iRhom2 controls the substrate selectivity of stimulated ADAM17-dependent ectodomain shedding
Bibliographic record
Abstract
Protein ectodomain shedding by ADAM17 (a disintegrin and metalloprotease 17), a principal regulator of EGF-receptor signaling and TNFα release, is rapidly and posttranslationally activated by a variety of signaling pathways, and yet little is known about the underlying mechanism. Here, we report that inactive rhomboid protein 2 (iRhom2), recently identified as essential for the maturation of ADAM17 in hematopoietic cells, is crucial for the rapid activation of the shedding of some, but not all substrates of ADAM17. Mature ADAM17 is present in mouse embryonic fibroblasts (mEFs) lacking iRhom2, and yet ADAM17 is unable to support stimulated shedding of several of its substrates, including heparin-binding EGF and Kit ligand 2 in this context. Stimulated shedding of other ADAM17 substrates, such as TGFα, is not affected in iRhom2(-/-) mEFs but can be strongly reduced by treating iRhom2(-/-) mEFs with siRNA against iRhom1. Activation of heparin-binding EGF or Kit ligand 2 shedding by ADAM17 in iRhom2(-/-) mEFs can be rescued by wild-type iRhom2 but not by iRhom2 lacking its N-terminal cytoplasmic domain. The requirement for the cytoplasmic domain of iRhom2 for stimulated shedding by ADAM17 may help explain why the cytoplasmic domain of ADAM17 is not required for stimulated shedding. The functional relevance of iRhom2 in regulating shedding of EGF receptor (EGFR) ligands is established by a lack of lysophasphatidic acid/ADAM17/EGFR-dependent crosstalk with ERK1/2 in iRhom2(-/-) mEFs, and a significant reduction of FGF7/ADAM17/EGFR-stimulated migration of iRhom2(-/-) keratinocytes. Taken together, these findings uncover functions for iRhom2 in the regulation of EGFR signaling and in controlling the activation and substrate selectivity of ADAM17-dependent shedding events.
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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".