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Genomic alterations and their pathologic responses in high-risk localized prostate cancer (HRLPC) in subprotocol 1 of the Genomic Umbrella Neoadjuvant study (GUNS).

2025· article· en· W4407701510 on OpenAlexafffundabout
Martin Gleave, Eric C. Bélanger, Joshua Scurll, Htoo Zarni Oo, Lucia Nappi, Himisha Beltran, Alexander W. Wyatt, Miles Mannas, Peter Black, Amina Zoubeidi, Jonathan Ma, Doron Berlin, Tiiu Sildva, Theodorus van der Kwast, Neil Fleshner

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsPrincess Margaret Cancer CentreVancouver Coastal HealthUniversity Health NetworkUniversity of British Columbia
FundersJohnson and JohnsonTerry Fox Research Institute
KeywordsMedicineProstate cancerGenome instabilityCancerProstateOncologyCancer researchPathologyInternal medicineGeneticsBiologyDNA damageDNA

Abstract

fetched live from OpenAlex

403 Background: GUNS (NCT04812366) is a multicenter adaptive phase II trial evaluating 24 weeks of biomarker-selected, neoadjuvant androgen receptor pathway inhibitor (ARPI) combination therapies on depth of pathologic response (complete response [pCR] or <5 mm minimal residual disease [MRD]) in HRLPC. After 8 weeks of LHRHa + apalutamide (APA), participants are assigned to 1 of 4 sub-protocols (SP) combining 16 weeks of an ARPI doublet with drugs defined by specific genomic alterations (e.g. SP-2, docetaxel for RB1 , PTEN , TP53 loss; SP-3, niraparib for DNA-repair def ; SP-4, atezolizumab for mismatch-repair def ). SP-1 randomises men without these aggressive genomic alt and includes those that enhance AR activity (ETS fusions, FOXA1 , SPOP ) to either SP-1a (LHRHa + APA) or SP-1b (LHRHa + APA + abiraterone acetate/prednisone). SP-1 tests the hypothesis that ARPI triplet intensification, in cancers with AR-associated genomic alt , will increase depth of pathologic response. Methods: From 9/2021 to 8/2024, GUNS enrolled 95 and 30 men at University of BC and Toronto, respectively. Diagnostic biopsies underwent Tempus’ CLIA-certified 648-gene panel DNA sequencing (seq) and whole-transcriptome RNA-seq. This analysis focuses on 46 men enrolled to the 1 st stage of SP-1 who completed neoadjuvant therapy and surgery. Results: DNA-seq from 105/125 patients reveals a genomic landscape dominated by AR-associated alterations ( 36% ETS fusion, 23% FOXA1, 13% SPOP ). Other frequently altered genes were TP53 (14%), PTEN (12%), and BRCA2 (9%). Transcriptomes largely cluster in alignment with ETS fusions and SPOP status. ETS fusions were associated with PCS2-luminal-subtype and decreased proliferative signatures, whereas most other genomic alt were associated with PCS1-luminal-subtype. AR signatures associated with SPOP and FOXA1 mutations but not ETS fusions. 46 men, equally balanced for high-risk features and genomic alt , were randomized to SP-1a or SP-1b. Undetectable pre-surgery PSA levels trended higher in SP-1b (16/23) vs. SP-1a (11/23), but was not statistically significant (p = 0.12). While there were no pCR, MRD rates were significantly higher in SP-1b compared to SP-1a (43% vs 13%, p=0.012, odds ratio = 5.9). Degenerative scores (morphologic indicators of treatment stress) also averaged higher in SP-1b vs. SP-1a. Positive margin (17%) and lymph node (35% vs 26%) status were similar in both arms. Although genomic PTEN alt were assigned to SP-2, 7 patients in SP-1 were found to be PTEN neg by IHC and 6 were non-MRD; PTEN-IHC neg trended more common in non-MRD (21%) than MRD (8%) cases. Conclusions: SP-1 associated genomic alt (ETS fusion, FOXA1, SPOP) are the most frequent alterations in GUNS. Significantly higher rates of MRD in SP-1 patients treated with an ARPI triplet vs. doublet are of interest and support further evaluation with 2 nd stage expansion. Clinical trial information: NCT04812366 .

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 score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.103
GPT teacher head0.489
Teacher spread0.385 · 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".

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Citations2
Published2025
Admission routes3
Has abstractyes

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