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Record W2135122661 · doi:10.1128/mcb.00004-10

Doubles Game: Src-Stat3 versus p53-PTEN in Cellular Migration and Invasion

2010· article· en· W2135122661 on OpenAlexafffund
Utpal K. Mukhopadhyay, Patrick Mooney, Lilly Jia, Robert Eves, Leda Raptis, Alan S. Mak

Bibliographic record

VenueMolecular and Cellular Biology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPI3K/AKT/mTOR signaling in cancer
Canadian institutionsQueen's University
FundersCanadian Institutes of Health ResearchHeart and Stroke Foundation of Canada
KeywordsPodosomeInvadopodiaPTENProto-oncogene tyrosine-protein kinase SrcBiologyCell biologyEffectorCancer researchCell migrationSignal transductionCellCancer cellPI3K/AKT/mTOR pathwayCytoskeletonCancerGenetics

Abstract

fetched live from OpenAlex

We have recently shown that Src induces the formation of podosomes and cell invasion by suppressing endogenous p53, while enhanced p53 strongly represses the Src-induced invasive phenotype. However, the mechanism by which Src and p53 play antagonistic roles in cell invasion is unknown. Here we show that the Stat3 oncogene is a required downstream effector of Src in inducing podosome structures and related invasive phenotypes. Stat3 promotes Src phenotypes through the suppression of p53 and the p53-inducible protein caldesmon, a known podosome antagonist. In contrast, enhanced p53 attenuates Stat3 function and Src-induced podosome formation by upregulating the tumor suppressor PTEN. PTEN, through the inactivation of Src/Stat3 function, also stabilizes the podosome-antagonizing p53/caldesmon axis, thereby further enhancing the anti-invasive potential of the cell. Furthermore, the protein phosphatase activity of PTEN plays a major role in the negative regulation of the Src/Stat3 pathway and represses podosome formation. Our data suggest that cellular invasiveness is dependent on the balance between two opposing forces: the proinvasive oncogenes Src-Stat3 and the anti-invasive tumor suppressors p53-PTEN.

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 categoriesMeta-epidemiology (narrow)
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 score0.026
Threshold uncertainty score1.000

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 science0.0000.000
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 head0.009
GPT teacher head0.243
Teacher spread0.233 · 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.

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

Citations49
Published2010
Admission routes2
Has abstractyes

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