Hepatocyte Growth Factor Receptor Tyrosine Kinase Met Is a Substrate of the Receptor Protein-tyrosine Phosphatase DEP-1
Bibliographic record
Abstract
The receptor protein-tyrosine phosphatase (PTP) DEP-1 (CD148/PTP-eta) has been implicated in the regulation of cell growth, differentiation, and transformation, and most recently has been identified as a potential tumor suppressor gene mutated in colon, lung, and breast cancers. We have generated constructs comprising the cytoplasmic segment of DEP-1 fused to the maltose-binding protein to identify potential substrates and thereby suggest a physiological function for DEP-1. We have shown that the substrate-trapping mutant form of DEP-1 interacted with a small subset of tyrosine-phosphorylated proteins from lysates of the human breast tumor cell lines MDA-MB-231, T-47D, and T-47D/Met and have identified the hepatocyte growth factor/scatter factor receptor Met, the adapter protein Gab1, and the junctional component p120 catenin as potential substrates. Following ligand stimulation, phosphorylation of specific tyrosyl residues in Met induces mitogenic, motogenic, and morphogenic responses. When co-expressed in 293 cells, the full-length substrate-trapping mutant form of DEP-1 formed a stable complex with the chimeric receptor colony stimulating factor 1 (CSF)-Met and wild type DEP-1 dephosphorylated CSF-Met. Furthermore, we observed that DEP-1 preferentially dephosphorylated a Gab1 binding site (Tyr(1349)) and a COOH-terminal tyrosine implicated in morphogenesis (Tyr(1365)), whereas tyrosine residues in the activation loop of Met (Tyr(1230), Tyr(1234), and Tyr(1235)) were not preferred targets of the PTP. The ability of DEP-1 preferentially to dephosphorylate particular tyrosine residues that are required for Met-induced signaling suggests that DEP-1 may function in controlling the specificity of signals induced by this PTK, rather than as a simple "off-switch" to counteract PTK activity.
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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 | 0.001 |
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".