Combination therapy with androgen receptor N‐terminal domain antagonist EPI‐7170 and enzalutamide yields synergistic activity in AR‐V7‐positive prostate cancer
Why this work is in the frame
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Bibliographic record
Abstract
Resistance of castration-resistant prostate cancer (CRPC) to enzalutamide and abiraterone involves the expression of constitutively active, truncated androgen receptor (AR) splice variants (AR-Vs) that lack a C-terminal ligand-binding domain (LBD). Both full-length AR and truncated AR-Vs require a functional N-terminal domain (NTD) for transcriptional activity thereby providing rationale for the development of ralaniten (EPI-002) as a first-in-class antagonist of the AR-NTD. Here, we evaluated the antitumor effect of a next-generation analog of ralaniten (EPI-7170) as a monotherapy or in combination with enzalutamide in prostate cancer cells that express AR-V7 that were resistant to enzalutamide. EPI-7170 had 8-9 times improved potency compared to ralaniten. Enzalutamide increased levels of AR-V7 and expression of its target genes. Knockdown of AR-V7 restored sensitivity to enzalutamide, indicating a role for AR-V7 in the mechanism of resistance. EPI-7170 inhibited expression of genes transcriptionally regulated by full-length AR and AR-V7. A combination of EPI-7170 and enzalutamide resulted in synergistic inhibition of proliferation of enzalutamide-resistant cells that was consistent with results from cell cycle and clonogenic assays. In addition, this drug enhanced the antitumor effect of enzalutamide in enzalutamide-resistant CRPC preclinical models. Thus, a combination therapy targeting both the NTD and LBD of AR, and thereby blocking both full-length AR and AR-Vs, has potential for the treatment of enzalutamide-resistant CRPC.
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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 | 0.000 |
| 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 it