Related Experiment Video
Updated: Jun 14, 2026
Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Published on: November 2, 2013
Clinical Utility of Transcriptomic Signatures to Identify Androgen Receptor and Neuroendocrine Signaling in Prostate
Yu-Wei Chen1, Joanne Xiu2, Kelsey Anne Poorman2
1Division of Hematology Oncology, Department of Medicine, University of California San Diego School of Medicine, San Diego, CA.
Purpose:
This study aimed to define molecular subtypes of prostate cancer by integrating androgen receptor (AR) signaling, neuroendocrine prostate cancer (NEPC) transcriptional signatures, and genomic alterations to inform biomarker-driven therapies in metastatic castration-resistant prostate cancer.
Methods:
We analyzed 8,019 prostate tumors using DNA/RNA sequencing (Caris Life Sciences), classifying them into four molecular subtypes (AR+/NE-, AR-/NE+, AR+/NE+, AR-/NE-). Genomic alterations, cell surface target expression, and overall survival (OS) were evaluated.
Results:
Of the 8,019 tumors, 87.2% were adenocarcinoma, 1.9% NEPC, and 0.4% had mixed histology; 63% were from primary sites and 36.5% from metastases. The median age was 68 years; 63% were White, 15% Black, and 2.6% Asian or Pacific Islander. Most tumors were classified as AR+/NE- (91%), and 4.6% were AR-/NE+. TP53 and PTEN alterations were enriched in AR-negative subtypes, whereas SPOP mutations were more frequent in AR+ tumors. FOLH1 (prostate-specific membrane antigen) expression was the highest in AR+ tumors, whereas DLL3 expression was elevated in NE+ tumors. Median OS was significantly longer in tumors with high AR signaling (55.0 v 14.0 months, P < .00001) and lower with the NEPC signature (54.3 v 16.1 months, P < .00001). Combined stratification showed the most favorable outcome in AR+/NE- tumors (55.3 months) and the poorest in AR-/NE+ tumors (12.0 months).
Conclusion:
Prostate cancer exhibits distinct molecular subtypes defined by AR signaling activity, NEPC transcriptional profiles, and genomic alterations. These biologically and clinically relevant subgroups provide a framework for precision oncology approaches and inform patient selection for biomarker-driven trials such as the ongoing PREDICT study (ClinicalTrials.gov identifier: NCT06632977).
