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Genomic analysis of circulating cell-free DNA (cfDNA) to investigate mechanisms of resistance to enzalutamide (ENZ) in metastatic castration-resistant prostate cancer (mCRPC) patients (pts).

2015· article· en· W2569288066 on OpenAlexaff
Arun Azad, Alexander W. Wyatt, Stanislav Volik, Anne Haegert, Stéphane Le Bihan, Robert H. Bell, Shawn Anderson, Brian McConeghy, Robert Shukin, Martin Gleave, Colin C. Collins, Kim N.

Bibliographic record

VenueJournal of Clinical Oncology · 2015
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsEnzalutamideMedicineProstate cancerInternal medicineAndrogen receptorAbiraterone acetateOncologyProgression-free survivalCancerChemotherapyAndrogen deprivation therapy

Abstract

fetched live from OpenAlex

157 Background: Factors driving clinical resistance to ENZ are poorly understood. Genomic analysis of cfDNA is a promising and minimally invasive approach for investigating mechanisms of therapeutic resistance in mCRPC. Methods: Baseline plasma samples were collected from 53 mCRPC pts commencing ENZ. In 31 of these pts, 12-week and treatment cessation samples were also obtained. DNA was extracted and subjected to array Comparative Genomic Hybridization (aCGH) for chromosome copy number (CN) analysis and androgen receptor (AR) gene sequencing (MiSeq) for mutation analysis. Endpoints were i) PSA50 or PSA30 response rates (RR) (PSA decline ≥ 50% or 30% for ≥ 3 weeks); and ii) radiographic/clinical progression-free survival (PFS). Results: CN changes on baseline aCGH included 8p loss (26%), 8q gain (32%), MYC gain (28%), CCND1 gain/amplification (amp) (11%), MET gain (13%), RB1 loss (21%) and AR gain/amp (30%). Correlation of clinical and genomic data showed multiple links between AR CN status and outcomes on ENZ. Firstly, compared to no AR gain/amp, pts with pre-treatment AR gain/amp had lower PSA50 (41% vs. 19%, P=0.12; Χ2) and PSA30 RR (54% vs. 25%, P=0.051; Χ2) and shorter median PFS (4.6 vs. 2.3 months, P<0.001; log-rank). Secondly, on multivariate analysis, pre-treatment AR gain/amp (HR 3.42, P=0.002) together with prior abiraterone (HR 4.72, P=0.001) was confirmed as an independent prognostic factor for PFS. Thirdly, in pts with serial plasma samples, 16% (5/31) had a change in AR CN status from baseline with 3 pts converting from no AR gain to AR gain and 2 pts from AR gain to AR amp. Of note, median PFS in these 5 pts was only 2.8 months. Finally, AR gain/amp at baseline or emergence of AR gain/amp on-treatment was associated with decreased median PFS compared with no AR CN increase at any timepoint (2.3 months vs. 6.5 months, P<0.001; log-rank). Conclusions: Detection of AR gain/amp in pre- or on-treatment cfDNA samples correlated with adverse outcomes on ENZ. These data indicate that AR gain/amp may be a biomarker of primary and acquired resistance to ENZ in mCRPC pts. Updated data including AR gene sequencing will be presented.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.170
GPT teacher head0.459
Teacher spread0.289 · 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 designObservational
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

Citations3
Published2015
Admission routes1
Has abstractyes

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