Dietary induction of NQO1 increases the antitumour activity of mitomycin C in human colon tumours in vivo
Bibliographic record
Abstract
The bioreductive antitumour agent, mitomycin C (MMC), requires activation by reductive enzymes like NAD(P)H:quinone oxidoreductase 1 (NQO1). We used a novel approach to increase MMC efficacy by selectively inducing NQO1 in tumour cells in vivo. CD-1 nude mice were implanted with HCT116 cells, and fed control diet or diet containing 0.3% of the NQO1 inducer, dimethyl fumarate (DMF). The mice were then treated with saline, 2.0, 3.5 or 2.0 mg kg(-1) MMC and dicoumarol, an NQO1 inhibitor. The DMF diet increased NQO1 activity by 2.5-fold in the tumours, but had no effect in marrow cells. Mice given control diet/2.0 mg kg(-1) MMC had tumours with the same volume as control mice; however, mice given DMF diet/2.0 mg kg(-1) MMC had significantly smaller tumours. Tumour volumes in mice given DMF/2.0 mg kg(-1) MMC were similar to those in mice given control diet/3.5 mg kg(-1) MMC. Tumour inhibition was partially reversed in mice given DMF/2.0 mg kg(-1) MMC and dicoumarol. DMF diet/2.0 mg kg(-1) MMC treatment did not increase myelosuppression and did not produce any organ toxicity. These results provide strong evidence that dietary inducers of NQO1 can increase the antitumour activity of bioreductive agents like MMC without increasing toxicity.
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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".