PEG10 is associated with treatment-induced neuroendocrine prostate cancer
Bibliographic record
Abstract
Neuroendocrine (NE) differentiation of advanced prostate adenocarcinoma following androgen receptor (AR) axis-directed therapy is becoming increasingly recognized. Several models of this transdifferentiation provide insight into its molecular pathogenesis and have highlighted the placental gene PEG10 for further study. Using our unique model of enzalutamide resistance (ENZR) and NE differentiation, we studied PEG10/AR interplay in enzalutamide treatment-resistant cell lines 42DENZR and 42FENZR compared to LNCaP and castration-resistant 16DCRPC cells. ENZR cell lines with positive terminal NE marker status also displayed higher baseline expression of PEG10 compared to LNCaP and 16DCRPC. Antagonism of AR activity increased PEG10 expression followed by an increase in terminal NE markers. Conversely, stimulating AR activity via androgen supplementation reversed PEG10 and NE marker expression in a time and dose-dependent manner. These results were supported by human data showing that PEG10 expression is highest in NEPC and that AR-dependent gene, PSA, is negatively correlated with PEG10 in adenocarcinoma. Further, ChIP assay confirmed binding of activated AR to the PEG10 enhancer, decreasing PEG10 expression. While PEG10 did not drive NEPC, its knockdown reduced NE markers in our cell lines. Moreover, PEG10 knockdown in vitro- and in vivo-attenuated tumor growth. Overall, these observations indicate that PEG10 is an AR-repressed gene which modulates NE markers in ENZR cells and targeting PEG10 in advanced prostate cancer with NE features is a rational and viable option.
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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) | 0.001 | 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".