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Record W2021850377 · doi:10.1083/jcb.200404146

p107 inhibits G1 to S phase progression by down-regulating expression of the F-box protein Skp2

2005· article· en· W2021850377 on OpenAlexaff
Geneviève Rodier, Constantin Makris, Philippe Coulombe, Anthony Scimè, Keiko Nakayama, Keiichi I. Nakayama, Sylvain Meloche

Bibliographic record

VenueThe Journal of Cell Biology · 2005
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsUniversité de MontréalInstitute for Research in Immunology and Cancer
Fundersnot available
KeywordsSKP2BiologyCell cycleEctopic expressionCell biologyPhosphorylationCyclin-dependent kinase 2KinaseEmbryonic stem cellCell cycle progressionApoptosisProtein kinase ACell cultureUbiquitinBiochemistryGeneUbiquitin ligaseGenetics

Abstract

fetched live from OpenAlex

Cell cycle progression is negatively regulated by the pocket proteins pRb, p107, and p130. However, the mechanisms responsible for this inhibition are not fully understood. Here, we show that overexpression of p107 in fibroblasts inhibits Cdk2 activation and delays S phase entry. The inhibition of Cdk2 activity is correlated with the accumulation of p27, consequent to a decreased degradation of the protein, with no change of Thr187 phosphorylation. Instead, we observed a marked decrease in the abundance of the F-box receptor Skp2 in p107-overexpressing cells. Reciprocally, Skp2 accumulates to higher levels in p107-/- embryonic fibroblasts. Ectopic expression of Skp2 restores p27 down-regulation and DNA synthesis to the levels observed in parental cells, whereas inactivation of Skp2 abrogates the inhibitory effect of p107 on S phase entry. We further show that the serum-dependent increase in Skp2 half-life observed during G1 progression is impaired in cells overexpressing p107. We propose that p107, in addition to its interaction with E2F, inhibits cell proliferation through the control of Skp2 expression and the resulting stabilization of p27.

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)0.001
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 score0.024
Threshold uncertainty score0.261

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.010
GPT teacher head0.294
Teacher spread0.284 · 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

Citations44
Published2005
Admission routes1
Has abstractyes

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