification of the presence of protein biomarkers. The sensitivity, reproducibility, and high-throughput quality of LMA technology make it a potentially powerful technology for profiling disease specific protein markers in clinical samples.

摘要

本研究介绍了蛋白质裂解物微阵列(LMA)技术的开发与应用,用于验证人类组织样本中蛋白质生物标志物的存在及定量。使用非酶蛋白检测方法在LMA上实现了亚皮克级的灵敏度。展示了一组质量控制实验的结果,证明了LMA方法的高灵敏度和可重复性。优化后的LMA方法已应用于验证动脉粥样硬化疾病标志物的存在及定量。LMA用于测量52例颈动脉内膜切除术样本中的脂蛋白[a]和载脂蛋白B100。LMA生成的数据通过使用相同蛋白质裂解物的ELISA进行验证。LMA和ELISA估计的蛋白质量之间的相关性非常显著,脂蛋白[a]的r2≥0.98(p≤0.001),载脂蛋白B100的r2≥0.94(p≤0.001)。这是第一份将使用蛋白质微阵列生成的数据与ELISA(一种用于验证蛋白质生物标志物存在的标准技术)进行比较的报告。LMA技术的灵敏度、可重复性和高通量特性使其成为一种在临床样本中分析疾病特异性蛋白质标志物的潜在强大技术。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62d9/1334216/f60ff7ae9ba5/1477-5956-3-9-1.jpg

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