Abstract 2521: The pan-RAF inhibitor PLX4032 inhibits ERK signaling and tumor cell proliferation in a V600E BRAF mutant-selective manner
Bibliographic record
Abstract
Abstract Activation of the RAS/RAF/MEK/ERK pathway occurs often in human cancer. Tumors with mutant BRAF and some with mutant RAS are dependent upon ERK signaling for proliferation and their growth is suppressed by selective inhibitors of MEK. In contrast, tumor cells with HER-kinase activation proliferate in a MEK-independent manner. These findings have led to the development of RAF and MEK inhibitors as anticancer agents. Like MEK inhibitors, the pan-RAF kinase inhibitor PLX4032 inhibits the proliferation of V600E BRAF mutant tumor cells, but not that of HER kinase dependent tumors. However, tumors with RAS mutation that are sensitive to MEK inhibition are insensitive to PLX4032. Whereas MEK inhibitors inhibit ERK phosphorylation in all normal and tumor cells, PLX4032 only inhibits ERK signaling in tumor cells with BRAF mutation. In contrast, the drug activates MEK and ERK phosphorylation in cells with wild-type BRAF. In mutant BRAF cells, the MEK and RAF inhibitors affect the expression of a common set of genes, whereas they have opposite effects on the expression of these genes in tumors with mutant RAS. Furthermore, PLX4032 inhibits ERK signaling output in mutant BRAF cells, but transiently activates it in tumor cells with wild-type RAF. Thus, PLX4032 inhibits ERK signaling output in a BRAF mutant-selective manner. These data suggest that PLX4032 may have a broader therapeutic index and help to explain the greater antitumor activity observed with this drug compared to MEK inhibitors, which inhibit ERK signaling in all cells. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2521.
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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) | 0.004 | 0.001 |
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".