基于微阵列数据的胃癌相关核心基因的挖掘和鉴定分析  

Mining and Identification of Gastric Cancer Related Core Genes Based on Microarray Data

作　　者：郭鹏[1] 赵建刚[2] 刘义粉[2] 赵光远[2] 鲍双振[2] 刘防震[2] 尹长恒[2] 裴晓露 

机构地区：[1]河北医科大学第四医院骨科,河北 石家庄 [2]哈励逊国际和平医院普外一科,河北 衡水 [3]河北省人民医院肿瘤内科,河北 石家庄

出　　处：《临床医学进展》2020年第11期2695-2704,共10页Advances in Clinical Medicine

摘　　要：背景:胃癌(GC)是起源于胃黏膜上皮的恶性肿瘤,在我国恶性肿瘤死亡率中占第3位,早期症状不明显,发现时多已发展至晚期,预后较差。为了筛选GC发生发展的潜在基因,本研究从GEO数据库中获得GSE109476和GSE118916进行生物信息学分析。方法:首先,利用GEO2R识别差异表达基因(DEGs),通过GO和KEGG分析对DEGs进行功能注释。利用STRING工具构建蛋白–蛋白相互作用网络,挖掘出最重要的模块和核心基因。结果:共鉴定出229个DEGs。DEGs的功能变化主要集中在细胞黏附、细胞骨架、细胞外基质和胶原蛋白合成等方面。COL4A1、DCN、FSTL1、SPARC、SERPINH1基因被鉴定为核心基因。结论:综上所述,本研究中发现的DEGs和核心基因有可能成为潜在的诊断和治疗靶点。Background: Gastric cancer (GC) is a malignant tumor originating from gastric mucosal epithelium, accounting for the third place in the mortality rate of malignant tumors in China. The early symptoms are not obvious, and most of them have advanced stage at the time of discovery, with poor prognosis. In order to screen the potential genes for GC occurrence and development, this study obtained GSE109476 and GSE118916 from the GEO database for bioinformatics analysis. Methods: First, the differentially expressed genes (DEGs) were identified by GEO2R and functional annotation of DEGs was performed by GO and KEGG analysis. The STRING tool was used to construct the protein-protein interaction network, and the most important modules and core genes were mined. Results: A total of 229 DEGs were identified. The functional changes of DEGs mainly focus on the aspects of cell adhesion, cytoskeleton, extracellular matrix and collagen synthesis. COL4A1, DCN, FSTL1, SPARC and SERPINH1 genes were identified as core genes. Conclusion: In summary, the DEGs and core genes identified in this study may be potential diagnostic and therapeutic targets.

关 键 词：胃癌 差异表达基因 蛋白质互作网络 生物信息学 

分 类 号：R73[医药卫生—肿瘤]