Androgen receptor targeted therapies in castration‐resistant prostate cancer: Bench to clinic
Bibliographic record
Abstract
The androgen receptor is a transcription factor and validated therapeutic target for prostate cancer. Androgen deprivation therapy remains the gold standard treatment, but it is not curative, and eventually the disease will return as lethal castration-resistant prostate cancer. There have been improvements in the therapeutic landscape with new agents approved, such as abiraterone acetate, enzalutamide, sipuleucel-T, cabazitaxel and Ra-223, in the past 5 years. New insight into the mechanisms of resistance to treatments in advanced disease is being and has been elucidated. All current androgen receptor-targeting therapies inhibit the growth of prostate cancer by blocking the ligand-binding domain, where androgen binds to activate the receptor. Persuasive evidence supports the concept that constitutively active androgen receptor splice variants lacking the ligand-binding domain are one of the resistant mechanisms underlying advanced disease. Transcriptional activity of the androgen receptor requires a functional AF-1 region in its N-terminal domain. Preclinical evidence proved that this domain is a druggable target to forecast a potential paradigm shift in the management of advanced prostate cancer. This review presents an overview of androgen receptor-related mechanisms of resistance as well as novel therapeutic agents to overcome resistance that is linked to the expression of androgen receptor splice variants in castration-resistant 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".