Co‐operative effect of c‐Src and ezrin in deregulation of cell–cell contacts and scattering of mammary carcinoma cells
Bibliographic record
Abstract
The non-receptor tyrosine kinase c-Src is activated in many human cancer types, and induces deregulation of cadherin-based cell-cell contacts and actin cytoskeleton. Because ezrin, a protein which cross-links the plasma membrane with the actin cytoskeleton, is often over-expressed in human cancers, and participates in cell adhesion, motility, and cell scattering, we therefore investigated whether c-Src co-operates with ezrin in regulating cell-cell contacts in a murine mammary carcinoma cell line, SP1. SP1 cells over-expressing wild type ezrin, or an activated c-Src mutant, formed loose aggregates which scattered spontaneously when plated on plastic. When wild type ezrin and activated c-Src were co-expressed, scattering was increased, cell-cell contacts disrupted, and cell aggregation prevented. Pre-treatment with the c-Src family kinase inhibitor PP2 partially restored aggregation of cells expressing activated c-Src and wild type ezrin, indicating that c-Src family kinases act co-operatively with ezrin in regulating cell-cell contacts. Furthermore, expression of a truncated NH2-terminal domain of ezrin, which has dominant negative function, blocked the cell scattering effect of activated c-Src and promoted formation of cohesive cell-cell contacts. Together, these results suggest co-operativity between c-Src and ezrin in deregulation of cell-cell contacts and enhancing scattering of mammary carcinoma cells.
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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".