AMG 595, an Anti-EGFRvIII Antibody–Drug Conjugate, Induces Potent Antitumor Activity against EGFRvIII-Expressing Glioblastoma
Bibliographic record
Abstract
Epidermal growth factor receptor variant III (EGFRvIII) is a cancer-specific deletion mutant observed in approximately 25% to 50% of glioblastoma multiforme (GBM) patients. An antibody drug conjugate, AMG 595, composed of the maytansinoid DM1 attached to a highly selective anti-EGFRvIII antibody via a noncleavable linker, was developed to treat EGFRvIII-positive GBM patients. AMG 595 binds to the cell surface and internalizes into the endo-lysosomal pathway of EGFRvIII-expressing cells. Incubation of AMG 595 with U251 cells expressing EGFRvIII led to potent growth inhibition. AMG 595 treatment induced significant tumor mitotic arrest, as measured by phospho-histone H3, in GBM subcutaneous xenografts expressing EGFRvIII. A single intravenous injection of AMG 595 at 17 mg/kg (250 μg DM1/kg) generated complete tumor regression in the U251vIII subcutaneous xenograft model. AMG 595 mediated tumor regression in the D317 subcutaneous xenograft model that endogenously expresses EGFRvIII. Finally, AMG 595 treatment inhibited the growth of D317 xenografts orthotopically implanted into the brain as determined by magnetic resonance imaging. These results demonstrate that AMG 595 is a promising candidate to evaluate in EGFRvIII-expressing GBM patients.
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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".