首页> 外文期刊>Journal of cellular biochemistry. >Identification of hub genes to regulate breast cancer metastasis to brain by bioinformatics analyses
【24h】

Identification of hub genes to regulate breast cancer metastasis to brain by bioinformatics analyses

机译:通过生物信息学分析鉴定枢纽基因以调节乳腺癌转移对脑的影响

获取原文
获取原文并翻译 | 示例
           

摘要

Abstract Breast cancer with metastasis especially brain metastasis represents a significant cause of morbidity and mortality in patients. In this study, we aimed to investigate the hub genes and potential molecular mechanism in brain metastasis breast cancer. Expression profiles of the genes were extracted from the Gene Expression Omnibus (GEO) database. GO and KEGG pathway enrichment analyses were conducted at Database for Annotation, Visualization, and Integrated Discovery. Protein‐protein interaction (PPI) network was established by STRING database constructed by Cytoscape software. Hub genes were identified by the molecular complex detection (MCODE) plugin and the CytoHubba plugin. The transcription factor (TF) that regulates the expression of hub genes was analyzed using the NetworkAnalyst algorithm. Kaplan‐Meier curve was used to analyze the effects of hub genes on overall survival. Two GEO databases (GSE100534 and GSE52604) were downloaded from GEO databases. A total of 102 overlapped genes were identified, and the top five KEGG pathways enriched were pathways in cancer, HTLV‐I infection, focal adhesion, ECM‐receptor interaction, and protein digestion and absorption. By combing the results of MCODE and CytoHubba, a total of 10 hub genes were selected. Kaplan‐Meier curve showed that ANLN, BUB1, TTK, and SKA3 were closely associated with the overall survival of breast cancer patients. TF analysis results showed that E2F4, KDM5B, and MYC were crucial regulators for these four hub genes. The current study based on the GEO database provided novel understanding regarding the mechanism of breast cancer metastasis to brain and may provide novel therapeutic targets.
机译:摘要乳腺癌患有转移尤其是脑转移是患者发病率和死亡率的显着原因。在这项研究中,我们旨在探讨脑转移乳腺癌中的轮毂基因和潜在的分子机制。从基因表达omnibus(Geo)数据库中提取基因的表达谱。在数据库中进行GO和Kegg途径浓缩分析,以进行注释,可视化和集成发现。通过Cytoscape软件构建的String数据库建立蛋白质 - 蛋白质相互作用(PPI)网络。通过分子复数(MCODE)插件和细胞霍布布插件鉴定了轮毂基因。使用NetworkAnalyst算法分析调节轮毂基因表达的转录因子(TF)。 Kaplan-Meier曲线用于分析中心基因对整体存活的影响。从Geo数据库下载了两个Geo数据库(GSE100534和GSE52604)。鉴定了总共102个重叠基因,富含10克GEGG途径在癌症,HTLV-I感染,局灶性粘附,ECM-受体相互作用和蛋白质消化和吸收中是途径。通过梳理MCODE和细胞凋亡的结果,选择总共10个枢纽基因。 Kaplan-Meier曲线表明,ANLN,BUB1,TTK和SKA3与乳腺癌患者的整体存活密切相关。 TF分析结果表明,E2F4,KDM5B和MYC是这四个轮毂基因的关键调节剂。基于Geo数据库的目前的研究提供了关于乳腺癌转移给脑的机制的新颖理解,并可提供新的治疗目标。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号