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Record W4245712234 · doi:10.5489/cuaj.1296

Unmoderated Poster Sessions: Oncology-Prostate

2013· article· en· W4245712234 on OpenAlexvenueno aff
CUAJ Editorial Office

Bibliographic record

VenueCanadian Urological Association Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsProstateMedicineMedical physicsOncologyInternal medicineCancer

Abstract

fetched live from OpenAlex

Introduction and Objectives: Mechanisms underlying prostate cancer (Pca) progression from an androgen-responsive to a refractory (castration-resistant) stage prove to be challenging and still poorly understood.Heterogeneity regarding tumor cell sensitivity to androgens may play an important role.Indeed by responding to diverse growth-promoting factors such as interleukin (IL)-6, tumor cells expressing the androgen receptor (AR) may adapt while subsets of AR(-) cells may concomitantly be selected.We identified Fer as the major tyrosine kinase implicated in the IL-6-mediated activation of STAT3 (the signal transducer and activator of transcription) that controls growth of human metastatic Pca cell lines, both AR(+) and AR(-).Moreover, Fer is implicated in cross-talks between IL-6 and AR signaling pathways in AR(+) tumor cells and controls AR-dependent genes.Since Fer is up-regulated in Pca, the aim was to test the hypothesis of an active pathway implicating pairs such as Fer/pSTAT3, Fer/AR, pSTAT3/AR in prostate cancer tissues from patients with advanced disease.Methods: Paraffin-embedded blocks of prostate tissues obtained by TURP from hormone-treated patients (n=29) were retrieved from pathology.Consecutive sections were processed to stain Fer, pSTAT3, and AR by immunohistochemistry. Tumor cell staining was quantified by percentage and intensity and used to calculate H scores. Significance of correlations was analyzed through the Spearman Rho's method.Results: Each TURP case was of good quality for immunohistochemistry.All three markers were primarily found in the nucleus.Overall, 97% (28/29) of cases were AR(+), 86% (25/29) of cases were Fer (+) and 83% (24/29) of cases were pSTAT3(+).A single case was AR(-), while positive for Fer and pSTAT3.Within each case, a majority of tumor cells were AR(+).Yet single cell analysis revealed the tumor heterogeneous nature with respect to AR.Indeed, all specimens contain AR(-) cells, the mean being 17%, interspersed among AR(+) cells.The analysis of pairs of markers revealed no correlation between AR and pSTAT3, and between Fer and AR.Nonetheless, Fer and pSTAT3 were strongly correlated, in both percentages of stained cells (p<0.01) and H score (p<0.0001), and regardless of the tumor cell AR status.In the end, Fer was expressed along with pSTAT3 in both AR(+) and AR(-) cells in 79% of cases.Conclusion: The co-expression of Fer and activated STAT3 in advanced prostate cancer supports that aberrant Fer signaling favors adaptation and selection of tumor cells during progression towards hormone-refractory disease.Supported by Prostate Cancer Canada.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.704
Threshold uncertainty score0.422

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.7040.429

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 head0.012
GPT teacher head0.248
Teacher spread0.236 · 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.

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
Published2013
Admission routes1
Has abstractyes

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