Deletions of the Androgen-Metabolizing<i>UGT2B</i>Genes Have an Effect on Circulating Steroid Levels and Biochemical Recurrence after Radical Prostatectomy in Localized Prostate Cancer
Bibliographic record
Abstract
CONTEXT: The prognostic relevance of inherited variations in hormone-related genes in the context of prostate cancer (PCa) progression has not been well studied. Of these, UDP-glucuronosyltransferase (UGT) gene products lead to inactivation of steroids. OBJECTIVE: Our objective was to determine whether polymorphisms in five UGT genes, involved in steroid metabolism, are associated with the risk of biochemical recurrence after radical prostatectomy (RP) and to examine their relationship with hormonal exposure. DESIGN: The study included 526 Caucasian and 320 Asian men who underwent RP for clinically localized PCa. The relationship between genotypes and biochemical recurrence were assessed with multivariate Cox proportional hazard models. Plasma steroids were measured using specific and sensitive mass spectrometry-based methods. RESULTS: The presence of at least two deleted copies of UGT2B17 and UGT2B28 genes resulted in a hazard ratio of 2.26 (95% confidence interval = 1.41-3.61; P = 0.0007) for Caucasians and 2.16 (95% confidence interval = 1.24-3.73; P = 0.006) for Asians. A positive association was observed only between UGT2B17 deletion and the Gleason score in Asians, whereas no other interaction was shown with prostate-specific antigen, Gleason score, and TNM (tumor node metastasis) staging. Patients carrying UGT2B17 deletions and those with three deleted UGT2B copies had significantly lower androgen glucuronides, in support of an altered androgen metabolism. CONCLUSION: This study is the first to recognize the prognostic significance of common deletions in steroid inactivation pathways in localized PCa after RP. Alteration of circulating steroid levels associated with UGT2B gene deletions further support the notion that such inherited genomic deletions have the potential to modify hormonal exposure and risk of recurrence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".