A preclinical study demonstrating the efficacy of nilotinib in inhibiting the growth of pediatric high-grade glioma
Bibliographic record
Abstract
Solid tumors arising from malignant transformation of glial cells are one of the leading causes of central nervous system tumor-related death in children. Recurrence in spite of rigorous surgical and chemoradiation therapies remains a major hurdle in management of these tumors. Here, we investigate the efficacy of the second-generation receptor tyrosine kinase inhibitor nilotinib as a therapeutic option for the management of pediatric gliomas. We have utilized two independent pediatric high-grade glioma cell lines with either high platelet-derived growth factor receptor alpha (PDGFRα) or high PDGFRβ expression in in vitro assays to investigate the specific downstream effects of nilotinib treatment. Using in vitro cell-based assays we show that nilotinib inhibits PDGF-BB-dependent activation of PDGFRα. We further show that nilotinib is able to decrease cell proliferation and anchorage-independent growth via suppression of AKT and ERK1/2 signaling pathways. Our results suggest that nilotinib may be effective for management of a PDGFRα-dependent group of pediatric gliomas.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".