Label-Free LC-MSe in Tissue and Serum Reveals Protein Networks Underlying Differences between Benign and Malignant Serous Ovarian Tumors

PurposeTo identify proteins and (molecular/biological) pathways associated with differences between benign and malignant epithelial ovarian tumors.Experimental ProceduresSerum 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.ResultsIn 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.DiscussionOur 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.

研究目的：本数据集旨在筛选与上皮性卵巢良、恶性肿瘤差异相关的蛋白质及（分子/生物学）通路。
实验方法：采集6例卵巢浆液性腺癌患者治疗前的血清样本，以6例匹配的浆液性囊腺瘤患者作为对照队列。除血清样本外，研究团队通过激光显微切割（laser microdissection）技术，从良性及癌性组织中分离出组织学形态均一的细胞均质区域。随后采用无标记液相色谱-串联质谱（LC-MSe）对上述血清及组织样本中的蛋白质进行鉴定。采用Bioconductor软件包及统计软件R中的自定义脚本开展样本间差异表达分析。此外，通过MetaCore工具完成层级聚类、通路富集分析、网络富集分析及相互作用组分析。
研究结果：最终分别在血清及组织样本中鉴定出20种和71种在良、恶性样本间显著差异表达的蛋白质。血清与组织中的差异表达蛋白质集合重合度极低，仅存在2种共有蛋白质。但MetaCore网络分析结果显示，GCR-α与Sp1为两者共有的转录调控因子。相互作用组分析表明，基于相对连接过度程度，14-3-3 ζ/δ、14-3-3 β/α、α-辅肌动蛋白4、HSP60及PCBP1是卵巢肿瘤蛋白质组特征中的关键蛋白质。本数据集已通过标识符PXD001084提交至ProteomeXchange数据库。
讨论：本研究鉴定出的蛋白质既包含与卵巢癌生物学相关的新靶点，也涵盖此前已被报道的关联分子。尽管血清与组织的差异表达蛋白质集合重叠度较低，但载脂蛋白A1（APOA1）与转铁蛋白（Serotransferrin）在血清及癌组织样本中均呈现显著低表达，提示其可能存在组织来源的血清效应。通路及后续相互作用组分析还揭示了血清与组织样本中共有的调控因子，提示PCBP1在卵巢癌病理生理过程中存在尚未阐明的作用。