低级别胶质瘤（LGG）被认为是一种异质性肿瘤，生存期高度可变，并且免疫治疗的疗效有限。为了有效识别高风险亚群并应用免疫治疗于LGG，必须探索胶质瘤微环境中免疫浸润的状态和功能。本研究纳入了1853名患者组成的四个独立胶质瘤队列进行生物信息学分析。我们使用ConsensusClusterPlus将患者根据免疫浸润分为四种不同的免疫亚型。利用LASSO回归分析构建了免疫浸润特征签名（IIS）。进行体细胞突变和拷贝数变异（CNV）分析，探索高风险和低风险组的基因组和转录组特征。在体胶质瘤模型中确认了IIS风险评分与程序性细胞凋亡1（PD-1）阻滞反应之间的相关性。 根据免疫浸润，将患者分为四种不同的免疫亚型，其中高免疫浸润亚型与LGG的生存率较差相关。高免疫浸润亚型表现出更强的炎症反应、免疫反应和免疫细胞趋化。IIS由EMP3、IQGAP2、METTL7B、SLC1A6和TNFRSF11B组成，可预测LGG的恶性进展，并得到内部临床样本的验证。M2巨噬细胞浸润与IIS风险评分呈正相关。高风险组存在更多的体细胞突变和CNV。IIS风险评分与免疫调节因子相关，并可预测免疫治疗的临床效果。在体内，对于免疫治疗敏感的胶质瘤模型表现出更高的IIS风险评分和更多的免疫细胞浸润，尤其是M2巨噬细胞。经抗PD-1免疫治疗后，免疫治疗敏感的胶质瘤模型的IIS风险评分降低。 LGG的不同免疫亚型具有独特的免疫细胞浸润特征，高免疫浸润亚型与免疫抑制信号通路相关。基于免疫浸润状态构建了一种新型的IIS预后模型，用于LGG的免疫表型分类、风险分层、预后和免疫治疗反应预测。©2023 BioMed Central有限公司，Springer Nature的一部分。

Low grade glioma (LGG) is considered a heterogeneous tumor with highly variable survival and limited efficacy of immunotherapy. To identify high-risk subsets and apply immunotherapy effectively in LGG, the status and function of immune infiltration in the glioma microenvironment must be explored.Four independent glioma cohorts comprising 1,853 patients were enrolled for bioinformatics analysis. We used ConsensusClusterPlus to cluster patients into four different immune subtypes based on immune infiltration. The immune-infiltration signature (IIS) was constructed by LASSO regression analysis. Somatic mutation and copy number variation (CNV) analyses were performed to explore genomic and transcriptomic traits in the high- and low- risk groups. The correlation between response to programmed cell death 1 (PD-1) blockade and the IIS risk score was confirmed in an in vivo glioma model.Patients were clustered into four different immune subtypes based on immune infiltration, and the high immune infiltration subtype was associated with worse survival in LGG. The high immune infiltration subtype had stronger inflammatory response, immune response and immune cell chemotaxis. The IIS, consisting of EMP3, IQGAP2, METTL7B, SLC1A6 and TNFRSF11B, could predict LGG malignant progression, which was validated with internal clinical samples. M2 macrophage infiltration positively correlated with the IIS risk score. The high-risk group had significantly more somatic mutations and CNVs. The IIS risk score was related to immunomodulatory molecules and could predict immunotherapy clinical benefit. In vivo, immunotherapy-sensitive glioma model exhibited higher IIS risk score and more infiltration of immune cells, especially M2 macrophages. The IIS risk score was decreased in an immunotherapy-sensitive glioma model after anti-PD1 immunotherapy.Different immune subtypes of LGG had unique immune cell infiltration characteristics, and the high immune infiltration subtype was associated with immunosuppressive signaling pathways. A novel IIS prognostic model based on immune infiltration status was constructed for immunophenotypic classification, risk stratification, prognostication and immunotherapy response prediction in LGG.© 2023. BioMed Central Ltd., part of Springer Nature.