Deletions in the cytoplasmic domain of iRhom1 and iRhom2 promote shedding of the TNF receptor by the protease ADAM17
Bibliographic record
Abstract
The protease ADAM17 (a disintegrin and metalloproteinase 17) catalyzes the shedding of various transmembrane proteins from the surface of cells, including tumor necrosis factor (TNF) and its receptors. Liberation of TNF receptors (TNFRs) from cell surfaces can dampen the cellular response to TNF, a cytokine that is critical in the innate immune response and promotes programmed cell death but can also promote sepsis. Catalytically inactive members of the rhomboid family of proteases, iRhom1 and iRhom2, mediate the intracellular transport and maturation of ADAM17. Using a genetic screen, we found that the presence of either iRhom1 or iRhom2 lacking part of their extended amino-terminal cytoplasmic domain (herein referred to as ΔN) increases ADAM17 activity, TNFR shedding, and resistance to TNF-induced cell death in fibrosarcoma cells. Inhibitors of ADAM17, but not of other ADAM family members, prevented the effects of iRhom-ΔN expression. iRhom1 and iRhom2 were functionally redundant, suggesting a conserved role for the iRhom amino termini. Cells from patients with a dominantly inherited cancer susceptibility syndrome called tylosis with esophageal cancer (TOC) have amino-terminal mutations in iRhom2. Keratinocytes from TOC patients exhibited increased TNFR1 shedding compared with cells from healthy donors. Our results explain how loss of the amino terminus in iRhom1 and iRhom2 impairs TNF signaling, despite enhancing ADAM17 activity, and may explain how mutations in the amino-terminal region contribute to the cancer predisposition syndrome TOC.
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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) | 0.002 | 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".