Transcription Factor Stat5 Knockdown Enhances Androgen Receptor Degradation and Delays Castration-Resistant Prostate Cancer Progression <i>In vivo</i>
Bibliographic record
Abstract
Signal transducer and activator of transcription 5 (Stat5) plays an important role in the transition of prostate cancer (PCa) to its castrate-resistant state. Pharmacologic targeting of Stat5 is a rational approach to delay castrate-resistant progression, in part, because Stat5 cooperates with the androgen receptor (AR) to promote PCa progression. Immunostaining of tissue microarrays was used to correlate Stat5 expression with Gleason grade and to characterize changes in treatment-naive and androgen-deprived human PCa. Potency of a Stat5 antisense oligonucleotide (ASO) on Stat5 knockdown, cell growth, and apoptosis was assessed in LNCaP, C4-2, and DU145 cells. Effects of Stat5 knockdown on AR activity and stability was assessed using a PSA transactivation-luciferase assay and cyclohexamide plus MG132 treatment, respectively. LNCaP tumor-bearing mice were castrated and randomly assigned to treatment with Stat5-ASO or controls. Here, we show that the frequency of Stat5 expression is significantly increased in high Gleason grade as well as in hormone-treated PCa. Also, specific knockdown of Stat5 with ASO abrogates androgen-induced AR nuclear translocation and PSA transactivation despite R1881 stimulation. Moreover, Stat5 knockdown destabilizes AR, which leads to AR degradation via the proteasome. Shown for the first time as a preclinical proof-of-principle, Stat5 knockdown with Stat5-ASO significantly delays CRPC tumor progression in vivo. Thereby, we are able to recapitulate our in vitro results by reducing serum PSA and expression levels of target proteins in the xenograft tumors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".