背景 。肿瘤、免疫和血管生态位之间的相互作用在驱动胶质母细胞瘤 (GBM) 恶性肿瘤和治疗反应中发挥着重要作用。然而，介导这种相互作用的细胞外核心基质蛋白（CMP）的组成、异质性和定位尚不清楚。方法 。在这里，通过计算基因组学和蛋白质组学方法，我们以批量、单细胞和空间解剖分辨率分析了 GBM 中 CMP 表达的功能和临床相关性。结果 。我们鉴定了编码 CMP 的基因，其表达水平将 GBM 肿瘤分为 CMP 高表达 (M-H) 和 CMP 低表达 (M-L) 组。 CMP 富集与患者生存率较差、特定驱动致癌改变、间充质状态、促肿瘤免疫细胞浸润和免疫检查点基因表达相关。解剖学和单细胞转录组分析表明，基质体基因表达在血管和前缘/浸润生态位中丰富，这些生态位已知含有驱动 GBM 进展的神经胶质瘤干细胞。最后，我们鉴定了一个 17 基因 CMP 表达特征，称为 Matrisome 17 (M17) 特征，进一步完善了 CMP 基因的预后价值。与 MGMT 启动子甲基化状态以及典型亚型相比，M17 特征是一个明显更强的预后因素，而且重要的是，它可能预测对 PD1 阻断的反应。结论 。基质体基因表达特征通过生存和功能相关 GBM 生态位的潜在生物标志物提供了对 GBM 患者的稳健分层，这些生物标志物可以介导间充质免疫串扰。基于基质体概况的患者分层有助于治疗策略的选择和优化。

Background . Interactions among tumor, immune, and vascular niches play major roles in driving glioblastoma (GBM) malignancy and treatment responses. The composition, heterogeneity, and localization of extracellular core matrix proteins (CMPs) that mediate such interactions, however, are not well understood. Methods . Here, through computational genomics and proteomics approaches, we analyzed the functional and clinical relevance of CMP expression in GBM at bulk, single cell, and spatial anatomical resolution. Results . We identified genes encoding CMPs whose expression levels categorize GBM tumors into CMP expression-high (M-H) and CMP expression-low (M-L) groups. CMP enrichment is associated with worse patient survival, specific driver oncogenic alterations, mesenchymal state, infiltration of pro-tumor immune cells, and immune checkpoint gene expression. Anatomical and single-cell transcriptome analyses indicate that matrisome gene expression is enriched in vascular and leading edge/infiltrative niches that are known to harbor glioma stem cells driving GBM progression. Finally, we identified a 17-gene CMP expression signature, termed Matrisome 17 (M17) signature that further refines the prognostic value of CMP genes. The M17 signature is a significantly stronger prognostic factor compared to MGMT promoter methylation status as well as canonical subtypes, and importantly, potentially predicts responses to PD1 blockade. Conclusion . The matrisome gene expression signature provides a robust stratification of GBM patients by survival and potential biomarkers of functionally relevant GBM niches that can mediate mesenchymal-immune cross talk. Patient stratification based on matrisome profiles can contribute to selection and optimization of treatment strategies.