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Background/Objectives: Bone metastasis is a frequent and life-threatening event in advanced cancers, affecting up to 70-85% of prostate cancer patients. Understanding the cellular and molecular mechanisms underlying bone metastasis is essential for developing targeted therapies. This study aimed to systematically characterize the heterogeneity and microenvironmental adaptation of prostate cancer bone metastases using single-cell transcriptomics. Methods: We integrated the largest single-cell transcriptome dataset to date, encompassing 124 samples from primary prostate tumors, various bone metastatic sites, and non-malignant tissues (e.g., benign prostatic hyperplasia, normal bone marrow). After quality control, 602,497 high-quality single-cell transcriptomes were analyzed. We employed unsupervised clustering, gene expression profiling, mutation analysis, and metabolic pathway reconstruction to characterize cancer cell subtypes and tumor microenvironmental remodeling. Results: Cancer epithelial cells dominated the tumor microenvironment but exhibited pronounced heterogeneity, posing challenges for conventional clustering methods. By integrating genetic and metabolic features, we revealed key evolutionary trajectories of epithelial cancer cells during metastasis. Notably, we identified a novel epithelial subpopulation, NEndoCs, characterized by unique differentiation patterns and distinct spatial distribution across metastatic niches. We also observed significant metabolic reprogramming and recurrent mutations linked to prostate-to-bone microenvironmental transitions. Conclusions: This study comprehensively elucidates the mutation patterns, metabolic reprogramming, and microenvironment adaptation mechanisms of bone metastasis in prostate cancer, providing key molecular targets and clinical strategies for the precise treatment of bone metastatic prostate cancer.

More information Original publication

DOI

10.3390/biomedicines13040909

Type

Journal article

Publication Date

2025-04-09T00:00:00+00:00

Volume

13

Keywords

bone metastasis, metabolism and cytokines, prostate cancer, single-cell RNA sequencing, spatiotemporal microevolution