Discovery of a Small-Molecule Inhibitor Targeting the Androgen Receptor N-Terminal Domain for Castration-Resistant Prostate Cancer
Bibliographic record
Abstract
The current mainstay therapeutic strategy for advanced prostate cancer is to suppress androgen receptor (AR) signaling. However, castration-resistant prostate cancer (CRPC) invariably arises with restored AR signaling activity. To date, the AR ligand-binding domain (LBD) is the only targeted region for all clinically available AR signaling antagonists, such as enzalutamide (ENZ). Major resistance mechanisms have been uncovered to sustain the AR signaling in CRPC despite these treatments, including AR amplification, AR LBD mutants, and the emergence of AR splice variants (AR-Vs) such as AR-V7. AR-V7 is a constitutively active truncated form of AR that lacks the LBD; thus, it can not be inhibited by AR LBD-targeting drugs. Therefore, an approach to inhibit AR through the regions outside of LBD is urgently needed. In this study, we have discovered a novel small molecule SC428, which directly binds to the AR N-terminal domain (NTD) and exhibits pan-AR inhibitory effect. SC428 potently decreased the transactivation of AR-V7, ARv567es, as well as full-length AR (AR-FL) and its LBD mutants. SC428 substantially suppressed androgen-stimulated AR-FL nuclear translocation, chromatin binding, and AR-regulated gene transcription. Moreover, SC428 also significantly attenuated AR-V7-mediated AR signaling that does not rely on androgen, hampered AR-V7 nuclear localization, and disrupted AR-V7 homodimerization. SC428 inhibited in vitro proliferation and in vivo tumor growth of cells that expressed a high level of AR-V7 and were unresponsive to ENZ treatment. Together, these results indicated the potential therapeutic benefits of AR-NTD targeting for overcoming drug resistance in CRPC.
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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".