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Record W2046855348 · doi:10.1074/jbc.m112.430934

MicroRNA-584 and the Protein Phosphatase and Actin Regulator 1 (PHACTR1), a New Signaling Route through Which Transforming Growth Factor-β Mediates the Migration and Actin Dynamics of Breast Cancer Cells

2013· article· en· W2046855348 on OpenAlexafffund
Nadège Fils-Aimé, Meiou Dai, Jimin Guo, Mayada El-Mousawi, Bora Kahramangil, Jean-Charles Neel, Jean‐Jacques Lebrun

Bibliographic record

VenueJournal of Biological Chemistry · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsMcGill UniversityRoyal Victoria Hospital
FundersCanadian Institutes of Health ResearchMcGill University
KeywordsBiologymicroRNACell biologyCell migrationActinGene knockdownCancer cellTransforming growth factorRegulatorActin cytoskeletonCancer researchCytoskeletonCellCancerCell cultureGeneticsGene

Abstract

fetched live from OpenAlex

TGF-β plays an important role in breast cancer progression as a prometastatic factor, notably through enhancement of cell migration. It is becoming clear that microRNAs, a new class of small regulatory molecules, also play crucial roles in mediating tumor formation and progression. We found TGF-β to down-regulate the expression of the microRNA miR-584 in breast cancer cells. Furthermore, we identified PHACTR1, an actin-binding protein, to be positively regulated by TGF-β in a miR-584-dependent manner. Moreover, we found TGF-β-mediated down-regulation of miR-584 and increased expression of PHACTR1 to be required for TGF-β-induced cell migration of breast cancer cells. Indeed, both overexpression of miR-584 and knockdown of PHACTR1 resulted in a drastic reorganization of the actin cytoskeleton and reduced TGF-β-induced cell migration. Our data highlight a novel signaling route whereby TGF-β silences the expression of miR-584, resulting in enhanced PHACTR1 expression, and further leading to actin rearrangement and breast cancer cell migration.

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 score0.006
Threshold uncertainty score0.380

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 head0.008
GPT teacher head0.223
Teacher spread0.215 · 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

Citations77
Published2013
Admission routes2
Has abstractyes

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