首页> 外文期刊>BMC Cancer >Computational analysis for identification of early diagnostic biomarkers and prognostic biomarkers of liver cancer based on GEO and TCGA databases and studies on pathways and biological functions affecting the survival time of liver cancer
【24h】

Computational analysis for identification of early diagnostic biomarkers and prognostic biomarkers of liver cancer based on GEO and TCGA databases and studies on pathways and biological functions affecting the survival time of liver cancer

机译:基于地理和TCGA数据库的肝癌早期诊断生物标志物和预后生物标志物的计算分析及影响肝癌存活时间的途径和生物学功能研究

获取原文
           

摘要

Liver cancer is the sixth most commonly diagnosed cancer and the fourth most common cause of cancer death. The purpose of this work is to find new diagnostic biomarkers or prognostic biomarkers and explore the biological functions related to the prognosis of liver cancer. GSE25097 datasets were firstly obtained and compared with TCGA LICA datasets and an analysis of the overlapping differentially expressed genes (DEGs) was conducted. Cytoscape was used to screen out the Hub Genes among the DEGs. ROC curve analysis was used to screen the Hub Genes to determine the genes that could be used as diagnostic biomarkers. Kaplan-Meier analysis and Cox proportional hazards model screened genes associated with prognosis biomarkers, and further Gene Set Enrichment Analysis was performed on the prognosis genes to explore the mechanism affecting the survival and prognosis of liver cancer patients. 790 DEGs and 2162 DEGs were obtained respectively from the GSE25097 and TCGA LIHC data sets, and 102 Common DEGs were identified by overlapping the two DEGs. Further screening identified 22 Hub Genes from 102 Common DEGs. ROC and survival curves were used to analyze these 22 Hub Genes and it was found that there were 16 genes with a value of AUC??90%. Among these, the expression levels of ESR1,SPP1 and FOSB genes were closely related to the survival time of liver cancer patients. Three common pathways of ESR1, FOBS and SPP1 genes were identified along with seven common pathways of ESR1 and SPP1 genes and four common pathways of ESR1 and FOSB genes. SPP1, AURKA, NUSAP1, TOP2A, UBE2C, AFP, GMNN, PTTG1, RRM2, SPARCL1, CXCL12, FOS, DCN, SOCS3, FOSB and PCK1 can be used as diagnostic biomarkers for liver cancer, among which FOBS and SPP1 genes can also be used as prognostic biomarkers. Activation of the cell cycle-related pathway, pancreas beta cells pathway, and the estrogen signaling pathway, while on the other hand inhibition of the hallmark heme metabolism pathway, hallmark coagulation pathway, and the fat metabolism pathway may promote prognosis in liver cancer patients.
机译:肝癌是第六最常见的癌症和第四次癌症死亡原因。这项工作的目的是寻找新的诊断生物标志物或预后生物标志物,并探讨与肝癌预后有关的生物学功能。首先获得GSE25097数据集并与TCGA LICA数据集进行比较,并进行重叠差异表达基因(DEGS)的分析。 Cytoscape用于筛选液体中的枢纽基因。 ROC曲线分析用于筛选轮毂基因以确定可用作诊断生物标志物的基因。 KAPLAN-MEIER分析和COX比例危害与预后生物标志物相关的筛选基因,以及进一步的基因设定富集分析对预后基因进行了预后基因,以探讨影响肝癌患者的存活和预后的机制。从GSE25097和TCGA LIHC数据组中分别获得790℃和2162次,通过重叠两次次数来识别102个常见的常见。进一步筛选来自102只常见的22个枢纽基因。 ROC和存活曲线用于分析这些22个枢纽基因,发现有16个基因具有AUC的值?&?90%。其中,ESR1,SPP1和FOSB基因的表达水平与肝癌患者的存活时间密切相关。鉴定了ESR1,FOB和SPP1基因的三种常见途径以及ESR1和SPP1基因的七种常见途径和ESR1和FOSB基因的四种常见途径。 SPP1,AURKA,NUSAP1,TOP2A,UBE2C,AFP,GMNN,PTTG1,RRM2,SPARCL1,CXCL12,FOS,DCN,SOCS3,FOSB和PCK1可用作肝癌的诊断生物标志物,其中FOB和SPP1基因也可以是用作预后生物标志物。对细胞周期相关途径,胰腺β细胞途径和雌激素信号传导途径的激活,同时对象血红蛋白代谢途径,标志性凝血途径和脂肪代谢途径可以促进肝癌患者的预后。

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