TMEM127 suppresses tumor development by promoting RET ubiquitination, positioning, and degradation
Bibliographic record
Abstract
The TMEM127 gene encodes a transmembrane protein of poorly known function that is mutated in pheochromocytomas, neural crest-derived tumors of adrenomedullary cells. Here, we report that, at single-nucleus resolution, TMEM127-mutant tumors share precursor cells and transcription regulatory elements with pheochromocytomas carrying mutations of the tyrosine kinase receptor RET. Additionally, TMEM127-mutant pheochromocytomas, human cells, and mouse knockout models of TMEM127 accumulate RET and increase its signaling. TMEM127 contributes to RET cellular positioning, trafficking, and lysosome-mediated degradation. Mechanistically, TMEM127 binds to RET and recruits the NEDD4 E3 ubiquitin ligase for RET ubiquitination and degradation via TMEM127 C-terminal PxxY motifs. Lastly, increased cell proliferation and tumor burden after TMEM127 loss can be reversed by selective RET inhibitors in vitro and in vivo. Our results define TMEM127 as a component of the ubiquitin system and identify aberrant RET stabilization as a likely mechanism through which TMEM127 loss-of-function mutations cause pheochromocytoma.
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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 | 0.000 |
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 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".