应用生物信息学技术筛选结直肠腺瘤相关基因

目的应用生物信息学技术筛选结直肠腺瘤与正常结直肠黏膜组织的差异表达基因，寻找其中的关键基因并分析分子机制。方法公共数据库GeneExpressionOmnibus（GEO）下载基因芯片GSE8671，通过R语言软件筛选出差异表达基因，进一步对差异表达基因进行GO功能富集分析和KEGG信号通路分析，并通过构建蛋白质-蛋白质相互作用网络筛选出关键基因。结果共筛选出381个差异表达基因，其中结直肠腺瘤中上调的基因248个，下调的基因133个。GO功能富集分析显示差异表达基因主要与趋化因子激活、趋化因子受体结合、激素激活和生长因子激活有关，KEGG信号通路分析表明差异表达基因与趋化因子信号通路、肿瘤坏死因子信号通路、细胞因子与受体相互作用和药物代谢有关。通过蛋白质-蛋白质相互作用网络共筛选出IL-8、CXCL1、CXCL12、CXCL13、CXCL11、CXCL2、CCL19、CCL20、PPBP、PF-4等10个关键基因。结论应用生物信息学技术分析筛选结直肠腺瘤基因有助于进一步探讨结直肠腺瘤和腺癌发病的分子机制，为两者的早期诊治提供理论依据。

Screening of colorectal adenoma related genes based on bioinformatics

Objective To screen the differentially expressed genes (DEGs) in colorectal adenoma by bioinformatic technique. The hub genes and their potential molecular mechanisms were further analyzed. Methods The gene series GSE8671 were downloaded from Gene Expression Omnibus database (GEO). R software was used for screening DEGs. Gene ontology (GO) enrichment analysis and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis of DEGs were performed by DAVID. STRING and Cytoscape were used to construct the protein-protein interaction network and screen hub genes. Results A total of 381 DEGs were identified, among which 248 genes were upregulated and 133 genes were downregulated. Go enrichment analysis showed that the DEGs mainly involved in chemokine activity, chemokine receptor binding, hormone activity and growth factor activity. KEGG pathway analysis revealed that the DEGs were related to chemokine signaling pathway, TNF signaling pathway, cytokine-cytokine receptor interaction and drug metabolism. Protein-protein interaction network identified 10 hub genes including IL -8, CXCL1, CXCL12, CXCL13, CXCL11, CXCL2, CCL19, CCL20, PPBP and PF-4. Conclusion Through analyzing the gene arrays of colorectal adenoma by bioinformatics method, this study may improve un- derstanding the molecular mechanism of colorectal adenoma and adenocarcinoma and provide information for early diagnosis and treatment of these two disorders.