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Record W2080727558 · doi:10.1158/1538-7445.am2012-466

Abstract 466: Synthetic triterpenoids target cell migration and cell adhesion via GSK3β

2012· article· en· W2080727558 on OpenAlexaff
Ciric To, Gianni M. Di Guglielmo

Bibliographic record

VenueCancer Research · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNatural product bioactivities and synthesis
Canadian institutionsWestern University
Fundersnot available
KeywordsFocal adhesionPaxillinIQGAP1PTK2Cell biologyGSK-3Cell migrationCell adhesionChemistryBiologyBiochemistryPhosphorylationCellCytoskeletonProtein kinase A

Abstract

fetched live from OpenAlex

Abstract Synthetic triterpenoids are a class of anti-tumor compounds that target various cellular functions including apoptosis, growth inhibition, anti-inflammation and cytoprotection. Previously, we have shown that triterpenoids also inhibit cell migration and the objective of our current study is to examine the molecular mechanisms. Since cellular adhesion dynamics play a critical role in cell migration, we investigated the effects of triterpenoids on focal adhesion morphology. Using immunofluorescence microscopic analysis of focal adhesion markers, paxillin and Focal Adhesion Kinase (FAK), we found that cells that were treated with synthetic triterpenoids possessed enlarged focal adhesions. Interestingly, numerous focal adhesion related proteins including IQGAP1, paxillin, FAK and Glycogen Synthase Kinase 3 (GSK3) were identified as drug-binding proteins using pull down and mass spectrometry approaches. Therefore, we investigated if triterpenoids target these proteins and affect cell adhesion turnover to inhibit cell migration. We found that focal adhesion re-establishment was altered by triterpenoids while pre-existing focal adhesions remained largely unaffected. To further explore the underlying mechanism of triterpenoids on GSK3β dependent cell adhesion dynamics, we analyzed GSK3β activity. We found that triterpenoids stimulate the phosphorylation of GSK3β at serine 9, however, both FAK and paxillin phosphorylation was largely unaffected by the triterpenoids. In parallel studies, we observed that focal adhesion staining was enlarged with cells that were treated with the GSK3β inhibitors, lithium chloride and SB216763. In addition, GSK3β inhibition affected the localization of not only GSK3β but also IQGAP1, an important scaffolding protein involved in cell polarity. From our results, we postulate that synthetic triterpenoids may affect cell migration by targeting GSK3β, which in turns, inhibits its activity and displaces its localization from the leading edge. More importantly, GSK3β inhibition by the triterpenoids and by GSK3β inhibitors also lead to the displacement of IQGAP1 from the leading edge, which further suggests that triterpenoids may act via a GSK3β mechanism to affect focal adhesions and cell migration. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 466. doi:1538-7445.AM2012-466

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 score0.005
Threshold uncertainty score0.016

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.028
GPT teacher head0.320
Teacher spread0.292 · 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".

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Citations0
Published2012
Admission routes1
Has abstractyes

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