Dual Farnesyl and Geranylgeranyl Transferase Inhibitor Thwarts Mutant KRAS-Driven Patient-Derived Pancreatic Tumors
Bibliographic record
Abstract
Abstract Purpose: Mutant KRAS is a major driver of pancreatic oncogenesis and therapy resistance, yet KRAS inhibitors are lacking in the clinic. KRAS requires farnesylation for membrane localization and cancer-causing activity prompting the development of farnesyltransferase inhibitors (FTIs) as anticancer agents. However, KRAS becomes geranylgeranylated and active when cancer cells are treated with FTIs. To overcome this geranylgeranylation-dependent resistance to FTIs, we designed FGTI-2734, a RAS C-terminal mimetic dual FT and geranylgeranyltransferase-1 inhibitor (GGTI). Experimental Design: Immunofluorescence, cellular fractionation, and gel shift assays were used to assess RAS membrane association, Western blotting to evaluate FGTI-2734 effects on signaling, and mouse models to demonstrate its antitumor activity. Results: FGTI-2734, but not the selective FTI-2148 and GGTI-2418, inhibited membrane localization of KRAS in pancreatic, lung, and colon human cancer cells. FGTI-2734 induced apoptosis and inhibited the growth in mice of mutant KRAS–dependent but not mutant KRAS–independent human tumors. Importantly, FGTI-2734 inhibited the growth of xenografts derived from four patients with pancreatic cancer with mutant KRAS (2 G12D and 2 G12V) tumors. FGTI-2734 was also highly effective at inhibiting, in three-dimensional cocultures with resistance promoting pancreatic stellate cells, the viability of primary and metastatic mutant KRAS tumor cells derived from eight patients with pancreatic cancer. Finally, FGTI-2734 suppressed oncogenic pathways mediated by AKT, mTOR, and cMYC while upregulating p53 and inducing apoptosis in patient-derived xenografts in vivo. Conclusions: The development of this novel dual FGTI overcomes a major hurdle in KRAS resistance, thwarting growth of patient-derived mutant KRAS–driven xenografts from patients with pancreatic cancer, and as such it warrants further preclinical and clinical studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".