Registered report: COT drives resistance to RAF inhibition through MAP kinase pathway reactivation
Bibliographic record
Abstract
The Reproducibility Project: Cancer Biology seeks to address growing concerns about reproducibility in scientific research by conducting replications of selected experiments from a number of high-profile papers in the field of cancer biology. The papers, which were published between 2010 and 2012, were selected on the basis of citations and Altmetric scores (Errington et al., 2014). This Registered Report describes the proposed replication plan of key experiments from "COT drives resistance to RAF inhibition through MAPK pathway reactivation" by Johannessen and colleagues, published in Nature in 2010 (Johannessen et al., 2010). The key experiments to be replicated are those reported in Figures 3B, 3D-E, 3I, and 4E-F. In Figures 3B, D-E, RPMI-7951 and OUMS023 cells were reported to exhibit robust ERK/MEK activity concomitant with reduced growth sensitivity in the presence of the BRAF inhibitor PLX4720. MAP3K8 (COT/TPL2) directly regulated MEK/ERK phosphorylation, as the treatment of RPMI-7951 cells with a MAP3K8 kinase inhibitor resulted in a dose-dependent suppression of MEK/ERK activity (Figure 3I). In contrast, MAP3K8-deficient A375 cells remained sensitive to BRAF inhibition, exhibiting reduced growth and MEK/ERK activity during inhibitor treatment. To determine if RAF and MEK inhibitors together can overcome single-agent resistance, MAP3K8-expressing A375 cells treated with PLX4720 along with MEK inhibitors significantly inhibited both cell viability and ERK activation compared to treatment with PLX4720 alone, as reported in Figures 4E-F. The Reproducibility Project: Cancer Biology is collaboration between the Center for Open Science and Science Exchange and the results of the replications will be published in eLife.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.006 |
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".