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Record W2598983248 · doi:10.1038/cddis.2017.92

Kaiso depletion attenuates the growth and survival of triple negative breast cancer cells

2017· article· en· W2598983248 on OpenAlexafffund
Blessing Bassey‐Archibong, Lyndsay G. A. Rayner, Shawn M. Hercules, Craig Aarts, Anna Dvorkin‐Gheva, Jonathan L. Bramson, John A. Hassell, Juliet M. Daniel

Bibliographic record

VenueCell Death and Disease · 2017
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaCure Brain Cancer Foundation
KeywordsTriple-negative breast cancerCancer researchBreast cancerApoptosisCell growthTranscription factorCancerMedicineBiologyInternal medicine

Abstract

fetched live from OpenAlex

Triple negative breast cancers (TNBC) are highly aggressive and lack specific targeted therapies. Recent studies have reported high expression of the transcription factor Kaiso in triple negative tumors, and this correlates with their increased aggressiveness. However, little is known about the clinical relevance of Kaiso in the growth and survival of TNBCs. Herein, we report that Kaiso depletion attenuates TNBC cell proliferation, and delays tumor onset in mice xenografted with the aggressive MDA-231 breast tumor cells. We further demonstrate that Kaiso depletion attenuates the survival of TNBC cells and increases their propensity for apoptotic-mediated cell death. Notably, Kaiso depletion downregulates BRCA1 expression in TNBC cells expressing mutant-p53 and we found that high Kaiso and BRCA1 expression correlates with a poor overall survival in breast cancer patients. Collectively, our findings reveal a role for Kaiso in the proliferation and survival of TNBC cells, and suggest a relevant role for Kaiso in the prognosis and treatment of TNBCs.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.214
Threshold uncertainty score0.315

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 head0.249
Teacher spread0.236 · 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 designObservational
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

Citations34
Published2017
Admission routes2
Has abstractyes

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