N‐terminal targeting of androgen receptor variant enhances response of castration resistant prostate cancer to taxane chemotherapy
Bibliographic record
Abstract
Taxane-based chemotherapy is an effective treatment for castration-resistant-prostate cancer (CRPC) via stabilization of microtubules. Previous studies identified that the inhibitory effect of microtubule-targeting chemotherapy on androgen receptor (AR) activity was conferred by interfering with AR intracellular trafficking. The N-terminal domain (NTD) of AR was identified as a tubulin-interacting domain that can be effectively targeted by the novel small molecule inhibitor, EPI. Taken together this evidence provided the rationale that targeting AR nuclear translocation and activity via a combination of an antagonist of the AR NTD and taxane-based chemotherapy may enhance the therapeutic response in CRPC. The present study investigated the anti-tumor efficacy of a combination of EPI with Docetaxel chemotherapy, in cell models of CRPC, harboring the AR splice variants in addition to the full length AR. Our findings demonstrate that there was no significant effect on the androgen-mediated nuclear transport of AR variants and AR transcriptional activity by Docetaxel. The therapeutic response to Docetaxel was enhanced by inhibition of the NTD of AR (by EPI) through cycling of epithelial-mesenchymal-transition (EMT) to mesenchymal-epithelial-transition (MET) among prostate cancer epithelial cells. These results support that transient "programming" of EMT by the AR NTD inhibitor, potentially drives the sensitivity of prostate tumors with differential distribution of AR variants to microtubule-targeting chemotherapy. This study is of major significance in dissecting mechanisms to overcome taxane resistance in advanced 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 | 0.000 |
| 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".