Hsp27 Regulates Epithelial Mesenchymal Transition, Metastasis, and Circulating Tumor Cells in Prostate Cancer
Bibliographic record
Abstract
Defining the mechanisms underlying metastatic progression of prostate cancer may lead to insights into how to decrease morbidity and mortality in this disease. An important determinant of metastasis is epithelial-to-mesenchymal transition (EMT), and the mechanisms that control the process of EMT in cancer cells are still emerging. Here, we report that the molecular chaperone Hsp27 (HSPB1) drives EMT in prostate cancer, whereas its attenuation reverses EMT and decreases cell migration, invasion, and matrix metalloproteinase activity. Mechanistically, silencing Hsp27 decreased IL-6-dependent STAT3 phosphorylation, nuclear translocation, and STAT3 binding to the Twist promoter, suggesting that Hsp27 is required for IL-6-mediated EMT via modulation of STAT3/Twist signaling. We observed a correlation between Hsp27 and Twist in patients with prostate cancer, with Hsp27 and Twist expression each elevated in high-grade prostate cancer tumors. Hsp27 inhibition by OGX-427, an antisense therapy currently in phase II trials, reduced tumor metastasis in a murine model of prostate cancer. More importantly, OGX-427 treatment decreased the number of circulating tumor cells in patients with metastatic castration-resistant prostate cancer in a phase I clinical trial. Overall, this study defines Hsp27 as a critical regulator of IL-6-dependent and IL-6-independent EMT, validating this chaperone as a therapeutic target to treat metastatic 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".