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Record W3182606016 · doi:10.1158/1538-7445.am2021-2562

Abstract 2562: EGCG targeting of adipogenesis reveals a STAT3-mediated paracrine oncogenic control of triple-negative breast cancer cell invasive phenotype

2021· article· en· W3182606016 on OpenAlexaff
Narjara González Suárez, Sahily Rodriguez Torres, Borhane Annabi

Bibliographic record

VenueCancer Research · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsParacrine signallingAdipogenesisCancer researchTriple-negative breast cancerBiologyAutocrine signallingGene silencingEndocrinologyInternal medicineCell biologyAdipose tissueMedicineBreast cancerCancerBiochemistryReceptor

Abstract

fetched live from OpenAlex

Abstract Background: Obese subjects have an increased risk of developing triple-negative breast cancer (TNBC), in part associated with the chronic low-grade inflammation state. On the other hand, epidemiological data indicates that increased consumption of polyphenol-rich fruits and vegetables plays a key role in reducing incidence of some cancers. Objectives: Here, we tested whether green tea-derived epigallocatechin-3-gallate (EGCG) could alter adipogenesis involved in the maturation of pre-adipocytes, and how this impacts the paracrine regulation of the mature adipocytes secretome on the TNBC invasive phenotype. Methods: Differentiation was performed and conditioned media (CM) from preadipocytes and mature adipocytes harvested. Human TNBC-derived MDA-MB-231 real-time cell migration was performed using the exCELLigence system. Differential gene arrays and RT-qPCR were used to assess gene expression levels. Western blotting was used to assess protein expression levels. In vitro vasculogenic mimicry (VM) was assessed with Matrigel. Results: EGCG was found to inhibit the induction of numerous key adipogenic biomarkers, including lipoprotein lipase, adiponectin, leptin, fatty acid synthase, and fatty acid binding protein 4. Increased MDA-MB-231 chemotaxis and VM were found in response to mature adipocytes secretome, and this was correlated with the induction of the STAT3 signaling pathway. This invasive phenotype was prevented by EGCG, JAK/STAT inhibitors Tofacitinib and AG490, as well as upon STAT3 gene silencing. Conclusion: Adipocytes secretome plays a key role in the paracrine regulation of TNBC cells invasive phenotype. Dietary catechin-mediated interventions may, in part through the inhibition of adipogenesis and modulation of adipocytes secretome, prevent the onset of an obesogenic environment that favors TNBC development. Citation Format: Narjara Gonzalez Suarez, Sahily Rodriguez Torres, Borhane Annabi. EGCG targeting of adipogenesis reveals a STAT3-mediated paracrine oncogenic control of triple-negative breast cancer cell invasive phenotype [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2562.

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 score0.003
Threshold uncertainty score0.010

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)0.0030.001

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 head0.027
GPT teacher head0.337
Teacher spread0.310 · 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
Published2021
Admission routes1
Has abstractyes

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