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

Autor: Yiqing Liu, Zhaoyang Cui, Zhiyong Yue, Anting Xu, Xuanchen Zhou, Jie Han, Xiaoyue Zhen
Rok vydání: 2020
Předmět:
0301 basic medicine
RNA
Untranslated
Article Subject
Computational biology
Biology
General Biochemistry
Genetics and Molecular Biology
CDH1
03 medical and health sciences
Mucoproteins
Nasal Polyps
0302 clinical medicine
Antigens
CD
Antigens
Neoplasm
microRNA
Humans
Gene Regulatory Networks
Proto-Oncogene Proteins c-cbl
Sinusitis
KEGG
Gene
Oncogene Proteins
MALAT1
General Immunology and Microbiology
Gene Expression Profiling
Membrane Transport Proteins
General Medicine
Cadherins
Phenotype
Long non-coding RNA
Neoplasm Proteins
Class Ia Phosphatidylinositol 3-Kinase
DNA-Binding Proteins
Gene Ontology
030104 developmental biology
030220 oncology & carcinogenesis
biology.protein
Medicine
Cytokines
RNA
Long Noncoding
XIST
Transcriptome
Proto-Oncogene Proteins c-akt
Low Density Lipoprotein Receptor-Related Protein-1
Research Article
Transcription Factors
Zdroj: BioMed Research International
BioMed Research International, Vol 2020 (2020)
ISSN: 2314-6141
2314-6133
DOI: 10.1155/2020/6140728
Popis: 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.
Databáze: OpenAIRE
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