Cotargeting Stress-Activated Hsp27 and Autophagy as a Combinatorial Strategy to Amplify Endoplasmic Reticular Stress in Prostate Cancer
Bibliographic record
Abstract
Hsp27 is a stress-activated multifunctional chaperone that inhibits treatment-induced apoptosis and causes treatment resistance in prostate and other cancers. We previously showed that targeted suppression of Hsp27 sensitizes cancer cells to hormone and chemotherapy. However, mechanisms by which Hsp27 confers cell treatment resistance are incompletely defined. Here, we report that Hsp27 protects human prostate cancer cells against proteotoxic stress induced by proteasome inhibition, and that Hsp27 silencing using siRNA or antisense (OGX-427) induced both apoptosis and autophagy through mechanisms involving reduced proteasome activity and induction of endoplasmic reticulum (ER) stress. We found that autophagy activation protected against ER stress-induced cell death, whereas inhibition of autophagy activation following Hsp27 silencing using either pharmacologic inhibitors or atg3 silencing enhanced cell death. Importantly, cotargeting Hsp27 and autophagy by combining OGX-427 with the autophagy inhibitor, chloroquine, significantly delayed PC-3 prostate tumor growth in vivo. These findings identify autophagy as a cytoprotective, stress-induced adaptive pathway, activated following disruption of protein homeostasis and ER stress induced by Hsp27 silencing. Combinatorial cotargeting cytoprotective Hsp27 and autophagy illustrates potential benefits of blocking activation of adaptive pathways to improve treatment outcomes in cancer.
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 | 0.000 | 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 | 0.001 |
| 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".