Vimentin-mediated buffering of internal integrin β1 pool increases survival of cells from anoikis
Bibliographic record
Abstract
BACKGROUND: The intermediate filament protein vimentin is widely recognized as a molecular marker of epithelial-to-mesenchymal transition. Although vimentin expression is strongly associated with cancer metastatic potential, the exact role of vimentin in cancer metastasis and the underlying mechanism of its pro-metastatic functions remain unclear. RESULTS: This study revealed that vimentin can enhance integrin β1 surface expression and induce integrin-dependent clustering of cells, shielding them against anoikis cell death. The increased integrin β1 surface expression in suspended cells was caused by vimentin-mediated protection of the internal integrin β1 pool against lysosomal degradation. Additionally, cell detachment was found to induce vimentin Ser38 phosphorylation, allowing the translocation of internal integrin β1 to the plasma membrane. Furthermore, the use of an inhibitor of p21-activated kinase PAK1, one of the kinases responsible for vimentin Ser38 phosphorylation, significantly reduced cancer metastasis in animal models. CONCLUSIONS: These findings suggest that vimentin can act as an integrin buffer, storing internalized integrin β1 and releasing it when needed. Overall, this study provides insights regarding the strong correlation between vimentin expression and cancer metastasis and a basis for blocking metastasis using this novel therapeutic mechanism.
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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".