ArticleTherapeutic advances in respiratory disease
Pan-transcriptome-based candidate therapeutic discovery for idiopathic pulmonary fibrosis.
Article in Therapeutic advances in respiratory disease. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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The trial behind it
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Who cites it
9 citing papers in PubMed, 16 citations in OpenAlex.
- A narrative review of the early diagnosis and treatment of idiopathic pulmonary fibrosis with lung cancer.Journal of thoracic disease · 2025Review
- From Gene Networks to Therapeutics: A Causal Inference and Deep Learning Approach for Drug Discovery.Pharmaceuticals (Basel, Switzerland) · 2025Article
- An Overview of the Role of Genetic factors in Idiopathic Pulmonary Fibrosis: Insights from Epidemiology to Prognosis.International journal of medical sciences · 2025Review
- Histone deacetylases: potential therapeutic targets for idiopathic pulmonary fibrosis.Frontiers in cell and developmental biology · 2024Review
- A polo-like kinase inhibitor identified by computational repositioning attenuates pulmonary fibrosis.Respiratory research · 2023Article
- Applying a Gene Reversal Rate Computational Methodology to Identify Drugs for a Rare Cancer: Inflammatory Breast Cancer.Cancer informatics · 2023Article
- Molecular Mechanisms and Cellular Contribution from Lung Fibrosis to Lung Cancer Development.International journal of molecular sciences · 2021Review
- Integrative chemogenomic analysis identifies small molecules that partially rescue ΔF508-CFTR for cystic fibrosis.CPT: pharmacometrics & systems pharmacology · 2021Article
- Hypoxia Inducible Factor 1A Supports a Pro-Fibrotic Phenotype Loop in Idiopathic Pulmonary Fibrosis.International journal of molecular sciences · 2021Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 2 countries.
Funding
Abstract
backgroundThere 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.
methodsPublicly 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.
resultsWe 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
conclusionsAs 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.