Synergy between the NAMPT Inhibitor GMX1777(8) and Pemetrexed in Non–Small Cell Lung Cancer Cells Is Mediated by PARP Activation and Enhanced NAD Consumption
Bibliographic record
Abstract
GMX1778 and its prodrug GMX1777 represent a new class of cancer drugs that targets nicotinamide phosphoribosyltransferase (NAMPT) as a new strategy to interfere with biosynthesis of the key enzymatic cofactor NAD, which is critical for a number of cell functions, including DNA repair. Using a genome-wide synthetic lethal siRNA screen, we identified the folate pathway-related genes, deoxyuridine triphosphatase and dihydrofolate reductase, the silencing of which sensitized non-small cell lung carcinoma (NSCLC) cells to the cytotoxic effects of GMX. Pemetrexed is an inhibitor of dihydrofolate reductase currently used to treat patients with nonsquamous NSCLC. We found that combining pemetrexed with GMX1777 produced a synergistic therapeutic benefit in A549 and H1299 NSCLC cells in vitro and in a mouse A549 xenograft model of lung cancer. Pemetrexed is known to activate PARPs, thereby accelerating NAD consumption. Genetic or pharmacologic blockade of PARP activity inhibited this effect, impairing cell death by pemetrexed either alone or in combination with GMX1777. Conversely, inhibiting the base excision repair pathway accentuated NAD decline in response to GMX and the cytotoxicity of both agents either alone or in combination. These findings provide a mechanistic rationale for combining GMX1777 with pemetrexed as an effective new therapeutic strategy to treat nonsquamous NSCLC.
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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) | 0.001 | 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) | 0.001 | 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".