Targeted inhibition of MEK1 by cobimetinib leads to differentiation and apoptosis in neuroblastoma cells
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Neuroblastoma (NB) is one of the most common childhood malignancies. Currently, high risk NB carries a poor outcome and significant treatment related toxicities and, thus has been a focus for new therapeutics research in pediatric oncology. In this study, we evaluated the effects of the MEK inhibitor cobimetinib, as a single agent and in combinations, on the growth, survival and differentiation properties against a molecularly representative panel of NB cell lines. METHODS: In vitro anti-proliferative activity of cobimetinib alone or in combination was investigated by cell viability assays and its target modulatory activity was evaluated using phospho-kinases antibody arrays and western blot analysis. To determine the effect of combination with cis-RA on differentiation and resulting enhanced cellular cytotoxicity, the expression of glial fibrillary acidic protein (GFAP) and microtubule-associated protein 2 (MAP2) expression levels were examined by immuno-fluorescence. RESULTS: Our findings show that cobimetinib alone induced a concentration-dependent loss of cell viability in all NB cell lines. In addition, cobimetinib showed feedback activation of MEK1/2, and the dephosphorylation of extracellular signal-regulated kinases (ERK1/2) and c-RAF, providing information on the biological correlates of MEK inhibition in NB. Combined treatment with cis-RA, led to differentiation and enhanced sensitization of NB cells lines to cobimetinib. CONCLUSION: Collectively, our results provide evidence that cobimetinib, in combination with cis-RA, represents a feasible option to develop novel treatment strategies for refractory NB.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it