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Record W4380768000 · doi:10.1038/s41467-023-39281-z

CNK2 promotes cancer cell motility by mediating ARF6 activation downstream of AXL signalling

2023· article· en· W4380768000 on OpenAlexafffund
Guillaume Serwe, David Kachaner, Jessica K. Gagnon, Cédric Plutoni, Driss Lajoie, Eloïse Duramé, Malha Sahmi, Damien Garrido, Martin Lefrançois, Geneviève Arseneault, Marc K. Saba-El-Leil, Sylvain Meloche, Grégory Emery, Marc Therrien

Bibliographic record

VenueNature Communications · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPhagocytosis and Immune Regulation
Canadian institutionsUniversité de MontréalInstitute for Research in Immunology and Cancer
FundersCIHR Skin Research Training CentreFonds de Recherche du Québec - SantéUniversité de MontréalGovernment of CanadaCanadian Institutes of Health ResearchCancer Research SocietyGenome Canada
KeywordsDownstream (manufacturing)MotilitySignallingCell biologyCancerChemistryCancer researchBiologyBusinessGenetics

Abstract

fetched live from OpenAlex

Cell motility is a critical feature of invasive tumour cells that is governed by complex signal transduction events. Particularly, the underlying mechanisms that bridge extracellular stimuli to the molecular machinery driving motility remain partially understood. Here, we show that the scaffold protein CNK2 promotes cancer cell migration by coupling the pro-metastatic receptor tyrosine kinase AXL to downstream activation of ARF6 GTPase. Mechanistically, AXL signalling induces PI3K-dependent recruitment of CNK2 to the plasma membrane. In turn, CNK2 stimulates ARF6 by associating with cytohesin ARF GEFs and with a novel adaptor protein called SAMD12. ARF6-GTP then controls motile forces by coordinating the respective activation and inhibition of RAC1 and RHOA GTPases. Significantly, genetic ablation of CNK2 or SAMD12 reduces metastasis in a mouse xenograft model. Together, this work identifies CNK2 and its partner SAMD12 as key components of a novel pro-motility pathway in cancer cells, which could be targeted in metastasis.

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 score0.027
Threshold uncertainty score0.468

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 science0.0010.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.297
Teacher spread0.275 · 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

Citations9
Published2023
Admission routes2
Has abstractyes

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