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基于蛋白质成药性预测鉴定 TNIK 为甲状腺癌的一个新的潜在药物靶点。

Identification of TNIK as a novel potential drug target in thyroid cancer based on protein druggability prediction.

机构信息

Department of Thyroid and Breast Surgery, The First People's Hospital of Yuhang, Hangzhou, Zhejiang, China.

出版信息

Medicine (Baltimore). 2021 Apr 23;100(16):e25541. doi: 10.1097/MD.0000000000025541.

Abstract

Thyroid cancer is a common endocrine malignancy; however, surgery remains its primary treatment option. A novel targeted drug for the development and application of targeted therapy in thyroid cancer treatment remain underexplored.We obtained RNA sequence data of thyroid cancer from The Cancer Genome Atlas database and identified differentially expressed genes (DEGs). Then, we constructed co-expression network with DEGs and combined it with differentially methylation analysis to screen the key genes in thyroid cancer. PockDrug-Server, an online tool, was applied to predict the druggability of the key genes. Finally, we constructed protein-protein interaction (PPI) network to observe potential targeted drugs for thyroid cancer.We identified 3 genes correlated with altered DNA methylation level and oncogenesis of thyroid cancer. According to the druggable analysis and PPI network, we predicted TRAF2 and NCK-interacting protein kinase (TNIK) sever as the drug targeted for thyroid cancer. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis indicated that genes in protein-protein interaction network of TNIK enriched in mitogen-activated protein kinase signaling pathway. For drug repositioning, we identified a targeted drug of genes in PPI network.Our study provides a bioinformatics method for screening drug targets and provides a theoretical basis for thyroid cancer targeted therapy.

摘要

甲状腺癌是一种常见的内分泌恶性肿瘤;然而,手术仍然是其主要的治疗选择。一种新型的靶向药物用于甲状腺癌治疗的靶向治疗的开发和应用仍未得到充分探索。我们从癌症基因组图谱数据库中获得了甲状腺癌的 RNA 序列数据,并鉴定了差异表达基因(DEGs)。然后,我们构建了包含 DEGs 的共表达网络,并将其与差异甲基化分析相结合,以筛选甲状腺癌中的关键基因。PockDrug-Server 是一种在线工具,用于预测关键基因的药物可开发性。最后,我们构建了蛋白质-蛋白质相互作用(PPI)网络,以观察甲状腺癌的潜在靶向药物。我们确定了 3 个与甲状腺癌 DNA 甲基化水平改变和致癌相关的基因。根据药物可开发性分析和 PPI 网络,我们预测 TRAF2 和 NCK 相互作用蛋白激酶(TNIK)是甲状腺癌的潜在药物靶点。基因本体论和京都基因与基因组百科全书通路富集分析表明,TNIK 的蛋白质-蛋白质相互作用网络中的基因富集于丝裂原活化蛋白激酶信号通路。对于药物重定位,我们鉴定了 PPI 网络中基因的靶向药物。我们的研究提供了一种筛选药物靶点的生物信息学方法,为甲状腺癌的靶向治疗提供了理论依据。

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