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Record W2948545418 · doi:10.1038/s41467-019-10307-9

Neuronal differentiation and cell-cycle programs mediate response to BET-bromodomain inhibition in MYC-driven medulloblastoma

2019· article· en· W2948545418 on OpenAlexfundno aff
Pratiti Bandopadhayay, Federica Piccioni, Ryan O’Rourke, Patricia Ho, Elizabeth M. Gonzalez, Graham Buchan, Kenin Qian, Gabrielle Gionet, Emily J. Girard, Margo Coxon, Matthew G. Rees, Lisa Brenan, Frank Dubois, Ofer Shapira, Noah F. Greenwald, Mélanie Pagès, Amanda Balboni Iniguez, Brenton R. Paolella, Alice Meng, Claire Sinai, Giovanni Roti, Neekesh V. Dharia, Amanda L. Creech, Benjamin Tanenbaum, Prasidda Khadka, Adam Tracy, Hong L. Tiv, Andrew L. Hong, Shannon Coy, Rumana Rashid, Jia‐Ren Lin, Glenn S. Cowley, Fred C. Lam, Amy Goodale, Yenarae Lee, Kathleen Schoolcraft, Francisca Vázquez, William C. Hahn, Aviad Tsherniak, James E. Bradner, Michael B. Yaffe, Till Milde, Stefan M. Pfister, Jun Qi, Monica Schenone, Steven A. Carr, Keith L. Ligon, Mark W. Kieran, Sandro Santagata, James M. Olson, Prafulla C. Gokhale, Jacob D. Jaffe, David E. Root, Kimberly Stegmaier, Cory M. Johannessen, Rameen Beroukhim

Bibliographic record

VenueNature Communications · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Degradation and Inhibitors
Canadian institutionsnot available
FundersNational Cancer InstituteNational Institutes of HealthBroad InstitutePediatric Brain Tumor FoundationDana-Farber/Harvard Cancer CenterAlex's Lemonade Stand Foundation for Childhood CancerNational Institute of Neurological Disorders and StrokeHannah's Heroes FoundationDamon Runyon Cancer Research Foundation
KeywordsBromodomainBiologyBET inhibitorCyclin-dependent kinase 6MedulloblastomaCell cycleTranscription factorCancer researchCell biologyGeneticsComputational biologyGeneEpigeneticsCyclin

Abstract

fetched live from OpenAlex

BET-bromodomain inhibition (BETi) has shown pre-clinical promise for MYC-amplified medulloblastoma. However, the mechanisms for its action, and ultimately for resistance, have not been fully defined. Here, using a combination of expression profiling, genome-scale CRISPR/Cas9-mediated loss of function and ORF/cDNA driven rescue screens, and cell-based models of spontaneous resistance, we identify bHLH/homeobox transcription factors and cell-cycle regulators as key genes mediating BETi's response and resistance. Cells that acquire drug tolerance exhibit a more neuronally differentiated cell-state and expression of lineage-specific bHLH/homeobox transcription factors. However, they do not terminally differentiate, maintain expression of CCND2, and continue to cycle through S-phase. Moreover, CDK4/CDK6 inhibition delays acquisition of resistance. Therefore, our data provide insights about the mechanisms underlying BETi effects and the appearance of resistance and support the therapeutic use of combined cell-cycle inhibitors with BETi in MYC-amplified medulloblastoma.

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 score0.498
Threshold uncertainty score0.487

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 head0.006
GPT teacher head0.246
Teacher spread0.240 · 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

Citations60
Published2019
Admission routes1
Has abstractyes

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