Shen Zhe, Li Tao, Yang Bo
Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450000, China.
Department of Neurosurgery, The First Affiliated Hospital of Henan University of Science and Technology, Luoyang, 471003, China.
J Mol Neurosci. 2025 Jan 14;75(1):6. doi: 10.1007/s12031-024-02294-4.
Hemorrhagic stroke is a known complication of glioma, yet the underlying mechanisms remain poorly understood. This study aims to investigate key biomarkers of glioma-related hemorrhage to provide insights into glioma molecular therapies. Data were obtained from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases to analyze differentially expressed genes (DEGs) in glioma by contrasting glioblastoma (GBM) with low-grade gliomas (LGGs). We conducted enrichment analyses using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) databases through the Database for Annotation, Visualization, and Integrated Discovery (DAVID). A STRING-based protein-protein interaction (PPI) network was developed to identify hub genes, which were subsequently analyzed for their functions in the GeneCards database. To identify angiogenesis-associated genes, we utilized the Human Protein Atlas (HPA) and Gene Expression Profiling Interactive Analysis (GEPIA) databases. A clinical pathological study was conducted using immunohistochemistry (IHC) staining to confirm the findings. In the GEO database, the GEO Series Experiments GSE26576 and GSE184941 included 4523 and 1471 differentially expressed genes (DEGs), respectively. We identified 2715 DEGs using the cBioPortal within the TCGA database. A Venn diagram identified 39 common DEGs. The KEGG pathways and Gene Ontology (GO) analysis highlighted functions related to angiogenesis. PPI network analyses pinpointed 13 hub genes. Through cross-referencing a gene set related to tumor angiogenesis in the GeneCards database, we identified MMP-2 and EGFR as key genes. In the HPA database, we observed EGFR and MMP-2 expression in the normal cerebral cortex, confirmed by IHC. In GEPIA database, high MMP-2 levels were associated with decreased survival time, while EGFR expression showed no significant differences in survival. A clinical study of 21 patients, 11 in the control group and 10 in the stroke group with glioma hemorrhage, revealed no significant differences in their characteristics or comorbidities. IDH1 positivity was higher in the control group (4/11) vs the stroke group (0/10). Tumor cells exhibited increased MMP-2 and EGFR expression, with stronger staining in the stroke group. Our study concluded that IDH1, MMP-2, and EGFR are implicated in the molecular mechanism of glioma hemorrhage as key biomarkers. MMP-2 and IDH1 are potential targets for molecular therapy.
出血性中风是胶质瘤已知的并发症，但其潜在机制仍知之甚少。本研究旨在探究胶质瘤相关出血的关键生物标志物，为胶质瘤分子治疗提供见解。从基因表达综合数据库（GEO）和癌症基因组图谱（TCGA）数据库获取数据，通过将胶质母细胞瘤（GBM）与低级别胶质瘤（LGG）对比分析胶质瘤中的差异表达基因（DEG）。我们通过注释、可视化和综合发现数据库（DAVID），利用京都基因与基因组百科全书（KEGG）通路和基因本体论（GO）数据库进行富集分析。构建基于STRING的蛋白质 - 蛋白质相互作用（PPI）网络以识别枢纽基因，随后在基因卡片数据库中分析这些基因的功能。为识别血管生成相关基因，我们利用人类蛋白质图谱（HPA）和基因表达谱交互式分析（GEPIA）数据库。通过免疫组织化学（IHC）染色进行临床病理研究以证实研究结果。在GEO数据库中，GEO系列实验GSE26576和GSE184941分别包含4523个和1471个差异表达基因（DEG）。我们在TCGA数据库中利用cBioPortal识别出2715个DEG。维恩图确定了39个共同的DEG。KEGG通路和基因本体论（GO）分析突出了与血管生成相关的功能。PPI网络分析确定了13个枢纽基因。通过在基因卡片数据库中交叉引用与肿瘤血管生成相关的基因集，我们确定基质金属蛋白酶 - 2（MMP - 2）和表皮生长因子受体（EGFR）为关键基因。在HPA数据库中，我们通过免疫组织化学证实了正常大脑皮层中EGFR和MMP - 2的表达。在GEPIA数据库中，MMP - 2水平高与生存时间缩短相关，而EGFR表达在生存方面无显著差异。对21例患者进行的临床研究，其中11例为对照组，10例为胶质瘤出血性中风组，结果显示两组在特征或合并症方面无显著差异。对照组（4/11）的异柠檬酸脱氢酶1（IDH1）阳性率高于中风组（0/10）。肿瘤细胞中MMP - 2和EGFR表达增加，中风组染色更强。我们的研究得出结论，IDH1、MMP - 2和EGFR作为关键生物标志物参与了胶质瘤出血的分子机制。MMP - 2和IDH1是分子治疗的潜在靶点。
