Protein-tyrosine Phosphatase ϵ Regulates Shc Signaling in a Kinase-specific Manner
Bibliographic record
Abstract
Individual protein tyrosine kinases and phosphatases target multiple substrates; this may generate conflicting signals, possibly within a single pathway. Protein-tyrosine phosphatase epsilon (PTPepsilon) performs two potentially opposing roles: in Neu-induced mammary tumors, PTPepsilon activates Src downstream of Neu, whereas in other systems PTPepsilon can indirectly down-regulate MAP kinase signaling. We now show that the latter effect is mediated at least in part via the adaptor protein Shc. PTPepsilon binds and dephosphorylates Shc in vivo, reducing the association of Shc with Grb2 and inhibiting downstream ERK activation. PTPepsilon binds Shc in a phosphotyrosine-independent manner mediated by the Shc PTB domain and aided by a sequence of 10 N-terminal residues in PTPepsilon. Surprisingly, PTPepsilon dephosphorylates Shc in a kinase-dependent manner; PTPepsilon targets Shc in the presence of Src but not in the presence of Neu. Using a series of point mutants of Shc and Neu, we show that Neu protects Shc from dephosphorylation by binding the PTB domain of Shc, most likely competing against PTPepsilon for binding the same domain. In agreement, PTPepsilon dephosphorylates Shc in mouse embryo fibroblasts but not in Neu-induced mammary tumor cells. We conclude that in the context of Neu-induced mammary tumor cells, Neu prevents PTPepsilon from targeting Shc and from reducing its promitogenic signal while phosphorylating PTPepsilon and directing it to activate Src in support of mitogenesis. In so doing, Neu contributes to the coherence of the promitogenic role of PTPepsilon in this system.
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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 | 0.001 | 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".