Co-dependency between KRAS addiction and ARHGEF2 promotes an adaptive escape from MAPK pathway inhibition
Bibliographic record
Abstract
Oncogenic KRAS engages multiple effector pathways including the MAPK cascade to promote proliferation and survival of pancreatic cancer cells. KRAS-transformed cancer cells exhibit oncogene addiction to sustained activity of RAS for maintenance of malignant phenotypes. Previously, we have shown an essential role for the RHO guanine exchange factor ARHGEF2 for growth and survival of RAS-transformed pancreatic tumors. Here, we have determined that pancreatic cancer cells demonstrating KRAS addiction are significantly dependent on expression of ARHGEF2. Furthermore, enforced expression of ARHGEF2 desensitizes cells to pharmacological MEK inhibition and initiates a positive feedback loop which activates ERK phosphorylation and the downstream ARHGEF2 promoter. Therefore, targeting ARHGEF2 expression may increase the efficacy of MAPK inhibitors for treatment of RAS-dependent pancreatic cancers.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".