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采用无标记二维 LC-MALDI MS 进行定量血浆 N-糖蛋白质组学的开发及其在肝癌生物标志物发现中的应用。

Development of quantitative plasma N-glycoproteomics using label-free 2-D LC-MALDI MS and its applicability for biomarker discovery in hepatocellular carcinoma.

机构信息

Discovery Research Laboratories, Shionogi & Co. Ltd., Fukushima-ku, Osaka 553-0002, Japan.

出版信息

J Proteomics. 2011 Sep 6;74(10):2159-68. doi: 10.1016/j.jprot.2011.06.010. Epub 2011 Jun 17.

Abstract

There has been rapid progress in the development of clinical proteomic methodologies with improvements in mass spectrometric technologies and bioinformatics, leading to many new methodologies for biomarker discovery from human plasma. However, it is not easy to find new biomarkers because of the wide dynamic range of plasma proteins and the need for their quantification. Here, we report a new methodology for relative quantitative proteomic analysis combining large-scale glycoproteomics with label-free 2-D LC-MALDI MS. In this method, enrichment of glycopeptides using hydrazide resin enables focusing on plasma proteins with lower abundance corresponding to the tissue leakage region. On quantitative analysis, signal intensities by 2-D LC-MALDI MS were normalized using a peptide internal control, and the values linked to LC data were treated with DeView™ software. Our proteomic method revealed that the quantitative dynamic ranged from 10² to 10⁶ pg/mL of plasma proteins with good reproducibility, and the limit of detection was of the order of a few ng/mL of proteins in biological samples. To evaluate the applicability of our method for biomarker discovery, we performed a feasibility study using plasma samples from patients with hepatocellular carcinoma, and identified biomarker candidates, including ceruloplasmin, alpha-1 antichymotrypsin, and multimerin-1.

摘要

临床蛋白质组学方法发展迅速,质谱技术和生物信息学不断改进,促使人们从人类血浆中发现生物标志物的新方法层出不穷。然而,由于血浆蛋白的动态范围很宽,需要对其进行定量,因此很难找到新的生物标志物。在这里,我们报告了一种新的相对定量蛋白质组学分析方法,该方法将大规模糖蛋白质组学与无标记二维 LC-MALDI MS 相结合。在这种方法中,使用酰腙树脂对糖肽进行富集,使我们能够专注于丰度较低的血浆蛋白,这些蛋白对应于组织渗漏区域。在定量分析中,使用肽内标对 2-D LC-MALDI MS 的信号强度进行归一化,并使用 DeView™软件处理与 LC 数据相关的值。我们的蛋白质组学方法表明,定量动态范围从血浆蛋白的 10²到 10⁶ pg/mL,具有良好的重现性,检测限为生物样品中几个 ng/mL 数量级的蛋白。为了评估我们的方法在生物标志物发现中的适用性,我们使用肝癌患者的血浆样本进行了一项可行性研究,鉴定出了包括铜蓝蛋白、α-1 抗胰蛋白酶和多聚蛋白-1 在内的候选生物标志物。

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