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Record W2610183112 · doi:10.1038/ncomms15289

Stat3 regulates centrosome clustering in cancer cells via Stathmin/PLK1

2017· article· en· W2610183112 on OpenAlexafffund
Edward J. Morris, Eiko Kawamura, Jordan Gillespie, Aruna D. Balgi, Nagarajan Kannan, William J. Muller, Michel Roberge, Shoukat Dedhar

Bibliographic record

VenueNature Communications · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrotubule and mitosis dynamics
Canadian institutionsMcGill University Health CentreUniversity of British ColumbiaBC Cancer Agency
FundersCanadian Cancer Society Research InstituteCanadian Institutes of Health Research
KeywordsCentrosomeStathminPLK1MitosisCell biologyBiologySpindle apparatusMicrotubuleCancer researchCancerCell divisionCell cycleCellGenetics

Abstract

fetched live from OpenAlex

Cancer cells frequently have amplified centrosomes that must be clustered together to form a bipolar mitotic spindle, and targeting centrosome clustering is considered a promising therapeutic strategy. A high-content chemical screen for inhibitors of centrosome clustering identified Stattic, a Stat3 inhibitor. Stat3 depletion and inhibition in cancer cell lines and in tumours in vivo caused significant inhibition of centrosome clustering and viability. Here we describe a transcription-independent mechanism for Stat3-mediated centrosome clustering that involves Stathmin, a Stat3 interactor involved in microtubule depolymerization, and the mitotic kinase PLK1. Furthermore, PLK4-driven centrosome amplified breast tumour cells are highly sensitive to Stat3 inhibitors. We have identified an unexpected role of Stat3 in the regulation of centrosome clustering, and this role of Stat3 may be critical in identifying tumours that are sensitive to Stat3 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 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 score0.519
Threshold uncertainty score0.680

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 science0.0010.001
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 head0.013
GPT teacher head0.308
Teacher spread0.294 · 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

Citations51
Published2017
Admission routes2
Has abstractyes

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