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Identification of key pathways and drug repurposing for anaplastic thyroid carcinoma by integrated bioinformatics analysis |
PAN Zongfu1( ),FANG Qilu1,ZHANG Yiwen1,LI Li2,HUANG Ping1,*( ) |
1. Department of Pharmacy, Zhejiang Cancer Hospital, Hangzhou 310022, China 2. Department of Pharmacy, First People's Hospital of Chun'an, Hangzhou 311700, China |
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Abstract Objective: To identify hub genes and key pathways associated with anaplastic thyroid carcinoma (ATC), and to explore possible intervention strategy. Methods: The differentially expressed genes (DEGs) in ATC were identified by Gene Expression Omnibus (GEO) combined with using R language; the pathway enrichment of DEGs were performed by using Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). The protein-protein interaction (PPI) network of DEGs was constructed by STRING database and visualized by Cytoscape. Furthermore, the hub genes and key nodes were calculated by MCODE. Finally, the drug repurposing was performed by L1000CDS2. Results: A total of 2087 DEGs were identified. The DEGs were clustered based on functions and pathways with significant enrichment analysis, among which PI3K-Akt signaling pathway, p53 signaling pathway, inflammatory response, extracellular matrix organization were significantly upregulated. The PPI network was constructed and the most significant three modules and nine genes were filtered. Twenty-two potential compounds were repurposed for ATC treatment. Conclusion: Using integrated bioinformatics analysis, we have identified hub genes and key pathways in ATC, and provide novel strategy for the treatment of ATC.
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Received: 26 January 2018
Published: 24 July 2018
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Corresponding Authors:
HUANG Ping
E-mail: panzf@zjcc.org.cn;huangping1841@zjcc.org.cn
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基于生物信息学的未分化甲状腺癌关键发病机制及其潜在干预靶点研究
目的: 阐明未分化型甲状腺癌(ATC)的分子病理状态,并挖掘其潜在的干预策略。方法: 利用GEO数据库联合R语言分析ATC组织与正常甲状腺组织差异表达的基因;利用京都基因与基因组百科全书(KEGG)通路数据库和基因本体(GO)数据库对差异表达的基因进行富集和功能注释;基于STRING数据库及Cytoscape软件构建蛋白质相互作用网络,分析其关键网络节点和基因簇;最后采用L1000CDS2数据库预测ATC的潜在治疗药物。结果: 共获得2087个差异表达基因。与正常甲状腺组织相比,ATC组织细胞内信号通路及肿瘤微环境均发生显著改变,包括PI3K-Akt信号的持续激活、p53通路的激活、炎症反应、细胞外基质重塑等。蛋白质相互作用网络提示存在3个重要的基因簇和9个关键节点。将差异表达基因与L1000CDS2数据库进行比对后发现22个能够逆转ATC病理状态的潜在化合物。结论: 本研究揭示了ATC发病机制中的关键节点,为ATC的治疗提供了潜在的靶点。
关键词:
甲状腺肿瘤/病理生理学,
计算生物学,
基因表达,
信号传导,
蛋白质类,
基因调控网络
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