Sympathetic signaling facilitates progression of neuroendocrine prostate cancer
Bibliographic record
Abstract
The progression of prostate cancer (PC) into neuroendocrine prostate cancer (NEPC) is a major challenge in treating PC. In NEPC, the PC cells undergo neuroendocrine differentiation (NED); however, the exact molecular mechanism that triggers NED is unknown. Peripheral nerves are recently shown to promote PC. However, their contribution to NEPC was not studied well. In this study, we explored whether sympathetic neurosignaling contributes to NED. We found that human prostate tumors from patients that later developed metastases and castration-resistant prostate cancer (CRPC), a stage preceding to NEPC, have high sympathetic innervations. Our work revealed that high concentrations of the sympathetic neurotransmitter norepinephrine (NE) induces NED-like changes in PC cells in vitro, evident by their characteristic cellular and molecular changes. The NE-mediated NED was effectively inhibited by the Adrβ2 blocker propranolol. Strikingly, propranolol along with castration also significantly inhibited the development and progression of NEPC in vivo in an orthotopic NEPC model. Altogether, our results indicate that the NE-Adrβ2 axis is a potential therapeutic intervention point for NEPC.
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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 | 0.001 |
| 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 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".