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基于网络的食管鳞状细胞癌中LCN2过表达基因表达谱分析

Network based analyses of gene expression profile of LCN2 overexpression in esophageal squamous cell carcinoma.

作者信息

Wu Bingli, Li Chunquan, Du Zepeng, Yao Qianlan, Wu Jianyi, Feng Li, Zhang Pixian, Li Shang, Xu Liyan, Li Enmin

机构信息

1] Department of Biochemistry and Molecular Biology, Shantou University Medical College, Shantou515041, China [2].

1] Department of Biochemistry and Molecular Biology, Shantou University Medical College, Shantou515041, China [2] College of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing163319, China [3].

出版信息

Sci Rep. 2014 Jun 23;4:5403. doi: 10.1038/srep05403.

Abstract

LCN2 (lipocalin 2) is a member of the lipocalin family of proteins that transport small, hydrophobic ligands. LCN2 is elevated in various cancers including esophageal squamous cell carcinoma (ESCC). In this study, LCN2 was overexpressed in the EC109 ESCC cell line and we applied integrated analyses of the gene expression data to identify protein-protein interactions (PPI) network to enhance our understanding of the role of LCN2 in ESCC. Through further mining of PPI sub-networks, hundreds of differentially expressed genes (DEGs) were identified to interact with thousands of other proteins. Subcellular localization analyses found the DEGs and their directly or indirectly interacting proteins distributed in multiple layers, which was applied to analyze the possible paths between two DEGs. Gene Ontology annotation generated a functional annotation map and found hundreds of significant terms, especially those associated with the known and potential roles of LCN2 protein. The algorithm of Random Walk with Restart was applied to prioritize the DEGs and identified several cancer-related DEGs ranked closest to LCN2 protein. These analyses based on PPI network have greatly expanded our understanding of the mRNA expression profile of LCN2 overexpression for future examination of the roles and mechanisms of LCN2.

摘要

脂联素2(LCN2)是运载小的疏水性配体的脂联素家族蛋白质成员。LCN2在包括食管鳞状细胞癌(ESCC)在内的多种癌症中表达升高。在本研究中,LCN2在ESCC细胞系EC109中过表达,我们应用基因表达数据的综合分析来识别蛋白质-蛋白质相互作用(PPI)网络,以加深我们对LCN2在ESCC中作用的理解。通过对PPI子网的进一步挖掘,鉴定出数百个差异表达基因(DEG)与数千种其他蛋白质相互作用。亚细胞定位分析发现DEG及其直接或间接相互作用的蛋白质分布在多个层次,这被用于分析两个DEG之间的可能路径。基因本体注释生成了一个功能注释图,并发现了数百个重要术语,特别是那些与LCN2蛋白的已知和潜在作用相关的术语。应用带重启的随机游走算法对DEG进行优先级排序,并鉴定出几个与癌症相关的、排名最接近LCN2蛋白的DEG。这些基于PPI网络的分析极大地扩展了我们对LCN2过表达的mRNA表达谱的理解,以便未来研究LCN2的作用和机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/06af/4066265/8a6013b232d7/srep05403-f1.jpg

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