MétaCan
Menu
Back to cohort
Record W2299942500 · doi:10.1016/j.celrep.2016.02.074

NPM and BRG1 Mediate Transcriptional Resistance to Retinoic Acid in Acute Promyelocytic Leukemia

2016· article· en· W2299942500 on OpenAlexafffund
Jessica N. Nichol, Matthew D. Galbraith, Claudia L. Kleinman, Joaquı́n M. Espinosa, Wilson H. Miller

Bibliographic record

VenueCell Reports · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinoids in leukemia and cellular processes
Canadian institutionsMcGill UniversityJewish General Hospital
FundersNational Cancer InstituteCanadian Institutes of Health ResearchCold Spring Harbor LaboratoryNational Institutes of HealthWarren H. and Clara Cole Foundation
KeywordsAcute promyelocytic leukemiaChromatinBiologyRetinoic acidCancer researchSMARCA4Chromatin remodelingLeukemiaTranscription factorCell biologyGeneticsMolecular biologyGene

Abstract

fetched live from OpenAlex

Perturbation in the transcriptional control of genes driving differentiation is an established paradigm whereby oncogenic fusion proteins promote leukemia. From a retinoic acid (RA)-sensitive acute promyelocytic leukemia (APL) cell line, we derived an RA-resistant clone characterized by a block in transcription initiation, despite maintaining wild-type PML/RARA expression. We uncovered an aberrant interaction among PML/RARA, nucleophosmin (NPM), and topoisomerase II beta (TOP2B). Surprisingly, RA stimulation in these cells results in enhanced chromatin association of the nucleosome remodeler BRG1. Inhibition of NPM or TOP2B abrogated BRG1 recruitment. Furthermore, NPM inhibition and targeting BRG1 restored differentiation when combined with RA. Here, we demonstrate a role for NPM and BRG1 in obstructing RA differentiation and implicate chromatin remodeling in mediating therapeutic resistance in malignancies. NPM mutations are the most common genetic change in patients with acute leukemia (AML); therefore, our model may be applicable to other more common leukemias driven by NPM.

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 score0.050
Threshold uncertainty score0.573

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 head0.005
GPT teacher head0.213
Teacher spread0.208 · 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

Citations16
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueCell ReportsSame topicRetinoids in leukemia and cellular processesFrench-language works237,207