AAL881, a Novel Small Molecule Inhibitor of RAF and Vascular Endothelial Growth Factor Receptor Activities, Blocks the Growth of Malignant Glioma
Bibliographic record
Abstract
Malignant gliomas are highly proliferative and angiogenic cancers resistant to conventional therapies. Although RAS and RAF mutations are uncommon in gliomas, RAS activity is increased in gliomas. Additionally, vascular endothelial growth factor and its cognate receptors are highly expressed in gliomas. We now report that AAL881, a novel low-molecular weight inhibitor of the kinase activities associated with B-RAF, C-RAF (RAF-1), and VEGF receptor-2 (VEGFR2), showed activity against glioma cell lines and xenografts. In culture, AAL881 inhibited the downstream effectors of RAF in a concentration-dependent manner, with inhibition of proliferation associated with a G(1) cell cycle arrest, induction of apoptosis, and decreased colony formation. AAL881 decreased the proliferation of bovine aortic endothelial cells as well as the tumor cell secretion of vascular endothelial growth factor and inhibited the invasion of glioma cells through an artificial extracellular matrix. Orally administered AAL881 was well tolerated with minimal weight loss in non-tumor-bearing mice. Established s.c. human malignant glioma xenografts grown in immunocompromised mice treated with a 10-day course of oral AAL881 exhibited growth delays relative to control tumors, frequently resulting in long-term complete regressions. AAL881 treatment extended the survival of immunocompromised mice bearing orthotopic glioma xenografts compared with placebo controls. The intraparenchymal portions of orthotopic AAL881-treated tumors underwent widespread necrosis consistent with vascular disruption compared with the subarachnoid elements. These effects are distinct from our prior experience with VEGFR2 inhibitors, suggesting that targeting RAF itself or in combination with VEGFR2 induces profound tumor responses in gliomas and may serve as a novel therapeutic approach in patients with malignant gliomas.
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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) | 0.001 | 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".