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开发一个综合平台,以鉴定人血清中的乳腺癌糖蛋白组变化。

The development of an integrated platform to identify breast cancer glycoproteome changes in human serum.

机构信息

Barnett Institute and Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, USA.

出版信息

J Chromatogr A. 2010 May 7;1217(19):3307-15. doi: 10.1016/j.chroma.2009.09.029. Epub 2009 Sep 16.

Abstract

Protein glycosylation represents one of the major post-translational modifications and can have significant effects on protein function. Moreover, changes in the carbohydrate structure are increasingly being recognized as an important modification associated with cancer etiology. In this report, we describe the development of a proteomics approach to identify breast cancer related changes in either concentration and/or the carbohydrate structures of glycoprotein(s) present in blood samples. Diseased and healthy serum samples were processed by an optimized sample preparation protocol using multiple lectin affinity chromatography (M-LAC) that partitions serum proteins based on glycan characteristics. Subsequently, three separate procedures, 1D SDS-PAGE, isoelectric focusing and an antibody microarray, were applied to identify potential candidate markers for future study. The combination of these three platforms is illustrated in this report with the analysis of control and cancer glycoproteomic fractions. Firstly, a molecular weight based separation of glycoproteins by 1D SDS-PAGE was performed, followed by protein, glycoprotein staining, lectin blotting and LC-MS analysis. To refine or confirm the list of interesting glycoproteins, isoelectric focusing (targeting sialic acid changes) and an antibody microarray (used to detect neutral glycan shifts) were selected as the orthogonal methods. As a result, several glycoproteins including alpha-1B-glycoprotein, complement C3, alpha-1-antitrypsin and transferrin were identified as potential candidates for further study.

摘要

蛋白质糖基化是一种重要的翻译后修饰方式,可对蛋白质功能产生显著影响。此外,糖链结构的变化也逐渐被认为是与癌症病因学相关的重要修饰方式。在本报告中,我们描述了一种蛋白质组学方法的开发,用于鉴定血液样本中糖蛋白浓度和/或糖链结构变化与乳腺癌的相关性。通过使用基于聚糖特性的多凝集素亲和层析(M-LAC)优化的样本制备方案处理患病和健康的血清样本。随后,应用三种单独的程序,即 1D SDS-PAGE、等电聚焦和抗体微阵列,来鉴定潜在的候选标志物用于进一步研究。本报告结合了这三种平台的分析,以研究对照和癌症糖蛋白组学部分。首先,通过 1D SDS-PAGE 基于分子量对糖蛋白进行分离,然后进行蛋白、糖蛋白染色、凝集素印迹和 LC-MS 分析。为了细化或确认感兴趣的糖蛋白列表,选择等电聚焦(针对唾液酸变化)和抗体微阵列(用于检测中性糖链变化)作为正交方法。结果,鉴定出几种糖蛋白,包括α-1B-糖蛋白、补体 C3、α-1-抗胰蛋白酶和转铁蛋白,作为进一步研究的潜在候选物。

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