Abstract A081 Biomarker-driven targeting of NAD metabolism in rhabdomyosarcoma
Bibliographic record
Abstract
Abstract Introduction/Background: New treatments are needed to improve survival in rhabdomyosarcoma (RMS). Cells primarily synthesize nicotinamide adenine dinucleotide (NAD+) through the Preiss-Handler and Salvage pathways driven by nicotinic acid phosphoribosyltransferase (NAPRT) and nicotinamide phosphoribosyltransferase (NAMPT), respectively. NAMPT inhibitors (NAMPTi) have been tested in clinical trials, but their efficacy has been limited by lack of appropriate biomarkers for patient selection. Here, we sought to determine if RMS harbors NAPRT silencing that confers a synthetic lethal interaction with NAMPTi. Methods: NAPRT expression was evaluated by immunohistochemistry (IHC) in human tumor samples. In vitro cell viability assays were performed in RMS cell lines using a panel of NAMPT inhibitors. RMS cells isogenic for NAPRT expression were generated via overexpression or CRISPR/Cas9 KO. For in vivo experiments, orthotopic tumor-bearing mice were treated with vehicle control or OT-82 at 25 mg/kg/dose by oral gavage with or without nicotinic acid (NA) at 25 mg/kg/dose once daily for 3 days per week. Results: In vitro, NAPRT negative isogenic RMS cells showed an exquisite sensitivity to a panel of NAMPT inhibitors. When NA was supplemented to model physiologic conditions, NAPRT+ cells were rescuved while cells harboring loss of NAPRT remained sensitive. In vivo, NAMPTi treatment induced significant tumor regression and improved survival in a NAPRT null RMS xenograft model even in the presence of NA, while NAPRT+ tumors did not response to NAMPTi when combined with NA supplementation. IHC staining in a collection of RMS tissue microarrays obtained from the Children’s Oncology Group demonstrated loss of NAPRT protein expression in roughly 25% of tumors.Conclusion: Overall, these data suggest that NAPRT loss may serve as a therapeutic target in RMS by inducing a synthetic lethal interaction with NAD+ depleting agents. Future studies will determine if NA supplementation can mitigate toxicity and widen the therapeutic index, paving the way for the development of biomarker-driven clinical trials in RMS. Citation Format: Juan C. Vasquez, Prateek Bhardwaj, Sophia Zhao, Katelyn Noronha, Karlie Lucas, Ranjini Sundaram, Collin Heer, Raffaella Morotti, Josh Spurrier, Ranjit S Bindra. Biomarker-driven targeting of NAD metabolism in rhabdomyosarcoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr A081.
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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) | 0.003 | 0.001 |
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".