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首页> 外文期刊>BMC Medical Genomics >Identification of biomarkers and drug repurposing candidates based on an immune-, inflammation- and membranous glomerulonephritis-associated triplets network for membranous glomerulonephritis
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Identification of biomarkers and drug repurposing candidates based on an immune-, inflammation- and membranous glomerulonephritis-associated triplets network for membranous glomerulonephritis

机译:基于免疫,炎症和膜状肾小球肾炎相关三体网络的膜状肾小球肾炎的生物标志物和药物重新探测候选

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Membranous glomerulonephritis (MGN) is a common kidney disease. Despite many evidences support that many immune and inflammation-related genes could serve as effective biomarkers and treatment targets for MGN patients, the potential associations among MGN-, immune- and inflammation-related genes have not been sufficiently understood. Here, a global immune-, inflammation- and MGN-associated triplets (IIMATs) network is constructed and analyzed. An integrated and computational approach is developed to identify dysregulated IIMATs for MGN patients based on expression and interaction data. 45 dysregulated IIMATs are identified in MGN by above method. Dysregulated patterns of these dysregulated IIMATs are complex and various. We identify four core clusters from dysregulated IIMATs network and some of these clusters could distinguish MGN and normal samples. Specially, some anti-cancer drugs including Tamoxifen, Bosutinib, Ponatinib and Nintedanib could become candidate drugs for MGN based on drug repurposing strategy follow IIMATs. Functional analysis shows these dysregulated IIMATs are associated with some key functions and chemokine signaling pathway. The present study explored the associations among immune, inflammation and MGN. Some effective candidate drugs for MGN were identified based on immune and inflammation. Overall, these comprehensive results provide novel insights into the mechanisms and treatment of MGN.
机译:膜状肾小球肾炎(MGN)是一种常见的肾病。尽管许多证据支持许多免疫和炎症相关的基因可以用作MGN患者的有效生物标志物和治疗靶标,但没有充分理解MgN-,免疫和炎症相关基因之间的潜在关联。这里,构建和分析了全局免疫,炎症和MGN相关的三元组(IIMATS)网络。开发了一种集成和计算方法,以根据表达和交互数据鉴定MGN患者的失调IIMATS。通过上述方法在MGN中鉴定了45个失调的IIMATS。这些失去的IIMATS的失调模式是复杂的和各种各样的。我们识别来自Dysrogure IIMATE网络的四个核心集群,其中一些群集可以区分MGN和正常样本。特别地,一些抗癌药物,包括Tamoxifen,Bosutinib,Ponatinib和Nintedanib可以基于药物重新训练策略的候选药物遵循IIMATS。功能分析显示这些失去的IIMATS与一些关键功能和趋化因子信号通路相关联。本研究探讨了免疫,炎症和MGN之间的关联。基于免疫和炎症来鉴定一些有效的MGN候选药物。总体而言,这些全面的结果为MGN的机制和治疗提供了新颖的见解。

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