Pak4, a Novel Gab1 Binding Partner, Modulates Cell Migration and Invasion by the Met Receptor
Bibliographic record
Abstract
Hepatocyte growth factor (HGF), the ligand for the Met receptor tyrosine kinase, induces epithelial cell dispersal, invasion, and morphogenesis, events that require remodeling of the actin cytoskeleton. The scaffold protein Gab1 is essential for these biological responses downstream from Met. We have identified p21-activated kinase 4 (Pak4) as a novel Gab1-interacting protein. We show that in response to HGF, Gab1 and Pak4 associate and colocalize at the cell periphery within lamellipodia. The association between Pak4 and Gab1 is dependent on Gab1 phosphorylation but independent of Pak4 kinase activity. The interaction is mediated through a region in Gab1, which displays no homology to known Gab1 interaction motifs and through the guanine exchange factor-interacting domain of Pak4. In response to HGF, Gab1 and Pak4 synergize to enhance epithelial cell dispersal, migration, and invasion, whereas knockdown of Pak4 attenuates these responses. A Gab1 mutant unable to recruit Pak4 fails to promote epithelial cell dispersal and an invasive morphogenic program in response to HGF, demonstrating a physiological requirement for Gab1-Pak4 association. These data demonstrate a novel association between Gab1 and Pak4 and identify Pak4 as a key integrator of cell migration and invasive growth downstream from the Met receptor.
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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".