Activated Pregnenolone X-Receptor Is a Target for Ketoconazole and Its Analogs
Bibliographic record
Abstract
PURPOSE: Variations in biotransformation and elimination of microtubule-binding drugs are a major cause of unpredictable side effects during cancer therapy. Because the orphan receptor, pregnenolone X-receptor (PXR), coordinately regulates the expression of paclitaxel metabolizing and transport enzymes, controlling this process could improve therapeutic outcome. EXPERIMENTAL DESIGN: In vitro RNA-, protein-, and transcription-based assays in multiple cell lines derived from hepatocytes and PXR wild-type and null mouse studies were employed to show the effects of ketoconazole and its analogues on ligand-activated PXR-mediated gene transcription and translation. RESULTS: The transcriptional activation of genes regulating biotransformation and transport by the liganded human nuclear xenobiotic receptor, PXR, was inhibited by the commonly used antifungal ketoconazole and related azole analogs. Mutations at the AF-2 surface of the human PXR ligand-binding domain indicate that ketoconazole may interact with specific residues outside the ligand-binding pocket. Furthermore, in contrast to that observed in PXR (+/+) mice, genetic loss of PXR results in increased (preserved) blood levels of paclitaxel. CONCLUSIONS: These studies show that some azole compounds repress the coordinated activation of genes involved in drug metabolism by blocking PXR activation. Because loss of PXR maintains blood levels of paclitaxel upon chronic dosing, ketoconazole analogues may also serve to preserve paclitaxel blood levels on chronic dosing of drugs. Our observations may facilitate new strategies to improve the clinical efficacy of drugs and to reduce therapeutic side effects.
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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 | 0.000 |
| 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".