Generation 2.5 Antisense Oligonucleotides Targeting the Androgen Receptor and Its Splice Variants Suppress Enzalutamide-Resistant Prostate Cancer Cell Growth
Bibliographic record
Abstract
PURPOSE: Enzalutamide (ENZ) is a potent androgen receptor (AR) antagonist with activity in castration-resistant prostate cancer (CRPC); however, progression to ENZ-resistant (ENZ-R) CRPC frequently occurs with rising serum PSA levels, implicating AR full-length (ARFL) or variants (AR-Vs) in disease progression. EXPERIMENTAL DESIGN: To define functional roles of ARFL and AR-Vs in ENZ-R CRPC, we designed 3 antisense oligonucleotides (ASO) targeting exon-1, intron-1, and exon-8 in AR pre-mRNA to knockdown ARFL alone or with AR-Vs, and examined their effects in three CRPC cell lines and patient-derived xenografts. RESULTS: ENZ-R-LNCaP cells express high levels of both ARFL and AR-V7 compared with CRPC-LNCaP; in particular, ARFL levels were approximately 12-fold higher than AR-V7. Both ARFL and AR-V7 are highly expressed in the nuclear fractions of ENZ-R-LNCaP cells even in the absence of exogenous androgens. In ENZ-R-LNCaP cells, knockdown of ARFL alone, or ARFL plus AR-Vs, similarly induced apoptosis, suppressed cell growth and AR-regulated gene expression, and delayed tumor growth in vivo. In 22Rv1 cells that are inherently ENZ-resistant, knockdown of both ARFL and AR-Vs more potently suppressed cell growth, AR transcriptional activity, and AR-regulated gene expression than knockdown of ARFL alone. Exon-1 AR-ASO also inhibited tumor growth of LTL-313BR patient-derived CRPC xenografts. CONCLUSIONS: These data identify the AR as an important driver of ENZ resistance, and while the contributions of ARFL and AR-Vs can vary across cell systems, ARFL is the key driver in the ENZ-R LNCaP model. AR targeting strategies against both ARFL and AR-Vs is a rational approach for AR-dependent CRPC.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".