Transcriptomics

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Functional genomic analysis of adult and pediatric brain tumor isolates


ABSTRACT: Despite in-depth knowledge of the molecular features and oncogenic drivers associated with adult and pediatric brain tumors, identifying effective targeted therapies for these cancers remains challenging. To identify novel gene dependencies in adult and pediatric brain tumor isolates, we integrated data from functional genomic lethality screens in primary brain tumor isolates with machine learning network models from lethality screens performed in >900 cancer cell lines. Integrated network models revealed molecular and phenotypic features that predict candidate genetic dependencies in multiple brain tumor types, including: atypical teratoid rhabdoid tumors, diffuse intrinsic pontine gliomas, ependymomas, medulloblastomas, and glioblastomas (primary and recurrent). Some examples of dependencies and predictors include: ADAR and MX1 protein expression; EFR3A and low EFR3B expression; FBXO42 and spindle assembly checkpoint activation; FGFR1 and high FGF2 expression; and SMARCC2 in SMARCB1 mutated ATRT tumors. In general, the results demonstrate that large functional genetic data sets can be leveraged to identify, validate, and categorize gene dependencies and their associated biomarkers in primary tumor isolates. The results also highlight some of the challenges and limitations of this approach.

ORGANISM(S): Homo sapiens

PROVIDER: GSE213269 | GEO | 2023/02/07

REPOSITORIES: GEO

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