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Record W3000411451 · doi:10.1158/1078-0432.ccr-19-3023

Diverse <i>AR</i> Gene Rearrangements Mediate Resistance to Androgen Receptor Inhibitors in Metastatic Prostate Cancer

2020· article· en· W3000411451 on OpenAlexaff
Yingming Li, Rendong Yang, Christine Henzler, Yeung Ho, Courtney N. Passow, Benjamin Auch, Suzanne Carreira, Daniel Nava Rodrigues, Cláudia Bertan, Tae Hyun Hwang, David A. Quigley, Ha X. Dang, Colm Morrissey, Michael Fraser, Stephen R. Plymate, Christopher A. Maher, Felix Y. Feng, Johann S. de Bono, Scott M. Dehm

Bibliographic record

VenueClinical Cancer Research · 2020
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsOntario Institute for Cancer Research
FundersNational Institutes of HealthProstate Cancer Foundation of AustraliaNational Cancer InstituteNational Institute for Health and Care ResearchU.S. Department of Veterans Affairs
KeywordsAndrogen receptorProstate cancerCancer researchProstateCancerGeneBiologyMedicineOncologyInternal medicineGenetics

Abstract

fetched live from OpenAlex

Abstract Purpose: Prostate cancer is the second leading cause of male cancer deaths. Castration-resistant prostate cancer (CRPC) is a lethal stage of the disease that emerges when endocrine therapies are no longer effective at suppressing activity of the androgen receptor (AR) transcription factor. The purpose of this study was to identify genomic mechanisms that contribute to the development and progression of CRPC. Experimental Design: We used whole-genome and targeted DNA-sequencing approaches to identify mechanisms underlying CRPC in an aggregate cohort of 272 prostate cancer patients. We analyzed structural rearrangements at the genome-wide level and carried out a detailed structural rearrangement analysis of the AR locus. We used genome engineering to perform experimental modeling of AR gene rearrangements and long-read RNA sequencing to analyze effects on expression of AR and truncated AR variants (AR-V). Results: AR was among the most frequently rearranged genes in CRPC tumors. AR gene rearrangements promoted expression of diverse AR-V species. AR gene rearrangements occurring in the context of AR amplification correlated with AR overexpression. Cell lines with experimentally derived AR gene rearrangements displayed high expression of tumor-specific AR-Vs and were resistant to endocrine therapies, including the AR antagonist enzalutamide. Conclusions: AR gene rearrangements are an important mechanism of resistance to endocrine therapies in CRPC.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.499
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.268
GPT teacher head0.509
Teacher spread0.241 · 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.

Study designNot applicable
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

Citations86
Published2020
Admission routes1
Has abstractyes

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