Increased Hsp27 after Androgen Ablation Facilitates Androgen-Independent Progression in Prostate Cancer via Signal Transducers and Activators of Transcription 3–Mediated Suppression of Apoptosis
Bibliographic record
Abstract
One strategy to improve therapies in prostate cancer involves targeting cytoprotective genes activated by androgen withdrawal to delay the emergence of the androgen-independent (AI) phenotype. The objectives of this study were to define changes in Hsp27 levels after androgen ablation and to evaluate the functional relevance of these changes in AI progression. Using a tissue microarray of 232 specimens of hormone-naïve and post-hormone ablation-treated prostate cancer, we found that Hsp27 levels increase after androgen ablation to become highly expressed (>4-fold, P < or = 0.01) in AI tumors. Hsp27 overexpression rendered LNCaP cells highly resistant to androgen withdrawal both in vitro and in vivo. Tumor volume and serum prostate-specific antigen levels increased 4.3- and 10-fold faster after castration when Hsp27 was overexpressed. Treatment of LNCaP tumor cells in vitro with Hsp27 antisense oligonucleotides (ASO) or short-interfering RNA suppressed Hsp27 levels in a dose-dependent and sequence-specific manner increased the apoptotic sub-G0-G1 fraction and caspase-3 cleavage >2-fold, as well as decreased signal transducers and activators of transcription 3 (Stat3) levels and its downstream genes, c-fos and sPLA-2. The cytoprotection afforded by Hsp27 overexpression was attenuated by Stat3 knockdown using specific Stat3 ASO. Coimmunoprecipitation and immunofluorescence confirmed that Hsp27 interacts with Stat3 and that Stat3 levels correlated directly with Hsp27 levels. Hsp27 ASO treatment in athymic mice bearing LNCaP tumors significantly delayed LNCaP tumor growth after castration, decreasing mean tumor volume and serum prostate-specific antigen levels by 57% and 69%, respectively. These findings identify Hsp27 as a modulator of Stat3-regulated apoptosis after androgen ablation and as a potential therapeutic target in advanced 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) | 0.000 | 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) | 0.001 | 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".