Prostate cancer progression can be associated with androgen receptor (AR) mutations acquired following treatment with castration and/or an antiandrogen. Abiraterone, a rationally designed inhibitor of CYP17A1 recently approved for the treatment of docetaxel-treated castration-resistant prostate cancer (CRPC), is often effective, but requires coadministration with glucocorticoids to curtail side effects. Here, we hypothesized that progressive disease on abiraterone may occur secondary to glucocorticoid-induced activation of mutated AR. We found that prednisolone plasma levels in patients with CRPC were sufficiently high to activate mutant AR. Mineralocorticoid receptor antagonists, such as spironolactone and eplerenone that are used to treat side effects related to mineralocorticoid excess, can also bind to and activate signaling through wild-type or mutant AR. Abiraterone inhibited in vitro proliferation and AR-regulated gene expression of AR-positive prostate cancer cells, which could be explained by AR antagonism in addition to inhibition of steroidogenesis. In fact, activation of mutant AR by eplerenone was inhibited by MDV3100, bicalutamide, or greater concentrations of abiraterone. Therefore, an increase in abiraterone exposure could reverse resistance secondary to activation of AR by residual ligands or coadministered drugs. Together, our findings provide a strong rationale for clinical evaluation of combined CYP17A1 inhibition and AR antagonism. Cancer Res; 72(9); 2176-82. Ó2012 AACR.

Prostate cancer is heterogeneous and patients would benefit from methods that stratify those who are likely to respond to systemic therapy. Here, we employ single-cell assays for transposase-accessible chromatin (ATAC) and RNA sequencing in models of early treatment response and resistance to enzalutamide. In doing so, we identify pre-existing and treatment-persistent cell subpopulations that possess regenerative potential when subjected to treatment. We find distinct chromatin landscapes associated with enzalutamide treatment and resistance that are linked to alternative transcriptional programs. Transcriptional profiles characteristic of persistent cells are able to stratify the treatment response of patients. Ultimately, we show that defining changes in chromatin and gene expression in single-cell populations from pre-clinical models can reveal as yet unrecognized molecular predictors of treatment response. This suggests that the application of single-cell methods with high analytical resolution in pre-clinical models may powerfully inform clinical decision-making.