Anticancer Activity of a Novel Selective CYP17A1 Inhibitor in Preclinical Models of Castrate-Resistant Prostate Cancer
Bibliographic record
Abstract
VT-464 is a novel, nonsteroidal, small-molecule CYP17A1 inhibitor with 17,20-lyase selectivity. This study evaluates the anticancer activity of VT-464 compared with abiraterone (ABI) in castrate-resistant prostate cancer cell lines and xenograft models that are enzalutamide (ENZ)-responsive (C4-2) or ENZ-resistant (MR49C, MR49F). In vitro, androgen receptor (AR) transactivation was assessed by probasin luciferase reporter, whereas AR and AR-regulated genes and steroidogenic pathway enzymes were assessed by Western blot and/or qRT-PCR. The MR49F xenograft model was used to compare effects of oral VT-464 treatment to vehicle and abiraterone acetate (AA). Steroid concentrations were measured using LC-MS chromatography. VT-464 demonstrated a greater decrease in AR transactivation compared with ABI in C4-2 and both ENZ-resistant cell lines. At the gene and protein level, VT-464 suppressed the AR axis to a greater extent compared with ABI. Gene transcripts StAR, CYP17A1, HSD17B3, and SRD5A1 increased following treatment with ABI and to a greater extent with VT-464. In vivo, intratumoral androgen levels were significantly lower after VT-464 or AA treatment compared with vehicle, with the greatest decrease seen with VT-464. Similarly, tumor growth inhibition and PSA decrease trends were greater with VT-464 than with AA. Finally, an AR-antagonist effect of VT-464 independent of CYP17A1 inhibition was observed using luciferase reporter assays, and a direct interaction was confirmed using an AR ligand binding domain biolayer interferometry. These preclinical results suggest greater suppression of the AR axis with VT-464 than ABI that is likely due to both superior selective suppression of androgen synthesis and AR antagonism.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".