前列腺癌患者尿液蛋白质组的2D PAGE/MS定位与鉴定

International journal of proteomics Pub Date : 2014-01-01 Epub Date: 2014-08-20 DOI:10.1155/2014/594761
Sanja Kiprijanovska, Sotir Stavridis, Oliver Stankov, Selim Komina, Gordana Petrusevska, Momir Polenakovic, Katarina Davalieva
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引用次数: 20

摘要

尿液的蛋白质组分析表明,尿液含有多种泌尿生殖系统疾病的疾病特异性信息,包括前列腺癌(PCa)。本研究的目的是确定前列腺癌患者尿液中的蛋白质成分。对8例经临床及组织学证实的前列腺癌患者的尿液进行常规二维PAGE分析。从尿液图谱中选取125个最突出的点进行质谱鉴定,发现45种不同的蛋白质。根据基因本体论,鉴定的蛋白质参与多种生物过程,其中大部分是分泌的(71%),一半是酶或转运蛋白。与正常尿液蛋白质组比较,发现有11种特异性蛋白。利用Ingenuity Pathways Analysis,我们发现了3种与细胞生长和增殖相关的蛋白(E3泛素蛋白连接酶rififylin,肿瘤蛋白D52和胸苷磷酸化酶)(p = 8.35 × 10(-4) - 3.41 × 10(-2))。11种蛋白之间的最高功能关联网络是细胞死亡和存活、细胞间信号传导和相互作用以及系统发育和功能(p = 10(-30))。总之,我们已经创建了PCa患者尿液的初始蛋白质组学图谱。本研究结果为了解前列腺癌的分子基础提供了一些线索。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Mapping and Identification of the Urine Proteome of Prostate Cancer Patients by 2D PAGE/MS.

Mapping and Identification of the Urine Proteome of Prostate Cancer Patients by 2D PAGE/MS.

Mapping and Identification of the Urine Proteome of Prostate Cancer Patients by 2D PAGE/MS.

Mapping and Identification of the Urine Proteome of Prostate Cancer Patients by 2D PAGE/MS.

Proteome analysis of the urine has shown that urine contains disease-specific information for a variety of urogenital system disorders, including prostate cancer (PCa). The aim of this study was to determine the protein components of urine from PCa patients. Urine from 8 patients with clinically and histologically confirmed PCa was analyzed by conventional 2D PAGE. The MS identification of the most prominent 125 spots from the urine map revealed 45 distinct proteins. According to Gene Ontology, the identified proteins are involved in a variety of biological processes, majority of them are secreted (71%), and half of them are enzymes or transporters. Comparison with the normal urine proteome revealed 11 proteins distinctive for PCa. Using Ingenuity Pathways Analysis, we have found 3 proteins (E3 ubiquitin-protein ligase rififylin, tumor protein D52, and thymidine phosphorylase) associated with cellular growth and proliferation (p = 8.35 × 10(-4) - 3.41 × 10(-2)). The top network of functional associations between 11 proteins was Cell Death and Survival, Cell-To-Cell Signaling and Interaction, and System Development and Function (p = 10(-30)). In summary, we have created an initial proteomic map of PCa patient's urine. The results from this study provide some leads to understand the molecular bases of prostate cancer.

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