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RNA-seq data from 27 glioblastoma samples

ABSTRACT: 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 GBMÃ¢Â€Â™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.

PROVIDER: EGAS00001005807 | EGA |

REPOSITORIES: EGA

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