Exploiting the tumor-suppressive activity of the androgen receptor by CDK4/6 inhibition in castration-resistant prostate cancer
Bibliographic record
Abstract
The androgen receptor (AR) plays a pivotal role in driving prostate cancer (PCa) development. However, when stimulated by high levels of androgens, AR can also function as a tumor suppressor in PCa cells. While the high-dose testosterone (high-T) treatment is currently being tested in clinical trials of castration-resistant prostate cancer (CRPC), there is still a pressing need to fully understand the underlying mechanism and thus develop treatment strategies to exploit this tumor-suppressive activity of AR. In this study, we demonstrate that retinoblastoma (Rb) family proteins play a central role in maintaining the global chromatin binding and transcriptional repression program of AR and that Rb inactivation desensitizes CRPC to the high-dose testosterone treatment in vitro and in vivo. Using a series of patient-derived xenograft (PDX) CRPC models, we further show that the efficacy of high-T treatment can be fully exploited by a CDK4/6 inhibitor, which strengthens the chromatin binding of the Rb-E2F repressor complex by blocking the hyperphosphorylation of Rb proteins. Overall, our study provides strong mechanistic and preclinical evidence on further developing clinical trials to combine high-T with CDK4/6 inhibitors in treating CRPC.
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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) | 0.002 | 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".