The combination of novel low molecular weight inhibitors of RAF (LBT613) and target of rapamycin (RAD001) decreases glioma proliferation and invasion
Bibliographic record
Abstract
Monotherapies have proven largely ineffective for the treatment of glioblastomas, suggesting that increased patient benefit may be achieved by combining therapies. Two protumorigenic pathways known to be active in glioblastoma include RAS/RAF/mitogen-activated protein kinase and phosphatidylinositol 3-kinase/AKT/target of rapamycin (TOR). We investigated the efficacy of a combination of novel low molecular weight inhibitors LBT613 and RAD001 (everolimus), which were designed to target RAF and TOR, respectively. LBT613 decreased phosphorylation of extracellular signal-regulated kinase 1 and 2, downstream effectors of RAF, in a human glioma cell line. RAD001 resulted in decreased phosphorylation of the TOR effector S6. To determine if targeting RAF and TOR activities could result in decreased protumorigenic glioma cellular behaviors, we evaluated the abilities of LBT613 and RAD001 to affect the proliferation, migration, and invasion of human glioma cells. Treatment with either LBT613 or RAD001 alone significantly decreased the proliferation of multiple human glioma cell lines. Furthermore, LBT613 and RAD001 in combination synergized to decrease glioma cell proliferation in association with G(1) cell cycle arrest. Glioma invasion is a critical contributor to tumor malignancy. The combination of LBT613 and RAD001 inhibited the invasion of human glioma cells through Matrigel to a greater degree than treatment with either drug alone. These data suggest that the combination of LBT613 and RAD001 reduces glioma cell proliferation and invasion and support examination of the combination of RAF and TOR inhibitors for the treatment of human glioblastoma patients.
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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 | 0.000 | 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) | 0.000 | 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".