Increased PrLZ-mediated androgen receptor transactivation promotes prostate cancer growth at castration-resistant stage
Bibliographic record
Abstract
Most advanced prostate cancers (PCa) will develop into the castration-resistant stage following androgen deprivation therapy, yet the molecular mechanisms remain unclear. In this study, we found PrLZ, a newly identified Prostate Leucine Zipper gene that is highly expressed in PCa could interact with the androgen receptor (AR) directly leading to enhance AR transactivation in the castration-resistant condition. PrLZ might enhance AR transactivation via a change of AR conformation that leads to promotion of AR nuclear translocation and suppression of AR degradation via modulating the proteasome pathway, which resulted in increased prostate-specific antigen expression and promoted PCa growth at the castration-resistant stage. Clinical PCa sample survey from same-patient paired specimens found increased PrLZ expression in castration-resistant PCa following the classical androgen deprivation therapy. Targeting the AR-PrLZ complex via ASC-J9® or PrLZ-siRNA resulted in suppression of PCa growth in various human PCa cells and in vivo mouse PCa models. Together, these data not only strengthen PrLZ roles in the transition from androgen dependence to androgen independence during the castration-resistant stage, but they may also provide a new potential therapy to battle PCa at the castration-resistant stage.
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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".