Inhibition of androgen receptor by decoy molecules delays progression to castration-recurrent prostate cancer
Bibliographic record
Abstract
Androgen receptor (AR) is a member of the steroid receptor family and a therapeutic target for all stages of prostate cancer. AR is activated by ligand binding within its C-terminus ligand-binding domain (LBD). Here we show that overexpression of the AR NTD to generate decoy molecules inhibited both the growth and progression of prostate cancer in castrated hosts. Specifically, it was shown that lentivirus delivery of decoys delayed hormonal progression in castrated hosts as indicated by increased doubling time of tumor volume, prolonged time to achieve pre-castrate levels of serum prostate-specific antigen (PSA) and PSA nadir. These clinical parameters are indicative of delayed hormonal progression and improved therapeutic response and prognosis. Decoys reduced the expression of androgen-regulated genes that correlated with reduced in situ interaction of the AR with androgen response elements. Decoys did not reduce levels of AR protein or prevent nuclear localization of the AR. Nor did decoys interact directly with the AR. Thus decoys did not inhibit AR transactivation by a dominant negative mechanism. This work provides evidence that the AR NTD plays an important role in the hormonal progression of prostate cancer and supports the development of AR antagonists that target the AR NTD.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".