胶质母细胞瘤（GBM）是最常见的原发性脑肿瘤，缺乏准确的预后标志物，预后较差。我们的研究旨在确定有效的生物标志物，用于 GBM 预后分析和精确治疗的开发。通过 Xena 数据库和 GEPIA 分析 GBM 患者和对照之间的差异表达基因 (DEG)。基于筛选的 DEG，进行单变量 COX 和 LASSO 回归分析，以确定与 GBM 预后最相关的基因。选择GBM患者中高表达的基因构建接受者操作特征分析，并对脂肪细胞增强子结合蛋白1（AEBP1）高表达和低表达的组构建富集分析。使用 CIBERSORT、ssGSEA 和 ESTIMATE 进行免疫浸润分析。使用 Xena 数据库的数据识别出约 3297 个 DEG；鉴定出 8 个预后基因。 AEBP1在神经元分化和发育中发挥作用，在GBM中与免疫浸润呈正相关；它在癌症患者中的高表达与总生存期短和肿瘤分期晚期有关。这项研究表明 AEBP1 可以作为 GBM 的预后标志物，高表达的患者可能对免疫治疗有更好的反应。© 作者 2024。由牛津大学出版社代表美国神经病理学家协会出版。版权所有。如需权限，请发送电子邮件至：journals.permissions@oup.com。

Glioblastomas (GBM), the most common primary brain tumor, lack accurate prognostic markers and have a poor prognosis. Our study was designed to identify effective biomarkers for GBM prognosis analysis and development of precise treatments. Differentially expressed genes (DEGs) between GBM patients and controls were analyzed from the Xena database and GEPIA. Based on the screened DEGs, univariate COX and LASSO regression analysis were performed to identify the most relevant genes associated with GBM prognosis. Genes highly expressed in GBM patients were selected to construct receiver operating characteristic analysis and enrichment analysis was constructed on groups of high and low expression of adipocyte enhancer-binding protein 1 (AEBP1). CIBERSORT, ssGSEA and ESTIMATE were used to perform immune infiltration analysis. About 3297 DEGs were identified using data from Xena database; 8 prognostic genes were identified. AEBP1, which plays a role in neuronal differentiation and development, was positively correlated in GBMs with immune infiltration; its high expression in cancer patients is associated with short overall survival and advanced tumor staging. This study suggests that AEBP1 could serve as a prognostic marker for GBMs and that patients with high expression may have a better response to immunotherapy.© The Author(s) 2024. Published by Oxford University Press on behalf of American Association of Neuropathologists, Inc. All rights reserved. For permissions, please email: journals.permissions@oup.com.