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Record W2561061456 · doi:10.1158/1538-7445.am2015-3592

Abstract 3592: Androgens interfere with enzalutamide agonism of mutant F876L androgen receptor

2015· article· en· W2561061456 on OpenAlexaff
Daniel J. Coleman, Katy Van Hook, Robert Lisac, Carly J. King, Nicholas Wang, Jacob Schwartzman, Martin Gleave, Lina Gao, Joshua A. Urrutia, Laura M. Heiser, Joshi J. Alumkal

Bibliographic record

VenueCancer Research · 2015
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEnzalutamideAndrogen receptorLNCaPAndrogenCancer researchAgonistCell cultureProstate cancerInternal medicineEndocrinologyMutantReceptorEctopic expressionBiologyChemistryMedicineHormoneGeneticsCancerGene

Abstract

fetched live from OpenAlex

Abstract Multiple lines of evidence demonstrate that castration-resistant prostate cancers (CRPCs) remain reliant on androgens that activate the androgen receptor (AR). Treatment with the novel anti-androgen enzalutamide improves both progression-free and overall survival in CRPC patients (Beer, 2014, Scher, 2012). However, progression is universal. Recently, F876L mutations in the AR ligand binding domain have been described (Balbas, 2013, Korpal, 2013, Joseph, 2013). This mutation confers resistance to enzalutamide treatment and in some cases converts enzalutamide to an AR agonist in pre-clinical studies (Balbas, 2013, Korpal, 2013, Joseph, 2013). Clinical studies demonstrate that ∼10% of patients harbor F876L mutations after treatment with novel anti-androgens (Joseph, 2013). However, anti-androgen withdrawal effects (PSA responses) after discontinuing enzalutamide are rarely seen clinically (Rodriguez-Vida, 2014). An enzalutamide-resistant cell line was developed after chronic treatment of LNCaP cells in vivo. We found that this resistant cell line was dependent on AR expression for survival and that this cell line harbored an AR F876L mutation. When these resistant cells were cultured in complete serum, enzalutamide treatment did not lead to agonistic effects. However, enzalutamide treatment of these resistant cells or cell lines with ectopic expression of AR F876L cultured in androgen-depleted serum led to a significant agonistic effect - an effect that was attenuated by the addition of androgens to culture. Finally, prior work and our own demonstrated that F876L mutant and wild-type AR activate similar pathways (Joseph, 2013). Therefore, we determined if suppression of previously described transcriptional co-activators of wild-type AR also blocked AR F876L function. We found several targetable AR co-activators that met that standard. Our data demonstrate that androgens interfere with enzalutamide-induced agonism of F876L mutant AR. Because androgens persist in enzalutamide-resistant CRPC, AR activation by androgens, rather than enzalutamide, may explain why enzalutamide discontinuation does not lead to anti-androgen withdrawal effects clinically. Further, our results provide a cautionary note on therapeutic efforts to deplete androgens concomitantly with enzalutamide treatment as this may accentuate AR agonism by enzalutamide in tumors harboring AR F876L mutations. Finally, targeting critical AR transcriptional co-activators is a promising strategy to suppress mutant AR F876L function irrespective of whether the AR agonist is androgens or enzalutamide. Citation Format: Daniel Coleman, Katy Van Hook, Robert Lisac, Carly King, Nicholas Wang, Jacob Schwartzman, Martin Gleave, Lina Gao, Joshua Urrutia, Laura Heiser, Joshi J. Alumkal. Androgens interfere with enzalutamide agonism of mutant F876L androgen receptor. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3592. doi:10.1158/1538-7445.AM2015-3592

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 score0.004
Threshold uncertainty score0.012

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)0.0040.001

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 head0.141
GPT teacher head0.421
Teacher spread0.279 · 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
Published2015
Admission routes1
Has abstractyes

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