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使用毛细管等电聚焦分离和通路分析对两种密切相关的卵巢子宫内膜样腺癌细胞系进行比较蛋白质组学研究。

Comparative proteomic study of two closely related ovarian endometrioid adenocarcinoma cell lines using cIEF fractionation and pathway analysis.

作者信息

Dai Lan, Li Chen, Shedden Kerby A, Misek David E, Lubman David M

机构信息

Bioinformatics Program, University of Michigan Medical Center, Ann Arbor, MI 48109-0656, USA.

出版信息

Electrophoresis. 2009 Apr;30(7):1119-31. doi: 10.1002/elps.200800505.

Abstract

The proteomic profiles from two distinct ovarian endometrioid tumor-derived cell lines, (MDAH-2774 and TOV-112D) each with different morphological characteristics and genetic mutations, have been studied. Characterization of the differential global protein expression between these two cell lines has important implications for the understanding of the pathogenesis of ovarian endometrioid carcinoma. In this comparative proteomic study, extensive fractionation of peptides generated from whole-cell trypsin digestion was achieved by coupling cIEF in the first-dimensional separation with capillary LC (RP-HPLC) in the second dimensional separation. Online analysis was performed using tandem mass spectra acquired by a linear ion trap mass spectrometer from triplicate runs. A total of 1749 and 1955 proteins with protein probability above 0.95 were identified from MDAH-2774 and TOV-112D after filtering through Peptide Prophet/Protein Prophet software. Differentially expressed proteins were further investigated by ingenuity pathway analysis (IPA) to reveal the association with important biological functions. Canonical pathway analysis using IPA demonstrates that important signaling pathways are highly associated with one of these two cell lines versus the other, such as the PI3K/AKT pathway, which is found to be significantly predominant in MDAH-2774 but not in TOV-112D. Also, protein network analysis using IPA highlights p53 as a central hub relating to other proteins from the connectivity map. These results illustrate the utility of high throughput proteomics methods using large-scale proteome profiling combined with bioinformatics tools to identify differential signaling pathways, thus contributing to the understanding of mechanisms of deregulation in neoplastic cells.

摘要

对来自两种不同的卵巢子宫内膜样肿瘤衍生细胞系(MDAH - 2774和TOV - 112D)的蛋白质组学图谱进行了研究,这两种细胞系具有不同的形态特征和基因突变。表征这两种细胞系之间差异的整体蛋白质表达,对于理解卵巢子宫内膜样癌的发病机制具有重要意义。在这项比较蛋白质组学研究中,通过将一维分离中的cIEF与二维分离中的毛细管液相色谱(RP - HPLC)相结合,实现了对全细胞胰蛋白酶消化产生的肽段进行广泛分离。使用线性离子阱质谱仪从三次重复运行中获取的串联质谱进行在线分析。通过Peptide Prophet/Protein Prophet软件过滤后,从MDAH - 2774和TOV - 112D中分别鉴定出1749种和1955种蛋白质概率高于0.95的蛋白质。通过 Ingenuity通路分析(IPA)进一步研究差异表达的蛋白质,以揭示其与重要生物学功能的关联。使用IPA进行的经典通路分析表明,重要的信号通路与这两种细胞系中的一种高度相关,而与另一种细胞系相关性较低,例如PI3K/AKT通路,该通路在MDAH - 2774中显著占主导地位,但在TOV - 112D中并非如此。此外,使用IPA进行的蛋白质网络分析突出显示p53是与连接图谱中其他蛋白质相关的中心枢纽。这些结果说明了使用大规模蛋白质组图谱结合生物信息学工具的高通量蛋白质组学方法在识别差异信号通路方面的实用性,从而有助于理解肿瘤细胞中失调机制。

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