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Record W2001566685 · doi:10.1182/blood-2008-02-139212

Constitutive activation of the Wnt canonical pathway in mantle cell lymphoma

2008· article· en· W2001566685 on OpenAlexafffund
Pascal Gélébart, Mona Anand, Hanan Armanious, Anthea Peters, Jennifer Dien Bard, Hesham M. Amin, Raymond Lai

Bibliographic record

VenueBlood · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicWnt/β-catenin signaling in development and cancer
Canadian institutionsUniversity of Alberta
FundersNational Cancer InstituteUniversity of Alberta
KeywordsWnt signaling pathwayMantle cell lymphomaCarcinogenesisCancer researchBiologyCell cultureSignal transductionTranscription factorCellMolecular biologyCell biologyChemistryLymphomaGeneGeneticsImmunology

Abstract

fetched live from OpenAlex

Aberrations of the Wnt canonical pathway (WCP) are known to contribute to the pathogenesis of various types of cancer. We hypothesize that these defects may exist in mantle cell lymphoma (MCL). Both the upstream and downstream aspects of WCP were examined in MCL cell lines and tumors. Using WCP-specific oligonucleotide arrays, we found that MCL highly and consistently expressed Wnt3 and Wnt10. beta-catenin, a transcriptional factor that is a downstream target of WCP, is localized to the nucleus and transcriptionally active in all 3 MCL cell lines examined. By immunohistochemistry, 33 (52%) of 64 MCL tumors showed nuclear localization of beta-catenin, which significantly correlated with the expression of the phosphorylated/inactive form of GSK3beta (p-GSK3beta; P = .011, Fisher). GSK3beta inactivation is directly linked to WCP stimulation, since addition of recombinant sFRP proteins (a naturally occurring decoy for the Wnt receptors) resulted in a significant decrease in p-GSK3beta. Down-regulation of DvL-2 (an upstream signaling protein in WCP) by siRNA or selective inhibition of beta-catenin using quercetin significantly decreased cell growth in MCL cell lines. To conclude, WCP is constitutively activated in a subset of MCL and it appears to promote tumorigenesis in MCL.

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 score0.010
Threshold uncertainty score0.181

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 head0.010
GPT teacher head0.199
Teacher spread0.190 · 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

Citations99
Published2008
Admission routes2
Has abstractyes

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