Dysregulated fibronectin trafficking by Hsp90 inhibition restricts prostate cancer cell invasion
Bibliographic record
Abstract
The molecular chaperone Hsp90 is overexpressed in prostate cancer (PCa) and is responsible for the folding, stabilization and maturation of multiple oncoproteins, which are implicated in PCa progression. Compared to first-in-class Hsp90 inhibitors such as 17-allylamino-demethoxygeldanamycin (17-AAG) that were clinically ineffective, second generation inhibitor AUY922 has greater solubility and efficacy. Here, transcriptomic and proteomic analyses of patient-derived PCa explants identified cytoskeletal organization as highly enriched with AUY922 treatment. Validation in PCa cell lines revealed that AUY922 caused marked alterations to cell morphology, and suppressed cell motility and invasion compared to vehicle or 17-AAG, concomitant with dysregulation of key extracellular matrix proteins such as fibronectin (FN1). Interestingly, while the expression of FN1 was increased by AUY922, FN1 secretion was significantly decreased. This resulted in cytosolic accumulation of FN1 protein within late endosomes, suggesting that AUY922 disrupts vesicular secretory trafficking pathways. Depletion of FN1 by siRNA knockdown markedly reduced the invasive capacity of PCa cells, phenocopying AUY922. These results highlight a novel mechanism of action for AUY922 beyond its established effects on cellular mitosis and survival and, furthermore, identifies extracellular matrix cargo delivery as a potential therapeutic target for the treatment of aggressive PCa.
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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".