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MP34-05 COMBINATION THERAPY FOR CASTRATION-RESISTANT PROSTATE CANCER USING ANTAGONISTS OF THE N-TERMINAL DOMAIN OF ANDROGEN RECEPTOR WITH IONIZING RADIATION

2019· article· en· W2941842789 on OpenAlexaboutno aff
Yusuke Ito, Carmen A. Bañuelos, Yukiyoshi Hirayama, Kunzhong Jian, Raymond J. Andersen, Marianne D. Sadar

Bibliographic record

VenueThe Journal of Urology · 2019
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsnot available
Fundersnot available
KeywordsEnzalutamideProstate cancerMedicineAndrogen receptorCancer researchCancerAndrogenRadiation therapyInternal medicineOncologyHormone

Abstract

fetched live from OpenAlex

You have accessJournal of UrologyProstate Cancer: Advanced (including Drug Therapy) IV (MP34)1 Apr 2019MP34-05 COMBINATION THERAPY FOR CASTRATION-RESISTANT PROSTATE CANCER USING ANTAGONISTS OF THE N-TERMINAL DOMAIN OF ANDROGEN RECEPTOR WITH IONIZING RADIATION Yusuke Ito*, C. Adriana Banuelos, Yukiyoshi Hirayama, Kunzhong Jian, Raymond Andersen, and Marianne Sadar Yusuke Ito*Yusuke Ito* More articles by this author , C. Adriana BanuelosC. Adriana Banuelos More articles by this author , Yukiyoshi HirayamaYukiyoshi Hirayama More articles by this author , Kunzhong JianKunzhong Jian More articles by this author , Raymond AndersenRaymond Andersen More articles by this author , and Marianne SadarMarianne Sadar More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000555948.83770.4eAboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: Emerging evidence supports that androgen receptor (AR) signaling regulates DNA repair in prostate cancer. Therefore, a combination approach using AR modulating drugs with radiation could be a promising option for the treatment of metastatic castration resistant prostate cancer (mCRPC). All currently approved AR modulating drugs, such as enzalutamide (ENZA) and abiraterone, either directly or indirectly target the AR C-terminus ligand-binding domain (LBD). Such drugs are often unsuccessful due to the emergence of AR splice variants (e.g., AR-V7) that are constitutively active and lack a LBD. EPI-002 is a first-in-class AR antagonist that binds to its N-terminus domain to inhibit the transcriptional activities of both full-length AR and AR splice variants. A next generation compound, EPI-7170 has been developed. Here we present data to support that a combination of EPI compounds and ionizing radiation maybe beneficial for the treatment of mCRPC. METHODS: Androgen-independent LNCaP95 cells that are resistant to ENZA and endogenously express both full-length AR and AR-V7 were used. The effect of EPI compounds on the expression of DNA repair genes was measured using TaqMan array and Western blot analysis. Monotherapies versus combination therapies using EPI-002, EPI-7170, or ENZA, with ionizing radiation were evaluated for effects on proliferation, colony formation, cell cycle and DNA damage using BrdU incorporation, FACS and Western blot and immune fluorescent staining. RESULTS: EPI-7170 was more potent than EPI-002. Both EPI-002 and EPI-7170 decreased expression of DNA repair genes contrary to ENZA. EPI-002 induced G1 cell cycle arrest whereas radiation induced G2/M cell cycle arrest. FACS analysis revealed a dose-dependent decrease of BrdU incorporation with increased accumulation of gammaH2AX with combination therapy. A synergistic inhibitory effect on proliferation of ENZA-resistant LNCaP95 cells was achieved with a combination of EPI compounds with ionizing radiation. CONCLUSIONS: Combination therapy with radiation and an antagonist to the AR NTD such as EPI-002 or EPI-7170 that inhibits the transcriptional activities of both AR-Vs and full-length AR, may provide a new therapeutic approach for mCRPC. Source of Funding: US National Cancer Institute (R01 CA105304) awarded to MDS Vancouver, Canada© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e497-e497 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Yusuke Ito* More articles by this author C. Adriana Banuelos More articles by this author Yukiyoshi Hirayama More articles by this author Kunzhong Jian More articles by this author Raymond Andersen More articles by this author Marianne Sadar More articles by this author Expand All Advertisement PDF downloadLoading ...

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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.065

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)0.0200.002

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 head0.025
GPT teacher head0.321
Teacher spread0.296 · 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 designNon-randomized trial
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
Published2019
Admission routes1
Has abstractyes

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