Patterns of intra- and intertumor phenotypic heterogeneity in lethal prostate cancer
Martine P. Roudier, … , Peter S. Nelson, Michael C. Haffner
Martine P. Roudier, … , Peter S. Nelson, Michael C. Haffner
Published June 10, 2025
Citation Information: J Clin Invest. 2025;135(15):e186599. https://doi.org/10.1172/JCI186599.
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Research Article Cell biology Oncology

Patterns of intra- and intertumor phenotypic heterogeneity in lethal prostate cancer

Abstract

Metastatic prostate cancer (mPC) is a clinically and molecularly heterogeneous disease. While there is increasing recognition of diverse tumor phenotypes across patients, less is known about the molecular and phenotypic heterogeneity present within an individual. In this study, we aimed to define the patterns, extent, and consequences of inter- and intratumoral heterogeneity in lethal prostate cancer. By combining and integrating in situ tissue-based and sequencing approaches, we analyzed over 630 tumor samples from 52 patients with mPC. Our efforts revealed phenotypic heterogeneity at the patient, metastasis, and cellular levels. We observed that intrapatient intertumoral molecular subtype heterogeneity was common in mPC and showed associations with genomic and clinical features. Additionally, cellular proliferation rates varied within a given patient across molecular subtypes and anatomic sites. Single-cell sequencing studies revealed features of morphologically and molecularly divergent tumor cell populations within a single metastatic site. These data provide a deeper insight into the complex patterns of tumoral heterogeneity in mPC with implications for clinical management and the future development of diagnostic and therapeutic approaches.

Authors

Martine P. Roudier, Roman Gulati, Erolcan Sayar, Radhika A. Patel, Micah Tratt, Helen M. Richards, Paloma Cejas, Miguel Munoz Gomez, Xintao Qiu, Yingtian Xie, Brian Hanratty, Samir Zaidi, Jimmy L. Zhao, Mohamed Adil, Chitvan Mittal, Yibai Zhao, Ruth Dumpit, Ilsa Coleman, Jin-Yih Low, Thomas Persse, Patricia Galipeau, John K. Lee, Maria Tretiakova, Meagan Chambers, Funda Vakar-Lopez, Lawrence D. True, Marie Perrone, Hung-Ming Lam, Lori A. Kollath, Chien-Kuang Cornelia Ding, Stephanie Harmon, Heather H. Cheng, Evan Y. Yu, Robert B. Montgomery, Jessica E. Hawley, Daniel W. Lin, Eva Corey, Michael T. Schweizer, Manu Setty, Gavin Ha, Charles L. Sawyers, Colm Morrissey, Henry Long, Peter S. Nelson, Michael C. Haffner

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Figure 5

Dissecting molecular subtype pattern at the single-cell level.

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Dissecting molecular subtype pattern at the single-cell level. UMAP and ...
UMAP and bar graphs depicting molecular subtype composition based on reanalysis of snRNA-seq data of patients with mPC (40). (A) Example of a homogeneous AR+/NE– tumor (MSK−HP13). (B) A more heterogenous AR+/NE– tumor with admixed AR–/NE– cell populations (MSK−HP03). (C and D) UMAPs from additional mPCs can be found in Supplemental Figure 8. IHC micrographs of AR (AR, NKX3.1) and NE markers (SYP, INSM1, ASCL1, and SOX2) representative of (C) an amphicrine carcinoma (10-056) and (D) a mixed/biphenotypic tumor. Note the absence of NE transcription factor expression in the amphicrine carcinoma. Scale bars: 50 mm. (E) Schematic showing different cell states in AR+/NE+ tumors. Note that despite widespread positivity for AR and NKX3.1, there are distinct cell populations that are negative for these AR markers but positive for SYP, INSM1, ASCL1, and SOX2 (arrows). (F) Coimmunolabeling of mixed/biphasic tumor (07-042) highlights distinct AR–/INSM1+ (arrows) and AR+/INSM1+ (arrowheads) cell populations that show adenocarcinoma and small-cell carcinoma morphology, respectively. Scale bars: 50 μm. (G and H) Integrated snRNA-seq and snATAC-seq UMAPs showing cell clusters with differential expression of AR and NE markers. Note low-level AR expression but high NE marker expression in cluster 3. (I) Pseudo–time analysis using Palantir and (J) cell state densities assessment using Mellon showing cell differentiation trajectories across the 3 clusters. (K) Bubble plot highlighting differential single-gene expression across the 3 clusters.