Identification of Key Modules, Hub Genes, and Noncoding RNAs in Chronic Rhinosinusitis with Nasal Polyps by Weighted Gene Coexpression Network Analysis

Abstract

Chronic rhinosinusitis with nasal polyps (CRSwNP) is a chronic inflammatory disease with relatively easy recurrence. However, the precise molecular mechanisms of this disease are poorly known. Based on gene sequencing data obtained from the Gene Expression Omnibus (GEO) database, we constructed coexpression networks by weighted gene coexpression network analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The core gene of pathogenesis, CRSwNP, was screened by protein-protein interaction data (PPI) from the HPRD database. Unsupervised clustering was applied to screen hub genes related to the phenotype of CRSwNP. Blue and turquoise modules were found to be most significantly related to the pathogenicity of CRSwNP. Functional enrichment analysis showed that cell proliferation in the blue modules, the apoptotic process in the turquoise module, and the cancer pathway in both modules were mostly significantly correlated with the development of CRSwNP. The noncoding RNAs (long noncoding RNA and microRNA) and the top 10 core genes in each module were found to be associated with the pathogenesis of CRSwNP. A total of nine hub genes were identified to be related to the CRSwNP phenotype. By qRT-PCR analysis, AKT1, CDH1, PIK3R1, CBL, LRP1, MALAT1, and XIST were proven to be associated with the pathogenesis of CRSwNP. AGR2, FAM3D, PIP, DSE, and TMC were identified to be related to the CRSwNP phenotype. Further exploration of these genes will reveal more important information about the mechanisms of CRSwNP.

Transcriptomic Signatures and Functional Network Analysis of Chronic Rhinosinusitis With Nasal Polyps

“…Although previous studies involved bioinformatic analysis of mRNAs and lncRNAs in CRSwNP (Liu et al, 2019 ; Zhou et al, 2020 ), one study included only 12 CRSwNP patients and 9 healthy controls. The other study used nasal tissue data combined with primary human basal cells cultured in an air-liquid interface system, which might be different from nasal polyp tissue.…”

Gene co-expression network analysis reveals immune cell infiltration as a favorable prognostic marker in non-uterine leiomyosarcoma

“…By applying WGCNA, detailed characteristics have been investigated at the genetic network level 15 . This framework has been successfully utilized to study different cancers and non-cancer diseases 16,17 .Finding co-expression patterns can also associate the unknown function genes with biological processes due to the guiltby-association (GBA) basis of WGCNA.…”

Construction and analysis of a ceRNA network and patterns of immune infiltration in chronic rhinosinusitis with nasal polyps: based on data mining and experimental verification

“…This novel transcript has been demonstrated to play important roles in a wide range of biological processes in humans. Recent studies have demonstrated the vital role of lncRNAs in CRSwNP, and some of these lncRNAs may be potential biomarkers for diagnosis and therapeutic targets 32 , 54 . The competing endogenous RNA (ceRNA) hypothesis proposed by Salmena et al in 2011 pointed to lncRNAs acting as endogenous molecular sponges that competitively bind miRNAs via shared MREs with reverse complementary binding seed regions to indirectly regulate mRNA expression levels 24 .…”