RETRACTED: Hsp27 regulates EGF/β‐catenin mediated epithelial to mesenchymal transition in prostate cancer
Post-publication record
OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.
Bibliographic record
Abstract
Increased expression of the molecular chaperone Hsp27 is associated with the progression of prostate cancer (PCa) to castration-resistant disease, which is lethal due to metastatic spread of the prostate tumor. Metastasis requires epithelial to mesenchymal transition (EMT), which endows cancer cells with the ability to disseminate from the primary tumor and colonize new tissue sites. A wide variety of secreted factors promote EMT, and while overexpression and constitutive activation of epidermal growth factor (EGF) signaling is associated with poor prognosis of PCa, a precise role of EGF in PCa progression to metastasis remains unclear. Here, we show that Hsp27 is required for EGF-induced cell migration, invasion and MMPs activity as well as the expression of EMT markers including Fibronectin, Vimentin and Slug with concomitant decrease of E-cadherin. Mechanistically, we found that Hsp27 is required for EGF-induced AKT and GSK3β phosphorylation and β-catenin nuclear translocation. Moreover, silencing Hsp27 decreases EGF dependent phosphorylation of β-catenin on tyrosine 142 and 654, enhances β-catenin ubiquitination and degradation, prevents β-catenin nuclear translocation and binding to the Slug promoter. These data suggest that Hsp27 is required for EGF-mediated EMT via modulation of the β-catenin/Slug signaling pathway. Together, our findings underscore the importance of Hsp27 in EGF induced EMT in PCa and highlight the use of Hsp27 knockdown as a useful strategy for patients with advanced disease.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.052 | 0.017 |
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".