Blockage of Drug Resistance In Vitro by Disulfiram, a Drug Used to Treat Alcoholism
Bibliographic record
Abstract
BACKGROUND: P-glycoprotein (P-gp) pumps a wide range of cytotoxic drugs out of cells. Inhibiting maturation of P-gp would be a novel method for circumventing P-gp-mediated multidrug resistance, which complicates cancer chemotherapy and treatment of patients infected with human immunodeficiency virus. We examined the effect of disulfiram (Antabuse(TM)) on the maturation and activity of P-gp. METHODS: Embryonic kidney cells were transfected with a complementary DNA for the P-pg gene, and the effects of disulfiram on the sensitivity of the transfected cells to cytotoxic agents were determined. Enzyme assays were used to determine the effects of disulfiram on the verapamil-stimulated adenosine triphosphatase (ATPase) activity of P-gp. Disulfiram modifies cysteine residues, and mutant forms of P-gp that lack individual cysteines were used to determine whether particular cysteine residues mediate disulfiram's effects on P-gp activity. Maturation of recombinant P-gp was followed on immunoblots. RESULTS: Disulfiram increased the sensitivity of P-gp-transfected cells to vinblastine and colchicine and inhibited P-gp's verapamil-stimulated ATPase activity. Half-maximal inhibition of ATPase activity occurred at 13.5 microM disulfiram. Disulfiram (at 100 microM) inhibited a P-gp mutant by 43% (95% confidence interval [CI] = 37%-48%) when cysteine was present at position 431 only and by 72% (95% CI = 66%-77%) when cysteine was present at position 1074 only. Treatment of P-gp-transfected cells with 50 nM disulfiram blocked maturation of recombinant P-gp. CONCLUSIONS: Disulfiram can potentially reduce P-gp-mediated drug resistance by inhibiting P-gp activity (possibly via cysteine modification) and/or by blocking its maturation. These results suggest that disulfiram has the potential to increase the efficacy of drug therapies for cancer and acquired immunodeficiency syndrome.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".