NAD+ depletion enhances reovirus-induced oncolysis in multiple myeloma
Bibliographic record
Abstract
Cancer cell energy metabolism plays an important role in dictating the efficacy of oncolysis by oncolytic viruses. To understand the role of multiple myeloma metabolism in reovirus oncolysis, we performed semi-targeted mass spectrometry-based metabolomics on 12 multiple myeloma cell lines and revealed a negative correlation between NAD+ levels and susceptibility to oncolysis. Likewise, a negative correlation was observed between the activity of the rate-limiting NAD+ synthesis enzyme NAMPT and oncolysis. Indeed, depletion of NAD+ levels by pharmacological inhibition of NAMPT using FK866 sensitized several myeloma cell lines to reovirus-induced killing. The myelomas that were most sensitive to this combination therapy expressed a functional p53 and had a metabolic and transcriptomic profile favoring mitochondrial metabolism over glycolysis, with the highest synergistic effect in KMS12 cells. Mechanistically, U- 13 C-labeled glucose flux, extracellular flux analysis, multiplex proteomics, and cell death assays revealed that the reovirus + FK866 combination caused mitochondrial dysfunction and energy depletion, leading to enhanced autophagic cell death in KMS12 cells. Finally, the combination of reovirus and NAD+ depletion achieved greater antitumor effects in KMS12 tumors in vivo and patient-derived CD138+ multiple myeloma cells. These findings identify NAD+ depletion as a potential combinatorial strategy to enhance the efficacy of oncolytic virus-based therapies in multiple myeloma.
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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) | 0.002 | 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".