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Genomic drivers of poor prognosis and enzalutamide resistance in metastatic castration-resistant prostate cancer.

2019· article· en· W2921037661 on OpenAlexaff
William S. Chen, Rahul Aggarwal, Li Zhang, Shuang G. Zhao, Tomasz M. Beer, David A. Quigley, Adam Foye, Denise Playdle, Paul Lloyd, Matthew B. Rettig, Martin Gleave, Christopher P. Evans, Primo N. Lara, Vishal Kothari, Kim N., Robert E. Reiter, Christopher G. Maher, Felix Y. Feng, Eric J. Small, Joshi J. Alumkal

Bibliographic record

VenueJournal of Clinical Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsBC Cancer AgencyUniversity of British Columbia
Fundersnot available
KeywordsEnzalutamideProstate cancerMedicineOncologyCancerCancer researchTranscriptomeInternal medicineGeneBiologyGeneticsGene expressionAndrogen receptor

Abstract

fetched live from OpenAlex

146 Background: Metastatic castration-resistant prostate cancer (mCRPC) is the lethal form of the disease. Several recent efforts have identified genomic alterations in mCRPC, but the clinical implications of these alterations have not been fully elucidated. We conducted a prospective cohort study (n = 101) using whole genome sequencing (WGS) to analyze the association between key driver gene alterations and overall survival. We also performed whole-transcriptome RNA sequencing (RNA-seq) analyses to identify potential mechanisms of enzalutamide resistance in mCRPC. Methods: Metastasis biopsies were obtained in 101 mCRPC patients as part of the multi-institutional West Coast Prostate Cancer Dream Team project. Samples underwent WGS and RNA-seq. The resulting mutation, copy number, and structural variant calls were integrated to determine functional copy number status of candidate genes for downstream clinical analyses. We performed univariate and multivariable analyses to assess the prognostic significance of candidate genomic events with respect to overall survival. To nominate and investigate genomic pathways associated with enzalutamide resistance, we performed expression-based gene set enrichment analysis followed by cross-sectional enrichment and survival analyses related to the top nominated pathway. Results: RB1 loss was associated with poor overall survival (median 14.1 vs. 42.0 months, p < 0.001). When we compared enzalutamide resistant versus naïve samples using gene set enrichment analysis, we identified the Wnt/beta-catenin pathway as the top differentially expressed pathway in enzalutamide-resistant patients. Furthermore, CTNNB1 (beta-catenin) activating mutations were exclusive to enzalutamide-resistant patients (p = 0.013) and predictive of poor overall survival (median 13.6 vs. 41.7 months, p < 0.001). Conclusions: Impaired survival in mCRPC patients is associated with RB1 loss, identified by integrated genomic analysis of CRPC metastasis biopsies. Among men with mCRPC that was enzalutamide-resistant, the Wnt/beta-catenin pathway is nominated as an important predictive (and potentially therapeutic) pathway.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.106
GPT teacher head0.465
Teacher spread0.359 · 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

Citations17
Published2019
Admission routes1
Has abstractyes

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