Using novobiocin as a specific inhibitor of breast cancer resistant protein to assess the role of transporter in the absorption and disposition of topotecan
Bibliographic record
Abstract
PURPOSE: To investigate the role of intestinal breast cancer resistant protein (BCRP) in the absorption and disposition of topotecan (TPT) using novobiocin (NOV) as a specific inhibitor. METHODS: Transporter inhibition specificity of NOV was assessed in cells overexpressing BCRP or Pgp. Sprague-Dawley rats were orally or intravenously dosed with TPT (2 and 1 mg/kg for p.o. and i.v., respectively) with or without oral co-administration of NOV (50 mg/kg). Pharmacokinetic parameters of TPT were obtained by noncompartmental analysis. To assess the role of BCRP in TPT intestinal permeation, rat ileal segment was perfused with 10 microM TPT in the presence or absence of NOV (500 microM), TPT permeability was calculated based on drug appearance in mesenteric blood. To assess the role of BCRP in TPT intestinal secretion, rat ileal segment was perfused with saline in the presence or absence of NOV (500 microM), while TPT was i.v. infused into rat. Intestinal secretion of TPT was calculated based on drug appearance in the perfusate. RESULTS: NOV significantly inhibited efflux activity of BCRP, but not Pgp. Coadministration of NOV markedly increased oral TPT AUC(0-720) and Cmax by 3- and 4.5-fold, respectively, and decreased systemic clearance of i.v. injected TPT (from 44.40+/-7.28 without NOV to 29.44+/-1.99 ml/min/kg with NOV). The inclusion of NOV in perfusate significantly increased TPT permeability from 0.81+/-0.30 x10(-6) to 1.26+/-0.12 x10(-6) cm/s, while, the intestinal secretion of TPT was reduced by ~50% when NOV was included in perfusate. CONCLUSIONS: The present study establishes in vitro and in vivo inhibition potency and specificity of NOV on BCRP and provides direct evidence that intestinal BCRP plays an important role in limiting the oral absorption and influencing the systemic elimination of TPT.
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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) | 0.001 | 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) | 0.001 | 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".