Cbl-transforming Variants Trigger a Cascade of Molecular Alterations That Lead to Epithelial Mesenchymal Conversion
Bibliographic record
Abstract
Dispersal of epithelial cells is an important aspect of tumorigenesis, and invasion. Factors such as hepatocyte growth factor induce the breakdown of cell junctions and promote cell spreading and the dispersal of colonies of epithelial cells, providing a model system to investigate the biochemical signals that regulate these events. Multiple signaling proteins are phosphorylated in epithelial cells during hepatocyte growth factor-induced cell dispersal, including c-Cbl, a protooncogene docking protein with ubiquitin ligase activity. We have examined the role of c-Cbl and a transforming variant (70z-Cbl) in epithelial cell dispersal. We show that the expression of 70z-Cbl in Madin-Darby canine kidney epithelial cells resulted in the breakdown of cell-cell contacts and alterations in cell morphology characteristic of epithelial-mesenchymal transition. Structure-function studies revealed that the amino-terminal portion of c-Cbl, which corresponds to the Cbl phosphotyrosine-binding/Src homology domain 2, is sufficient to promote the morphological changes in cell shape. Moreover, a point mutation at Gly-306 abrogates the ability of the Cbl Src homology domain 2 to induce these morphological changes. Our results identify a role for Cbl in the regulation of epithelial-mesenchymal transition, including loss of adherens junctions, cell spreading, and the initiation of cell dispersal.
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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 | 0.001 |
| 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".