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Bioinformatic analysis of next?generation sequencing data to identify dysregulated genes in fibroblasts of idiopathic pulmonary fibrosis.

ABSTRACT: Idiopathic pulmonary fibrosis (IPF) is a lethal fibrotic lung disease with an increasing global burden. It is hypothesized that fibroblasts have a number of functions that may affect the development and progression of IPF. However, the present understanding of cellular and molecular mechanisms associated with fibroblasts in IPF remains limited. The present study aimed to identify the dysregulated genes in IPF fibroblasts, elucidate their functions and explore potential microRNA (miRNA)?mRNA interactions. mRNA and miRNA expression profiles were obtained from IPF fibroblasts and normal lung fibroblasts using a next?generation sequencing platform, and bioinformatic analyses were performed in a step?wise manner. A total of 42 dysregulated genes (>2 fold?change of expression) were identified, of which 5 were verified in the Gene Expression Omnibus (GEO) database analysis, including the upregulation of neurotrimin (NTM), paired box 8 (PAX8) and mesoderm development LRP chaperone, and the downregulation of ITPR interacting domain containing 2 and Inka box actin regulator 2 (INKA2). Previous data indicated that PAX8 and INKA2 serve roles in cell growth, proliferation and survival. Gene Ontology analysis indicated that the most significant function of these 42 dysregulated genes was associated with the composition and function of the extracellular matrix (ECM). A total of 60 dysregulated miRNAs were also identified, and 1,908 targets were predicted by the miRmap database. The integrated analysis of mRNA and miRNA expression data, combined with GEO verification, finally identified Homo sapiens (hsa)?miR?1254?INKA2 and hsa?miR?766?3p?INKA2 as the potential miRNA?mRNA interactions in IPF fibroblasts. In summary, the results of the present study suggest that dysregulation of PAX8, hsa?miR?1254?INKA2 and hsa?miR?766?3p?INKA2 may promote the proliferation and survival of IPF fibroblasts. In the functional analysis of the dysregulated genes, a marked association between fibroblasts and the ECM was identified. These data improve the current understanding of fibroblasts as key cells in the pathogenesis of IPF. As a screening study using bioinformatics approaches, the results of the present study require additional validation.

SUBMITTER: Sheu CC

PROVIDER: S-EPMC6414167 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Bioinformatic analysis of next‑generation sequencing data to identify dysregulated genes in fibroblasts of idiopathic pulmonary fibrosis.

Sheu Chau-Chyun CC Chang Wei-An WA Tsai Ming-Ju MJ Liao Ssu-Hui SH Chong Inn-Wen IW Kuo Po-Lin PL

International journal of molecular medicine 20190131 4

Idiopathic pulmonary fibrosis (IPF) is a lethal fibrotic lung disease with an increasing global burden. It is hypothesized that fibroblasts have a number of functions that may affect the development and progression of IPF. However, the present understanding of cellular and molecular mechanisms associated with fibroblasts in IPF remains limited. The present study aimed to identify the dysregulated genes in IPF fibroblasts, elucidate their functions and explore potential microRNA (miRNA)‑mRNA inte ...[more]

PMID: 30720061

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Project description:Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with reduced quality of life and earlier mortality, but its pathogenesis and key genes are still unclear. In this investigation, bioinformatics was used to deeply analyze the pathogenesis of IPF and related key genes, so as to investigate the potential molecular pathogenesis of IPF and provide guidance for clinical treatment. Next-generation sequencing dataset GSE213001 was obtained from Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) were identified between IPF and normal control group. The DEGs between IPF and normal control group were screened with the DESeq2 package of R language. The Gene Ontology (GO) and REACTOME pathway enrichment analyses of the DEGs were performed. Using the g:Profiler, the function and pathway enrichment analyses of DEGs were performed. Then, a protein-protein interaction (PPI) network was constructed via the Integrated Interactions Database (IID) database. Cytoscape with Network Analyzer was used to identify the hub genes. miRNet and NetworkAnalyst databaseswereused to construct the targeted microRNAs (miRNAs), transcription factors (TFs), and small drug molecules. Finally, receiver operating characteristic (ROC) curve analysis was used to validate the hub genes. A total of 958 DEGs were screened out in this study, including 479 up regulated genes and 479 down regulated genes. Most of the DEGs were significantly enriched in response to stimulus, GPCR ligand binding, microtubule-based process, and defective GALNT3 causes HFTC. In combination with the results of the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network, hub genes including LRRK2, BMI1, EBP, MNDA, KBTBD7, KRT15, OTX1, TEKT4, SPAG8, and EFHC2 were selected. Cyclothiazide and rotigotinethe are predicted small drug molecules for IPF treatment. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of IPF, and provide a novel strategy for clinical therapy.

Dataset Information

Bioinformatic analysis of next?generation sequencing data to identify dysregulated genes in fibroblasts of idiopathic pulmonary fibrosis.

Publications

Bioinformatic analysis of next‑generation sequencing data to identify dysregulated genes in fibroblasts of idiopathic pulmonary fibrosis.

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