Androgen Glucuronidation: An Unexpected Target for Androgen Deprivation Therapy, with Prognosis and Diagnostic Implications
Bibliographic record
Abstract
Androgen deprivation therapy (ADTh) remains a mainstay of prostate cancer treatment, but its efficacy is bypassed by mechanisms that are not fully understood. In human prostate cancer cells, androgen glucuronidation, catalyzed by the two UDP-glucuronosyltransferase (UGT) enzymes UGT2B15 and UGT2B17, is the major androgen inactivation pathway. In this study, we investigated the effect of ADTh on androgen glucuronidation to evaluate its potential clinical utility for prostate cancer prognosis or therapy. UGT2B15 and UGT2B17 expression was evaluated in prostate cancer specimens from untreated or treated patients and in cell models of prostate cancer exposed to clinically relevant antiandrogens. UGT2B15 and UGT2B17 protein levels in prostate were increased after 5 months of ADTh when compared with specimens from untreated patients. UGT2B15 expression remained elevated for up to 12 months, but UGT2B17 returned to initial levels as soon as after 6 months. Several androgen receptor (AR) antagonists tested caused a dose- and time-dependent stimulation of UGT2B15 and UGT2B17 expression and androgen glucuronidation in prostate cancer cell lines. The role of AR in these regulatory events was confirmed using AR-deficient LNCaP cells, in which UGT2B attenuation reduced the antiproliferative effects of AR pharmacologic antagonists. Through this combination of clinical and functional investigations, our work revealed that ADTh stimulates a local androgen metabolism in prostate cells, establishing a foundation to evaluate the potential of UGT2B15 and UGT2B17 as drug targets and/or molecular markers for ADTh responsiveness and maintenance in prostate cancer.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".