Novel Methionine Aminopeptidase 2 Inhibitor M8891 Synergizes with VEGF Receptor Inhibitors to Inhibit Tumor Growth of Renal Cell Carcinoma Models
Bibliographic record
Abstract
N-terminal processing by methionine aminopeptidases (MetAP) is a crucial step in the maturation of proteins during protein biosynthesis. Small-molecule inhibitors of MetAP2 have antiangiogenic and antitumoral activity. Herein, we characterize the structurally novel MetAP2 inhibitor M8891. M8891 is a potent, selective, reversible small-molecule inhibitor blocking the growth of human endothelial cells and differentially inhibiting cancer cell growth. A CRISPR genome-wide screen identified the tumor suppressor p53 and MetAP1/MetAP2 as determinants of resistance and sensitivity to pharmacologic MetAP2 inhibition. A newly identified substrate of MetAP2, translation elongation factor 1-alpha-1 (EF1a-1), served as a pharmacodynamic biomarker to follow target inhibition in cell and mouse studies. Robust angiogenesis and tumor growth inhibition was observed with M8891 monotherapy. In combination with VEGF receptor inhibitors, tumor stasis and regression occurred in patient-derived xenograft renal cell carcinoma models, particularly those that were p53 wild-type, had Von Hippel-Landau gene (VHL) loss-of-function mutations, and a mid/high MetAP1/2 expression score.
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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) | 0.001 | 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".