scholarly journals Integrated Analysis of a Gene Correlation Network Identifies Critical Regulation of Fibrosis by lncRNAs and TFs in Idiopathic Pulmonary Fibrosis

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Fan Wang ◽  
Pei Li ◽  
Feng-sen Li
Keyword(s):  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Pcr Analysis ◽  
Unknown Etiology ◽  
Integrated Analysis ◽  
Protein Protein Interaction ◽  
Lncrna Malat1 ◽  
Significant Difference

Idiopathic pulmonary fibrosis (IPF), the most frequent form of irreversible interstitial pneumonia with unknown etiology, is characterized by massive remodeling of lung architecture and followed by progressive loss of lung function. However, the key regulatory genes and the specific signaling pathways involved in the onset and progression of IPF still remain unclear. The present study is aimed at investigating the key role of long noncoding RNAs (lncRNAs) and transcription factors (TFs) involved in the pathogenesis of IPF through the integrated analysis of three gene expression profiles from the GEO dataset (GSE2052, GSE44723, and GSE24206). A total of 8483 differentially expressed genes (DEGs) including 988 upregulated and 7495 downregulated genes were filtered. Subsequently, following the intersection of these DEGs, 29 overlapping genes were identified and further analyzed using a bioinformatics approach. Furthermore, the protein-protein interaction (PPI) network was used to obtain 18 modules of related genes. The hub genes were identified through hypergeometric testing, which were closely associated with ubiquitin-mediated proteolysis, the spliceosome, and the cell cycle. The significant difference was observed in the expression of these key genes, such as lncRNA MALAT1, E2F1, and YBX1, in the peripheral blood of IPF patients when compared with those normal control subjects by real-time polymerase chain reaction (RT-PCR) analysis. This study indicated that lncRNA MALAT1, E2F1, and YBX1 may be key regulators for the pathogenesis of IPF.

scholarly journals Identification of Key Candidate Genes Involved in the Progression of Idiopathic Pulmonary Fibrosis

Molecules ◽  
2021 ◽  
Vol 26 (4) ◽  
pp. 1123
Author(s):  
Yu Cui ◽  
Jie Ji ◽  
Jiwei Hou ◽  
Yi Tan ◽  
Xiaodong Han
Keyword(s):  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Candidate Genes ◽  
Expression Profiles ◽  
Biological Processes ◽  
Protein Protein Interaction ◽  
Novel Treatments ◽  
Kegg Pathway Analysis ◽  
Cell Components ◽  
Upregulated Genes

Idiopathic pulmonary fibrosis (IPF) is a lethal, agnogenic interstitial lung disease with limited therapeutic options. To investigate vital genes involved in the development of IPF, we integrated and compared four expression profiles (GSE110147, GSE53845, GSE24206, and GSE10667), including 87 IPF samples and 40 normal samples. By reanalyzing these datasets, we managed to identify 62 upregulated genes and 20 downregulated genes in IPF samples compared with normal samples. Differentially expressed genes (DEGs) were analyzed by gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis to illustrate relevant pathways of IPF, biological processes, molecular function, and cell components. The DEGs were then subjected to protein–protein interaction (PPI) for network analysis, serving to find 11 key candidate genes (ANXA3, STX11, THBS2, MMP1, MMP9, MMP7, MMP10, SPP1, COL1A1, ITGB8, IGF1). The result of RT-qPCR and immunohistochemical staining verified our finding as well. In summary, we identified 11 key candidate genes related to the process of IPF, which may contribute to novel treatments of IPF.

scholarly journals Identification of Differentially Expressed Genes Triggered by Aberrant Methylation in Idiopathic Pulmonary Fibrosis Using Integrated Bioinformatic Analysis

2020 ◽  
Author(s):  
Shuaijun Chen ◽  
Jun Zhang ◽  
Wanli Ma ◽  
Hong Ye
Keyword(s):  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Epigenetic Mechanism ◽  
Integrated Analysis ◽  
Aberrant Methylation ◽  
Mrna Levels

Abstract BackgroundIdiopathic pulmonary fibrosis (IPF) is a relentlessly progressive and fatal fibrotic lung disease all over the world, and specific pathogenesis is still not well understood. DNA methylation is an essential epigenetic mechanism, which likely contributes to the progress of IPF. The purpose of this study is to identify aberrantly methylated differentially expressed genes (DEGs) in IPF and to explore the underlying mechanisms of IPF by using integrated bioinformatics analysis.MethodGene expression profiles and gene methylation profile were downloaded and analyzed to identify the aberrantly methylated‐differentially expressed genes. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Search Tool for the Retrieval of Interacting Genes Database (STRING) and Gene set enrichment analysis (GSEA) were used to evaluate function of DEGs. RT-PCR was used to verify the mRNA levels of DEGs in mice with pulmonary fibrosis.ResultsBy analyzing the differentially expressed genes of the three IPF expression profiles, and taking the intersection, we got 143 co-upregulated genes and 104 co-downregulated genes; GO and KEGG pathway analysis of the DEGs suggested these genes involved in the extracellular matrix organization, multicellular organismal homeostasis. Combining the sequencing data of two IPF methylation chips, we have identified genes that may be regulated by methylation in IPF. Finally, we obtained the mRNA expression of DEGs using a mouse model of pulmonary fibrosis.ConclusionThrough integrated analysis and experimental verification, we found a series of biomarkers which were regulated by methylation should be potential therapeutic targets for IPF.

scholarly journals Integrated analysis of lncRNA–miRNA–mRNA ceRNA network and the potential prognosis indicators in sarcomas

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Lu Gao ◽  
Yu Zhao ◽  
Xuelei Ma ◽  
Ling Zhang
Keyword(s):  
Gene Expression ◽  
Survival Analysis ◽  
Gene Prediction ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Gene Expression Omnibus ◽  
Integrated Analysis ◽  
Ppi Network ◽  
Protein Protein Interaction ◽  
Cerna Network

Abstract Background Competitive endogenous RNA (ceRNA) networks have revealed a new mechanism of interaction between RNAs, and play crucial roles in multiple biological processes and development of neoplasms. They might serve as diagnostic and prognosis markers as well as therapeutic targets. Methods In this work, we identified differentially expressed mRNAs (DEGs), lncRNAs (DELs) and miRNAs (DEMs) in sarcomas by comparing the gene expression profiles between sarcoma and normal muscle samples in Gene Expression Omnibus (GEO) datasets. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses were applied to investigate the primary functions of the overlapped DEGs. Then, lncRNA-miRNA and miRNA-mRNA interactions were predicted, and the ceRNA regulatory network was constructed using Cytoscape software. In addition, the protein–protein interaction (PPI) network and survival analysis were performed. Results A total of 1296 DEGs were identified in sarcoma samples by combining the GO and KEGG enrichment analyses, 338 DELs were discovered after the probes were reannotated, and 36 DEMs were ascertained through intersecting two different expression miRNAs sets. Further, through target gene prediction, a lncRNA–miRNA–mRNA ceRNA network that contained 113 mRNAs, 69 lncRNAs and 29 miRNAs was constructed. The PPI network identified the six most significant hub proteins. Survival analysis revealed that seven mRNAs, four miRNAs and one lncRNA were associated with overall survival of sarcoma patients. Conclusions Overall, we constructed a ceRNA network in sarcomas, which might provide insights for further research on the molecular mechanism and potential prognosis biomarkers.

scholarly journals Identification of differentially expressed genes triggered by aberrant methylation in idiopathic pulmonary fibrosis using integrated bioinformatic analysis

2021 ◽  
Author(s):  
Shuaijun Chen ◽  
Jun Zhang ◽  
Wanli Ma ◽  
Hong Ye
Keyword(s):  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Epigenetic Mechanism ◽  
Integrated Analysis ◽  
Aberrant Methylation ◽  
Mrna Levels

Abstract Background Idiopathic pulmonary fibrosis (IPF) is a relentlessly progressive and fatal fibrotic lung disease all over the world, and specific pathogenesis is still not well understood. DNA methylation is an essential epigenetic mechanism, which likely contributes to the progress of IPF. The purpose of this study is to identify aberrantly methylated differentially expressed genes (DEGs) in IPF and to explore the underlying mechanisms of IPF by using integrated bioinformatics analysis.Methods Gene expression profiles and gene methylation profiles were downloaded and analyzed to identify the aberrantly methylated‐differentially expressed genes. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Search Tool for the Retrieval of Interacting Genes Database (STRING), and Gene set enrichment analysis (GSEA) were used to evaluate the function of DEGs. RT-PCR was used to verify the mRNA levels of DEGs in mice with pulmonary fibrosis.Results By analyzing the differentially expressed genes of the three IPF expression profiles, and taking the intersection, we got 143 co-upregulated genes and 104 co-downregulated genes; GO and KEGG pathway analysis of the DEGs suggested these genes involved in the extracellular matrix organization, multicellular organismal homeostasis. Combining the sequencing data of two IPF methylation chips, we have identified genes that may be regulated by methylation in IPF. Finally, we obtained the mRNA expression of DEGs using a mouse model of pulmonary fibrosis.Conclusions Through integrated analysis and experimental verification, we found a series of biomarkers that were regulated by methylation should be potential therapeutic targets for IPF.

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