Oncogenic met receptor induces cell‐cycle progression in <i>Xenopus</i> oocytes independent of direct Grb2 and Shc binding or mos synthesis, but requires phosphatidylinositol 3‐kinase and raf signaling
Bibliographic record
Abstract
Biological responses of hepatocyte growth factor (HGF) are mediated by the Met receptor tyrosine kinase. Although HGF is a potent mitogen for a variety of cells, the signals required for cell-cycle progression by the Met/HGF receptor are poorly defined. In this study, we have used the Xenopus oocyte system to define the role of various Met proximal-binding partners and downstream signaling pathways in cell-cycle regulation. We show that cell-cycle progression and activation of MAPK and JNK mediated by the oncogenic Met receptor, Tpr-Met, are dependent on its kinase activity and the presence of the twin phosphotyrosine (Y482 & Y489) residues in its C-terminus, but that the recruitment of Grb2 and Shc adaptor proteins is dispensable, implicating other signaling molecules. However, using Met receptor oncoproteins engineered to recruit specific signaling proteins, we demonstrate that recruitment of Grb2 or Shc adaptor proteins is sufficient to induce cell-cycle progression and activation of MAPK and JNK, while the binding of phospholipase-Cgamma or phosphatidylinositol 3-kinase alone fails to elicit these responses. Using various means to block phosphatidylinositol 3-kinase, phospholipase-Cgamma, MEK, JNK, Mos, and Raf1 activity, we show that unlike the fibroblast growth factor receptor, MEK-dependent and independent signaling contribute to Met receptor-mediated cell-cycle progression, but phospholipase-Cgamma or JNK activity and Mos synthesis are not critical. Notably, we demonstrate that Raf1 and phosphatidylinositol 3-kinase signaling are required for cell-cycle progression initiated by the Met receptor, a protein frequently deregulated in human tumors.
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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) | 0.003 | 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".