Clinical Utility of Transcriptomic Signatures to Identify Androgen Receptor and Neuroendocrine Signaling in Prostate Cancer.
1/5 보강
[PURPOSE] This study aimed to define molecular subtypes of prostate cancer by integrating androgen receptor (AR) signaling, neuroendocrine prostate cancer (NEPC) transcriptional signatures, and genomi
APA
Chen YW, Xiu J, et al. (2026). Clinical Utility of Transcriptomic Signatures to Identify Androgen Receptor and Neuroendocrine Signaling in Prostate Cancer.. JCO precision oncology, 10, e2500756. https://doi.org/10.1200/PO-25-00756
MLA
Chen YW, et al.. "Clinical Utility of Transcriptomic Signatures to Identify Androgen Receptor and Neuroendocrine Signaling in Prostate Cancer.." JCO precision oncology, vol. 10, 2026, pp. e2500756.
PMID
41785440 ↗
Abstract 한글 요약
[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 14.0 months, < .00001) and lower with the NEPC signature (54.3 16.1 months, < .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).
[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 14.0 months, < .00001) and lower with the NEPC signature (54.3 16.1 months, < .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).
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