Du Ran, Jing Lijun, Fu Denggang
Department of Neurology Intensive Care Unit, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
College of Medicine, Medical University of South Carolina, Charleston, SC, United States.
Front Immunol. 2025 Aug 6;16:1577920. doi: 10.3389/fimmu.2025.1577920. eCollection 2025.
Glioblastoma (GBM) is a highly aggressive brain tumor with poor prognosis and limited response to immunotherapy. Immune escape-related genes (IERGs) are increasingly recognized as critical regulators of tumor progression and immune evasion. However, their prognostic value in GBM remains unclear. This study aims to evaluate the clinical relevance of IERGs and develop a predictive gene signature to guide prognosis and characterize the tumor immune microenvironment (TIME).
We performed a comprehensive analysis of IERGs using the TCGA GBM dataset. Prognostic IERGs were identified through univariate Cox regression, and a multivariate Cox model was used to develop a prognostic signature. Risk scores (IEScore) were calculated to classify patients into high- and low-risk groups. The signature was validated in two independent GBM cohorts. Its prognostic independence was assessed after adjusting for clinicopathological features. Receiver operating characteristic (ROC) analysis confirmed the signature's reliability. TIME analysis was carried out using multiple deconvolution algorithms. Additionally, functional assays including CCK8, cell cycle, and apoptosis assays were conducted on PPP1R8-silenced U251 cells using CRISPR/Cas9 technology.
Thirty-six IERGs were associated with GBM outcomes, with 20 linked to poor survival and 16 to better outcomes. Key genes, including STAT2, IFNGR2, and PPP1R8, formed a robust prognostic signature. High-risk patients had significantly poorer overall survival (OS) compared to low-risk patients. The signature showed strong predictive power with AUC values of 0.68, 0.73, and 0.76 for 2-, 3-, and 5-year survival, respectively. Validation in two independent cohorts confirmed its robustness. Immune cell infiltration analysis revealed distinct patterns in high- and low-risk groups, with the high-risk group showing a more aggressive and immunosuppressive tumor microenvironment. The signature also effectively stratified low-grade glioma patients across four independent datasets. Knockout of PPP1R8 in GBM cells using CRISPR/Cas9 inhibited cell proliferation and increased apoptosis.
The IERGs-based signature offers reliable prognostication for GBM, validated across multiple datasets. It can guide patient stratification and inform therapeutic decisions for GBM and potentially low-grade gliomas (LGG). Furthermore, we identify PPP1R8 as a key regulator of GBM cell proliferation and growth, providing insights into the immune microenvironment's role in GBM progression.
胶质母细胞瘤（GBM）是一种侵袭性很强的脑肿瘤，预后较差，对免疫治疗反应有限。免疫逃逸相关基因（IERGs）越来越被认为是肿瘤进展和免疫逃逸的关键调节因子。然而，它们在GBM中的预后价值仍不清楚。本研究旨在评估IERGs的临床相关性，并开发一种预测基因特征以指导预后并表征肿瘤免疫微环境（TIME）。
我们使用TCGA GBM数据集对IERGs进行了全面分析。通过单变量Cox回归确定预后IERGs，并使用多变量Cox模型开发预后特征。计算风险评分（IEScore）以将患者分为高风险和低风险组。该特征在两个独立的GBM队列中得到验证。在调整临床病理特征后评估其预后独立性。受试者操作特征（ROC）分析证实了该特征的可靠性。使用多种反卷积算法进行TIME分析。此外，使用CRISPR/Cas9技术对PPP1R8沉默的U251细胞进行了包括CCK8、细胞周期和凋亡分析在内的功能测定。
36个IERGs与GBM结局相关，其中20个与较差的生存率相关，16个与较好的结局相关。关键基因，包括STAT2、IFNGR2和PPP1R8，形成了一个强大的预后特征。与低风险患者相比，高风险患者的总生存期（OS）明显更差。该特征显示出强大的预测能力，2年、3年和5年生存率的AUC值分别为0.68、0.73和0.76。在两个独立队列中的验证证实了其稳健性。免疫细胞浸润分析揭示了高风险和低风险组中的不同模式，高风险组显示出更具侵袭性和免疫抑制性的肿瘤微环境。该特征还在四个独立数据集中有效地对低级别胶质瘤患者进行了分层。使用CRISPR/Cas9敲除GBM细胞中的PPP1R8可抑制细胞增殖并增加凋亡。
基于IERGs的特征为GBM提供了可靠的预后评估，在多个数据集中得到验证。它可以指导患者分层，并为GBM以及潜在的低级别胶质瘤（LGG）的治疗决策提供信息。此外，我们确定PPP1R8是GBM细胞增殖和生长的关键调节因子，为免疫微环境在GBM进展中的作用提供了见解。
