Wang Jiajia, Ma Jie
Department of Pediatric Neurosurgery, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
J Neurol Surg A Cent Eur Neurosurg. 2019 Jul;80(4):240-249. doi: 10.1055/s-0039-1683448. Epub 2019 Apr 1.
Glioblastoma multiforme (GBM), an aggressive brain tumor, is characterized histologically by the presence of a necrotic center surrounded by so-called pseudopalisading cells. Pseudopalisading necrosis has long been used as a prognostic feature. However, the underlying molecular mechanism regulating the progression of GBMs remains unclear. We hypothesized that the gene expression profiles of individual cancers, specifically necrosis-related genes, would provide objective information that would allow for the creation of a prognostic index. Gene expression profiles of necrotic and nonnecrotic areas were obtained from the Ivy Glioblastoma Atlas Project (IVY GAP) database to explore the differentially expressed genes.A robust signature of seven genes was identified as a predictor for glioblastoma and low-grade glioma (GBM/LGG) in patients from The Cancer Genome Atlas (TCGA) cohort. This set of genes was able to stratify GBM/LGG and GBM patients into high-risk and low-risk groups in the training set as well as the validation set. The TCGA, Repository for Molecular Brain Neoplasia Data (Rembrandt), and GSE16011 databases were then used to validate the expression level of these seven genes in GBMs and LGGs. Finally, the differentially expressed genes (DEGs) in the high-risk and low-risk groups were subjected to gene ontology enrichment, Kyoto Encyclopedia of Genes and Genomes pathway, and gene set enrichment analyses, and they revealed that these DEGs were associated with immune and inflammatory responses. In conclusion, our study identified a novel seven-gene signature that may guide the prognostic prediction and development of therapeutic applications.
多形性胶质母细胞瘤(GBM)是一种侵袭性脑肿瘤,其组织学特征是存在一个坏死中心,周围环绕着所谓的假栅栏状细胞。假栅栏状坏死长期以来一直被用作预后特征。然而,调节GBM进展的潜在分子机制仍不清楚。我们假设个体癌症的基因表达谱,特别是与坏死相关的基因,将提供客观信息,从而能够创建一个预后指数。从常春藤胶质母细胞瘤图谱项目(IVY GAP)数据库中获取坏死和非坏死区域的基因表达谱,以探索差异表达基因。在来自癌症基因组图谱(TCGA)队列的患者中,确定了一个由七个基因组成的强大特征作为胶质母细胞瘤和低级别胶质瘤(GBM/LGG)的预测指标。这组基因能够在训练集和验证集中将GBM/LGG和GBM患者分为高风险和低风险组。然后使用TCGA、分子脑肿瘤数据储存库(Rembrandt)和GSE16011数据库来验证这七个基因在GBM和LGG中的表达水平。最后,对高风险和低风险组中的差异表达基因(DEG)进行基因本体富集、京都基因与基因组百科全书通路以及基因集富集分析,结果显示这些DEG与免疫和炎症反应相关。总之,我们的研究确定了一种新的七基因特征,可能指导预后预测和治疗应用的开发。