Dataset Information

Drug repurposing in idiopathic pulmonary fibrosis filtered by a bioinformatics-derived composite score.

ABSTRACT: Idiopathic Pulmonary Fibrosis (IPF) is a rare disease of the respiratory system in which the lungs stiffen and get scarred, resulting in breathing weakness and eventually leading to death. Drug repurposing is a process that provides evidence for existing drugs that may also be effective in different diseases. In this study, we present a computational pipeline having as input a number of gene expression datasets from early and advanced stages of IPF and as output lists of repurposed drugs ranked with a novel composite score. We have devised and used a scoring formula in order to rank the repurposed drugs, consolidating the standard repurposing score with structural, functional and side effects' scores for each drug per stage of IPF. The whole pipeline involves the selection of proper gene expression datasets, data preprocessing and statistical analysis, selection of the most important genes related to the disease, analysis of biological pathways, investigation of related molecular mechanisms, identification of fibrosis-related microRNAs, drug repurposing, structural and literature-based analysis of the repurposed drugs.

SUBMITTER: Karatzas E

PROVIDER: S-EPMC5626774 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Drug repurposing in idiopathic pulmonary fibrosis filtered by a bioinformatics-derived composite score.

Karatzas E E Bourdakou M M MM Kolios G G Spyrou G M GM

Scientific reports 20171003 1

Idiopathic Pulmonary Fibrosis (IPF) is a rare disease of the respiratory system in which the lungs stiffen and get scarred, resulting in breathing weakness and eventually leading to death. Drug repurposing is a process that provides evidence for existing drugs that may also be effective in different diseases. In this study, we present a computational pipeline having as input a number of gene expression datasets from early and advanced stages of IPF and as output lists of repurposed drugs ranked ...[more]

PMID: 28974751

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Project description:Some recent studies showed that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and idiopathic pulmonary fibrosis (IPF) disease might stimulate each other through the shared genes. Therefore, in this study, an attempt was made to explore common genomic biomarkers for SARS-CoV-2 infections and IPF disease highlighting their functions, pathways, regulators and associated drug molecules. At first, we identified 32 statistically significant common differentially expressed genes (cDEGs) between disease (SARS-CoV-2 and IPF) and control samples of RNA-Seq profiles by using a statistical r-package (edgeR). Then we detected 10 cDEGs (CXCR4, TNFAIP3, VCAM1, NLRP3, TNFAIP6, SELE, MX2, IRF4, UBD and CH25H) out of 32 as the common hub genes (cHubGs) by the protein-protein interaction (PPI) network analysis. The cHubGs regulatory network analysis detected few key TFs-proteins and miRNAs as the transcriptional and post-transcriptional regulators of cHubGs. The cDEGs-set enrichment analysis identified some crucial SARS-CoV-2 and IPF causing common molecular mechanisms including biological processes, molecular functions, cellular components and signaling pathways. Then, we suggested the cHubGs-guided top-ranked 10 candidate drug molecules (Tegobuvir, Nilotinib, Digoxin, Proscillaridin, Simeprevir, Sorafenib, Torin 2, Rapamycin, Vancomycin and Hesperidin) for the treatment against SARS-CoV-2 infections with IFP diseases as comorbidity. Finally, we investigated the resistance performance of our proposed drug molecules compare to the already published molecules, against the state-of-the-art alternatives publicly available top-ranked independent receptors by molecular docking analysis. Molecular docking results suggested that our proposed drug molecules would be more effective compare to the already published drug molecules. Thus, the findings of this study might be played a vital role for diagnosis and therapies of SARS-CoV-2 infections with IPF disease as comorbidity risk.

Project description:BackgroundIdiopathic pulmonary fibrosis (IPF) is a serious interstitial lung disease with a complex pathogenesis and high mortality. The development of new drugs is time-consuming and laborious; therefore, research on the new use of old drugs can save time and clinical costs and even avoid serious side effects. Nifuroxazide (NIF) was originally used to treat diarrhoea, but more recently, it has been found to have additional pharmacological effects, such as anti-tumour effects and inhibition of inflammatory diseases related to diabetic nephropathy. However, there are no reports regarding its role in pulmonary fibrosis.MethodsThe therapeutic effect of NIF on pulmonary fibrosis in vivo was measured by ELISA, hydroxyproline content, H&E and Masson staining, immunohistochemistry (IHC) and western blot. Immune cell content in lung tissue was also analysed by flow cytometry. NIF cytotoxicity was evaluated in NIH/3T3 cells, human pulmonary fibroblasts (HPFs), A549 cells and rat primary lung fibroblasts (RPLFs) using the MTT assay. Finally, an in vitro cell model created by transforming growth factor-β1 (TGF-β1) stimulation was assessed using different experiments (immunofluorescence, western blot and wound migration assay) to evaluate the effects of NIF on the activation of NIH/3T3 and HPF cells and the epithelial-mesenchymal transition (EMT) and migration of A549 cells.ResultsIn vivo, intraperitoneal injection of NIF relieved and reversed pulmonary fibrosis caused by bleomycin (BLM) bronchial instillation. In addition, NIF inhibited the expression of a variety of cellular inflammatory factors and immune cells. Furthermore, NIF suppressed the activation of fibroblasts and EMT of epithelial cells induced by TGF-β1. Most importantly, we used an analytical docking experiment and thermal shift assay to further verify that NIF functions in conjunction with signal transducer and activator of transcription 3 (Stat3). Moreover, NIF inhibited the TGF-β/Smad pathway in vitro and decreased the expression of phosphorylated Stat3 in vitro and in vivo.ConclusionTaken together, we conclude that NIF inhibits and reverses pulmonary fibrosis, and these results support NIF as a viable therapeutic option for IPF treatment.

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.

Dataset Information

Drug repurposing in idiopathic pulmonary fibrosis filtered by a bioinformatics-derived composite score.

Publications

Drug repurposing in idiopathic pulmonary fibrosis filtered by a bioinformatics-derived composite score.

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