Impaired Dihydrotestosterone Catabolism in Human Prostate Cancer: Critical Role of AKR1C2 as a Pre-Receptor Regulator of Androgen Receptor Signaling
Bibliographic record
Abstract
We previously reported the selective loss of AKR1C2 and AKR1C1 in prostate cancers compared with their expression in paired benign tissues. We now report that dihydrotestosterone (DHT) levels are significantly greater in prostate cancer tumors compared with their paired benign tissues. Decreased catabolism seems to account for the increased DHT levels as expression of AKR1C2 and SRD5A2 was reduced in these tumors compared with their paired benign tissues. After 4 h of incubation with benign tissue samples, (3)H-DHT was predominantly catabolized to the 5alpha-androstane-3alpha,17beta-diol metabolite. Reduced capacity to metabolize DHT was observed in tumor samples from four of five freshly isolated pairs of tissue samples, which paralleled loss of AKR1C2 and AKR1C1 expression. LAPC-4 cells transiently transfected with AKR1C1 and AKR1C2, but not AKR1C3, were able to significantly inhibit a dose-dependent, DHT-stimulated proliferation, which was associated with a significant reduction in the concentration of DHT remaining in the media. R1881-stimulated proliferation was equivalent in all transfected cells, showing that metabolism of DHT was responsible for the inhibition of proliferation. PC-3 cells overexpressing AKR1C2 and, to a lesser extent, AKR1C1 were able to significantly inhibit DHT-dependent androgen receptor reporter activity, which was abrogated by increasing DHT levels. We speculate that selective loss of AKR1C2 in prostate cancer promotes clonal expansion of tumor cells by enhancement of androgen-dependent cellular proliferation by reducing DHT metabolism.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".