Abstract

Background: Asthmatic chronic rhinosinusitis with nasal polyps (aCRSwNP) is a common disruptive eosinophilic disease. However, up to now, there is no effective medical treatment for the disease, which is partly due to that the molecular mechanism of aCRSwNP is still unknown. Objectives: The aim of this study was to facilitate the systematic discovery of diagnostic biomarkers of aCRSwNP based on integrating pathways, differentially expressed genes (DEGs), and mutual information networks (MINs). Methods: This was a foundation-application study carried out in Dongying, Shandong Province, P.R. China, in 2016. First, the gene expression profile of aCRSwNPcomposed of 13 normal samples and 21aCRSwNPsamples was recruited from the gene expression omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/) and then, data preprocessing was performed. Second, the attract method was utilized to identify differential pathways. In the following, MINs were constructed and underwent topological analysis. Then, DEGs were examined in aCRSwNP group and normal control group to identify significant genes and key genes. Finally, the support vector machine (SVM) with C-classification was utilized to evaluate the performance of the classification. Results: A total of 11,100 genes and 273 pathways (gene count > 5) were initially obtained. Then, 5 differential pathways which contained 346 genes were identified. Topological analysis conducted on the MINs revealed 20 hub genes (degree centrality 220). In the following, 795 DEGs were identified (|log fold change (FC)| 2.0, P value0.01). Furthermore, 35 significant genes and 14 key genes were detected. Finally, the results of SVM with C-classification indicated that the key genes gave the best result. Conclusions: Our research identified several key genes (such as IL6R), which might play key roles in the occurrence and development of aCRSwNP.We predicted that these genes might provide additional diagnostic and therapeutic targets for aCRSwNP.

Authors and Affiliations