Abstract B31: The RhoGEF GEF-H1 is required for RAS oncogene-driven pancreatic cancer
Bibliographic record
Abstract
Abstract Cellular transformation by oncogenic RAS engages the MAPK pathway under strict spatiotemporal regulation by the scaffold protein KSR-1. Here, we find using a whole genome functional shRNA-based screen, that the guanine nucleotide exchange factor GEF-H1 plays a critical role in a positive feedback loop for the RAS/MAPK pathway independently of its RhoGEF activity. GEF-H1 acts as an adaptor protein, linking the PP2A B' subunits to KSR-1, required for the dephosphorylation of KSR-1 S392 and activation of MAPK signaling. GEF-H1 is required for the growth and survival of RASV12-transformed cells and pancreatic xenografts. GEF-H1 expression is induced by oncogenic RAS and is correlated with pancreatic neoplastic progression. Our results therefore identify GEF-H1 as an amplifier of MAPK signaling required for cell transformation and provide mechanistic insight into the progression of RAS-mutant tumors. Citation Format: Jane Cullis, Dedi Meiri, Maria Jose-Sandi, Oliver Kent, Mauricio Medrano, Daphna Mokady, Ming Tsao, Anne-Claude Gingras, Robert Rottapel. The RhoGEF GEF-H1 is required for RAS oncogene-driven pancreatic cancer. [abstract]. In: Proceedings of the AACR Special Conference on RAS Oncogenes: From Biology to Therapy; Feb 24-27, 2014; Lake Buena Vista, FL. Philadelphia (PA): AACR; Mol Cancer Res 2014;12(12 Suppl):Abstract nr B31. doi: 10.1158/1557-3125.RASONC14-B31
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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) | 0.006 | 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".