组织和血清中的无标记液相色谱-质谱联用技术揭示了良性和恶性浆液性卵巢肿瘤差异背后的蛋白质网络。
Label-free LC-MSe in tissue and serum reveals protein networks underlying differences between benign and malignant serous ovarian tumors.
作者信息
Wegdam Wouter, Argmann Carmen A, Kramer Gertjan, Vissers Johannes P, Buist Marrije R, Kenter Gemma G, Aerts Johannes M F G, Meijer Danielle, Moerland Perry D
机构信息
Department of Gynecology, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands.
Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.
出版信息
PLoS One. 2014 Sep 29;9(9):e108046. doi: 10.1371/journal.pone.0108046. eCollection 2014.
PURPOSE
To identify proteins and (molecular/biological) pathways associated with differences between benign and malignant epithelial ovarian tumors.
EXPERIMENTAL PROCEDURES
Serum of six patients with a serous adenocarcinoma of the ovary was collected before treatment, with a control group consisting of six matched patients with a serous cystadenoma. In addition to the serum, homogeneous regions of cells exhibiting uniform histology were isolated from benign and cancerous tissue by laser microdissection. We subsequently employed label-free liquid chromatography tandem mass spectrometry (LC-MSe) to identify proteins in these serum and tissues samples. Analyses of differential expression between samples were performed using Bioconductor packages and in-house scripts in the statistical software package R. Hierarchical clustering and pathway enrichment analyses were performed, as well as network enrichment and interactome analysis using MetaCore.
RESULTS
In total, we identified 20 and 71 proteins that were significantly differentially expressed between benign and malignant serum and tissue samples, respectively. The differentially expressed protein sets in serum and tissue largely differed with only 2 proteins in common. MetaCore network analysis, however inferred GCR-alpha and Sp1 as common transcriptional regulators. Interactome analysis highlighted 14-3-3 zeta/delta, 14-3-3 beta/alpha, Alpha-actinin 4, HSP60, and PCBP1 as critical proteins in the tumor proteome signature based on their relative overconnectivity. The data have been deposited to the ProteomeXchange with identifier PXD001084.
DISCUSSION
Our analysis identified proteins with both novel and previously known associations to ovarian cancer biology. Despite the small overlap between differentially expressed protein sets in serum and tissue, APOA1 and Serotransferrin were significantly lower expressed in both serum and cancer tissue samples, suggesting a tissue-derived effect in serum. Pathway and subsequent interactome analysis also highlighted common regulators in serum and tissue samples, suggesting a yet unknown role for PCBP1 in ovarian cancer pathophysiology.
目的
鉴定与良性和恶性上皮性卵巢肿瘤差异相关的蛋白质及（分子/生物学）通路。
实验步骤
收集6例卵巢浆液性腺癌患者治疗前的血清，对照组为6例匹配的浆液性囊腺瘤患者。除血清外，通过激光显微切割从良性和癌组织中分离出组织学一致的细胞均质区域。随后，我们采用无标记液相色谱串联质谱（LC-MSe）来鉴定这些血清和组织样本中的蛋白质。使用统计软件包R中的Bioconductor软件包和内部脚本对样本间的差异表达进行分析。进行了层次聚类和通路富集分析，以及使用MetaCore进行的网络富集和相互作用组分析。
结果
我们总共鉴定出分别在良性和恶性血清及组织样本之间显著差异表达的20种和71种蛋白质。血清和组织中差异表达的蛋白质组在很大程度上不同，仅有2种蛋白质相同。然而，MetaCore网络分析推断GCR-α和Sp1为共同的转录调节因子。相互作用组分析突出显示14-3-3 ζ/δ、14-3-3 β/α、α-辅肌动蛋白4、HSP60和PCBP1因其相对较高的连接性而成为肿瘤蛋白质组特征中的关键蛋白质。数据已存入ProteomeXchange，标识符为PXD001084。
讨论
我们的分析鉴定出了与卵巢癌生物学既有新关联又有已知关联的蛋白质。尽管血清和组织中差异表达的蛋白质组之间重叠较小，但载脂蛋白A1和转铁蛋白在血清和癌组织样本中均显著低表达，提示血清中有组织来源的影响。通路及随后的相互作用组分析还突出显示了血清和组织样本中的共同调节因子，提示PCBP1在卵巢癌病理生理学中存在未知作用。
Zotero 插件