Conclusions
This study demonstrates that further analytical validation and clinical qualification are required before AR-V7 can be considered for clinical use in CSPC as a predictive biomarker.
Purpose
Therapies targeting the androgen receptor (AR) have improved the outcome for patients with castration-sensitive prostate cancer (CSPC). Expression of the constitutively active AR splice variant-7 (AR-V7) has shown clinical utility as a predictive biomarker of AR-targeted therapy resistance in castration-resistant prostate cancer (CRPC), but its importance in CSPC remains understudied. Experimental design: We assessed different approaches to quantify AR-V7 mRNA and protein in prostate cancer cell lines, patient-derived xenograft (PDX) models, publicly available cohorts, and independent institutional clinical cohorts, to identify reliable approaches for detecting AR-V7 mRNA and protein and its association with clinical outcome.
Results
In CSPC and CRPC cohorts, AR-V7 mRNA was much less abundant when detected using reads across splice boundaries than when considering isoform-specific exonic reads. The RM7 AR-V7 antibody had increased sensitivity and specificity for AR-V7 protein detection by immunohistochemistry (IHC) in CRPC cohorts but rarely identified AR-V7 protein reactivity in CSPC cohorts, when compared with the EPR15656 AR-V7 antibody. Using multiple CRPC PDX models, we demonstrated that AR-V7 expression was exquisitely sensitive to hormonal manipulation. In CSPC institutional cohorts, AR-V7 protein quantification by either assay was associated neither with time to development of castration resistance nor with overall survival, and intense neoadjuvant androgen-deprivation therapy did not lead to significant AR-V7 mRNA or staining following treatment. Neither pre- nor posttreatment AR-V7 levels were associated with volumes of residual disease after therapy. Conclusions: This study demonstrates that further analytical validation and clinical qualification are required before AR-V7 can be considered for clinical use in CSPC as a predictive biomarker.