Galectin-3 Overrides PTRF/Cavin-1 Reduction of PC3 Prostate Cancer Cell Migration
Bibliographic record
Abstract
Expression of Caveolin-1 (Cav1), a key component of cell surface caveolae, is elevated in prostate cancer (PCa) and associated with PCa metastasis and a poor prognosis for PCa patients. Polymerase I and Transcript Release Factor (PTRF)/cavin-1 is a cytoplasmic protein required for Cav1-dependent formation of caveolae. Expression of PTRF reduces the motility of PC3 cells, a metastatic prostate cancer cell line that endogenously expresses abundant Cav1 but no PTRF and no caveolae, suggesting a role for non-caveolar Cav1 domains, or Cav1 scaffolds, in PCa cell migration. Tyrosine phosphorylated Cav1 (pCav1) functions in concert with Galectin-3 (Gal3) and the galectin lattice to stabilize focal adhesion kinase (FAK) within focal adhesions (FAs) and promote cancer cell motility. However, whether PTRF regulation of Cav1 function in PCa cell migration is related to Gal3 expression and functionality has yet to be determined. Here we show that PTRF expression in PC3 cells reduces FAK stabilization in focal adhesions and reduces cell motility without affecting pCav1 levels. Exogenous Gal3 stabilized FAK in focal adhesions of PTRF-expressing cells and restored cell motility of PTRF-expressing PC3 cells to levels of PC3 cells in a dose-dependent manner, with an optimal concentration of 2 µg/ml. Exogenous Gal3 stabilized FAK in focal adhesions of Gal3 knockdown PC3 cells but not in Cav1 knockdown PC3 cells. Cav1 knockdown also prevented Gal3 rescue of FA-associated FAK stabilization in PTRF-expressing PC3 cells. Our data support a role for PTRF/cavin-1, through caveolae formation, as an attenuator of the non-caveolar functionality of Cav1 in Gal3-Cav1 signalling and regulation of focal adhesion dynamics and cancer cell migration.
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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 | 0.001 |
| 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) | 0.002 | 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".