BioMediTech Institute and Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland.
Science Center, Tampere University Hospital, Tampere, Finland.
Cancer Res. 2018 Oct 1;78(19):5574-5585. doi: 10.1158/0008-5472.CAN-17-3714. Epub 2018 Jun 19.
The immunosuppressive microenvironment in glioblastoma (GBM) prevents an efficient antitumoral immune response and enables tumor formation and growth. Although an understanding of the nature of immunosuppression is still largely lacking, it is important for successful cancer treatment through immune system modulation. To gain insight into immunosuppression in GBM, we performed a computational analysis to model relative immune cell content and type of immune response in each GBM tumor sample from The Cancer Genome Atlas RNA-seq data set. We uncovered high variability in immune system-related responses and in the composition of the microenvironment across the cohort, suggesting immunologic diversity. Immune cell compositions were associated with typical alterations such as IDH mutation or inactivating NF1 mutation/deletion. Furthermore, our analysis identified three GBM subgroups presenting different adaptive immune responses: negative, humoral, and cellular-like. These subgroups were linked to transcriptional GBM subtypes and typical genetic alterations. All G-CIMP and IDH-mutated samples were in the negative group, which was also enriched by cases with focal amplification of CDK4 and MARCH9. IDH1-mutated samples showed lower expression and higher DNA methylation of MHC-I-type HLA genes. Overall, our analysis reveals heterogeneity in the immune microenvironment of GBM and identifies new markers for immunosuppression. Characterization of diverse immune responses will facilitate patient stratification and improve personalized immunotherapy in the future. This study utilizes a computational approach to characterize the immune environments in glioblastoma and shows that glioblastoma immune microenvironments can be classified into three major subgroups, which are linked to typical glioblastoma alterations such as IDH mutation, NF1 inactivation, and CDK4-MARCH9 locus amplification. http://cancerres.aacrjournals.org/content/canres/78/19/5574/F1.large.jpg .
胶质母细胞瘤（GBM）中的免疫抑制微环境阻止了有效的抗肿瘤免疫反应，从而促进了肿瘤的形成和生长。尽管对免疫抑制的本质仍缺乏深入了解，但通过免疫系统调节来成功治疗癌症仍然非常重要。为了深入了解 GBM 中的免疫抑制，我们对来自癌症基因组图谱 RNA-seq 数据集中的每个 GBM 肿瘤样本进行了计算分析，以模拟相对免疫细胞含量和免疫反应类型。我们发现，整个队列中免疫相关反应和微环境组成存在高度变异性，表明存在免疫多样性。免疫细胞组成与典型改变相关，如 IDH 突变或失活的 NF1 突变/缺失。此外，我们的分析还确定了三个具有不同适应性免疫反应的 GBM 亚组：阴性、体液和细胞样。这些亚组与转录组学 GBM 亚型和典型遗传改变相关。所有 G-CIMP 和 IDH 突变的样本均属于阴性组，该组还富集了 CDK4 和 MARCH9 的局灶性扩增病例。IDH1 突变的样本显示 MHC-I 类 HLA 基因的表达降低和 DNA 甲基化水平升高。总体而言，我们的分析揭示了 GBM 免疫微环境的异质性，并确定了新的免疫抑制标志物。对不同免疫反应的特征描述将有助于未来患者分层和个性化免疫治疗的改善。本研究利用计算方法对胶质母细胞瘤的免疫环境进行了特征描述，结果表明胶质母细胞瘤的免疫微环境可以分为三个主要亚组，这与 IDH 突变、NF1 失活和 CDK4-MARCH9 基因座扩增等典型胶质母细胞瘤改变相关。
