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Record W4386516247 · doi:10.1093/jnci/djad184

Molecular features of prostate cancer after neoadjuvant therapy in the phase 3 CALGB 90203 trial

2023· article· en· W4386516247 on OpenAlexafffund
Takayuki Sumiyoshi, Xiaofei Wang, Evan W. Warner, Andrea Sboner, Matti Annala, Michael Sigouros, Kevin Beja, Kei Mizuno, Sheng‐Yu Ku, Ladan Fazli, James A. Eastham, Mary‐Ellen Taplin, Jeffrey P. Simko, Susan Halabi, Michael J. Morris, Martin Gleave, Alexander W. Wyatt, Himisha Beltran

Bibliographic record

VenueJNCI Journal of the National Cancer Institute · 2023
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health ResearchNational Cancer InstituteProstate Cancer FoundationNational Institutes of HealthAlliance for Clinical Trials in Oncology FoundationSanofiU.S. Department of Defense
KeywordsProstate cancerProstatectomyDocetaxelAndrogen deprivation therapyOncologyInternal medicineNeoadjuvant therapyMedicineProstateCancerCancer research

Abstract

fetched live from OpenAlex

BACKGROUND: The phase 3 CALGB 90203 (Alliance) trial evaluated neoadjuvant chemohormonal therapy for high-risk localized prostate cancer before radical prostatectomy. We dissected the molecular features of post-treated tumors with long-term clinical outcomes to explore mechanisms of response and resistance to chemohormonal therapy. METHODS: We evaluated 471 radical prostatectomy tumors, including 294 samples from 166 patients treated with 6 cycles of docetaxel plus androgen deprivation therapy before radical prostatectomy and 177 samples from 97 patients in the control arm (radical prostatectomy alone). Targeted DNA sequencing and RNA expression of tumor foci and adjacent noncancer regions were analyzed in conjunction with pathologic changes and clinical outcomes. RESULTS: Tumor fraction estimated from DNA sequencing was significantly lower in post-treated tumor tissues after chemohormonal therapy compared with controls. Higher tumor fraction after chemohormonal therapy was associated with aggressive pathologic features and poor outcomes, including prostate-specific antigen-progression-free survival. SPOP alterations were infrequently detected after chemohormonal therapy, while TP53 alterations were enriched and associated with shorter overall survival. Residual tumor fraction after chemohormonal therapy was linked to higher expression of androgen receptor-regulated genes, cell cycle genes, and neuroendocrine genes, suggesting persistent populations of active prostate cancer cells. Supervised clustering of post-treated high-tumor-fraction tissues identified a group of patients with elevated cell cycle-related gene expression and poor clinical outcomes. CONCLUSIONS: Distinct recurrent prostate cancer genomic and transcriptomic features are observed after exposure to docetaxel and androgen deprivation therapy. Tumor fraction assessed by DNA sequencing quantifies pathologic response and could be a useful trial endpoint or prognostic biomarker. TP53 alterations and high cell cycle transcriptomic activity are linked to aggressive residual disease, despite potent chemohormonal therapy.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.075
GPT teacher head0.433
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

Citations9
Published2023
Admission routes2
Has abstractyes

Explore more

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