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Record W2116657387 · doi:10.7150/ijbs.6.599

Aberrant Cytoplasm Localization and Protein Stability of SIRT1 is Regulated by PI3K/IGF-1R Signaling in Human Cancer Cells

2010· article· en· W2116657387 on OpenAlexfundno aff
Vanessa Byles, Laura K. Chmilewski, Joyce Wang, Lijia Zhu, Lora W. Forman, Douglas V. Faller, Yan Dai

Bibliographic record

VenueInternational Journal of Biological Sciences · 2010
Typearticle
Languageen
FieldMedicine
TopicSirtuins and Resveratrol in Medicine
Canadian institutionsnot available
FundersNational Center for Research ResourcesNational Cancer InstituteUniversité Laval
KeywordsCytoplasmCancer cellCell biologyHistone deacetylasePI3K/AKT/mTOR pathwayBiologySignal transductionMitosisCancerHistoneBiochemistryGeneticsDNA

Abstract

fetched live from OpenAlex

SIRT1, an NAD-dependent histone/protein deacetylase, has classically been thought of as a nuclear protein. In this study, we demonstrate that SIRT1 is mainly localized in the nucleus of normal cells, but is predominantly localized in the cytoplasm of the cancer / transformed cells we tested. We found this predominant cytoplasmic localization of SIRT1 is regulated by elevated mitotic activity and PI3K/IGF-1R signaling in cancer cells. We show that aberrant cytoplasmic localization of SIRT1 is due to increased protein stability and is regulated by PI3K/IGF-1R signaling. In addition, we determined that SIRT1 is required for PI3K-mediated cancer cell growth. Our study represents the first identification that aberrant cytoplasm localization is one of the specific alternations to SIRT1 that occur in cancer cells, and PI3K/IGF-1R signaling plays an important role in the regulation of cytoplasmic SIRT1 stability. Our findings suggest that the over-expressed cytoplasmic SIRT1 in cancer cells may greatly contribute to its cancer-specific function by working downstream of the PI3K/IGF-1R signaling pathway.

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 score0.001
Threshold uncertainty score0.005

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.034
GPT teacher head0.334
Teacher spread0.300 · 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

Citations120
Published2010
Admission routes1
Has abstractyes

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Same venueInternational Journal of Biological SciencesSame topicSirtuins and Resveratrol in MedicineFrench-language works237,207