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鼻咽癌原发肿瘤相关基因相互作用网络的功能分析

Functional analysis of the nasopharyngeal carcinoma primary tumor‑associated gene interaction network.

作者信息

An Fengwei, Zhang Zhiqiang, Xia Ming

机构信息

Department of Otorhinolaryngology, Jinan Military General Hospital, Jinan, Shandong 250031, P.R. China.

Department of Gastroenterology and Hepatology, People's Hospital of Huangdao, Qingdao, Shandong 266400, P.R. China.

出版信息

Mol Med Rep. 2015 Oct;12(4):4975-80. doi: 10.3892/mmr.2015.4090. Epub 2015 Jul 20.

Abstract

The aim of the present study was to investigate the molecular mechanism of nasopharyngeal carcinoma (NPC) primary tumor development through the identification of key genes using bioinformatics approaches. Using the GSE53819 microarray dataset, acquired from the Gene Expression Omnibus database, differentially expressed genes (DEGs) were screened out between NPC primary tumor and control samples, followed by hierarchical clustering analysis. The Search Tool for the Retrieval of Interacting Genes database was utilized to build a protein‑protein interaction network to identify key node proteins. In total, 1,067 DEGs, including 326 upregulated genes and 741 downregulated genes, were identified between the NPC and control samples. The results of the hierarchical clustering analysis demonstrated that 95% of the DEGs were sample‑specific. Furthermore, PDZ binding kinase (PBK), centromere protein F (CENPF), actin‑binding protein anillin (ANLN), exonuclease 1 (EXO1) and chromosome 15 open reading frame 42 (C15ORF42) were included in the obtained network module, which was closely associated with the cell cycle and nucleic acid metabolic process GO functions. The results of the present study revealed that EXO1, CENPF, ANLN, PBK and C15ORF42 may be involved in the mechanism of NPC via modulating the cell cycle and nucleic acid metabolic processes, and may serve as molecular biomarkers for the diagnosis of this disease.

摘要

本研究的目的是通过生物信息学方法鉴定关键基因,以探讨鼻咽癌(NPC)原发肿瘤发生发展的分子机制。利用从基因表达综合数据库获取的GSE53819微阵列数据集,筛选出NPC原发肿瘤与对照样本之间的差异表达基因(DEG),随后进行层次聚类分析。利用检索相互作用基因数据库的搜索工具构建蛋白质-蛋白质相互作用网络,以识别关键节点蛋白。在NPC与对照样本之间共鉴定出1067个DEG,其中包括326个上调基因和741个下调基因。层次聚类分析结果表明,95%的DEG具有样本特异性。此外,PDZ结合激酶(PBK)、着丝粒蛋白F(CENPF)、肌动蛋白结合蛋白膜收缩蛋白(ANLN)、核酸外切酶1(EXO1)和15号染色体开放阅读框42(C15ORF42)包含在获得的网络模块中,该模块与细胞周期和核酸代谢过程的GO功能密切相关。本研究结果表明,EXO1、CENPF、ANLN、PBK和C15ORF42可能通过调节细胞周期和核酸代谢过程参与NPC的发病机制,并可能作为该疾病诊断的分子生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cdd/4581807/b3d3d2166c34/MMR-12-04-4975-g00.jpg

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