Dimerization drives EGF receptor endocytosis through two sets of compatible endocytic codes
Bibliographic record
Abstract
We have shown previously that epidermal growth factor (EGF) receptor (EGFR) endocytosis is controlled by EGFR dimerization. However, it is not clear how the dimerization drives receptor internalization. We propose that EGFR endocytosis is driven by dimerization, bringing two sets of endocytic codes, one contained in each receptor monomer, in close proximity. Here, we tested this hypothesis by generating specific homo- or hetero-dimers of various receptors and their mutants. We show that ErbB2 and ErbB3 homodimers are endocytosis deficient owing to the lack of endocytic codes. Interestingly, EGFR-ErbB2 or EGFR-ErbB3 heterodimers are also endocytosis deficient. Moreover, the heterodimer of EGFR and the endocytosis-deficient mutant EGFRΔ1005-1017 is also impaired in endocytosis. These results indicate that two sets of endocytic codes are required for receptor endocytosis. We found that an EGFR-PDGFRβ heterodimer is endocytosis deficient, although both EGFR and PDGFRβ homodimers are endocytosis-competent, indicating that two compatible sets of endocytic codes are required. Finally, we found that to mediate the endocytosis of the receptor dimer, the two sets of compatible endocytic codes, one contained in each receptor molecule, have to be spatially coordinated.
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".