Single-cell analysis revealing the metabolic landscape of prostate cancer.
Jing Wang, He-Kang Ding, Han-Jiang Xu, De-Kai Hu, William Hankey, Li Chen, Jun Xiao, Chao-Zhao Liang, Bing Zhao, Ling-Fan Xu
Author Information
Jing Wang: Department of Urologic Oncology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230031, China.
He-Kang Ding: Department of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei 230001, China.
Han-Jiang Xu: Department of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei 230001, China.
De-Kai Hu: Department of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei 230001, China.
William Hankey: Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.
Li Chen: Department of Geriatrics, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China.
Jun Xiao: Department of Urology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China.
Chao-Zhao Liang: Department of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei 230001, China.
Bing Zhao: Department of Geriatrics, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China.
Ling-Fan Xu: Department of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei 230001, China.
ABSTRACT: Tumor metabolic reprogramming is a hallmark of cancer development, and targeting metabolic vulnerabilities has been proven to be an effective approach for castration-resistant prostate cancer (CRPC) treatment. Nevertheless, treatment failure inevitably occurs, largely due to cellular heterogeneity, which cannot be deciphered by traditional bulk sequencing techniques. By employing computational pipelines for single-cell RNA sequencing, we demonstrated that epithelial cells within the prostate are more metabolically active and plastic than stromal cells. Moreover, we identified that neuroendocrine (NE) cells tend to have high metabolic rates, which might explain the high demand for nutrients and energy exhibited by neuroendocrine prostate cancer (NEPC), one of the most lethal variants of prostate cancer (PCa). Additionally, we demonstrated through computational and experimental approaches that variation in mitochondrial activity is the greatest contributor to metabolic heterogeneity among both tumor cells and nontumor cells. These results establish a detailed metabolic landscape of PCa, highlight a potential mechanism of disease progression, and emphasize the importance of future studies on tumor heterogeneity and the tumor microenvironment from a metabolic perspective.
