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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.
BMC Medical Genomics ( IF 2.1 ) Pub Date : 2020-01-07 , DOI: 10.1186/s12920-019-0655-8
Chengwei Zhang 1 , Lei Leng 2 , Zhaozheng Li 1 , Yao Zhao 1 , Jundong Jiao 1
Affiliation  

BACKGROUND 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. METHODS 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. RESULTS 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. CONCLUSIONS 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.

中文翻译:

基于免疫,炎症和膜性肾小球肾炎相关的三联体网络,针对膜性肾小球肾炎的生物标志物和药物替代候选物的鉴定。

背景技术膜性肾小球肾炎(MGN)是一种常见的肾脏疾病。尽管有许多证据支持许多免疫和炎症相关基因可以作为MGN患者的有效生物标志物和治疗靶标,但尚未充分了解MGN,免疫和炎症相关基因之间的潜在关联。方法在这里,构建并分析了一个与免疫,炎症和MGN相关的全球三联症(IIMAT)网络。开发了一种集成的计算方法,可根据表达和相互作用数据为MGN患者识别失调的IIMAT。结果通过上述方法在MGN中鉴定出45种IIMATs失调。这些失调的IIMAT失调的模式是复杂而多样的。我们从失调的IIMATs网络中识别出四个核心类群,其中一些类群可以区分MGN和正常样本。特别是,根据IIMATs的药物调整策略,包括他莫昔芬,博舒替尼,波纳替尼和Nintedanib在内的一些抗癌药物可能成为MGN的候选药物。功能分析表明,这些失调的IIMAT与某些关键功能和趋化因子信号通路相关。结论本研究探讨了免疫,炎症和MGN之间的关系。根据免疫和炎症鉴定了一些有效的MGN候选药物。总体而言,这些综合结果为MGN的机制和治疗提供了新颖的见解。基于IIMATs的药物重用策略,Ponatinib和Nintedanib可能成为MGN的候选药物。功能分析表明,这些失调的IIMAT与某些关键功能和趋化因子信号通路相关。结论本研究探讨了免疫,炎症和MGN之间的关系。根据免疫和炎症鉴定了一些有效的MGN候选药物。总体而言,这些综合结果为MGN的机制和治疗提供了新颖的见解。根据IIMATs的药物重用策略,Ponatinib和Nintedanib可能成为MGN的候选药物。功能分析表明,这些失调的IIMAT与某些关键功能和趋化因子信号通路相关。结论本研究探讨了免疫,炎症和MGN之间的关联。根据免疫和炎症鉴定了一些有效的MGN候选药物。总体而言,这些综合结果为MGN的机制和治疗提供了新颖的见解。根据免疫和炎症鉴定了一些有效的MGN候选药物。总体而言,这些综合结果为MGN的机制和治疗提供了新颖的见解。根据免疫和炎症鉴定了一些有效的MGN候选药物。总体而言,这些综合结果为MGN的机制和治疗提供了新颖的见解。
更新日期:2020-01-07
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