Topographic mapping of the glioblastoma proteome reveals a triple-axis model of intra-tumoral heterogeneity.
Nat Commun
; 13(1): 116, 2022 01 10.
Article
em En
| MEDLINE
| ID: mdl-35013227
ABSTRACT
Glioblastoma 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 glioblastoma have been recently resolved, downstream phenotype-level proteomic programs have yet to be assigned across glioblastoma's hallmark histomorphologic niches. Here, we leverage mass spectrometry to spatially align abundance levels of 4,794 proteins to distinct histologic patterns across 20 patients and propose diverse 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 glioblastoma cell lines with enhanced KRAS programs. Importantly, these pharmacological differences are less pronounced in transcriptional glioblastoma subgroups suggesting that this model may provide insights for targeting heterogeneity and overcoming therapy resistance.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Neoplasias Encefálicas
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Proteínas Proto-Oncogênicas p21(ras)
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Proteínas Proto-Oncogênicas c-myc
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Glioblastoma
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Heterogeneidade Genética
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Hipóxia
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Proteínas de Neoplasias
Tipo de estudo:
Diagnostic_studies
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Etiology_studies
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Incidence_studies
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Observational_studies
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Prognostic_studies
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Risk_factors_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2022
Tipo de documento:
Article