Targeting Alternative Sites on the Androgen Receptor to Treat Castration-Resistant Prostate Cancer
Bibliographic record
Abstract
Recurrent, metastatic prostate cancer continues to be a leading cause of cancer-death in men. The androgen receptor (AR) is a modular, ligand-inducible transcription factor that regulates the expression of genes that can drive the progression of this disease, and as a consequence, this receptor is a key therapeutic target for controlling prostate cancer. The current drugs designed to directly inhibit the AR are called anti-androgens, and all act by competing with androgens for binding to the androgen/ligand binding site. Unfortunately, with the inevitable progression of the cancer to castration resistance, many of these drugs become ineffective. However, there are numerous other regulatory sites on this protein that have not been exploited therapeutically. The regulation of AR activity involves a cascade of complex interactions with numerous chaperones, co-factors and co-regulatory proteins, leading ultimately to direct binding of AR dimers to specific DNA androgen response elements within the promoter and enhancers of androgen-regulated genes. As part of the family of nuclear receptors, the AR is organized into modular structural and functional domains with specialized roles in facilitating their inter-molecular interactions. These regions of the AR present attractive, yet largely unexploited, drug target sites for reducing or eliminating androgen signaling in prostate cancers. The design of small molecule inhibitors targeting these specific AR domains is only now being realized and is the culmination of decades of work, including crystallographic and biochemistry approaches to map the shape and accessibility of the AR surfaces and cavities. Here, we review the structure of the AR protein and describe recent advancements in inhibiting its activity with small molecules specifically designed to target areas distinct from the receptor's androgen binding site. It is anticipated that these new classes of anti-AR drugs will provide an additional arsenal to treat 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".