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A biotin label-based antibody array for high-content profiling of protein expression.

机译:基于生物素标记的抗体阵列,用于蛋白质表达的高含量分析。

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BACKGROUND/AIM: Profiling protein expression on a global scale will have significant impact on biomedical research, particularly in the discovery and development of drugs and biomarkers. Through the years, several antibody array systems have been invented and developed for multiple protein detection. However, a reliable and high-content system for protein profiling from many biological samples has yet been developed. This study aimed to develop a reliable, easy to use and cost effective method to profile protein expression levels in high-content manner with sufficient sensitivity and specificity. MATERIALS AND METHODS: To address this problem, a high density antibody array was developed and used this technology to uncover the potential biomarkers of ovarian cancer. In this system, biological samples are labeled with biotin. The biotinylated proteins are then incubated with antibody chips. The presence of proteins captured by the antibody chip is detected using streptavidin-conjugated fluorescent dye (Cy3 equivalent) as a reporter. The signals, which are visualized by laser scanning, are normalized using positive, negative, and internal controls. RESULTS: Using this biotin label-based antibody array technology, the expression levels of 507 human, 308 mouse and 90 rat target proteins can be simultaneously detected, including of cytokines, chemokines, adipokines, growth factors, angiogenic factors, proteases, soluble receptors, soluble adhesion molecules, and other proteins in a variety of samples. Most proteins can be detected at pg/ml and ng/ml levels, with a coefficient of variation of less than 20%. Using human biotin-based antibody arrays, we screened the serum expression profiles of 507 proteins in ovarian cancer patients and healthy individuals. A panel of protein expression showed significant difference between normal and cancer samples (p<0.05). By classification analysis and split-point score analysis of these two groups, a small group of proteins were found to be useful in distinguishing ovarian cancer patients from normal subjects. CONCLUSION: Our results suggest the biotin label-based antibody arrays that we have developed have great potential in applications for biomarker discovery.
机译:背景/目的:在全球范围内分析蛋白质表达将对生物医学研究产生重大影响,特别是在药物和生物标志物的发现和开发中。多年以来,已经发明和开发了用于多种蛋白质检测的几种抗体阵列系统。但是,已经开发了一种可靠的高含量系统,用于从许多生物样品中进行蛋白质谱分析。这项研究旨在开发一种可靠,易于使用且具有成本效益的方法,以足够的敏感性和特异性以高含量方式分析蛋白质表达水平。材料和方法:为了解决这个问题,开发了一种高密度抗体阵列,并使用该技术发现了卵巢癌的潜在生物标志物。在该系统中,生物样品用生物素标记。然后将生物素化的蛋白质与抗体芯片孵育。使用链霉亲和素偶联的荧光染料(Cy3当量)作为报告基因,检测抗体芯片捕获的蛋白质的存在。使用正,负和内部控制对通过激光扫描可视化的信号进行归一化。结果:使用这种基于生物素标记的抗体阵列技术,可以同时检测507种人,308种小鼠和90种大鼠靶蛋白的表达水平,包括细胞因子,趋化因子,脂肪因子,生长因子,血管生成因子,蛋白酶,可溶性受体,各种样品中的可溶性粘附分子和其他蛋白质。可以以pg / ml和ng / ml的水平检测到大多数蛋白质,变异系数小于20%。使用基于人类生物素的抗体阵列,我们筛选了卵巢癌患者和健康个体中507种蛋白质的血清表达谱。一组蛋白质表达显示正常样品和癌症样品之间的显着差异(p <0.05)。通过这两组的分类分析和分裂点评分分析,发现了一小部分蛋白质可用于区分卵巢癌患者和正常受试者。结论:我们的结果表明,我们开发的基于生物素标记的抗体阵列在生物标记发现的应用中具有巨大潜力。

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