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Record W4282944316 · doi:10.1158/1538-7445.am2022-5283

Abstract 5283: Characterization of Gli activation by the estrogen receptor in breast cancer cells

2022· article· en· W4282944316 on OpenAlexaff
Shabnam Massah, Jane Foo, Na Li, Sarah Truong, Mannan Nouri, Lishi Xie, Gail S. Prins, Ralph Buttyan, Nada Lallous, Artem Cherkasov

Bibliographic record

VenueCancer Research · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHedgehog Signaling Pathway Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEstrogen receptorCancer researchBiologyHedgehogFulvestrantTranscription factorGene knockdownAndrogen receptorSteroid hormone receptorHedgehog signaling pathwaySignal transductionEstrogen receptor alphaProstate cancerCell biologyChemistryCancerBreast cancerApoptosisBiochemistryGenetics

Abstract

fetched live from OpenAlex

Abstract Background: The nuclear steroid receptor superfamily encompasses a group of proteins best known fortheir functions as primary transcription factors that are conditionally active when bound to a ligand.Here, we show that a prominent member of this family, the estrogen receptor [ER-α] have a secondaryfunction of activating the Gli family of transcription factors. Gli is recognized as the mediator of activeHedgehog (Hh) signaling and plays an important role in cell development and growth. Gli activity isregulated by a post-translational proteolytic process that is suppressed by Hedgehog signaling.Previously we found that in prostate cancer, the ligand activated androgen receptor [AR] recognizes andbinds to Gli proteins at their Protein Processing Domains. This binding stabilizes Gli proteins in their un-proteolyzed active form and bypasses the Hedgehog signaling, thus promoting cancer progressionthrough non-canonical activation of Gli proteins. Due to the high similarity between AR and ER, wehypothesized that a similar Gli regulation could play a role in Breast Cancer (BrCA) progression. We thustested the ability of human ER-α to bind and activate Gli in BrCa and evaluated the role of this pathwayin tumor cell growth. Methods: we measured Gli activity in 293T and BrCa cells (MCF7, T47D, MDA-MB-453) in presence andabsence of steroid ligand using Gli-luciferase reporter assay. We evaluated the interaction between Gli3and ER-α by co-immunoprecipitation and proximity ligation assay and assessed the stability of Gli3stability in BrCa cell extracts by western blots. We also studied the effect of ER-α knockdown ordestabilization (by fulvestrant treatment) on Gli3 stability, formation of intranuclear ER-α-Gli3complexes and Gli reporter activity. We also measured the expression level of Gli target genes in thepresence and absence of estradiol by qPCR in BrCa cells. Lastly, we evaluated the importance of Gli3expression on BrCa growth by Gli3 knockdown and Cyquant assay. Results: We found that ER co-immunoprecipitates with Gli3. Transfection with ER-α increased Glireporter activity which was further increased by estradiol treatment. Acute (2hr) estradiol treatmentincreased intranuclear ER-α-Gli3 complex formation in BrCa cells. Chronic (48hr) estradiol treatmentincreased Gli3 stability and endogenous activity in BrCa cells. Destabilization or knockdown of ER-αdecreased estradiol-induced formation of ER-α-Gli3 complexes as well as Gli activity and stability in BrCacells. In addition, siRNA knockdown of Gli3 reduced growth in BrCa cells. Conclusion: Collectively our results uncovered a new role of the steroid receptors ER and AR inregulating Gli oncogenic transcriptional activity in BrCa and PCa, respectively. Citation Format: Shabnam Massah, Jane Foo, Na Li, Sarah Truong, Mannan Nouri, Lishi Xie, Gail Prins, Ralph Buttyan, Nada Lallous, Artem Cherkasov. Characterization of Gli activation by the estrogen receptor in breast cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5283.

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 score0.022
Threshold uncertainty score0.334

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 head0.039
GPT teacher head0.347
Teacher spread0.308 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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