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mTORC1 controls GSK3β nuclear localization

2018· article· en· W3177313507 on OpenAlexafffundabout
Costin N. Antonescu, Stephen Bautista, Ivan Boras, Adriao Vissa, Noa Mecica, Christopher M. Yip, Peter Kim

Bibliographic record

VenueThe FASEB Journal · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPI3K/AKT/mTOR signaling in cancer
Canadian institutionsHospital for Sick ChildrenUniversity of TorontoToronto Metropolitan University
FundersCanadian Institutes of Health ResearchOntario Ministry of Research, Innovation and Science
KeywordsmTORC1Cell biologyPI3K/AKT/mTOR pathwayGSK-3PhosphorylationEndosomeBiologyProtein kinase BLysosomeNuclear transportGSK3BCytosolSignal transductionChemistryCell nucleusBiochemistryCytoplasmIntracellular

Abstract

fetched live from OpenAlex

Glycogen synthase kinase 3β (GSK3β) is a serine/threonine kinase that regulates numerous cellular processes such as apoptosis, self‐renewal, growth, and metabolism. GSK3β phosphorylates over 100 substrates ranging from cytosolic to nuclear substrate targets, including c‐myc, a key ongogenic transcription factor, leading to control of c‐myc stability. GSK3β is itself regulated by phosphorylation on S9 by signals such as Akt (activated within the phosphatidylinositol‐3kinase, PI3K, signaling pathway), resulting in reduced GSK3β kinase activity. Given the wide range of substrates and the incomplete regulation of GSK3β by S9 phosphorylation, it is likely that other mechanisms gate GSK3β function. GSK3β may be localized within different cellular compartments such early endosomes, the nucleus, and in multivesicular bodies. However, how GSK3β localization is regulated, and how this may control GSK3β function is poorly understood, which we have examined here. Specifically, we examined how mTORC1, a key cellular sensor of mitogenic and metabolic signals, controls GSK3β localization and function. Using pharmacological inhibitors of mTORC1 and GSK3β, as well as siRNA gene silencing approaches, we uncovered that GSK3β‐mediated c‐myc degradation is negatively regulated by mTORC1. Using fluorescence microscopy approaches, we find that inhibition of PI3K‐Akt‐mTOR signaling axis, and metabolic insufficiency (e.g. amino acid deficiency), elicit GSK3β nuclear translocation from the cytosol, suggesting that mTORC1 mediates GSK3β nucleocytoplasmic shuttling. Consistent with regulation of GSK3β by mTORC1, we also uncovered that GSK3β localizes to LAMP1 positive late endosome/lysosomes, and perturbations of late endosome/lysosome membrane traffic impacted nuclear localization of GSK3β. This suggests that late endosomes/lysosomal compartments serve as organizing platforms, integrating mitogenic and metabolic signals via mTORC1 to elicit GSK3β cytosolic retention, thus impacting access of GSK3β to nuclear targets and controlling c‐myc degradation. Understanding how mTORC1 dependent signals regulate GSK3b subcellular localization to control GSK3β function may give useful insight to the development of drugs and therapies targeting GSK3β for the treatment of cancer cell growth and survival. Support or Funding Information This work is supported by a Discovery Grant from the Natural Science and Engineering Research Council (of Canada), an Early Researcher Award from the Ontario Ministry of Research, Innovation and Science, and a New Investigator Award from the Canadian Institutes of Health Research to C.N.A. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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 score0.006

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.010
GPT teacher head0.250
Teacher spread0.240 · 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

Citations0
Published2018
Admission routes3
Has abstractyes

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