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Record W2118416891 · doi:10.1093/carcin/bgu181

Synergistic effects of combined DNA methyltransferase inhibition and MBD2 depletion on breast cancer cells; MBD2 depletion blocks 5-aza-2ʹ-deoxycytidine-triggered invasiveness

2014· article· en· W2118416891 on OpenAlexafffund
David Cheishvili, Flora Chik, Chen Chen Li, Bishnu Bhattacharya, Matthew Suderman, Ani Arakelian, Michael Hallett, Shafaat A. Rabbani, Moshe Szyf

Bibliographic record

VenueCarcinogenesis · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsMcGill University Health CentreMcGill University
FundersCanadian Institutes of Health ResearchGlaxoSmithKline
KeywordsDNA methylationGene silencingMethyltransferaseCancer researchDNA methyltransferaseDNMT1MethylationChemistryCell growthBreast cancerCancer cellIn vitroBiologyDNACancerGeneGene expressionBiochemistryGenetics

Abstract

fetched live from OpenAlex

5-Aza-2'-deoxycytidine (5-azaCdR) not only inhibits growth of non-invasive breast cancer cells but also increases their invasiveness through induction of pro-metastatic genes. Methylated DNA binding protein 2 (MBD2) is involved in silencing methylated tumor suppressor genes as well as activation of pro-metastatic genes. In this study, we show that a combination of MBD2 depletion and DNA methyltransferases (DNMT) inhibition in breast cancer cells results in a combined effect in vitro and in vivo, enhancing tumor growth arrest on one hand, while inhibiting invasiveness triggered by 5-azaCdR on the other hand. The combined treatment of MBD2 depletion and 5-azaCdR suppresses and augments distinct gene networks that are induced by DNMT inhibition alone. These data point to a potential new approach in targeting the DNA methylation machinery by combination of MBD2 and DNMT inhibitors.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.006
GPT teacher head0.218
Teacher spread0.211 · 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 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

Citations25
Published2014
Admission routes2
Has abstractyes

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