Insulin Increases <i>De Novo</i> Steroidogenesis in Prostate Cancer Cells
Bibliographic record
Abstract
Androgen-dependent pathways regulate maintenance and growth of normal and malignant prostate tissues. Androgen deprivation therapy (ADT) exploits this dependence and is used to treat metastatic prostate cancer; however, regression initially seen with ADT gives way to development of incurable castration-resistant prostate cancer (CRPC). Although ADT generates a therapeutic response, it is also associated with a pattern of metabolic alterations consistent with metabolic syndrome including elevated circulating insulin. Because CRPC cells are capable of synthesizing androgens de novo, we hypothesized that insulin may also influence steroidogenesis in CRPC. In this study, we examined this hypothesis by evaluating the effect of insulin on steroid synthesis in prostate cancer cell lines. Treatment with 10 nmol/L insulin increased mRNA and protein expression of steroidogenesis enzymes and upregulated the insulin receptor substrate insulin receptor substrate 2 (IRS-2). Similarly, insulin treatment upregulated intracellular testosterone levels and secreted androgens, with the concentrations of steroids observed similar to the levels reported in prostate cancer patients. With similar potency to dihydrotestosterone, insulin treatment resulted in increased mRNA expression of prostate-specific antigen. CRPC progression also correlated with increased expression of IRS-2 and insulin receptor in vivo. Taken together, our findings support the hypothesis that the elevated insulin levels associated with therapeutic castration may exacerbate progression of prostate cancer to incurable CRPC in part by enhancing steroidogenesis.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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 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".