AR-V7 condensates drive androgen-independent transcription in castration resistant prostate cancer
Bibliographic record
Abstract
Summary Biomolecular condensates organize cellular environments and regulate key processes such as transcription. We previously showed that full-length androgen receptor (AR-FL), a major oncogenic driver in prostate cancer (PCa), forms nuclear condensates upon androgen stimulation in androgen-sensitive PCa cells. Disrupting these condensates impairs AR-FL transcriptional activity, highlighting their functional importance. However, resistance to androgen deprivation therapy often leads to castration-resistant prostate cancer (CRPC), driven by constitutively active splice variants like AR variant 7 (AR-V7). The mechanisms underlying AR-V7’s role in CRPC remain unclear. In this study, we characterized the condensate-forming ability of AR-V7 and compared its phase behavior with AR-FL across a spectrum of PCa models and in vitro conditions. Our findings indicate that cellular context can influence AR-V7’s condensate-forming capacity. Unlike AR-FL, AR-V7 spontaneously forms condensates in the absence of androgen stimulation and functions independently of AR-FL in CRPC models. However, AR-V7 requires a higher concentration to form condensates, both in cellular contexts and in vitro . We further reveal that AR-V7 drives transcription via both condensate-dependent and condensate-independent mechanisms. Using an AR-V7 mutant incapable of forming condensates, while retaining nuclear localization and DNA-binding ability, we reveal that the condensate-dependent regime activates part of the oncogenic KRAS pathway in CRPC models. Genes under this condensate-dependent regime were found to harbor significantly higher numbers of AR-binding sites and exhibited boosted expression in response to AR-V7. These findings uncover a previously unrecognized role of AR-V7 condensate formation in driving oncogenic transcriptional programs and shed light on its unique contribution to CRPC progression. Highlights AR-V7 condensates form independently of both androgens and AR-FL in CRPC models. AR-V7 mediates condensate-dependent and independent transcription Condensate-dependent transcription enables boosted expression of oncogenic KRAS genes Condensate-dependent genes exhibit an exponential increase in expression, with a higher number of AR binding sites potentially playing a key role in their reliance on condensate formation. Graphical Abstract
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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) | 0.002 | 0.001 |
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".