Zhang Zhenpan, Huang Jianhuang, Lin Caihou, Liang Risheng
Department of Neurosurgery, Fujian Medical University Union Hospital, Fuzhou, 350001, China.
Department of Neurosurgery, Affiliated Hospital of Putian University, Putian, 351100, China.
Sci Rep. 2025 Apr 14;15(1):12833. doi: 10.1038/s41598-025-97333-4.
Gliomas are the most common primary tumors of the central nervous system, with epilepsy serving as a frequent clinical manifestation. Glioma-related epilepsy (GRE) significantly affects patients' quality of life and prognosis. In this study, we integrated bioinformatics and multiple machine learning methods to perform a proteomic analysis of brain tumor samples from patients with GRE and from those with gliomas none epilepsy (GNE). Our findings identified LY6H and GRM3 as potential signature proteins of GRE. Further investigation showed that LY6H and GRM3 expression levels were markedly reduced in GRE samples, with favorable diagnostic performance according to ROC curve analyses. Finally, we conducted an independent external validation using the Bluk-RNA dataset GSE199759, and the results corroborated our prior analyses. This work not only provides new biomarkers for the early detection of GRE but also offers valuable insights into its molecular mechanisms and potential therapeutic strategies.
胶质瘤是中枢神经系统最常见的原发性肿瘤,癫痫是其常见的临床表现。胶质瘤相关性癫痫(GRE)显著影响患者的生活质量和预后。在本研究中,我们整合了生物信息学和多种机器学习方法,对GRE患者和非癫痫性胶质瘤(GNE)患者的脑肿瘤样本进行了蛋白质组学分析。我们的研究结果确定LY6H和GRM3为GRE的潜在标志性蛋白。进一步研究表明,GRE样本中LY6H和GRM3的表达水平显著降低,根据ROC曲线分析,其具有良好的诊断性能。最后,我们使用Bluk-RNA数据集GSE199759进行了独立的外部验证,结果证实了我们之前的分析。这项工作不仅为GRE的早期检测提供了新的生物标志物,还为其分子机制和潜在治疗策略提供了有价值的见解。