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Record W4200584799 · doi:10.3390/ijms23010215

High Level of Staufen1 Expression Confers Longer Recurrence Free Survival to Non-Small Cell Lung Cancer Patients by Promoting THBS1 mRNA Degradation

2021· article· en· W4200584799 on OpenAlexaff
Florence Bonnet‐Magnaval, Leïla Halidou Diallo, Valérie Brunchault, Nathalie Laugero, Florent Morfoisse, Florian David, Émilie Roussel, Manon Nougué, Audrey Zamora, Emmanuelle Marchaud, Florence Tatin, Anne‐Catherine Prats, Barbara Garmy‐Susini, Luc DesGroseillers, Éric Lacazette

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsUniversité de Montréal
FundersLigue Contre le Cancer
KeywordsBiologyCell biologyMessenger RNACancer researchCellCell adhesionLung cancerInternal medicineGeneBiochemistryMedicine

Abstract

fetched live from OpenAlex

Stau1 is a pluripotent RNA-binding protein that is responsible for the post-transcriptional regulation of a multitude of transcripts. Here, we observed that lung cancer patients with a high Stau1 expression have a longer recurrence free survival. Strikingly, Stau1 did not impair cell proliferation in vitro, but rather cell migration and cell adhesion. In vivo, Stau1 depletion favored tumor progression and metastases development. In addition, Stau1 depletion strongly impaired vessel maturation. Among a panel of candidate genes, we specifically identified the mRNA encoding the cell adhesion molecule Thrombospondin 1 (THBS1) as a new target for Staufen-mediated mRNA decay. Altogether, our results suggest that regulation of THBS1 expression by Stau1 may be a key process involved in lung cancer progression.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.028
GPT teacher head0.313
Teacher spread0.285 · 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 source (direct Gemma or distilled Codex), 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

Citations15
Published2021
Admission routes1
Has abstractyes

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