摘要
目的构建与多形性胶质母细胞瘤患者生存期相关的权重基因共表达网络。方法采用R软件平台下的权重基因共表达网络构建多形性胶质母细胞瘤组织表达谱共表达网络,与患者生存期进行相关性分析,并对与生存期显著相关的共表达网络中的基因集进行通路富集。结果权重基因共表达网络共构建了31个共表达模块,其中有一个包含199个基因的模块与患者生存期显著相关(r=0.35,P<0.01)。通路分析发现,这199个基因显著富集于整合素、胶原蛋白、硫酸软骨素等细胞外基质相关通路以及Wnt、表皮生长因子受体(EGFR)、血管内皮生长因子(VEGF)、尿激酶型纤溶酶原激活因子(uPA)和伊立替康等代谢相关通路中。结论成功构建了与多形性胶质母细胞瘤患者生存期相关的权重基因共表达网络,应用该网络分析发现了与多形性胶质母细胞瘤患者生存期相关的信号通路。
Objective To construct a weighted gene co-expression network related to the survival of patients with glioblastoma multiforme.Methods The weighted gene co-expression network under the R software platform was used to construct a co-expression network of glioblastoma multiforme tissue expression profiles.The correlation analysis was performed with the survival time of patients and pathway enrichment was performed for gene sets in co-expression networks that were significantly related to survival.Results 31 co-expression modules were constructed using a weighted gene co-expression network,of which one module containing 199 genes was significantly related to patient survival(r=0.35,P<0.01).Pathway analysis revealed that these 199 genes were significantly enriched in extracellular matrix-related pathways such as integrin,collagen and chondroitin sulfate,as well as wnt,epidermal growth factor receptor(EGFR),vascular endothelial growth factor(VEGF),urokinase-type plasminogen activator(uPA),irinotecan and other metabolic-related pathways.Conclusion The weighted gene co-expression network related to the survival of patients with glioblastoma multiforme was successfully constructed.The network analysis was used to find the signal pathway related to the survival of patients with glioblastoma multiforme.
作者
徐晓文
何玉琪
张露
潘名志
杨旭娜
惠李
谷晓楚
XU Xiaowen;HE Yuqi;ZHANG Lu;PAN Mingzhi;YANG Xu'na;HUI Li;GU Xiaochu(Department of Clinical Laboratory,Guangji Hospital,Suzhou 215008,China;Department of Medical Affairs,Guangji Hospital,Suzhou 215008,China;Department of Science and Education,Guangji Hospital,Suzhou 215008,China)
出处
《中国医药科学》
2019年第24期287-289,293,共4页
China Medicine And Pharmacy
基金
江苏省苏州市产业技术创新专项(SYSD2016141)
