Sodek Katharine L, Evangelou Andreas I, Ignatchenko Alex, Agochiya Mahima, Brown Theodore J, Ringuette Maurice J, Jurisica Igor, Kislinger Thomas
Cell and Systems Biology, University of Toronto, Toronto, Canada.
Mol Biosyst. 2008 Jul;4(7):762-73. doi: 10.1039/b717542f. Epub 2008 Apr 17.
Proteomic profiling has emerged as a useful tool for identifying tissue alterations in disease states including malignant transformation. The aim of this study was to reveal expression profiles associated with the highly motile/invasive ovarian cancer cell phenotype. Six ovarian cancer cell lines were subjected to proteomic characterization using multidimensional protein identification technology (MudPIT), and evaluated for their motile/invasive behavior, so that these parameters could be compared. Within whole cell extracts of the ovarian cancer cells, MudPIT identified proteins that mapped to 2245 unique genes. Western blot analysis for selected proteins confirmed the expression profiles revealed by MudPIT, demonstrating the fidelity of this high-throughput analysis. Unsupervised cluster analysis partitioned the cell lines in a manner that reflected their motile/invasive capacity. A comparison of protein expression profiles between cell lines of high (group 1) versus low (group 2) motile/invasive capacity revealed 300 proteins that were differentially expressed, of which 196 proteins were significantly upregulated in group 1. Protein network and KEGG pathway analysis indicated a functional interplay between proteins up-regulated in group 1 cells, with increased expression of several key members of the actin cytoskeleton, extracellular matrix (ECM) and focal adhesion pathways. These proteomic expression profiles can be utilized to distinguish highly motile, aggressive ovarian cancer cells from lesser invasive ones, and could prove to be essential in the development of more effective strategies that target pivotal cell signaling pathways used by cancer cells during local invasion and distant metastasis.
蛋白质组学分析已成为一种有用的工具,可用于识别包括恶性转化在内的疾病状态下的组织改变。本研究的目的是揭示与高迁移性/侵袭性卵巢癌细胞表型相关的表达谱。使用多维蛋白质鉴定技术(MudPIT)对六种卵巢癌细胞系进行蛋白质组学表征,并评估它们的迁移/侵袭行为,以便比较这些参数。在卵巢癌细胞的全细胞提取物中,MudPIT鉴定出了映射到2245个独特基因的蛋白质。对选定蛋白质的蛋白质印迹分析证实了MudPIT揭示的表达谱,证明了这种高通量分析的准确性。无监督聚类分析以反映其迁移/侵袭能力的方式对细胞系进行了划分。对高迁移/侵袭能力(第1组)与低迁移/侵袭能力(第2组)的细胞系之间的蛋白质表达谱进行比较,发现有300种蛋白质表达存在差异,其中196种蛋白质在第1组中显著上调。蛋白质网络和KEGG通路分析表明,第1组细胞中上调的蛋白质之间存在功能相互作用,肌动蛋白细胞骨架、细胞外基质(ECM)和粘着斑通路的几个关键成员的表达增加。这些蛋白质组学表达谱可用于区分高迁移性、侵袭性强的卵巢癌细胞与侵袭性较弱的细胞,并可能在开发更有效的策略中至关重要,这些策略针对癌细胞在局部侵袭和远处转移过程中使用的关键细胞信号通路。