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Record W4409634813 · doi:10.1158/1538-7445.am2025-4656

Abstract 4656: Fatty acid β-oxidation enzyme ECI1: a biomarker of poor survival outcome in prostate cancer patients after transurethral resection of the prostate (TURP)

2025· article· en· W4409634813 on OpenAlexaff
Karl‐Philippe Guérard, Elie Fadel, Ryan Antel, Fadi Brimo, Tarek A. Bismar, Jacques Lapointe

Bibliographic record

VenueCancer Research · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Lipids, and Metabolism
Canadian institutionsUniversity of CalgaryMcGill University
Fundersnot available
KeywordsProstate cancerMedicineTransurethral resection of the prostateProstateUrologyResectionBiomarkerOncologyInternal medicineProstatectomyCancerSurgeryChemistry

Abstract

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Deregulated mitochondrial fatty acid β-oxidation is known to drive prostate cancer (PCa) pathogenesis. ECI1 (Δ3, Δ2-Enoyl-CoA Delta Isomerase 1) is a key mitochondrial fatty acid β-oxidation enzyme whose role in PCa remains to be explored. We recently showed the impacts of ECI1 on PCa phenotype by modulating its expression in cell lines and assessed the clinical implications of its expression in human prostate tissue samples. ECI1 overexpression increased PCa cell growth and enhanced colony formation, cell motility, and maximal mitochondrial respiratory capacity. PCa cells stably overexpressing ECI1 injected orthotopically in nude mice formed larger prostate tumors with higher number of metastases. Immunohistochemistry analysis of a tissue microarray representing radical prostatectomy cases revealed a stronger ECI1 staining in prostate tumors compared to corresponding benign tissues. ECI1 expression was higher in cases with high tumor grade and advanced tumor stage. ECI1 overexpression was a strong independent predictor of biochemical recurrence after adjusting for known clinicopathologic parameters. ECI1 overexpression was also associated with increased risk of distant metastasis and reduced overall survival, suggesting a key role in disease progression. The purpose of this study was to assess the prognostic value ECI1 expression in PCa tissue on overall survival of patients who underwent palliative transurethral resection of the prostate (TURP). ECI1 immunohistochemistry was performed on a tissue microarray representing 257 TURP cases. ECI1 staining of malignant epithelial cells was assessed using the H-score method and patients were dichotomized into two groups based on ECI1 expression (high vs low). ECI1 overexpression was associated with an increased risk of death, which remained significant after adjusting for age and tumor grade group (hazard ratio=1.57, P=0.01). Moreover, a subgroup of this cohort considered of favorable survival outcome according to their PTEN positive and ERG negative tumor expression statuses (n=121) were further risk stratified by ECI1 even after adjusting for age and tumor grade group (hazard ratio =2.26, P=0.004). Overall, this study supports the contribution of ECI1 to PCa progression and highlights its potential as biomarker to identify patients at high risk of death among those who underwent a palliative TURP procedure. Future studies should explore whether the ECI1 metabolic pathway may serve as therapeutic target to improve patient survival and quality of life. Citation Format: Karl-Philippe Guérard, Elie Fadel, Ryan Antel, Fadi Brimo, Tarek Bismar, Jacques Lapointe. Fatty acid β-oxidation enzyme ECI1: a biomarker of poor survival outcome in prostate cancer patients after transurethral resection of the prostate (TURP) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4656.

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 score0.006

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)0.0020.000

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 head0.032
GPT teacher head0.363
Teacher spread0.331 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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