RNA-seq data from 27 glioblastoma samples

Glioblastoma (GBM) is an aggressive form of brain cancer with well-established patterns of intra-tumoral heterogeneity implicated in treatment resistance and progression. While regional and single cell transcriptomic variations of GBM have been recently resolved, downstream phenotype-level proteomic programs have yet to be assigned to specific niches. Here, we leverage mass spectrometry to spatially align abundance levels of 4,794 proteins to GBM’s hallmark histomorphologic niches across 20 patients and define distinct molecular programs operational within these regional tumor compartments. Using machine learning, we overlay concordant transcriptional information, and define two distinct proteogenomic programs, MYC- and KRAS-axis hereon, that cooperate with hypoxia to produce a tri-dimensional model of intra-tumoral heterogeneity. Moreover, we highlight differential drug sensitivities and relative chemoresistance in GBM cell lines with enhanced KRAS programs. Importantly, pharmacological differences were less evident in transcriptional subgroups suggesting the proposed model may provide insights for targeting heterogeneity and overcoming therapy resistance in glioblastoma.EGA study EGAS00001005807

胶质母细胞瘤（Glioblastoma, GBM）是一种侵袭性极强的原发性脑恶性肿瘤，其公认的瘤内异质性模式与治疗抵抗及疾病进展密切相关。尽管近期研究已阐明胶质母细胞瘤的区域转录组与单细胞转录组变异特征，但下游表型层面的蛋白质组程序仍未被归属于特定的瘤内微区。本研究借助质谱分析法，将20例胶质母细胞瘤患者体内4794种蛋白质的丰度水平与该疾病标志性组织形态学微区进行空间匹配，并明确了这些区域肿瘤区室中活跃的独特分子程序。本研究通过机器学习整合匹配的转录组信息，定义了两类截然不同的蛋白质基因组程序——下文统称为MYC通路与KRAS通路，二者与缺氧信号协同作用，构建出瘤内异质性的三维模型。此外，本研究还发现，KRAS通路活化的胶质母细胞瘤细胞系呈现出差异化的药物敏感性与相对化疗抵抗特性。值得注意的是，转录组亚型间的药理学差异并不显著，这提示本研究提出的模型可为靶向胶质母细胞瘤异质性、克服治疗抵抗提供全新思路。EGA研究编号：EGAS00001005807