Division of Rheumatology, Department of Internal Medicine, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
St. Vincent's Hospital, 93 Jungbu-daero, Paldal-gu, Suwon, Gyeonggi-do, 16247, Republic of Korea.
Sci Rep. 2020 Aug 7;10(1):13393. doi: 10.1038/s41598-020-70280-y.
The network-based proximity between drug targets and disease genes can provide novel insights regarding the repercussions, interplay, and repositioning of drugs in the context of disease. Current understanding and treatment for reversing of the fibrotic process is limited in systemic sclerosis (SSc). We have developed a network-based analysis for drug effects that takes into account the human interactome network, proximity measures between drug targets and disease-associated genes, genome-wide gene expression and disease modules that emerge through pertinent analysis. Currently used and potential drugs showed a wide variation in proximity to SSc-associated genes and distinctive proximity to the SSc-relevant pathways, depending on their class and targets. Tyrosine kinase inhibitors (TyKIs) approach disease gene through multiple pathways, including both inflammatory and fibrosing processes. The SSc disease module includes the emerging molecular targets and is in better accord with the current knowledge of the pathophysiology of the disease. In the disease-module network, the greatest perturbing activity was shown by nintedanib, followed by imatinib, dasatinib, and acetylcysteine. Suppression of the SSc-relevant pathways and alleviation of the skin fibrosis was remarkable in the inflammatory subsets of the SSc patients receiving TyKI therapy. Our results show that network-based drug-disease proximity offers a novel perspective into a drug's therapeutic effect in the SSc disease module. This could be applied to drug combinations or drug repositioning, and be helpful guiding clinical trial design and subgroup analysis.
基于网络的药物靶点与疾病基因之间的临近性，可以为药物在疾病背景下的影响、相互作用和重新定位提供新的见解。目前对于系统性硬化症（SSc）逆转纤维化过程的理解和治疗方法有限。我们开发了一种基于网络的药物效应分析方法，该方法考虑了人类相互作用网络、药物靶点与疾病相关基因之间的临近度测量、全基因组基因表达和通过相关分析出现的疾病模块。目前使用的和潜在的药物在与 SSc 相关基因的临近度以及与 SSc 相关途径的临近度方面存在很大差异，这取决于它们的类别和靶点。酪氨酸激酶抑制剂（TyKIs）通过多种途径接近疾病基因，包括炎症和纤维化过程。SSc 疾病模块包含新兴的分子靶点，与疾病病理生理学的当前知识更为一致。在疾病模块网络中，尼达尼布显示出最大的扰动活性，其次是伊马替尼、达沙替尼和乙酰半胱氨酸。在接受 TyKI 治疗的 SSc 患者的炎症亚群中，抑制 SSc 相关途径和减轻皮肤纤维化的效果显著。我们的研究结果表明，基于网络的药物-疾病临近度为药物在 SSc 疾病模块中的治疗效果提供了新的视角。这可以应用于药物联合或药物重定位，并有助于指导临床试验设计和亚组分析。
