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脑癌癫痫患者的蛋白质-蛋白质相互作用网络分析和基因集富集分析

Protein-protein interaction network analysis and gene set enrichment analysis in epilepsy patients with brain cancer.

作者信息

Kong Bin, Yang Tao, Chen Lin, Kuang Yong-Qin, Gu Jian-Wen, Xia Xun, Cheng Lin, Zhang Jun-Hai

机构信息

Department of Neurosurgery, Chengdu Military General Hospital, 270 Rong Du Road, Chengdu 610083, Sichuan Province, China; Third Military Medical University, Chongqing, China.

Department of Neurology, Chengdu Military General Hospital, Chengdu, Sichuan Province, China.

出版信息

J Clin Neurosci. 2014 Feb;21(2):316-9. doi: 10.1016/j.jocn.2013.06.026. Epub 2013 Nov 14.

Abstract

Many patients with brain cancer experience seizures or epilepsy and tumor-associated epilepsy (TAE) significantly decreases their quality of life. This study aimed to achieve a better understanding of the mechanisms of TAE. The differentially expressed genes (DEG) between epilepsy patients with or without brain tumor were firstly screened using the Linear Models for Microarray Data package using GSE4290 datasets from the USA National Center for Biotechnology Information Gene Expression Omnibus database. Then the protein-protein interaction (PPI) network, using data from the Human Protein Reference Database and the Biological General Repository for Interaction Datasets, was constructed. For further analysis, the PPI network structure and clusters in this PPI network were identified by ClusterOne. Meanwhile, gene set enrichment analysis was performed to illuminate the biological pathways and processes which generally affect patients with TAE. A total of 5113 DEG were identified and a PPI network, which contained 114 DEG and 21 normal genes, was established. Proteins, which mainly belonged to the mini chromosome maintenance and collagen families, were discovered to be enriched in the three identified clusters in the PPI network. Finally, several biological pathways (including cell cycle, DNA replication and transforming growth factor β1 signaling pathways) and processes (such as nucleocytoplasmic transport, nuclear transport and regulation of phosphorylation) were identified. Proteins in these three clusters may become new targets for TAE treatment. Our results provide some potential underlying biomarkers for understanding the pathogenesis of epilepsy in patients with brain tumor.

摘要

许多脑癌患者会经历癫痫发作或患有癫痫,而肿瘤相关性癫痫(TAE)会显著降低他们的生活质量。本研究旨在更好地了解TAE的发病机制。首先,使用来自美国国立生物技术信息中心基因表达综合数据库的GSE4290数据集,通过微阵列数据线性模型软件包筛选出有或无脑肿瘤的癫痫患者之间的差异表达基因(DEG)。然后,利用来自人类蛋白质参考数据库和相互作用数据集生物学通用存储库的数据构建蛋白质-蛋白质相互作用(PPI)网络。为了进一步分析,通过ClusterOne识别该PPI网络的结构和簇。同时,进行基因集富集分析以阐明通常影响TAE患者的生物学途径和过程。共鉴定出5113个DEG,并建立了一个包含114个DEG和21个正常基因的PPI网络。发现主要属于微小染色体维持和胶原蛋白家族的蛋白质在PPI网络中鉴定出的三个簇中富集。最后,确定了几个生物学途径(包括细胞周期、DNA复制和转化生长因子β1信号通路)和过程(如核质运输、核运输和磷酸化调节)。这三个簇中的蛋白质可能成为TAE治疗的新靶点。我们的结果为理解脑肿瘤患者癫痫的发病机制提供了一些潜在的生物标志物。

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