The Small Molecule GMX1778 Is a Potent Inhibitor of NAD <sup>+</sup> Biosynthesis: Strategy for Enhanced Therapy in Nicotinic Acid Phosphoribosyltransferase 1-Deficient Tumors
Bibliographic record
Abstract
GMX1777 is a prodrug of the small molecule GMX1778, currently in phase I clinical trials for the treatment of cancer. We describe findings indicating that GMX1778 is a potent and specific inhibitor of the NAD(+) biosynthesis enzyme nicotinamide phosphoribosyltransferase (NAMPT). Cancer cells have a very high rate of NAD(+) turnover, which makes NAD(+) modulation an attractive target for anticancer therapy. Selective inhibition by GMX1778 of NAMPT blocks the production of NAD(+) and results in tumor cell death. Furthermore, GMX1778 is phosphoribosylated by NAMPT, which increases its cellular retention. The cytotoxicity of GMX1778 can be bypassed with exogenous nicotinic acid (NA), which permits NAD(+) repletion via NA phosphoribosyltransferase 1 (NAPRT1). The cytotoxicity of GMX1778 in cells with NAPRT1 deficiency, however, cannot be rescued by NA. Analyses of NAPRT1 mRNA and protein levels in cell lines and primary tumor tissue indicate that high frequencies of glioblastomas, neuroblastomas, and sarcomas are deficient in NAPRT1 and not susceptible to rescue with NA. As a result, the therapeutic index of GMX1777 can be widended in the treatment animals bearing NAPRT1-deficient tumors by coadministration with NA. This provides the rationale for a novel therapeutic approach for the use of GMX1777 in the treatment of human 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".