The Master Neural Transcription Factor BRN2 Is an Androgen Receptor–Suppressed Driver of Neuroendocrine Differentiation in Prostate Cancer
Why this work is in the frame
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Bibliographic record
Abstract
Mechanisms controlling the emergence of lethal neuroendocrine prostate cancer (NEPC), especially those that are consequences of treatment-induced suppression of the androgen receptor (AR), remain elusive. Using a unique model of AR pathway inhibitor-resistant prostate cancer, we identified AR-dependent control of the neural transcription factor BRN2 (encoded by POU3F2) as a major driver of NEPC and aggressive tumor growth, both in vitro and in vivo Mechanistic studies showed that AR directly suppresses BRN2 transcription, which is required for NEPC, and BRN2-dependent regulation of the NEPC marker SOX2. Underscoring its inverse correlation with classic AR activity in clinical samples, BRN2 expression was highest in NEPC tumors and was significantly increased in castration-resistant prostate cancer compared with adenocarcinoma, especially in patients with low serum PSA. These data reveal a novel mechanism of AR-dependent control of NEPC and suggest that targeting BRN2 is a strategy to treat or prevent neuroendocrine differentiation in prostate tumors. SIGNIFICANCE: Understanding the contribution of the AR to the emergence of highly lethal, drug-resistant NEPC is critical for better implementation of current standard-of-care therapies and novel drug design. Our first-in-field data underscore the consequences of potent AR inhibition in prostate tumors, revealing a novel mechanism of AR-dependent control of neuroendocrine differentiation, and uncover BRN2 as a potential therapeutic target to prevent emergence of NEPC. Cancer Discov; 7(1); 54-71. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 1.
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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 | 0.001 |
| 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 it