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Record W2550669964 · doi:10.1002/1873-3468.12496

Both bulk and cancer stem cell subpopulations in triple‐negative breast cancer are susceptible to Wnt, <scp>HDAC</scp>, and <scp>ER</scp>α coinhibition

2016· article· en· W2550669964 on OpenAlexafffund
Andrew Sulaiman, Brandon Sulaiman, Lara Khouri, Sarah McGarry, Carolyn Nessim, Angel Arnaout, Xuguang Li, Christina Addison, Jim Dimitroulakos, Lisheng Wang

Bibliographic record

VenueFEBS Letters · 2016
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsOttawa HospitalOntario Institute for Cancer ResearchHealth CanadaUniversity of Ottawa
FundersCanadian Institutes of Health ResearchCanadian Cancer Society
KeywordsTriple-negative breast cancerWnt signaling pathwayCancer researchBreast cancerCancer stem cellEstrogen receptorPsychological repressionHistone deacetylaseProgesterone receptorCancerStem cellBiologyHistoneChemistryInternal medicineMedicineSignal transductionCell biologyGene expressionGeneticsGene

Abstract

fetched live from OpenAlex

Development of targeted therapies for triple-negative breast cancer (TNBC, a more aggressive subtype) is an unmet medical need. We analyzed data from 887 patients with invasive breast cancer and observed that increased Wnt and histone deacetylase (HDAC) activities are associated with estrogen receptor 1 (ESR1) and progesterone receptor (PGR) repression, poor survival, and increased relapse. The inverse correlation between Wnt signaling and repression of ESR1 and PGR expression was found to be magnified in cancer stem cell (CSC) subpopulations in TNBC cell lines. Cosuppression of Wnt, HDAC, and ESR1 using clinically relevant low-dose inhibitors effectively repressed both bulk and CSC subpopulations and converted CSCs to non-CSCs in TNBC cells without affecting MCF-10A mammary epithelial cells.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.512
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.017
GPT teacher head0.256
Teacher spread0.239 · 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.

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

Citations30
Published2016
Admission routes2
Has abstractyes

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