Table_1_Comprehensive Analysis of the Tumor Immune Microenvironment Landscape in Glioblastoma Reveals Tumor Heterogeneity and Implications for Prognosis and Immunotherapy.docx

BackgroundGlioblastoma (GBM) is a fatal brain tumor with no effective treatment. The specific GBM tumor immune microenvironment (TIME) may contribute to resistance to immunotherapy, a tumor therapy with great potential. Thus, an in-depth understanding of the characteristics of tumor-infiltrating immune cells is essential for exploring biomarkers in GBM pathogenesis and immunotherapy.
MethodsWe estimated the relative abundances of 25 immune cell types in 796 GBM samples using single sample gene set enrichment analysis (ssGSEA). Unsupervised clustering was used to identify different GBM-associated TIME immune cell infiltration (GTMEI) patterns. The GTMEIscore system was constructed with principal component analysis (PCA) to determine the immune infiltration pattern of individual tumors.
ResultsWe revealed three distinct GTMEI patterns with different clinical outcomes and modulated biological pathways. We developed a scoring system (GTMEIscore) to determine the immune infiltration pattern of individual tumors. We comprehensively analyzed the genomic characteristics, molecular subtypes and clinicopathological features as well as proteomic, phosphoproteomic, acetylomic, lipidomic and metabolomic properties associated with the GTMEIscore and revealed many novel dysregulated pathways and precise targets in GBM. Moreover, the GTMEIscore accurately quantified the immune status of many other cancer types. Clinically, the GTMEIscore was found to have significant potential therapeutic value for chemotherapy/radiotherapy, immune checkpoint inhibitor (ICI) therapy and targeted therapy.
ConclusionsFor the first time, we employed a multilevel and multiplatform strategy to construct a multidimensional molecular map of tumors with different immune infiltration patterns. These results may provide theoretical basises for identifying more effective predictive biomarkers and developing more effective drug combination strategies or novel immunotherapeutic agents for GBM.

**背景**
胶质母细胞瘤（Glioblastoma, GBM）是一种致死性颅脑肿瘤，目前尚无有效治疗手段。GBM特有的肿瘤免疫微环境（tumor immune microenvironment, TIME）可能是其对极具应用前景的肿瘤免疫治疗产生耐药性的重要原因。因此，深入解析肿瘤浸润免疫细胞的特征，对于探索GBM发病机制及免疫治疗相关的生物标志物至关重要。

**方法**
本研究采用单样本基因集富集分析（single sample gene set enrichment analysis, ssGSEA），对796例GBM样本中25种免疫细胞类型的相对丰度进行估算。通过无监督聚类识别与GBM相关的TIME免疫细胞浸润（GBM-associated TIME immune cell infiltration, GTMEI）分型。利用主成分分析（principal component analysis, PCA）构建GTMEIscore评分系统，以判定单个肿瘤的免疫浸润模式。

**结果**
本研究揭示了3种具有不同临床结局及调控生物学通路的GTMEI分型。我们开发了GTMEIscore评分系统，用于判定单个肿瘤的免疫浸润模式。本研究全面分析了与GTMEIscore相关的基因组特征、分子亚型、临床病理特征，以及蛋白质组、磷酸化蛋白质组、乙酰化蛋白质组、脂质组和代谢组学特征，进而揭示了GBM中多条新的失调通路及精准治疗靶点。此外，GTMEIscore可准确量化多种其他癌症类型的免疫状态。临床研究表明，GTMEIscore在化疗/放疗、免疫检查点抑制剂（immune checkpoint inhibitor, ICI）治疗及靶向治疗中均具有显著的潜在治疗指导价值。

**结论**
本研究首次采用多维度、多平台策略，构建了不同免疫浸润模式肿瘤的多维分子图谱。本研究结果可为GBM更有效的预测性生物标志物的筛选，以及更优化的药物联合策略或新型免疫治疗药物的开发提供理论依据。