ASCL1 regulates and cooperates with FOXA2 to drive terminal neuroendocrine phenotype in prostate cancer
Bibliographic record
Abstract
Lineage plasticity mediates resistance to androgen receptor pathway inhibitors (ARPIs) and progression from adenocarcinoma to neuroendocrine prostate cancer (NEPC), a highly aggressive and poorly understood subtype. Neuronal transcription factor ASCL1 has emerged as a central regulator of the lineage plasticity driving neuroendocrine differentiation. Here, we showed that ASCL1 was reprogrammed in ARPI-induced transition to terminal NEPC and identified that the ASCL1 binding pattern tailored the expression of lineage-determinant transcription factor combinations that underlie discrete terminal NEPC identity. Notably, we identified FOXA2 as a major cofactor of ASCL1 in terminal NEPC, which is highly expressed in ASCL1-driven NEPC. Mechanistically, FOXA2 and ASCL1 interacted and worked in concert to orchestrate terminal neuronal differentiation. We identified that prospero homeobox 1 was a target of ASCL1 and FOXA2. Targeting prospero homeobox 1 abrogated neuroendocrine characteristics and led to a decrease in cell proliferation in vitro and tumor growth in vivo. Our findings provide insights into the molecular conduit underlying the interplay between different lineage-determinant transcription factors to support the neuroendocrine identity and nominate prospero homeobox 1 as a potential target in ASCL1-high NEPC.
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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 | 0.000 | 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 | 0.000 |
| 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".