Identification of core genes and outcome in gastric cancer using bioinformatics analysis.
Identification of core genes and outcome in gastric cancer using bioinformatics analysis.
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DOI：
10.18632/oncotarget.20082
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发表时间：
2017-09-19
期刊：
影响因子：
--
通讯作者：
Wang B
中科院分区：
文献类型：
--
作者：
Sun C;Yuan Q;Wu D;Meng X;Wang B
胃癌是一种常见的胃肠道恶性肿瘤。我们从GEO数据库中选取GSE 54129的基因表达谱，旨在寻找胃癌发生发展的关键基因。132个样本，包括111个癌症和21个正常胃粘膜上皮，被纳入该分析。利用GEO 2 R工具筛选出胃癌患者与健康人的差异表达基因（DEG），并利用大卫数据库进行基因本体（GO）分析和京都基因与基因组百科全书（KEGG）通路分析。此外，Cytoscape与搜索工具检索相互作用基因（STRING）和分子复合物检测（MCODE）插件被用来可视化这些DEG的蛋白质-蛋白质相互作用（PPI）。共检测到971个DEG，其中468个基因在粘着斑、ECM-受体相互作用和PI 3 K-Akt信号通路中表达上调，503个基因在细胞色素P450代谢异种药物、化学致癌、视黄醇代谢和胃酸分泌中表达下调。利用MCODE软件从PPI网络中检测出三个重要模块。此外，还筛选出15个具有高度连接性的枢纽基因，包括BGN、MMP 2、COL 1A 1和FN 1。采用Kaplan-Meier法分析总生存率，并对各基因进行相关性分析。总之，生物信息学分析表明，DEGs和枢纽基因，如BGN，可能促进胃癌的发展，特别是在肿瘤转移。此外，它还可作为一种新的生物标志物用于胃癌的诊断和指导联合用药。
Gastric cancer (GC) is a common malignant neoplasm of gastrointestinal tract. We chose gene expression profile of GSE54129 from GEO database aiming to find key genes during the occurrence and development of GC. 132 samples, including 111 cancer and 21 normal gastric mucosa epitheliums, were included in this analysis. Differentially expressed genes (DEGs) between GC patients and health people were picked out using GEO2R tool, then we performed gene ontology (GO) analysis and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis using The Database for Annotation, Visualization and Integrated Discovery (DAVID). Moreover, Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING) and Molecular Complex Detection (MCODE) plug-in was utilized to visualize protein-protein interaction (PPI) of these DEGs. There were 971 DEGs, including 468 up-regulated genes enriched in focal adhesion, ECM-receptor interaction and PI3K-Akt signaling pathway, while 503 down-regulated genes enriched in metabolism of xenbiotics and drug by cytochrome P450, chemical carcinogenesis, retinol metabolism and gastric acid secretion. Three important modules were detected from PPI network using MCODE software. Besides, Fifteen hub genes with high degree of connectivity were selected, including BGN, MMP2, COL1A1, and FN1. Moreover, the Kaplan–Meier analysis for overall survival and correlation analysis were applied among those genes. In conclusion, this bioinformatics analysis demonstrated that DEGs and hub genes, such as BGN, might promote the development of gastric cancer, especially in tumor metastasis. In addition, it could be used as a new biomarker for diagnosis and to guide the combination medicine of gastric cancer.
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