The data-set of chronic rhinosinusitis expression profiles was downloaded from NCBI sub-database Gene Expression Omnibus. The differentially expressed genes were analyzed by GEO2R. The DEGs were analyzed and shown by the volcano plot. The GO analysis and KEGG analysis were performed by using David online tool.The DEGs were introduced into the String online data-base for analysis and the differential gene interaction network map was drawn.The interaction network data was imported into Cytoscape software, which can select Hub genes. The key sub-network was analyzed. A total of 699 DEGs were screened, of which 475 genes were up-regulated genes and 224 genes were down-regulated genes.The GO analysis showed that up-regulated DEGs were enriched in biological processes significantly,including inflammatory response, immune response,positive regulation of inflammatory response,chemotaxis and cell adhesion. The down-regulated DEGs were enriched in saliva secretion, biomineral tissue development, cellular amino acid biosynthetic process, retina homeostasis and ion transmembrane transport.The KEGG pathway analysis showed that up-regulated DEGs were enriched in hematopoietic cell lineage, cytokine-cytokine receptor interaction,osteoclast differentiation,chemokine signaling pathway. The down-regulated DEGs were enriched in salivary secretion, bile secretion.The top 10 Hub genes contained ITGAM, IL10, CD86, TLR8, ITGAX, CCL2, CCR7, SRC, EGF and ITGB2, which were identified from PPI network. The results provide a comprehensive bioinformatics analysis of DEGs in chronic rhinosinusitis with nasal polyps, however, more fundamental research is needed to validate the findings.Not only can the conclusion provide a new idea for the research direction of chronic rhinosinusitis and nasal polyps,but also make a suggestive effect on the pathogenesis of nasal polyps.