【摘要】 目的:联合多种生物信息学分析方法筛选结肠癌枢纽基因,进一步对枢纽基因进行分析并构建调控网络,以期探索结肠癌的发病机制。方法:从GEO基因芯片数据库筛选结肠癌组织的基因表达数据集,利用在线工具GEO2R筛选差异表达基因(differentially expressed genes,DEG),对差异基因进行Gene Ontolog(GO)分析、KEGG通路分析、蛋白相互作用网络构建等。结果:共纳入2个结肠癌GEO数据集(GSE41258和GSE44076),筛选出在这2个数据集中有交集的差异表达2倍以上的基因120个,其中表达上调的基因29个,表达下调的基因91个。对上述120个差异表达基因进行KEGG通路分析发现近端小管碳酸氢钠回收、氮素代谢、胰液分泌、PPAR信号通路等与结肠癌的发生密切相关。利用STRING及Cytoscape软件筛选得到包括趋化因子1(CXCL1)、基质金属蛋白酶1 (MMP1)、MMP7等在内的10个调控结肠癌发生的枢纽基因,进一步在TCGA数据库中验证这些基因的表达。结论:通过生物信息学方法有效地筛选出与结肠癌发生密切相关的枢纽基因,为进一步研究其机制提供了理论依据。更多还原

【Abstract】 Objective: To pick out the driven-genes of colon cancer by bioinformatics analysis so as to have a better understanding of the pathogenesis of colon cancer. Methods: Gene expression profile of GSE41258 and GSE44076 from GEO database were deeply analyzed. GEO2 R tool was utilized to screen the differentially expressed genes( DEG) between colon cancer tissues and normal controls. Gene ontology( GO) analysis and KEGG pathway analysis were performed for differentially expressed genes. Moreover,Search Tool for the Retrieval of Interacting Genes( STRING) and Cytoscape software were used to visualize the protein-protein interaction( PPI) of these differentially expressed genes. Results: A total of 120 differentially expressed genes were obtained,including 29 upregulated genes and 91 downregulated genes. These differentially expressed genes were mainly enriched in proximal tubule bicarbonate reclamation,nitrogen metabolism,pancreatic secretion and PPAR signaling pathway. Moreover,10 hub genes with high degree of connectivity were selected,including CXCL1,MMP1,and MMP7,etc. The expression analysis of hub genes was verified in TCGA database. Conclusion: Taken together,the key genes can be effectively screened by bioinformatics analysis. Our results may provide new insights for further study.更多还原