HGF‐independent regulation of MET and Gab1 through non‐receptor tyrosine kinase FER (609.4)
Bibliographic record
Abstract
HGF‐MET signaling has versatile functions in tissue remodeling, wound repair, organ homeostasis and cancer metastasis. Activation of MET involves HGF ligand association and relayed receptor autophosphorylation on tyrosine residues within its kinase domain, followed by tyrosine residues within its C‐terminal docking domain. Here, we reported an alternative, HGF‐independent activation of MET through a non‐receptor tyrosine kinase FER. By using ovarian cancer as model, we observed up‐regulation of FER in a panel of the ovarian cancer cell lines. RNAi‐mediated inactivation of FER robustly decreased the cancer cell motility in vitro, and the ability to metastasize to liver and lung in vivo, and rescue experiments indicated that tyrosine kinase activity of FER was essential. Of great interest, we demonstrated that FER modulated activities of MET and Gab1 in an HGF‐independent manner, with both being substrates of the kinase. Consistently, loss of FER sensitized ovarian cancer cells to MET inhibitor PHA‐665752. Meanwhile, we also observed the significant loss of membrane distribution of MET in the absence of FER, as well as of its tyrosine kinase activity. Further analysis suggested FER sustained MET on the membrane to delay both inactivation by protein‐tyrosine phosphatase 1B. In conclusion, our study, for the first time, illustrated multiple functions of FER in regulation of MET‐mediated signaling pathway.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".