MP68-16 XENOBIOTIC METABOLISM OF ABIRATERONE ACETATE AND GLUCOCORTICOIDS BY THE GUT MICROBIOTA
Bibliographic record
Abstract
You have accessJournal of UrologyProstate Cancer: Basic Research & Pathophysiology II (MP68)1 Apr 2019MP68-16 XENOBIOTIC METABOLISM OF ABIRATERONE ACETATE AND GLUCOCORTICOIDS BY THE GUT MICROBIOTA Kamilah Abdur-Rashid*, Shiva Nair, Ryan Chanyi, Joseph Chin, and Jeremy Burton Kamilah Abdur-Rashid*Kamilah Abdur-Rashid* More articles by this author , Shiva NairShiva Nair More articles by this author , Ryan ChanyiRyan Chanyi More articles by this author , Joseph ChinJoseph Chin More articles by this author , and Jeremy BurtonJeremy Burton More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000557031.40448.62AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: Testosterone and dihydrotestosterone (DHT) stimulate the growth of prostate cancer by activating androgen receptors. Androgen deprivation therapy (ADT), the first line of systemic treatment, aims to decrease circulating androgens to castrate levels; however, castration resistant prostate cancer (CRPC) can develop. Abiraterone acetate (AA), an inhibitor of androgen synthesis, in combination with supportive glucocorticoids are used to treat CRPC. Many drugs are orally ingested and pass through the gastrointestinal tract, however, the dense bacterial population in the gut is often overlooked. We hypothesize that AA can modify the composition of the gut microbiota and gut bacteria can transform glucocorticoids into compounds that can activate androgen receptors. METHODS: A chemostat gut model was inoculated with human feces and exposed to physiological doses of AA. Samples were analyzed by culture-dependent and -independent methodologies. Bacterial isolates that increased in abundance upon exposure to AA were tested on agar containing AA. Secondly, Clostridium scindens, a corticosteroid-utilizing gut bacterium with known androgenic-producing abilities, were exposed to various clinically relevant glucocorticoids (prednisone, prednisolone and dexamethasone). The metabolic products were measured by liquid chromatography-mass spectrometry and bacterial gene expression by quantitative PCR. A yeast-based human androgen receptor assay was also used to detect the biotransformation of glucocorticoids for potential activation by bacterial metabolites. RESULTS: The bacterial composition of the gut model changed when exposed to AA. Select bacterial isolates were also able to utilize AA as a sole carbon source. C. scindens was found to metabolize prednisone, prednisolone and dexamethasone, possibly using machinery encoded on the desABCD operon. Gene expression analysis revealed increased expression of: desA by 8-fold; desB by 5.2-fold; desC by 4.8-fold; and desD by 2.6-fold. DHT-like activity on human androgen receptor assay increased significantly with C. scindens incubation with prednisone (3.6±0.8×10−9M) but not with prednisolone (no detectable activation) or dexamethasone (no detectable activation). CONCLUSIONS: These results suggest that we may need to consider the role of the gut microbiota in the treatment of CRPC. Bacterial interactions may change the pharmaceutical properties of drugs such as AA. Prednisone, co-administered with AA, can also be metabolized into androgenic compounds, which may play a part in CRPC treatment failure. Source of Funding: none London, Canada© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e981-e981 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Kamilah Abdur-Rashid* More articles by this author Shiva Nair More articles by this author Ryan Chanyi More articles by this author Joseph Chin More articles by this author Jeremy Burton More articles by this author Expand All Advertisement PDF downloadLoading ...
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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 | 0.000 | 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) | 0.000 | 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".