Lyn tyrosine kinase regulates androgen receptor expression and activity in castrate-resistant prostate cancer
Bibliographic record
Abstract
Castrate-resistant prostate cancer (CRPC) progression is a complex process by which prostate cells acquire the ability to survive and proliferate in the absence or under very low levels of androgens. Most CRPC tumors continue to express the androgen receptor (AR) as well as androgen-responsive genes owing to reactivation of AR. Protein tyrosine kinases have been implicated in supporting AR activation under castrate conditions. Here we report that Lyn tyrosine kinase expression is upregulated in CRPC human specimens compared with hormone naive or normal tissue. Lyn overexpression enhanced AR transcriptional activity both in vitro and in vivo and accelerated CRPC. Reciprocally, specific targeting of Lyn resulted in a decrease of AR transcriptional activity in vitro and in vivo and prolonged time to castration. Mechanistically, we found that targeting Lyn kinase induces AR dissociation from the molecular chaperone Hsp90, leading to its ubiquitination and proteasomal degradation. This work indicates a novel mechanism of regulation of AR stability and transcriptional activity by Lyn and justifies further investigation of the Lyn tyrosine kinase as a therapeutic target for the treatment of CRPC.Oncogenesis (2014) 3, e115; doi:10.1038/oncsis.2014.30; published online 18 August 2014.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".