Abstract A079: A single-cell RNA expression atlas of metastatic prostate cancer: tumor cell evolution from AR sensitive to castration resistance

Abstract Background: Metastatic prostate cancer, a leading cause of prostate cancer mortality, exhibits therapy-induced tumor cells plasticity and associated intra-tumoral and organ-specific heterogeneity. Patients with alterations of tumor suppressor genes (TSGs) represent a hard-to-treat subgroup that often progresses to metastatic castration resistant prostate cancer (mCRPC) and neuroendocrine (NE) prostate cancer (NEPC). To understand the molecular mechanisms of mCRPC/NEPC progression and develop targeted therapies, we developed an AR positive patient-derived metastasis model that harbors TSGs alterations in TP53, PTEN, and RB1 (termed PDM136). Upon intracardiac injection in NSG mice, PDM136 develops bone, liver and adrenal metastases with AR+NE- histological phenotypes; tumor cells became heterogeneous with ARlowNE-, AR-NE+, AR-NE- subgroups following castration. Interestingly, bone metastatic tumors are mainly ARlowNE- and AR-NE-, while the majority of liver metastases are AR-NE+, recapitulating the major phenotypes of bone and liver metastasis in mCRPC patients. Methods: To understand global changes in tumor cell evolution across during castration, we profiled the single-cell transcriptomes of > 70,000 cells encompassing intact, early castrated, intermediate castrated and later castrated stages from bone, liver and adrenal metastases. Clustering, velocity and trajectory analyses were performed. Pseudo-bulk differential expression analyses were used to identify cell states, enriched pathways, and distinct castration-responsive tumor cell populations. Results: We identified 14 unique clusters representing heterogeneous cell states. Velocity and trajectory analysis of specific clusters suggested castration-associated plasticity. The transition from castration sensitive to castration resistance is associated with decreased AR signature and increased NE signature in a subset of neuroendocrine clusters marked by high expression of SOX2 and ASCL1. Tumor cells in liver metastases switched to a NE state earlier than bone and adrenal metastases. Many clusters also maintained a transition state during the development of castration resistance marked by dual negativity for AR and NE signatures. The transition state in bone metastases showed an upregulation of TGFb, notch and Wnt pathways that trigger EMT and stemness. Conclusions: These results suggest that while prostate tumor cells harboring TSGs are initially AR sensitive, they can achieve castration resistance via different mechanisms. Our study highlights the significance of using clinically relevant animal models to assess variable mechanisms that drive progression of mCRPC. Observed cellular plasticity and intra-/inter-tumor heterogeneity suggest that combination therapies targeting multiple pathways may be crucial for the effective management of mCRPC. Citation Format: JuanJuan I. Yin, Anson Ku, Chennan Li, Joseph Twohig, Tri Truong, Dana Vargas, Adam Sowalsky. A single-cell RNA expression atlas of metastatic prostate cancer: tumor cell evolution from AR sensitive to castration resistance [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Innovations in Prostate Cancer Research and Treatment; 2026 Jan 20-22; Philadelphia PA. Philadelphia (PA): AACR; Cancer Res 2026;86(2_Suppl):Abstract nr A079.

Authors

Publication Details

Journal
Cancer Research
Published
2026-01-20
DOI
https://doi.org/10.1158/1538-7445.prostateca26-a079
Primary Topic
Prostate Cancer Treatment and Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract A079: A single-cell RNA expression atlas of metastatic prostate cancer: tumor cell evolution from AR sensitive to castration resistance

Anson T. Ku, Adam G. Sowalsky, Chennan Li, Tri M. Truong et al.
Cancer Research
Prostate Cancer Treatment and Research
article

Abstract A079: A single-cell RNA expression atlas of metastatic prostate cancer: tumor cell evolution from AR sensitive to castration resistance

Anson T. Ku, Adam G. Sowalsky, Chennan Li, Tri M. Truong, Joseph D. Twohig, Dana S. Vargas, JuanJuan I. Yin
article en

Abstract

Abstract Background: Metastatic prostate cancer, a leading cause of prostate cancer mortality, exhibits therapy-induced tumor cells plasticity and associated intra-tumoral and organ-specific heterogeneity. Patients with alterations of tumor suppressor genes (TSGs) represent a hard-to-treat subgroup that often progresses to metastatic castration resistant prostate cancer (mCRPC) and neuroendocrine (NE) prostate cancer (NEPC). To understand the molecular mechanisms of mCRPC/NEPC progression and develop targeted therapies, we developed an AR positive patient-derived metastasis model that harbors TSGs alterations in TP53, PTEN, and RB1 (termed PDM136). Upon intracardiac injection in NSG mice, PDM136 develops bone, liver and adrenal metastases with AR+NE- histological phenotypes; tumor cells became heterogeneous with ARlowNE-, AR-NE+, AR-NE- subgroups following castration. Interestingly, bone metastatic tumors are mainly ARlowNE- and AR-NE-, while the majority of liver metastases are AR-NE+, recapitulating the major phenotypes of bone and liver metastasis in mCRPC patients. Methods: To understand global changes in tumor cell evolution across during castration, we profiled the single-cell transcriptomes of > 70,000 cells encompassing intact, early castrated, intermediate castrated and later castrated stages from bone, liver and adrenal metastases. Clustering, velocity and trajectory analyses were performed. Pseudo-bulk differential expression analyses were used to identify cell states, enriched pathways, and distinct castration-responsive tumor cell populations. Results: We identified 14 unique clusters representing heterogeneous cell states. Velocity and trajectory analysis of specific clusters suggested castration-associated plasticity. The transition from castration sensitive to castration resistance is associated with decreased AR signature and increased NE signature in a subset of neuroendocrine clusters marked by high expression of SOX2 and ASCL1. Tumor cells in liver metastases switched to a NE state earlier than bone and adrenal metastases. Many clusters also maintained a transition state during the development of castration resistance marked by dual negativity for AR and NE signatures. The transition state in bone metastases showed an upregulation of TGFb, notch and Wnt pathways that trigger EMT and stemness. Conclusions: These results suggest that while prostate tumor cells harboring TSGs are initially AR sensitive, they can achieve castration resistance via different mechanisms. Our study highlights the significance of using clinically relevant animal models to assess variable mechanisms that drive progression of mCRPC. Observed cellular plasticity and intra-/inter-tumor heterogeneity suggest that combination therapies targeting multiple pathways may be crucial for the effective management of mCRPC. Citation Format: JuanJuan I. Yin, Anson Ku, Chennan Li, Joseph Twohig, Tri Truong, Dana Vargas, Adam Sowalsky. A single-cell RNA expression atlas of metastatic prostate cancer: tumor cell evolution from AR sensitive to castration resistance [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Innovations in Prostate Cancer Research and Treatment; 2026 Jan 20-22; Philadelphia PA. Philadelphia (PA): AACR; Cancer Res 2026;86(2_Suppl):Abstract nr A079.

Cancer ResearchVol. 86(2_Supplement)
Good health and well-being
Openalex Percentile: Top 83%
Prostate Cancer Treatment and Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.