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Record W2771661958 · doi:10.1093/carcin/bgx134

MicroRNA-128-3p-mediated depletion of Drosha promotes lung cancer cell migration

2017· article· en· W2771661958 on OpenAlexaff
Tania Frixa, Andrea Sacconi, Mario Cioce, Giuseppe Roscilli, Fabiana Fosca Ferrara, Luigi Aurisicchio, Claudio Pulito, Stefano Telera, Mariantonia Carosi, Paola Muti, Sabrina Strano, Sara Donzelli, Giovanni Blandino

Bibliographic record

VenueCarcinogenesis · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsMcMaster UniversityJuravinski Cancer Centre
FundersAboca S.p.A. Società AgricolaAssociazione Italiana per la Ricerca sul CancroArcelorMittal
KeywordsDroshaDicermicroRNABiologyDownregulation and upregulationCancer researchLung cancerCancerEpithelial–mesenchymal transitionPhenotypeRibonuclease IIIMetastasisRNA interferenceTransfectionPathologyCell cultureSmall interfering RNAGeneticsMedicineGeneRNA

Abstract

fetched live from OpenAlex

Alteration in microRNAs (miRNAs) expression is a frequent finding in human cancers. In particular, widespread miRNAs down-regulation is a hallmark of malignant transformation. In the present report, we showed that the miR-128-3p, which is up-regulated in lung cancer tissues, has Drosha and Dicer, two key enzymes of miRNAs processing, as the main modulation targets leading to the widespread down-regulation of miRNA expression. We observed that the miRNAs downregulation induced by miR-128-3p contributed to the tumorigenic properties of lung cancer cells. In particular, miR-128-3p-mediated miRNAs down-regulation contributed to aberrant SNAIL and ZEB1 expression thereby promoting the epithelial-to-mesenchymal transition (EMT) program. Drosha also resulted to be implicated in the control of migratory phenotype as its expression counteracted miR-128-3p functional effects. Our study provides mechanistic insights into the function of miR-128-3p as a key regulator of the malignant phenotype of lung cancer cells. This also enforces the remarkable impact of Drosha and Dicer alteration in cancer, and in particular it highlights a role for Drosha in non-small-cell lung cancer cells 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 score0.083
Threshold uncertainty score0.610

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 head0.011
GPT teacher head0.258
Teacher spread0.247 · 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

Citations40
Published2017
Admission routes1
Has abstractyes

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