The NAMPT Inhibitor FK866 Increases Metformin Sensitivity in Pancreatic Cancer Cells
Bibliographic record
Abstract
Pancreatic cancer (pancreatic ductal adenocarcinoma: PDAC) is one of the most aggressive neoplastic diseases. Metformin use has been associated with reduced pancreatic cancer incidence and better survival in diabetics. Metformin has been shown to inhibit PDAC cells growth and survival, both in vitro and in vivo. However, clinical trials using metformin have failed to reduce pancreatic cancer progression in patients, raising important questions about molecular mechanisms that protect tumor cells from the antineoplastic activities of metformin. We confirmed that metformin acts through inhibition of mitochondrial complex I, decreasing the NAD+/NADH ratio, and that NAD+/NADH homeostasis determines metformin sensitivity in several cancer cell lines. Metabolites that can restore the NAD+/NADH ratio caused PDAC cells to be resistant to metformin. In addition, metformin treatment of PDAC cell lines induced a compensatory NAMPT expression, increasing the pool of cellular NAD+. The NAMPT inhibitor FK866 sensitized PDAC cells to the antiproliferative effects of metformin in vitro and decreased the cellular NAD+ pool. Intriguingly, FK866 combined with metformin increased survival in mice bearing KP4 cell line xenografts, but not in mice with PANC-1 cell line xenografts. Transcriptome analysis revealed that the drug combination reactivated genes in the p53 pathway and oxidative stress, providing new insights about the mechanisms leading to cancer cell death.
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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".