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Abstract A087: Enzalutamide-induced hypoxia attenuates response and promotes resistance to enzalutamide in preclinical models of prostate cancer

2018· article· en· W2911986230 on OpenAlexaff
Pamela Maxwell, Melanie McKechnie, Oisin Duddy, Christopher W. Armstrong, Judith M. Manley, Chee Wee Ong, Jenny Worthington, Elena I. Deryugina, James P. Quigley, Amina Zoubeidi, David Waugh, Melissa J. LaBonte

Bibliographic record

VenueCancer Research · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEnzalutamideLNCaPProstate cancerAngiogenesisCancer researchAndrogen receptorHypoxia (environmental)In vivoCancer cellDownregulation and upregulationMedicineCancerChemistryBiologyInternal medicineGeneBiochemistry

Abstract

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Abstract Inhibition of androgen signaling remains the therapeutic mainstay in castrate-resistant prostate cancer. The expression of androgen receptor (AR) splice variants and the retention of active AR signaling have been reported as mechanisms of resistance to the anti-androgen enzalutamide. Other non-AR dependent mechanisms of resistance have also been proposed, including acquisition of a hypoxic tumor microenvironment. We propose that treatment-induced hypoxia and the subsequent induction of angiogenesis may define a novel mechanism of relapse to enzalutamide. Preclinical experiments were conducted in LNCaP tumors, endothelial cells, and established human prostate cancer cell lines. The effects of enzalutamide on endothelial cells were examined in vivo and in vitro. Tumor growth, intratumoral hypoxia, and blood vessel density were measured in vivo. AR expression, activation, and target gene expression were measured in vitro. The effect of enzalutamide on hypoxia-driven, disease-progressing pathways and genes of interest, and the role of these genes in resistance to enzalutamide, was investigated. Administration of enzalutamide rapidly induced hypoxia in LNCaP tumors in vivo, followed by angiogenesis-promoted restoration of oxygen tension, increased vessel density, and accelerated tumor growth. In vitro, enzalutamide directly targeted AR-expressing endothelial cells, resulting in decreased growth and tubule formation. Exposure to hypoxia in vitro increased AR expression and transcriptional activity in LNCaP prostate cancer cells and sustained, but did not further potentiate, high basal AR and ARv7 expression and activity in 22Rv1 cells. Enzalutamide failed to attenuate the concurrent hypoxia-induced HIF-1 and NF-κB signaling, resulting in upregulation of disease-progressing genes and pathways. Administration of neutralizing antibodies to two hypoxia-regulated genes, interleukin-8 (IL-8) and VEGF, prolonged enzalutamide-mediated hypoxia over 14 days and LNCaP tumor growth control over 28 days in vivo (p<0.001). Elevated expression of IL-8 and VEGF-A was also detected in MDV3100-resistant models, where neutralization of IL-8 and VEGF-A inhibited tumor angiogenesis and partially reversed resistance to enzalutamide. We conclude that enzalutamide-induced hypoxia upregulates the expression of VEGF and IL-8, whose multimodel signaling effects, in turn, contribute to microenvironment-promoted resistance in prostate tumors. Citation Format: Pamela J. Maxwell, Melanie McKechnie, Oisin Duddy, Christopher W. Armstrong, Judith M. Manley, Chee Wee Ong, Jenny Worthington, Elena Deryugina, James P. Quigley, Amina Zoubeidi, David J.J. Waugh, Melissa J. LaBonte. Enzalutamide-induced hypoxia attenuates response and promotes resistance to enzalutamide in preclinical models of prostate cancer [abstract]. In: Proceedings of the AACR Special Conference: Prostate Cancer: Advances in Basic, Translational, and Clinical Research; 2017 Dec 2-5; Orlando, Florida. Philadelphia (PA): AACR; Cancer Res 2018;78(16 Suppl):Abstract nr A087.

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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
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)0.0030.000

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 head0.089
GPT teacher head0.416
Teacher spread0.327 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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