Author/Authors :
Zhang Zhili نويسنده Department of Stomatology, Dongying People’s Hospital,
Dongying, 257091, Shandong Province, P.R. China , Yan Xia نويسنده Department of Pediatrics, Dongying People’s Hospital,
Dongying, 257091, Shandong Province, P.R. China , Jiang Jingqin نويسنده Department of Stomatology, Dongying People’s Hospital,
Dongying, 257091, Shandong Province, P.R. China
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 aCRSwNP composed of 13 normal samples and 21
aCRSwNP samples 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 value ≤ 0.01).
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.