Project description:Background: Acute exacerbation of idiopathic pulmonary fibrosis (AE-IPF) is the most common cause of acute respiratory deterioration and death in IPF patients, with an elusive etiology and pathogenesis. Roles of noncoding RNAs in AE-IPF have been proposed, however, it was rare to find studies have systematically investigated the crosstalk among various transcripts until now. The construction of RNA functional networks such as lncRNA-miRNA-mRNA and circRNA-miRNA-mRNA interaction networks could therefore facilitate our understanding of RNA interactions in AE-IPF. The study aimed to identify the expression differences of RNA transcripts in RNA sequencing from AE-IPF patients and stable IPF (S-IPF), and further to construct the potential RNA networks. Methods: Five AE-IPF patients and five S-IPF were recruited in this study to perform RNA sequencing and miRNA sequencing. The differentially expression profiles of lncRNAs, circRNAs, miRNAs and mRNAs between AE-IPF and S-IPF patients were identified for further analyses. Gene Oncology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of were performed. The competing endogenous RNAs (ceRNAs) network of lncRNA/circRNA-miRNA-mRNA was constructed, and the core regulatory molecules in the ceRNA network were analyzed. Results: A total of 69 lncRNAs, 150 circRNAs, 27 miRNAs and 56 mRNAs were differentially expressed between AE-IPF and S-IPF. GO and KEGG analysis show that differentially expression mRNAs are significantly associated with tight junction and Hepatitis C, etc. In the ceRNA network, all nodes are directly or indirectly involved in the progression of AE-IPF. 1 lncRNAs, 6 circRNAs, 1 miRNAs, and 5 mRNAs constituted a hsa-miR-150-5p core sub-network. Based on the analysis of ceRNA sub-network, NR_120628/hsa-miR-150-5p/E2F3 and has-circ-0053515/hsa-miR-150-5p/E2F3 were considered to be the key ceRNA axis. Conclusions: In conclusion, this study reveals NR_120628/hsa-miR-150-5p/E2F3 and has-circ-0053515/hsa-miR-150-5p/E2F3 may be the key ceRNA axis in the regulation of AE-IPF, providing clues for future studies on their roles for AE-IPF. Our findings will help to explore the pathological mechanism of AE-IPF from a transcriptomic perspective and provide enlightenment for the biomarker and therapeutic targets of AE-IPF.

Project description:Background: Lung cancer is the most common comorbidity of idiopathic pulmonary fibrosis. Thus there is an urgent need for the research of IPF and carcinogenesis Objective: The objective of this study was to explore hub genes which are common in pulmonary fibrosis and lung cancer progression through bioinformatic analysis. Methods: All the analysis was performed in R software. Differentially expressed genes (DEGs) were explored by comparing gene expression profiles between IPF tissues and healthy lung tissues from GSE24206, GSE53845, GSE101286 and GSE110147 datasets. Venn Diagram analysis was used to identify the overlapping genes, while GO and KEGG pathway enrichment analysis were used to explore the biological functions of the DEGs using clusterprofiler package. Hub genes were identified by analyzing protein-protein interaction networks using Cytoscape software. Nomogram was constructed using the rms package. Tumor immune dysfunction and exclusion (TIDE) and Genomics of Drug Sensitivity in Cancer (GDSC) analysis was used to quantify the immunotherapy and chemotherapy sensitivity of non-small cell lung cancer (NSCLC) patients. Results: COL1A1, COL3A1, MMP1, POSTN1 and TIMP3 were identified as the top five hub genes. The five hub genes were used to construct a diagnostic nomogram that was validated in another IPF dataset. Since the hub genes were also associated with lung cancer progression, we found that the nomogram also had diagnostic value in NSCLC patients. These five genes achieved a statistically difference of overall survival in NSCLC patients (p < 0.05). The expression of the five hub genes was mostly enriched in fibroblasts. Fibroblasts and the hub genes also showed significant ability to predict the susceptibility of NSCLC patients to chemotherapy and immunotherapy. Conclusion: We identified five hub genes as potential biomarkers of IPF and NSCLC progression. This finding may give insight into the underlying molecular mechanisms of IPF and lung cancer progression and provides potential targets for developing new therapeutic agents for IPF patients.

Project description:BackgroundIdiopathic pulmonary fibrosis (IPF) is a chronic and progressive interstitial lung disease, characterized by a decline in lung function. To date, the pathophysiologic mechanisms associated with lung dysfunction remain unclear, and no effective therapy has been identified to improve lung function.MethodsIn the present study, we used weighted gene co-expression network analysis (WGCNA) to identify key modules and hub genes associated with lung function in IPF. Three datasets, containing clinical information, were downloaded from Gene Expression Omnibus. WGCNA was performed on the GSE32537 dataset. Differentially expressed gene s (DEGs) between IPF patients and healthy controls were also identified to filter hub genes. The relationship between hub genes and lung function was then validated using the GSE47460 and GSE24206 datasets.ResultsThe red module, containing 267 genes, was positively correlated with the St. George's Respiratory Questionnaire score (r = 0.37, p < 0.001) and negatively correlated with the percent predicted forced vital capacity (FVC% predicted) (r = - 0.46, p < 0.001) and the percent predicted diffusion capacity of the lung for carbon monoxide (Dlco% predicted) (r = - 0.42, p < 0.001). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis suggested that the genes in the red module were primarily involved in inflammation and immune pathways. Based on Module Membership and Gene Significance, 32 candidate hub genes were selected in the red module to construct a protein-protein interaction network . Based on the identified DEGs and the degree of connectivity in the network, we identified three hub genes, including interleukin 6 (IL6), suppressor of cytokine signaling-3 (SOCS3), and serpin family E member 1 (SERPINE1). In the GSE47460 dataset, Spearman correlation coefficients between Dlco% predicted and expression levels of IL6, SERPINE1, SOCS3 were -0.32, -0.41, and -0.46, respectively. Spearman correlation coefficients between FVC% predicted and expression levels of IL6, SERPINE1, SOCS3 were -0.29, -0.33, and -0.27, respectively. In the GSE24206 dataset, all three hub genes were upregulated in patients with advanced IPF.ConclusionWe identified three hub genes that negatively correlated with the lung function of IPF patients. Our results provide insights into the pathogenesis underlying the progressive disruption of lung function, and the identified hub genes may serve as biomarkers and potential therapeutictargets for the treatment of IPF patients.

Dataset Information

Analysis of the Interaction Network of Hub miRNAs-Hub Genes, Being Involved in Idiopathic Pulmonary Fibers and Its Emerging Role in Non-small Cell Lung Cancer.

Publications

Analysis of the Interaction Network of Hub miRNAs-Hub Genes, Being Involved in Idiopathic Pulmonary Fibers and Its Emerging Role in Non-small Cell Lung Cancer.

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