Table1_Novel Immune-Related Gene-Based Signature Characterizing an Inflamed Microenvironment Predicts Prognosis and Radiotherapy Efficacy in Glioblastoma.DOCX

Effective treatment of glioblastoma (GBM) remains an open challenge. Given the critical role of the immune microenvironment in the progression of cancers, we aimed to develop an immune-related gene (IRG) signature for predicting prognosis and improving the current treatment paradigm of GBM. Multi-omics data were collected, and various bioinformatics methods, as well as machine learning algorithms, were employed to construct and validate the IRG-based signature and to explore the characteristics of the immune microenvironment of GBM. A five-gene signature (ARPC1B, FCGR2B, NCF2, PLAUR, and S100A11) was identified based on the expression of IRGs, and an effective prognostic risk model was developed. The IRG-based risk model had superior time-dependent prognostic performance compared to well-studied molecular pathology markers. Besides, we found prominent inflamed features in the microenvironment of the high-risk group, including neutrophil infiltration, immune checkpoint expression, and activation of the adaptive immune response, which may be associated with increased hypoxia, epidermal growth factor receptor (EGFR) wild type, and necrosis. Notably, the IRG-based risk model had the potential to predict the effectiveness of radiotherapy. Together, our study offers insights into the immune microenvironment of GBM and provides useful information for clinical management of this desperate disease.

胶质母细胞瘤（glioblastoma, GBM）的有效治疗仍是一项亟待攻克的临床挑战。鉴于免疫微环境在癌症进展中的关键作用，本研究旨在构建免疫相关基因（immune-related gene, IRG）特征模型，以预测胶质母细胞瘤患者的预后并优化现有治疗范式。本研究收集多组学数据，采用多种生物信息学方法与机器学习算法，构建并验证基于免疫相关基因的特征模型，同时探究胶质母细胞瘤的免疫微环境特征。基于免疫相关基因的表达谱，本研究筛选得到包含ARPC1B、FCGR2B、NCF2、PLAUR及S100A11的五基因特征模型，并构建了高效的预后风险模型。相较于已被广泛研究的分子病理标志物，该基于免疫相关基因的风险模型展现出更优的时间依赖性预后效能。此外，本研究发现高风险组肿瘤微环境呈现显著的炎性特征，包括中性粒细胞浸润、免疫检查点表达及适应性免疫应答激活，上述特征可能与肿瘤缺氧程度升高、表皮生长因子受体（epidermal growth factor receptor, EGFR）野生型状态及肿瘤坏死相关。值得注意的是，该基于免疫相关基因的风险模型具备预测放疗疗效的潜在价值。综上，本研究为胶质母细胞瘤的免疫微环境研究提供了新视角，也为这一难治性疾病的临床管理提供了有益参考。