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Engineering Genetic Predisposition in Human Neuroepithelial Stem Cells Recapitulates Medulloblastoma Tumorigenesis.

Miller Huang | Jignesh Tailor | Qiqi Zhen | Aaron H Gillmor | Matthew L Miller | Holger Weishaupt | Justin Chen | Tina Zheng | Emily K Nash | Lauren K McHenry | Zhenyi An | Fubaiyang Ye | Yasuhiro Takashima | James Clarke | Harold Ayetey | Florence M G Cavalli | Betty Luu | Branden S Moriarity | Shirin Ilkhanizadeh | Lukas Chavez | Chunying Yu | Kathreena M Kurian | Thierry Magnaldo | Nicolas Sevenet | Philipp Koch | Steven M Pollard | Peter Dirks | Michael P Snyder | David A Largaespada | Yoon Jae Cho | Joanna J Phillips | Fredrik J Swartling | A Sorana Morrissy | Marcel Kool | Stefan M Pfister | Michael D Taylor | Austin Smith | William A Weiss
Cell stem cell | 2019

Human neural stem cell cultures provide progenitor cells that are potential cells of origin for brain cancers. However, the extent to which genetic predisposition to tumor formation can be faithfully captured in stem cell lines is uncertain. Here, we evaluated neuroepithelial stem (NES) cells, representative of cerebellar progenitors. We transduced NES cells with MYCN, observing medulloblastoma upon orthotopic implantation in mice. Significantly, transcriptomes and patterns of DNA methylation from xenograft tumors were globally more representative of human medulloblastoma compared to a MYCN-driven genetically engineered mouse model. Orthotopic transplantation of NES cells generated from Gorlin syndrome patients, who are predisposed to medulloblastoma due to germline-mutated PTCH1, also generated medulloblastoma. We engineered candidate cooperating mutations in Gorlin NES cells, with mutation of DDX3X or loss of GSE1 both accelerating tumorigenesis. These findings demonstrate that human NES cells provide a potent experimental resource for dissecting genetic causation in medulloblastoma.

Pubmed ID: 31204176

Research resources used in this publication

None found

Associated grants

  • Agency: Medical Research Council, United Kingdom
    Id: G1100526
  • Agency: NIGMS NIH HHS, United States
    Id: T32 GM007618
  • Agency: Department of Health, United Kingdom
  • Agency: NCI NIH HHS, United States
    Id: P30 CA082103
  • Agency: NCI NIH HHS, United States
    Id: K99 CA197484
  • Agency: NCI NIH HHS, United States
    Id: P50 CA097257
  • Agency: NINDS NIH HHS, United States
    Id: R01 NS089868
  • Agency: Wellcome Trust, United Kingdom
  • Agency: Wellcome Trust, United Kingdom
    Id: 201511/Z/16/Z
  • Agency: NINDS NIH HHS, United States
    Id: R01 NS106155
  • Agency: NCI NIH HHS, United States
    Id: R01 CA159859
  • Agency: NCI NIH HHS, United States
    Id: U01 CA217864
  • Agency: Medical Research Council, United Kingdom
    Id: G1001028

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This is a list of tools and resources that we have found mentioned in this publication.


SAMTOOLS (tool)

RRID:SCR_002105

Original SAMTOOLS package has been split into three separate repositories including Samtools, BCFtools and HTSlib. Samtools for manipulating next generation sequencing data used for reading, writing, editing, indexing,viewing nucleotide alignments in SAM,BAM,CRAM format. BCFtools used for reading, writing BCF2,VCF, gVCF files and calling, filtering, summarising SNP and short indel sequence variants. HTSlib used for reading, writing high throughput sequencing data.

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GENEWIZ (tool)

RRID:SCR_003177

Commercial organization for research and development genomics services and technical support to researchers.

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Systems Transcriptional Activity Reconstruction (tool)

RRID:SCR_005622

A next-generation web-based application that aims to provide an integrated solution for both visualization and analysis of deep-sequencing data, along with simple access to public datasets.

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Bioconductor (tool)

RRID:SCR_006442

Software repository for R packages related to analysis and comprehension of high throughput genomic data. Uses separate set of commands for installation of packages. Software project based on R programming language that provides tools for analysis and comprehension of high throughput genomic data.

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Picard (tool)

RRID:SCR_006525

Java toolset for working with next generation sequencing data in the BAM format.

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IARC TP53 Database (tool)

RRID:SCR_007731

The IARC TP53 Mutation Database compiles all TP53 gene variations identified in human populations and tumor samples. Data are compiled from the peer-reviewed literature and from generalist databases. The following datasets are available: # TP53 somatic mutations in sporadic cancers # TP53 germline mutation in familial cancers # Common TP53 polymorphisms identified in human populations # Functional and structural properties of P53 mutant proteins # TP53 gene status in human cell-lines # Mouse-models with engineered TP53 The database includes various annotations on the predicted or experimentally assessed functional impact of mutations, clinicopathologic characteristics of tumors and demographic and life-style information on patients. The database is meant to be a source of information on TP53 mutations for a broad range of scientists and clinicians who work in different research areas: # Basic research, to study the structural and functional aspects of the p53 protein # Molecular pathology of cancer, to understand the clinical significance of mutations identified in cancer patients # Molecular epidemiology of cancer, to analyze the links between specific exposures and mutation patterns and to make inferences about possible causes of cancer # Molecular genetics, to analyze genotype/phenotype relationships

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1000 Genomes Project and AWS (tool)

RRID:SCR_008801

A dataset containing the full genomic sequence of 1,700 individuals, freely available for research use. The 1000 Genomes Project is an international research effort coordinated by a consortium of 75 companies and organizations to establish the most detailed catalogue of human genetic variation. The project has grown to 200 terabytes of genomic data including DNA sequenced from more than 1,700 individuals that researchers can now access on AWS for use in disease research free of charge. The dataset containing the full genomic sequence of 1,700 individuals is now available to all via Amazon S3. The data can be found at: http://s3.amazonaws.com/1000genomes The 1000 Genomes Project aims to include the genomes of more than 2,662 individuals from 26 populations around the world, and the NIH will continue to add the remaining genome samples to the data collection this year. Public Data Sets on AWS provide a centralized repository of public data hosted on Amazon Simple Storage Service (Amazon S3). The data can be seamlessly accessed from AWS services such Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Elastic MapReduce (Amazon EMR), which provide organizations with the highly scalable compute resources needed to take advantage of these large data collections. AWS is storing the public data sets at no charge to the community. Researchers pay only for the additional AWS resources they need for further processing or analysis of the data. All 200 TB of the latest 1000 Genomes Project data is available in a publicly available Amazon S3 bucket. You can access the data via simple HTTP requests, or take advantage of the AWS SDKs in languages such as Ruby, Java, Python, .NET and PHP. Researchers can use the Amazon EC2 utility computing service to dive into this data without the usual capital investment required to work with data at this scale. AWS also provides a number of orchestration and automation services to help teams make their research available to others to remix and reuse. Making the data available via a bucket in Amazon S3 also means that customers can crunch the information using Hadoop via Amazon Elastic MapReduce, and take advantage of the growing collection of tools for running bioinformatics job flows, such as CloudBurst and Crossbow.

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featureCounts (tool)

RRID:SCR_012919

A read summarization program, which counts mapped reads for the genomic features such as genes and exons.

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GENCODE (tool)

RRID:SCR_014966

Human and mouse genome annotation project which aims to identify all gene features in the human genome using computational analysis, manual annotation, and experimental validation.

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DESeq2 (tool)

RRID:SCR_015687

Software package for differential gene expression analysis based on the negative binomial distribution. Used for analyzing RNA-seq data for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates.

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BD FACSAria II Cell Sorter (tool)

RRID:SCR_018934

Cell sorter features hardware and software enhancements that improve overall ease of use, flexibility,and aseptic capability. Offers new options in lasers and nozzles to support more advanced multicolor applications. Built on fixed alignment technology. FACSAria II cell sorter is first generation of BD FACSAria system where flow cell is in true fixed alignment with laser, to reduce startup time and improve reproducibility.

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biomaRt (tool)

RRID:SCR_019214

Software package that integrates BioMart data resources with data analysis software in Bioconductor. Can annotate range of gene or gene product identifiers including Entrez Gene and Affymetrix probe identifiers with information such as gene symbol, chromosomal coordinates, Gene Ontology and OMIM annotation. Enables retrieval of genomic sequences and single nucleotide polymorphism information, which can be used in data analysis.

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Synaptophysin Monoclonal Antibody (SP11) (antibody)

RRID:AB_10983675

This monoclonal targets Synaptophysin

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Human Nanog Antibody (antibody)

RRID:AB_355097

This polyclonal targets Nanog

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PAX6 antibody (antibody)

RRID:AB_2159695

This polyclonal targets PAX6

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p53 Tumor Suppressor Protein (antibody)

RRID:AB_2206626

This monoclonal targets Recombinant human wild-type p53 protein (1).

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Human Nestin MAb (Clone 196908) (antibody)

RRID:AB_2251304

This monoclonal targets Human Nestin MAb (Clone 196908)

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Oct3/4 Antibody (C-10) (antibody)

RRID:AB_628051

This monoclonal targets Oct-3/4

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