Isoform-Specific Regulation of Uridine Diphosphate-Glucuronosyltransferase 2B Enzymes in the Human Prostate: Differential Consequences for Androgen and Bioactive Lipid Inactivation
Bibliographic record
Abstract
Androgens as well as monohydroxy-fatty acids are implicated in the pathogenesis of prostate cancer. Like a huge variety of endo- and xenobiotics, they are eliminated as glucuronide conjugates formed by uridine diphosphate-glucuronosyltransferase (UGT) enzymes. In the present study, we observe that treatment of the prostate cancer cells LNCaP with natural and synthetic androgens, IL-1alpha, or epidermal growth factor (EGF) differently modulates the glucuronidation of androgen and bioactive lipid metabolites. Indeed, glucuronidation of 5alpha-androstane-3alpha,17beta-diol and 13-hydroxyoctadecadienoic acid was drastically reduced, whereas 12-hydroxyeicosatetraenoic acid conjugation by UGT was increased after androgen treatment. These effects reflected the reduction of UGT2B10, -B15, and -B17 enzyme expression, and the activation of the UGT2B11 gene. In human prostate epithelial cells, only UGT2B11 and -B15 mRNAs are detected and are regulated by androgens in a similar manner as in LNCaP cells. In LNCaP cells, IL-1alpha and EGF also regulate UGT2B expression in an isoform-specific manner; IL-1alpha induced UGT2B10 and reduced UGT2B17, while having no effects on UGT2B11 mRNA levels. EGF treatment resulted in a decreased UGT2B17 expression, whereas UGT2B10 and -B11 mRNA remained at their basal levels. Overall, these results demonstrate that in the human prostate, androgens do not only affect their own inactivation but also influence the levels of monohydroxy-fatty acids by regulating the expression of UGT2B enzymes in an isoform-specific manner. These differential effects of androgens, IL-1alpha, and EGF on lipid metabolism likely constitute an additional mechanism by which these endogenous factors promote prostate cancer development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".