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ABSTRACT: Investigation of genetic dependencies in atypical teratoid rhabdoid tumors

PROVIDER: PRJNA986706 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR25003557_1.fastq.gz	Fastqsanger.gz
	SRR25003557_2.fastq.gz	Fastqsanger.gz
	SRR25003558_1.fastq.gz	Fastqsanger.gz
	SRR25003558_2.fastq.gz	Fastqsanger.gz
	SRR25003559_1.fastq.gz	Fastqsanger.gz

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Investigation of genetic dependencies in atypical teratoid rhabdoid tumors

Project description:Investigation of genetic dependencies in atypical teratoid rhabdoid tumors

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Project description:Investigation of genetic dependencies in atypical teratoid rhabdoid tumors (ATRTs) [I]

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Investigation of genetic dependencies in atypical teratoid rhabdoid tumors (ATRTs) [II]

Project description:Investigation of genetic dependencies in atypical teratoid rhabdoid tumors (ATRTs) [II]

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DNA methylation data from 153 ATRT tumor samples

Project description:Clinical and molecular risk factors were analyzed in a large cohort of patients with Atypical Teratoid Rhabdoid Tumors (ATRT) recruited to the European Rhabdoid Regsitry (EU-RHAB) and data were validated in a second independent cohort of ATRT patients.

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RNA sequencing data from primary atypical teratoid rhabdoid tumor (ATRT) samples

Project description:Atypical teratoid/rhabdoid tumors (ATRTs) are very aggressive childhood malignancies of the central nervous system. The underlying genetic cause are inactivating bi-allelic mutations in SMARCB1 or (rarely) in SMARCA4. The purpose of this study was to compare the transcriptomes of ATRTs with SMARCA4 mutations to those carrying SMARCB1 mutations.

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Functional genomic analysis of adult and pediatric brain tumor isolates

Project description: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.

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Mouse Smarcb1-deficient models recapitulate subtypes of human rhabdoid tumors.

Project description:Rhabdoid Tumors (RT) are highly aggressive tumors that are frequently localized in the central nervous system (CNS) where they are termed atypical teratoid and rhabdoid tumors (ATRT). We generated conditional Smarcb1-deficient mouse model leads to CNS Smarcb1-deficient tumors. We used microarrays to compared gene expression profilings of various human and mouse tumors. Our data demonstrate that the Smarcb1-deficient mouse model recapitulates the diversity of human RT.

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DNA methylation data from 13 ATRT tumor samples

Project description:The samples deposited here are part of the ATRT consensus cohort as published in Ho et al. ("Molecular subgrouping of Atypical Teratoid/Rhabdoid Tumors (ATRT) - a reinvestigation and current consensus") and have so far not been included in any publication.

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Transcriptome analysis in medulloblastoma groups

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