Replication Study: RAF inhibitors prime wild-type RAF to activate the MAPK pathway and enhance growth
Bibliographic record
Abstract
Abstract As part of the Reproducibility Project: Cancer Biology, we published a Registered Report (Bhargava et al., 2016) that described how we intended to replicate selected experiments from the paper “RAF inhibitors prime wild-type RAF to activate the MAPK pathway and enhance growth” (Hatzivassiliou et al., 2010). Here we report the results. We found two unrelated RAF inhibitors, PLX4720 or GDC-0879, selectively inhibited BRAF(V600E) cell proliferation, while the MEK inhibitor, PD0325901, inhibited BRAF(V600E), wild-type RAF/RAS, and mutant RAS cancer cell proliferation, similar to the original study (Figure 1A; Hatzivassiliou et al., 2010). We found knockdown of CRAF , but not BRAF , in mutant RAS cells attenuated the phospho-MEK induction observed after PLX4720 treatment, similar to the original study (Figure 2B; Hatzivassiliou et al., 2010). The original study reported analogous results with GDC-0879, which was not observed in this replication, although unexpected control results confound the interpretation. We also attempted a replication of an assay with recombinant proteins to test the differential effect of RAF inhibitors on BRAF-CRAF heterodimerization (Figure 4A; Hatzivassiliou et al., 2010). Although we were unable to conduct the experiment as planned, we observed differential binding of BRAF by RAF inhibitors; however, it was between BRAF and beads, independent of CRAF. While these data were unable to address whether, under the conditions of the original study, the same observations could be observed, we discuss key differences between the original study and this replication that are important to consider for further experiments. Finally, where possible, we report meta-analyses for each result.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".