PGM2在脑胶质瘤中的表达及临床意义  

Expression and clinical significance of PGM2 in glioma

作　　者：沈若菲 蒋传路[1] 蔡金全 Shen Ruofei;Jiang Chuanlu;Cai Jinquan(Department of Neurosurgery,the Second Affiliated Hospital of Harbin Medical University,Harbin 150001,China)

机构地区：[1]哈尔滨医科大学附属第二医院神经外科,150001

出　　处：《神经疾病与精神卫生》2024年第5期348-356,共9页Journal of Neuroscience and Mental Health

摘　　要：目的探讨磷酸葡糖变位酶2(PGM2)在脑胶质瘤中的表达及临床意义。方法提取中国胶质瘤基因组图谱计划(CGGA)数据库和癌症基因组图谱计划(TCGA)数据库中脑胶质瘤患者的临床数据和mRNA测序数据,将测序数据与临床数据相匹配后提取PGM2基因的表达情况,并剔除临床数据缺失的病例。根据受试者工作特征(receiver operating characteristic,ROC)曲线获得的临界值(Cut-off值)将病例分为PGM2高表达组和PGM2低表达组。采用ROC曲线下面积(AUC)和Kaplan-Meier生存曲线评价PGM2表达水平对胶质瘤患者总生存率的预测价值。采用单因素分析影响PGM2表达水平的胶质瘤临床病理因素。采用单因素、多因素Cox回归分析脑胶质瘤相关临床病理因素和PGM2表达与胶质瘤患者预后的关系。通过筛选共表达基因,进行基因本体(GO)富集分析和KEGG通路分析,探讨PGM2参与生物学过程以及调控的相关信号通路。采用CIBERSORT算法分析胶质瘤PGM2表达与免疫细胞浸润的关系。结果CGGA-325数据库剔除缺失值后余273例,TCGA数据库剔除缺失值后余560例。PGM2表达量预测胶质瘤患者总生存率的ROC曲线分析显示,其在CGGA-325数据库中的AUC为0.705(95%CI:0.640~0.769),Cut-off值为10.1;在TCGA数据库中的AUC为0.739(95%CI:0.699~0.778),Cut-off值为8.9。根据Cut-off值将病例分为PGM2高表达组和PGM2低表达组。Kaplan-Meier生存分析显示,PGM2高表达组患者的总生存率较PGM2低表达组患者下降,差异有统计学意义(P<0.001)。CGGA-325和TCGA数据库中,PGM2低表达与高表达组的胶质瘤级别、IDH分型以及1p/19q缺失情况比较,差异均有统计学意义(均P<0.05)。多因素Cox回归分析显示,CGGA-325数据库与TCGA数据库中胶质瘤共同独立预后因素是胶质瘤级别与1P/19q共缺失,PGM2表达在CGGA-325数据库中显示为独立预后因素(均P<0.05)。GO富集分析和KEGG通路分析显示,PGM2表达与内质网蛋白转运、Toll样�Objective To explore the expression and clinical significance of phosphoglucomutase 2(PGM2)in glioma.Methods Clinical data and mRNA sequencing data of glioma patients were collected from the Chinese Glioma Genome Atlas(CGGA)database and the Cancer Genome Atlas(TCGA)database.After matching the sequencing data with clinical data,the gene expression of PGM2 was extracted,and cases with missing clinical data were excluded.According to the cut-off value obtained from the receiver operating characteristic(ROC)curve,the cases were divided into PGM2 high expression group and PGM2 low expression group.The predictive value of PGM2 expression on the overall survival rate of glioma patients was evaluated using area under the ROC curve(AUC)and Kaplan Meier survival curve.Univariate analysis was used to explore the clinical and pathological factors affecting the expression level of PGM2 in gliomas.Univariate and multivariate Cox regression were used to analyze the relationship between prognosis in glioma patients and clinical and pathological factors related to glioma,as well as PGM2 expression.Gene Ontology(GO)enrichment analysis and KEGG pathway analysis were performed by screening co-expressed genes to explore the involvement of PGM2 in biological processes and related signaling pathways regulation.CIBERSORT algorithm was used to analyze the relationship between PGM2 expression in gliomas and immune cell infiltration.Results A total of 273 cases were left after the deletion of missing values from the CGGA-325 and 560 cases were left after the deletion of missing values from the TCGA.ROC curve analysis of PGM2 expression predicting the overall survival rate of glioma patients showed that the AUC in the CGGA-325 database was 0.705[95%CI(0.640,0.769)],with a cut-off value of 10.1,and the AUC in the TCGA database was 0.739[95%CI(0.699,0.778)],with a cut-off value of 8.9.According to the cut off value,the cases were divided into PGM2 high expression group and PGM2 low expression group.Kaplan Meier survival analysis showed that t

关 键 词：胶质瘤 PGM2 分子病理 预后 

分 类 号：R739.4[医药卫生—肿瘤]