Proprotein Convertase PC7 Enhances the Activation of the EGF Receptor Pathway through Processing of the EGF Precursor
Bibliographic record
Abstract
Although the processing profile of the membrane-bound epidermal growth factor precursor (pro-EGF) is tissue-specific, it has not been investigated at the cellular level nor have the cognate proteinases been defined. Among the proprotein convertases (PCs), only the membrane-bound PC7, the most ancient and conserved basic amino acid-specific PC family member, induces the processing of pro-EGF into an ∼115-kDa transmembrane form (EGF-115) at an unusual VHPR(290)↓A motif. Because site-directed mutagenesis revealed that Arg(290) is not critical, the generation of EGF-115 by PC7 is likely indirect. This was confirmed by testing a wide range of protease inhibitors, which revealed that the production of EGF-115 is most probably achieved via the activation by PC7 of a latent serine and/or cysteine protease(s). EGF-115 is more abundant at the cell surface than pro-EGF and is associated with a stronger EGF receptor (EGFR) activation, as evidenced by higher levels of phosphorylated ERK1/2. This suggests that the generation of EGF-115 represents a regulatory mechanism of juxtacrine EGFR activation. Thus, PC7 is distinct from the other PCs in its ability to enhance the activation of the cell surface EGFR.
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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".