Efficacy of Combining GMX1777 with Radiation Therapy for Human Head and Neck Carcinoma
Bibliographic record
Abstract
PURPOSE: Rapidly metabolizing tumor cells have elevated levels of nicotinamide phosphoribosyltransferase, an enzyme involved in NAD(+) biosynthesis, which serves as an important substrate for proteins involved in DNA repair. GMX1777, which inhibits nicotinamide phosphoribosyltransferase, was evaluated in two human head and neck cancer models in combination with radiotherapy. EXPERIMENTAL DESIGN: Effects of GMX1777-mediated radiosensitization were examined via metabolic and cytotoxicity assays in vitro; mechanism of action, in vivo antitumor efficacy, and radiosensitization were also investigated. RESULTS: IC(50) values of GMX1777 for FaDu and C666-1 cells were 10 and 5 nmol/L, respectively, which interacted synergistically with radiotherapy. GMX1777 induced a rapid decline in intracellular NAD(+) followed by ATP reduction associated with significant cytotoxicity. These metabolic changes were slightly increased with the addition of radiotherapy, although poly(ADP-ribose) polymerase activity was significantly reduced when GMX1777 was combined with radiotherapy, thereby accounting for the synergistic cytotoxicity of these two modalities. Systemic GMX1777 administration with local tumor radiotherapy caused complete disappearance of FaDu and C666-1 tumors for 50 and 20 days, respectively. There was also significant reduction in tumor vascularity, particularly for the more sensitive FaDu model. [(18)F]FDG-positron emission tomography/computed tomography images showed reduction in [(18)F]FDG uptake after GMX1777 administration, showing decreased glucose metabolism in vivo. CONCLUSIONS: Our data represent the first report showing that GMX1777 plus radiotherapy is an effective therapeutic strategy for head and neck cancer, mediated via pleiotropic effects of inhibition of DNA repair and tumor angiogenesis, while sparing normal tissues. Therefore, GMX1777 combined with radiotherapy definitely warrants clinical evaluation in human head and neck cancer patients.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".