Amino-terminus domain of the androgen receptor as a molecular target to prevent the hormonal progression of prostate cancer
Bibliographic record
Abstract
Prostate cancer has a propensity to metastasize to the bone. Currently the only effective systemic treatment for these patients is androgen ablation therapy. However, the tumor will invariably progress to an androgen-independent stage and the patient will succumb to his disease within approximately 2 years. The earliest indication of hormonal progression is the rising titer of serum prostate specific antigen. Current evidence implicates the androgen receptor (AR) as a key factor in maintaining the growth of prostate cancer cells in an androgen-depleted state. Under normal conditions, binding of ligand activates the receptor, allowing it to effectively bind to its respective DNA element. However, AR is also transformed in the absence of androgen (ligand-independent activation) in prostate cells via multiple protein kinase pathways and the interleukin-6 (IL-6) pathway that converge upon the N-terminal domain of the AR. This domain is the main region for phosphorylation and is also critical for normal coregulator recruitment. Here we discuss evidence supporting the role of the AR, IL-6 and other protein kinase pathways in the hormonal progression of prostate cancer to androgen independence and the mechanisms involved in activation of the AR by these pathways. Receptor-targeted therapy, especially potential drugs targeting the N-terminal domain, may effectively prevent or delay the hormonal progression of AR-dependent 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 | 0.002 |
| 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 | 0.004 |
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".