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Record W2773618384 · doi:10.1016/j.celrep.2017.11.021

Convergence of BMI1 and CHD7 on ERK Signaling in Medulloblastoma

2017· article· en· W2773618384 on OpenAlexaff
Sara Badodi, Adrian M. Dubuc, Xinyu Zhang, Gabriel Rosser, Mariane da Cunha Jaeger, Michelle Kameda-Smith, Anca Sorana Morrissy, Paul Guilhamon, Philipp Suetterlin, Xiao‐Nan Li, Loredana Guglielmi, Ashirwad Merve, Hamza Farooq, Mathieu Lupien, Sheila K. Singh, M. Albert Basson, Michael D. Taylor, Silvia Marino

Bibliographic record

VenueCell Reports · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHedgehog Signaling Pathway Studies
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkUniversity of TorontoOntario Institute for Cancer ResearchMcMaster Children's HospitalHospital for Sick Children
FundersMedical Research CouncilBrain Tumour ResearchMinistério da EducaçãoNational Institute for Health and Care ResearchCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorPathological Society of Great Britain and Ireland
KeywordsBMI1MedulloblastomaPsychological repressionMAPK/ERK pathwayBiologyCancer researchConvergence (economics)ChromatinCell biologySignal transductionGeneticsGene expressionStem cellGene

Abstract

fetched live from OpenAlex

expression signature within medulloblastoma characterizes patients with poor overall survival. We show that BMI1-mediated repression of the ERK1/2 pathway leads to increased proliferation and tumor burden in primary human MB cells and in a xenograft model, respectively. We provide evidence that repression of the ERK inhibitor DUSP4 by BMI1 is dependent on a more accessible chromatin configuration in G4 MB cells with low CHD7 expression. These findings extend current knowledge of the role of BMI1 and CHD7 in medulloblastoma pathogenesis, and they raise the possibility that pharmacological targeting of BMI1 or ERK may be particularly indicated in a subgroup of MB with low expression levels of CHD7.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.390

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.256
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations39
Published2017
Admission routes1
Has abstractyes

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