Li Huijun, Luo Bin, Tulufu Yibadaiti, Wang Xiong, Yue Daoyuan
Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Department of Laboratory Medicine, Xianning Central Hospital, the First Affiliated Hospital of Hubei Institute of Science and Technology, Xianning, China.
Cell Mol Biol (Noisy-le-grand). 2025 Jul 6;71(6):102-109. doi: 10.14715/cmb/2025.71.6.14.
Glioma is the most frequent malignant tumor in the brain. Super-enhancer (SE) is a class of transcriptional activator, which drives gene expression. SE-related genes (SERGs) affect occurrence and development of several tumors. We explored the predictive role of SERGs in the prognosis and immune features of glioma. A total of 1557 glioma patients were collected from four data sets, including The Cancer Genomic Atlas (TCGA, n = 691), the Chinese Glioma Genomic Atlas (CGGA) array (n = 286), the CGGA sequencing (n = 316), and GSE16011 (n = 264) from Gene Expression Omnibus (GEO) database. SERGs were selected from SEdb (http://www.licpathway.net/sedb), a comprehensive human SE database. Survival analysis and visualization were performed using the R packages survival (v3.3-1) and survminer (v0.4.9). Immune subtype classification was conducted with the ImmuneSubtypeClassifier (v0.1.0) R package. A nomogram was generated using the rms (v6.7-1) package. A risk score model based on 13 super-enhancer-related genes (SERGs) was constructed, demonstrating that patients in the low-risk group had significantly better prognosis. The SERGs signature significantly correlated with age, molecular and immune subtypes, IDH mutation, MTMG promoter methylation, 1p19q co-deletion, and expression of immune checkpoint genes in glioma patients. The SERGs signature could predict the prognosis and immune features of glioma, and SERGs might serve as novel immunotherapy options for glioma.
胶质瘤是大脑中最常见的恶性肿瘤。超级增强子(SE)是一类转录激活因子,可驱动基因表达。SE相关基因(SERGs)影响多种肿瘤的发生和发展。我们探讨了SERGs在胶质瘤预后和免疫特征中的预测作用。从四个数据集收集了总共1557例胶质瘤患者,包括癌症基因组图谱(TCGA,n = 691)、中国胶质瘤基因组图谱(CGGA)阵列(n = 286)、CGGA测序(n = 316)以及来自基因表达综合数据库(GEO)的GSE16011(n = 264)。SERGs是从综合人类SE数据库SEdb(http://www.licpathway.net/sedb)中选择的。使用R包survival(v3.3 - 1)和survminer(v0.4.9)进行生存分析和可视化。使用免疫亚型分类器(ImmuneSubtypeClassifier,v0.1.0)R包进行免疫亚型分类。使用rms(v6.7 - 1)包生成列线图。构建了基于13个超级增强子相关基因(SERGs)的风险评分模型,结果表明低风险组患者的预后明显更好。SERGs特征与胶质瘤患者的年龄、分子和免疫亚型、异柠檬酸脱氢酶(IDH)突变、甲基化MGMT启动子、1p19q共缺失以及免疫检查点基因的表达显著相关。SERGs特征可以预测胶质瘤的预后和免疫特征,并且SERGs可能成为胶质瘤新的免疫治疗选择。