Numb regulates cell–cell adhesion and polarity in response to tyrosine kinase signalling
Bibliographic record
Abstract
Epithelial-mesenchymal transition (EMT), which can be caused by aberrant tyrosine kinase signalling, marks epithelial tumour progression and metastasis, yet the underlying molecular mechanism is not fully understood. Here, we report that Numb interacts with E-cadherin (E-cad) through its phosphotyrosine-binding domain (PTB) and thereby regulates the localization of E-cad to the lateral domain of epithelial cell-cell junction. Moreover, Numb engages the polarity complex Par3-aPKC-Par6 by binding to Par3 in polarized Madin-Darby canine kidney cells. Intriguingly, after Src activation or hepatocyte growth factor (HGF) treatment, Numb decouples from E-cad and Par3 and associates preferably with aPKC-Par6. Binding of Numb to aPKC is necessary for sequestering the latter in the cytosol during HGF-induced EMT. Knockdown of Numb by small hairpin RNA caused a basolateral-to-apicolateral translocation of E-cad and beta-catenin accompanied by elevated actin polymerization, accumulation of Par3 and aPKC in the nucleus, an enhanced sensitivity to HGF-induced cell scattering, a decrease in cell-cell adhesion, and an increase in cell migration. Our work identifies Numb as an important regulator of epithelial polarity and cell-cell adhesion and a sensor of HGF signalling or Src activity during EMT.
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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".