Effect of the anti-receptor ligand-blocking 225 monoclonal antibody on EGF receptor endocytosis and sorting
Bibliographic record
Abstract
1243 mAbs directed to the epidermal growth factor receptor (EGFR) have been shown to have tumor-inhibitory potential. The mechanisms underlying this effect are not well understood. The anti-receptor antibody, 225 mAb, is known to block binding of ligand to the EGFR, thus preventing ligand-induced receptor tyrosine kinase activation. However, the effect of this neutralizing antibody on EGFR endocytosis, trafficking and degradation remains unclear. Here, we demonstrate that endocytosis of 125I-225 mAb occurs, with the ratio of internalized-to-cell surface 125I-225 mAb reaching approximately 0.4 at steady state. Using recycling assays, we show that internalized 125I-225 mAb is recycled to the surface much more efficiently than internalized 125I-EGF. Also, in contrast to EGF, internalization of 125I-225 mAb is independent of receptor tyrosine-kinase activity, as evidenced by its insensitivity to AG1478, a specific tyrosine kinase inhibitor for EGFR. Analysis of EGF receptor cell surface levels showed that treatment with 225 mAb results in a 30-40% decrease in surface EGFR and a concomitant increase in surface erbB2. Taken together, these data indicate that 225 mAb induces internalization and down-regulation of EGFR via a mechanism distinct from that underlying EGF-induced EGFR internalization and down-regulation.
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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) | 0.002 | 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".