基于囊性纤维化疾病分子特征及其作用机制的生物信息学分析

目的：筛选囊性纤维化（CF）特异性相关基因，预测其靶基因，并探讨其作用机制。方方法法：从基因表达汇编（GEO）数据库获取CF样本和正常对照样本的高通量芯片数据集GSE71799、GSE24206、GSE98925和GSE69764，并分为CF组和对照组。采用R软件limma包筛选CF组和对照组差异表达基因（DEGs），使用基因本体（GO）功能注释和京都基因与基因组百科全书（KEGG）对DEGs进行功能和通路富集分析，使用基因集富集分析（GSEA）获取DEGs显著富集的基因集，采用STRING数据库建立蛋白-蛋白互作（PPI）网络，采用Cytoscape软件可视化并筛选hub基因。结果：GEO数据库获取并筛选共429个DEGs （|log2 (FC)|>1, P<0.05）, CF组中显著高表达DEGs 105个，对照组中显著高表达DEGs 324个。GO富集分析，DEGs主要富集于中性粒细胞介导的免疫、趋化因子活动和细胞黏附分子结合等方面；KEGG通路分析，DEGs主要富集于白细胞介素17 (IL-17)信号通路（P<0.05）。GSEA分析，DEGs主要富集于信号通...

Bioinformatics analysis based on molecular characteristics and mechanism of cystic fibrosis

Objective To screen the specific genes of cystic fibrosis （CF） and predict the target genes， and to study its mechanism. Methods The datasets（GSE71799，GSE24206，GSE98925 and GSE69764） including CF samples and normal samples were downloaded from the Gene Expression Omnibus（GEO）database and divided into CF group and control group. The R software limma package was used to screen the differentially expressed genes（DEGs） in CF group and control group. Gene Ontology（GO） and Kyoto Encyclopedia of Genes and Genomes（KEGG）were used to analyze the function and pathway enrichment of DEGs， Gene Set Enrichment Analysis（GSEA）was used to obtain the significantly enriched gene sets of DEGs， and STRING database was used to establish the protein-protein interaction（PPI）network. The PPI network was analyzed and visualized by Cytoscape software， and the hub genes were screened. Results A total of 429 DEGs were obtained and screened， including 105 DEGs that were overexpressed in CF group and 324 DEGs that were overexpressed in control group（|log2（FC）|>1，P<0.05）. The GO enrichment analysis results showed that DEGs were mainly enriched in the neutrophil mediated immunity， chemokine activity and cell adhesion molecule binding and so on（P<0.05）. The results of KEGG pathway analysis demonstrated that DEGs were mainly enriched in interleukin-17（IL-17） signaling pathway（P<0.05）. The results of GSEA demonstrated that DEGs were mainly enriched in signaling pathway translation， ribosomal RNA（rRNA） processing and mitochondrial translation and so on. Through STRING database and Cytoscape software， 35 hub genes in the PPI network were screened out， including matrix metallopeptidase 9（MMP9）， C-X-C motif chemokine ligand 2（CXCL2） and C-X-C motif chemokine ligand 3（CXCL3）. In addition， CXCL2 and CXCL3 were associated with DNA methylation. Conclusion The disorder of neutrophil-mediated immunity-related genes and IL-17 signaling pathway-related genes may play an important role in the occurrence and development of CF. CXCL2 and CXCL3 genes may become the biomarkers for DNA methylation therapy of CF.