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Record W2016100326 · doi:10.1084/jem.20121484

Notch pathway activation targets AML-initiating cell homeostasis and differentiation

2013· article· en· W2016100326 on OpenAlexfundno aff
Camille Lobry, Panagiotis Ntziachristos, Delphine Ndiaye‐Lobry, Philmo Oh, Luisa Cimmino, Nan Zhu, Elisa Araldi, Wenhuo Hu, Jacquelyn Freund, Omar Abdel‐Wahab, Sherif Ibrahim, Dimitris Skokos, Scott A. Armstrong, Ross L. Levine, Christopher Y. Park, Iannis Aifantis

Bibliographic record

VenueThe Journal of Experimental Medicine · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHistone Deacetylase Inhibitors Research
Canadian institutionsnot available
FundersNational Institute of General Medical SciencesNational Cancer InstituteNational Institutes of HealthIrma T. Hirschl TrustYork UniversityHoward Hughes Medical Institute
KeywordsNotch signaling pathwayCancer researchCyclin-dependent kinase 8Myeloid leukemiaBiologyHes3 signaling axisMyeloidLeukemiaSignal transductionNotch proteinsCellular differentiationCell biologyImmunologyGeneticsGene

Abstract

fetched live from OpenAlex

Notch signaling pathway activation is known to contribute to the pathogenesis of a spectrum of human malignancies, including T cell leukemia. However, recent studies have implicated the Notch pathway as a tumor suppressor in myeloproliferative neoplasms and several solid tumors. Here we report a novel tumor suppressor role for Notch signaling in acute myeloid leukemia (AML) and demonstrate that Notch pathway activation could represent a therapeutic strategy in this disease. We show that Notch signaling is silenced in human AML samples, as well as in AML-initiating cells in an animal model of the disease. In vivo activation of Notch signaling using genetic Notch gain of function models or in vitro using synthetic Notch ligand induces rapid cell cycle arrest, differentiation, and apoptosis of AML-initiating cells. Moreover, we demonstrate that Notch inactivation cooperates in vivo with loss of the myeloid tumor suppressor Tet2 to induce AML-like disease. These data demonstrate a novel tumor suppressor role for Notch signaling in AML and elucidate the potential therapeutic use of Notch receptor agonists in the treatment of this devastating leukemia.

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 score0.005
Threshold uncertainty score0.230

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 head0.013
GPT teacher head0.276
Teacher spread0.262 · 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

Citations153
Published2013
Admission routes1
Has abstractyes

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