Data from Phosphorylated Caveolin-1 Regulates Rho/ROCK-Dependent Focal Adhesion Dynamics and Tumor Cell Migration and Invasion
Bibliographic record
Abstract
Abstract Rho/ROCK signaling and caveolin-1 (Cav1) are implicated in tumor cell migration and metastasis; however, the underlying molecular mechanisms remain poorly defined. Cav1 was found here to be an independent predictor of decreased survival in breast and rectal cancer and significantly associated with the presence of distant metastasis for colon cancer patients. Rho/ROCK signaling promotes tumor cell migration by regulating focal adhesion (FA) dynamics through tyrosine (Y14) phosphorylation of Cav1. Phosphorylated Cav1 is localized to protrusive domains of tumor cells and Cav1 tyrosine phosphorylation is dependent on Src kinase and Rho/ROCK signaling. Increased levels of phosphorylated Cav1 were associated with elevated GTP-RhoA levels in metastatic tumor cells of various tissue origins. Stable expression and knockdown studies of Cav1 in tumor cells showed that phosphorylated Cav1 expression stimulates Rho activation, stabilizes FAK association with FAs, and promotes cell migration and invasion in a ROCK-dependent and Src-dependent manner. Tyrosine-phosphorylated Cav1, therefore, functions as an effector of Rho/ROCK signaling in the regulation of FA turnover and, thereby, tumor cell migration and invasion. These studies define a feedback loop between Rho/ROCK, Src, and phosphorylated Cav1 in tumor cell protrusions, identifying a novel function for Cav1 in tumor metastasis that may contribute to the poor prognosis of some Cav1-expressing tumors. [Cancer Res 2008;68(20):8210–20]
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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".