Gab2 Phosphorylation by RSK Inhibits Shp2 Recruitment and Cell Motility
Bibliographic record
Abstract
The scaffolding adapter protein Gab2 (Grb2-associated binder) participates in the signaling response evoked by various growth factors and cytokines. Gab2 is overexpressed in several human malignancies, including breast cancer, and was shown to promote mammary epithelial cell migration. The role of Gab2 in the activation of different signaling pathways is well documented, but less is known regarding the feedback mechanisms responsible for its inactivation. We now demonstrate that activation of the Ras/mitogen-activated protein kinase (MAPK) pathway promotes Gab2 phosphorylation on basic consensus motifs. More specifically, we show that RSK (p90 ribosomal S6 kinase) phosphorylates Gab2 on three conserved residues, both in vivo and in vitro. Mutation of these phosphorylation sites does not alter Gab2 binding to Grb2, but instead, we show that Gab2 phosphorylation inhibits the recruitment of the tyrosine phosphatase Shp2 in response to growth factors. Expression of an unphosphorylatable Gab2 mutant in mammary epithelial cells promotes an invasion-like phenotype and increases cell motility. Taken together, these results suggest that RSK is part of a negative-feedback loop that restricts Gab2-dependent epithelial cell motility. On the basis of the widespread role of Gab2 in receptor signaling, these findings also suggest that RSK plays a regulatory function in diverse receptor systems.
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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) | 0.002 | 0.001 |
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".