scholarly journals Pan-transcriptome-based candidate therapeutic discovery for idiopathic pulmonary fibrosis

2020 ◽  
Vol 14 ◽  
pp. 175346662097114
Author(s):  
Yunguan Wang ◽  
Jaswanth K. Yella ◽  
Sudhir Ghandikota ◽  
Tejaswini C. Cherukuri ◽  
Harshavardhana H. Ediga ◽  
...  
Keyword(s):  
Gene Expression ◽  
Clinical Trials ◽  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Histone Deacetylase Inhibitors ◽  
Kinase Inhibitor ◽  
Lung Fibroblasts ◽  
Joint Analysis ◽  
Potential Candidate ◽  
Opioid Receptor Antagonists

Background: There are two US Food and Drug Administration (FDA)-approved drugs, pirfenidone and nintedanib, for treatment of patients with idiopathic pulmonary fibrosis (IPF). However, neither of these drugs provide a cure. In addition, both are associated with several drug-related adverse events. Hence, the pursuit for newer IPF therapeutics continues. Recent studies show that joint analysis of systems-biology-level information with drug–disease connectivity are effective in discovery of biologically relevant candidate therapeutics. Methods: Publicly available gene expression signatures from patients with IPF were used to query a large-scale perturbagen signature library to discover compounds that can potentially reverse dysregulated gene expression in IPF. Two methods were used to calculate IPF–compound connectivity: gene expression-based connectivity and feature-based connectivity. Identified compounds were further prioritized if their shared mechanism(s) of action were IPF-related. Results: We found 77 compounds as potential candidate therapeutics for IPF. Of these, 39 compounds are either FDA-approved for other diseases or are currently in phase II/III clinical trials suggesting their repurposing potential for IPF. Among these compounds are multiple receptor kinase inhibitors (e.g. nintedanib, currently approved for IPF, and sunitinib), aurora kinase inhibitor (barasertib), epidermal growth factor receptor inhibitors (erlotinib, gefitinib), calcium channel blocker (verapamil), phosphodiesterase inhibitors (roflumilast, sildenafil), PPAR agonists (pioglitazone), histone deacetylase inhibitors (entinostat), and opioid receptor antagonists (nalbuphine). As a proof of concept, we performed in vitro validations with verapamil using lung fibroblasts from IPF and show its potential benefits in pulmonary fibrosis. Conclusions: As about half of the candidates discovered in this study are either FDA-approved or are currently in clinical trials for other diseases, rapid translation of these compounds as potential IPF therapeutics is possible. Further, the integrative connectivity analysis framework in this study can be adapted in early phase drug discovery for other common and rare diseases with transcriptomic profiles. The reviews of this paper are available via the supplemental material section.

scholarly journals Pan-transcriptome-based Candidate Therapeutic Discovery for Idiopathic Pulmonary Fibrosis

2019 ◽  
Author(s):  
Yunguan Wang ◽  
Jaswanth K. Yella ◽  
Sudhir Ghandikota ◽  
Tejaswini C. Cherukuri ◽  
Harshavardhana H. Ediga ◽  
...  
Keyword(s):  
Gene Expression ◽  
Clinical Trials ◽  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Large Scale ◽  
Kinase Inhibitor ◽  
Lung Fibroblasts ◽  
Joint Analysis ◽  
Potential Candidate ◽  
Opioid Receptor Antagonists

ABSTRACTBACKGROUNDAlthough the advent of two FDA-approved therapies for idiopathic pulmonary fibrosis (IPF) has energized the field, their effects are largely suppressive than pulmonary fibrosis remission- or reversion-inducing. Hence, the pursuit for newer IPF therapeutics continues. Recent studies show that joint analysis of systems biology level information with drug-disease connectivity are effective in discovery of biologically relevant candidate therapeutics.METHODSPublicly available gene expression signatures from IPF patients are used to query large scale perturbagen signature library to discover compounds that can potentially reverse dysregulated gene expression in IPF. Two methods are used to calculate IPF-compound connectivity: gene expression-based connectivity and feature-based connectivity. Identified compounds are further prioritized based on their shared mechanism(s) of action.RESULTSWe identified 77 compounds as potential candidate therapeutics for IPF. Of these 39 compounds are either FDA-approved for other diseases or are currently in phase 2/3 clinical trials suggesting their repurposing potential for IPF. Among these compounds are multiple receptor kinase inhibitors (e.g., nintedanib, currently approved for IPF, and sunitinib), aurora kinase inhibitor (barasertib), EGFR inhibitors (erlotinib, gefitinib), calcium channel blocker (verapamil), phosphodiesterase inhibitors (roflumilast, sildenafil), PPAR agonists (pioglitazone), HDAC inhibitors (entinostat), and opioid receptor antagonists (nalbuphine). As a proof-of-concept, we performed in vitro validations with verapamil using lung fibroblasts from IPF and show its potential benefits in pulmonary fibrosis.CONCLUSIONSSince about half of the candidates discovered in this study are either FDA-approved or are currently in clinical trials for other diseases, rapid translation of these compounds as potential IPF therapeutics is feasible. Further, the generalizable, integrative connectivity analysis framework in this study can be readily adapted in early phase drug discovery for other common and rare diseases with transcriptomic profiles.

scholarly journals Itaconate controls the severity of pulmonary fibrosis

2020 ◽  
Vol 5 (52) ◽  
pp. eabc1884 ◽  
Author(s):  
Patricia P. Ogger ◽  
Gesa J. Albers ◽  
Richard J. Hewitt ◽  
Brendan J. O’Sullivan ◽  
Joseph E. Powell ◽  
...  
Keyword(s):  
Gene Expression ◽  
Wound Healing ◽  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Lung Fibrosis ◽  
Therapeutic Strategy ◽  
Lung Fibroblasts ◽  
Disease Phenotype ◽  
Wild Type

Idiopathic pulmonary fibrosis (IPF) is a fatal lung disease in which airway macrophages (AMs) play a key role. Itaconate has emerged as a mediator of macrophage function, but its role during fibrosis is unknown. Here, we reveal that itaconate is an endogenous antifibrotic factor in the lung. Itaconate levels are reduced in bronchoalveolar lavage, and itaconate-synthesizing cis-aconitate decarboxylase expression (ACOD1) is reduced in AMs from patients with IPF compared with controls. In the murine bleomycin model of pulmonary fibrosis, Acod1−/− mice develop persistent fibrosis, unlike wild-type (WT) littermates. Profibrotic gene expression is increased in Acod1−/− tissue-resident AMs compared with WT, and adoptive transfer of WT monocyte-recruited AMs rescued mice from disease phenotype. Culture of lung fibroblasts with itaconate decreased proliferation and wound healing capacity, and inhaled itaconate was protective in mice in vivo. Collectively, these data identify itaconate as critical for controlling the severity of lung fibrosis, and targeting this pathway may be a viable therapeutic strategy.

scholarly journals Identification of Targetable Kinases in Idiopathic Pulmonary Fibrosis

2021 ◽  
Author(s):  
Hisao Higo ◽  
Kadoaki Ohashi ◽  
Shuta Tomida ◽  
Sachi Okawa ◽  
Hiromasa Yamamoto ◽  
...  
Keyword(s):  
Gene Expression ◽  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Therapeutic Targets ◽  
Integrated Analysis ◽  
Potential Candidate ◽  
Tissue Samples ◽  
Kinase Expression

Abstract Background: Tyrosine kinase activation plays an important role in the progression of pulmonary fibrosis. In this study, we analyzed the expression of 612 kinase-coding and cancer-related genes using next-generation sequencing to identify potential therapeutic targets for idiopathic pulmonary fibrosis (IPF).Methods: Thirteen samples from five patients with IPF (Cases 1-5) and eight samples from four patients without IPF (control) were included in this study. Six of the thirteen samples were obtained from different lung segments of a single patient who underwent bilateral pneumonectomy. Gene expression analysis of IPF lung tissue samples (n=13) and control samples (n=8) was performed using SureSelect RNA Human Kinome Kit. The expression of the selected genes was further confirmed at the protein level by immunohistochemistry (IHC).Results: Gene expression analysis revealed a correlation between the gene expression signatures and the degree of fibrosis, as assessed by Ashcroft score. In addition, the expression analysis indicated a stronger heterogeneity among the IPF lung samples than among the control lung samples. In the integrated analysis of the 21 samples, DCLK1 and STK33 were found to be upregulated in IPF lung samples compared to control lung samples. However, the top most upregulated genes were distinct in individual cases. DCLK1, PDK4, and ERBB4 were upregulated in IPF case 1, whereas STK33, PIM2, and SYK were upregulated in IPF case 2. IHC revealed that these proteins were expressed in the epithelial layer of the fibrotic lesions.Conclusions: We performed a comprehensive kinase expression analysis to explore the potential therapeutic targets for IPF. DCLK1 and STK33 can serve as potential candidate targets for molecular targeted therapy of IPF. In addition, PDK4, ERBB4, PIM2, and SYK may serve as personalized therapeutic targets of IPF.

scholarly journals Reconstruction of the miR-506-Quaking axis in Idiopathic Pulmonary Fibrosis using integrative multi-source bioinformatics

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Stevan D. Stojanović ◽  
Maximilian Fuchs ◽  
Chunguang Liang ◽  
Kevin Schmidt ◽  
Ke Xiao ◽  
...  
Keyword(s):  
Data Mining ◽  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Rna Sequencing ◽  
In Silico ◽  
Rna Binding ◽  
Human Lung ◽  
Model Systems ◽  
Lung Fibroblasts ◽  
Sequencing Analysis

AbstractThe family of RNA-binding proteins (RBP) functions as a crucial regulator of multiple biological processes and diseases. However, RBP function in the clinical setting of idiopathic pulmonary fibrosis (IPF) is still unknown. We developed a practical in silico screening approach for the characterization of RBPs using multi-sources data information and comparative molecular network bioinformatics followed by wet-lab validation studies. Data mining of bulk RNA-Sequencing data of tissues of patients with IPF identified Quaking (QKI) as a significant downregulated RBP. Cell-type specific expression was confirmed by single-cell RNA-Sequencing analysis of IPF patient data. We systematically analyzed the molecular interaction network around QKI and its functional interplay with microRNAs (miRs) in human lung fibroblasts and discovered a novel regulatory miR-506-QKI axis contributing to the pathogenesis of IPF. The in silico results were validated by in-house experiments applying model systems of miR and lung biology. This study supports an understanding of the intrinsic molecular mechanisms of IPF regulated by the miR-506-QKI axis. Initially applied to human lung disease, the herein presented integrative in silico data mining approach can be adapted to other disease entities, underlining its practical relevance in RBP research.

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