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Record W7117355659 · doi:10.1016/j.euros.2025.12.011

Downregulation of ANPEP Is Associated with Aggressive Prostate Cancer and Poor Disease-specific Outcomes

2025· article· en· W7117355659 on OpenAlexaff
Ryan M. Putney, Purvish Trivedi, Shivanshu Awasthi, Amparo Serna, Jasreman Dhillon, Christopher J. Sweeney, R. Jeffrey Karnes, Matthew R. Cooperberg, Alejandro G Berlin, Paul L. Nguyen, Daniel E. Spratt, Elai Davicioni, James Proudfoot, Monica Ryu, Esther N. Katende, Jong Y. Park, Timothy R. Rebbeck, Asmaa El-Kenawi

Bibliographic record

VenueEuropean Urology Open Science · 2025
Typearticle
Languageen
FieldMedicine
TopicPeptidase Inhibition and Analysis
Canadian institutionsUniversity of Toronto
FundersNational Cancer InstituteNational Institutes of HealthMoffitt Cancer CenterU.S. Department of Defense
KeywordsProstate cancerDownregulation and upregulationDiseaseCancerAminopeptidase

Abstract

fetched live from OpenAlex

Our study findings indicate that ANPEP is linked to markers that indicate a more aggressive disease profile, and that its expression may serve as a prognostic factor for treatment response, with higher levels of ANPEP associated with more favorable outcomes. We conclude that ANPEP expression is strongly linked to aggressive tumor biology, while loss of ANPEP expression may indicate an aggressive prostate cancer phenotype. Aminopeptidase N (ANPEP) is linked to malignancy in certain tumor types, but its role in aggressive prostate cancer (PCa) is less well defined. Our aim was to characterize ANPEP expression in various PCa stages to determine whether it is a robust prognostic biomarker of aggressive disease. We established baseline ANPEP expression in benign prostate tissue using multiple large databases. Next, we determined the association between ANPEP expression and various clinicopathologic features and molecular subtypes using ∼170 000 tumor samples from the GRID registry. We calculated median expression values, and reported standardized mean differences. We used receiver operating characteristic and Cox regression analyses to evaluate the diagnostic and prognostic significance of ANPEP for several endpoints, and performed preranked gene set enrichment analysis (GSEA) to identify biological pathways over-represented by race or ANPEP category according to hallmark gene sets. ANPEP expression was higher in normal prostate tissues than in prostate tumors. Advanced clinical stage, higher National Comprehensive Cancer Network risk category, and worse Gleason grade group were all associated with lower median ANPEP expression. Genomic markers of aggressive PCa, such as high Decipher scores, low androgen receptor (AR) activity, ERG overexpression, and loss of PTEN expression, were correlated with lower ANPEP expression. Among patients with locally advanced or metastatic PCa, higher ANPEP expression was significantly associated with more favorable PCa-specific outcomes, including biochemical recurrence, distant metastasis, castration-resistant PCa, and overall survival. GSEA revealed AR upregulation for the ANPEP-high group and men with genomic-derived African race. Conversely, the G 2 -M DNA damage checkpoint and MYC target genes were enriched in the ANPEP-low and genomic-derived European race groups. Our findings show that ANPEP downregulation is linked to a more aggressive PCa phenotype. Higher ANPEP levels were associated with more favorable outcomes, thereby, establishing ANPEP expression as a prognostic factor for treatment response. We looked at levels of a protein called aminopeptidase N (ANPEP) in prostate tumors using information from large databases. We found that ANPEP is linked to markers that indicate more aggressive disease and that higher ANPEP levels are associated with more favorable treatment outcomes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.046
Threshold uncertainty score0.330

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.307
Teacher spread0.286 · 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 teacher head, 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

Citations0
Published2025
Admission routes1
Has abstractyes

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