Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Department of Computer Science, University of Cincinnati College of Engineering, Cincinnati, OH, USA.
Ther Adv Respir Dis. 2020 Jan-Dec;14:1753466620971143. doi: 10.1177/1753466620971143.
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.
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.
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 validations with verapamil using lung fibroblasts from IPF and show its potential benefits in pulmonary fibrosis.
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..
美国食品和药物管理局(FDA)批准了两种药物,吡非尼酮和尼达尼布,用于治疗特发性肺纤维化(IPF)患者。然而,这两种药物都不能治愈这种疾病。此外,它们都与一些与药物相关的不良事件有关。因此,人们继续寻求新的 IPF 治疗方法。最近的研究表明,系统生物学水平信息与药物疾病相关性的联合分析在发现具有生物学相关性的候选治疗药物方面是有效的。
使用来自 IPF 患者的公开基因表达谱,查询大规模的扰动剂特征库,以发现可能逆转 IPF 中失调基因表达的化合物。使用两种方法计算 IPF-化合物的连接性:基于基因表达的连接性和基于特征的连接性。如果鉴定出的化合物的作用机制与 IPF 相关,则进一步对其进行优先级排序。
我们发现了 77 种可能用于治疗 IPF 的潜在候选治疗药物。其中,39 种化合物要么是 FDA 批准用于治疗其他疾病的药物,要么是目前处于 II/III 期临床试验阶段,表明它们有用于治疗 IPF 的潜力。这些化合物包括多种受体激酶抑制剂(如尼达尼布,目前批准用于 IPF,和舒尼替尼)、极光激酶抑制剂(巴拉斯替尼)、表皮生长因子受体抑制剂(厄洛替尼、吉非替尼)、钙通道阻滞剂(维拉帕米)、磷酸二酯酶抑制剂(罗氟司特、西地那非)、PPAR 激动剂(吡格列酮)、组蛋白去乙酰化酶抑制剂(恩替诺特)和阿片受体拮抗剂(纳布啡)。作为概念验证,我们使用来自 IPF 的肺成纤维细胞对维拉帕米进行了验证,并显示了其在肺纤维化中的潜在益处。
由于本研究中发现的候选药物约有一半是 FDA 批准的或目前正在其他疾病的临床试验中,因此这些化合物作为潜在的 IPF 治疗药物的快速转化是可能的。此外,本研究中的综合连接性分析框架可以适应其他常见和罕见疾病的早期药物发现,这些疾病都有转录组特征。