The identification of key genes in nasopharyngeal carcinoma by bioinformatics analysis of high-throughput data
The identification of key genes in nasopharyngeal carcinoma by bioinformatics analysis of high-throughput data
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高通量数据生物信息学分析识别鼻咽癌关键基因
DOI：
10.1007/s11033-019-04729-3
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发表时间：
2019-06-01
影响因子：
2.8
通讯作者：
Zhou, Yanhong
中科院分区：
文献类型：
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作者：
Ge, Yanshan;He, Zhengxi;Zhou, Yanhong
鼻咽癌（Nasopharyngealcarcinoma，NPC）是我国南方地区，特别是广东省常见的区域性恶性肿瘤。CT技术的发展和放疗方案的改进可提高鼻咽癌患者的生存率。然而，鼻咽癌的患病率和复发率每年都在上升。揭示鼻咽癌发病的分子机制已成为当务之急。本研究使用GEO（gene expression omnibus）数据库中的科学信息检索下载了GSE 12452，共包含41个样本，其中鼻咽癌样本31个，对照样本10个。借助GO（基因本体）分析（京都基因与基因组百科全书）分析（蛋白质-蛋白质相互作用）网络模型的构建和WGCNA（加权基因共表达网络分析），我们发现了6896个差异表达基因，它们影响着细胞周期过程、DNA代谢过程、DNA修复、免疫应答、细胞活化调节免疫系统过程，炎症反应。出现在我们面前的20个枢纽基因是SYK、PIK 3CG、FYN、ACACB、LRRK 2、RIPK 4、RAC 2、PIK 3CD、PTPRC、LCR、RAD 51、MAD 2L 1、CDK 1、PCNA、GMPS、CCNB 1、GAPDH、CCNA 2、RFC 4、TOP 2A。未来，这些都是我们需要重点研究NPC分子机制的领域。
Nasopharyngeal carcinoma (NPC) is a common pattern of regional malignancy in the south of China, especially in Guangdong province. The development of computerized tomography (CT) technology and the improvement of radiotherapy scheme can improve the survival rate of NPC patients. However, the prevalence and recurrence rate of NPC are increasing every year. It is urgent for us to uncover the molecular mechanism of NPC. In this study, we used scientific information retrieval from the GEO (gene expression omnibus) database to download the GSE12452, which contained 41 samples, including 31 nasopharyngeal carcinoma samples and 10 control samples. With the help of GO (gene ontology) analysis, KEGG (kyoto encyclopedia of genes and genomes) analysis, PPI (protein–protein interaction) network model construction, and WGCNA (weighted gene co-expression network analysis), we found 6896 differentially expressed genes, which affected the biological processes included cell cycle process, DNA metabolic process, DNA repairing, immune response, cell activation, regulation of immune system process, inflammatory response. The 20 hub genes present in front of us are SYK, PIK3CG, FYN, ACACB, LRRK2, RIPK4, RAC2, PIK3CD, PTPRC, LCR, RAD51, MAD2L1, CDK1, PCNA, GMPS, CCNB1, GAPDH, CCNA2, RFC4, TOP2A. In the future, these are the areas where we need to focus on the molecular mechanism of NPC.