Li Xue-Yuan, Yu Zhi-Yun, Li Hong-Jiang, Yan Dong-Ming, Yang Chao, Liu Xian-Zhi
Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Front Neurol. 2025 May 14;16:1545608. doi: 10.3389/fneur.2025.1545608. eCollection 2025.
M2 phenotype tumor-associated macrophages (TAMs) can promote tumor growth, invasion, chemotherapy resistance and so on, leading to malignant progression. The aim of this study was to identify novel prognostic profiles in glioblastoma (GBM) by integrating single-cell RNA sequencing (scRNA-seq) with bulk RNA-seq.
We identified M2-associated genes by intersecting TAM marker genes derived from scRNA-seq with macrophage module genes from WGCNA RNA-seq data. Prognostic M2 TAM-related genes were determined using univariate Cox and LASSO regression analyses. In the following steps, prognostic characteristics, risk groups, and external validation were constructed and validated. The immune landscape of patients with GBM was examined by evaluating immune cells, functions, evasion scores, and checkpoint genes.
Analysis of scRNA-seq and bulk-seq data revealed 107 genes linked to M2 TAMs. Using univariate Cox and LASSO regression, 16 genes were identified as prognostic for GBM, leading to the creation and validation of a prognostic signature for GBM survival prediction.
Our findings reveal the immune landscape of GBM and enhance understanding of the molecular mechanisms associated with M2 TAMs.
M2表型肿瘤相关巨噬细胞（TAM）可促进肿瘤生长、侵袭、化疗耐药等，导致恶性进展。本研究旨在通过将单细胞RNA测序（scRNA-seq）与批量RNA测序（bulk RNA-seq）相结合，确定胶质母细胞瘤（GBM）新的预后特征。
我们通过将来自scRNA-seq的TAM标记基因与来自WGCNA RNA-seq数据的巨噬细胞模块基因相交，确定了与M2相关的基因。使用单变量Cox和LASSO回归分析确定预后性M2 TAM相关基因。在接下来的步骤中，构建并验证了预后特征、风险组和外部验证。通过评估免疫细胞、功能、逃逸评分和检查点基因，研究了GBM患者的免疫格局。
对scRNA-seq和批量测序数据的分析揭示了107个与M2 TAM相关的基因。使用单变量Cox和LASSO回归，确定了16个基因对GBM具有预后意义，从而创建并验证了用于GBM生存预测的预后特征。
我们的研究结果揭示了GBM的免疫格局，并增强了对与M2 TAM相关分子机制的理解。
