基于癌症和肿瘤基因图谱筛选低级别胶质瘤中潜在抑癌基因的研究

目的:基于癌症和肿瘤基因图谱(TCGA)计划数据库的胶质瘤标本信息,探讨较低级别胶质瘤标本中相对低表达的基因与患者预后的关系。方法:在TCGA数据库中选取678例胶质瘤患者[包括低级别胶质瘤(LGG)患者512例,胶质瘤母细胞瘤(GBM)166例]的698例胶质瘤标本[包括LGG患者529例,GBM169例]以及5例正...

Data mining of potential tumor suppressor genes in lower grade gliomas from the cancer genome atlas database

Objective To investigate the low expressed genes,and the relationship between gene and prognosis in lower grade gliomas(LGG)from The Cancer Genome Atlas(TCGA)database.Methods In the TCGA database,698 cases of glioma specimens[including 529 cases of lower grade glioma samples and 169 cases of glioblastoma(GBM)samples that were from 678 patients including 512 LGG patients and 166 GBM patients]and 5 cases of normal samples were analyzed for gene expression level data and clinical data of patients.R software was used to analyze and screen the low expressed genes in gliomas.We performed gene annotation and gene function enrichment analysis,constructed protein interaction networks using STRING and cytoscape software,and used R software to analyze survival data based on the level of gene expression combined with clinical data.Results A total of 155 genes were both lowly expressed in glioma samples and normal bran tissues,and glioblastoma and lower grade glioma samples.Among the top 20 genes with the highest weight in the protein interaction relationship,there were 12 genes with available functional enrichment data.And glutamate ion receptor NMDA may be the one of the important signaling pathways about glioma growth.The survival analysis results showed 7 of the 12 genes were associated with improved survival outcomes(P<0.05).Conclusion Data mining from the TCGA is an effective means of exploring biological information of glioma suppressor genes.Glutamate ion receptor NDMA family may be obviously related to the growth and prognosis of glioma.