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Record W4282946122 · doi:10.1158/1538-7445.am2022-6317

Abstract 6317: Molecular subtyping in prostate cancer associate with outcomes to abiraterone and ipatasertib treatment from the phase III IPATential150 trial

2022· article· en· W4282946122 on OpenAlexaff
Zhen Shi, Małgorzata Nowicka, Johann S. de Bono, Kim N., Christopher Sweeney, Cora N. Sternberg, David Olmos, Sergio Bracarda, Christophe Massard, Nobuaki Matsubara, Josep Garcia, Geng Chen, Matthew Wongchenko, Shahneen Sandhu

Bibliographic record

VenueCancer Research · 2022
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsProstate cancerCell cycleCancer researchCancerTranscriptomeInternal medicineProstateOncologyMedicineBiologyGeneGeneticsGene expression

Abstract

fetched live from OpenAlex

Abstract Prostate cancer is a heterogeneous disease and genomic subtyping offers an opportunity to better understand underlying disease biology. Here, we performed transcriptional profiling by RNA-Seq (n=582) and targeted genomic sequencing by FoundationONE CDx (n=743) from prostate cancer tumor specimens in the phase III IPATential150 trial of first-line ipatasertib (Ipat) plus abiraterone (Abi) in metastatic castration-resistant prostate cancer (N=1101). Unsupervised transcriptomic analysis of the 582 samples with RNA-Seq with Nonnegative Matrix Factorization (NMF) reveals four consensus subtypes. This includes an immune/cell cycle-high, an AR signature/cell cycle-high, a stroma program-enriched, and an ERG fusion-enriched subtype. Subgroups of patients with immune/cell cycle-high and AR signature/cell cycle-high tumors had the shortest radiographic progression-free survival (rPFS) and were characterized by high MYC and cell cycle-related gene signatures. Patients with AR signature/cell cycle-high tumors showed the greatest increase in rPFS with Ipat + Abi vs. Placebo (Pbo) + Abi (HR = 0.58). Cluster n Enriched processes Median rPFS (Pbo + Abi) (months, 95% CI) Median rPFS (Ipat + Abi) (months, 95% CI) HR (95% CI) NMF1 84 Immune processes, metabolism, cell cycle 10.3 (8.3 - 12.7) 13.9 (10.9 - 16.4) 0.77 (0.47 - 1.28) NMF2 165 Androgen response signature, cell cycle, MYC signature 11.9 (8.8 - 16.5) 20.9 (16.4 - NA) 0.58 (0.38 - 0.90) NMF3 156 Fibroblast, Wnt, Notch, Hedgehog, TGFb 20.0 (16.4 - NA) 22.3 (15.6 - 24.9) 0.96 (0.59 - 1.56) NMF4 177 ERG fusion 18.4 (13.8 - 23.8) 24.7 (16.2 - NA) 0.78 (0.50 - 1.20) Citation Format: Zhen Shi, Malgorzata Nowicka, Johann de Bono, Kim N. Chi, Christopher Sweeney, Cora N. Sternberg, David Olmos, Sergio Bracarda, Christophe Massard, Nobuaki Matsubara, Josep Garcia, Geng Chen, Matthew Wongchenko, Shahneen K. Sandhu. Molecular subtyping in prostate cancer associate with outcomes to abiraterone and ipatasertib treatment from the phase III IPATential150 trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6317.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.003
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)0.0030.000

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 head0.105
GPT teacher head0.448
Teacher spread0.343 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2022
Admission routes1
Has abstractyes

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