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Active DHEA uptake in the prostate gland correlates with aggressive prostate cancer
Xuebin Zhang, … , Denglong Wu, Zhenfei Li
Xuebin Zhang, … , Denglong Wu, Zhenfei Li
Published December 15, 2023
Citation Information: J Clin Invest. 2023;133(24):e171199. https://doi.org/10.1172/JCI171199.
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Research Article Oncology

Active DHEA uptake in the prostate gland correlates with aggressive prostate cancer

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Abstract

Strategies for patient stratification and early intervention are required to improve clinical benefits for patients with prostate cancer. Here, we found that active DHEA utilization in the prostate gland correlated with tumor aggressiveness at early disease stages, and 3βHSD1 inhibitors were promising for early intervention. [3H]-labeled DHEA consumption was traced in fresh prostatic biopsies ex vivo. Active DHEA utilization was more frequently found in patients with metastatic disease or therapy-resistant disease. Genetic and transcriptomic features associated with the potency of prostatic DHEA utilization were analyzed to generate clinically accessible approaches for patient stratification. UBE3D, by regulating 3βHSD1 homeostasis, was discovered to be a regulator of patient metabolic heterogeneity. Equilin suppressed DHEA utilization and inhibited tumor growth as a potent 3βHSD1 antagonist, providing a promising strategy for the early treatment of aggressive prostate cancer. Overall, our findings indicate that patients with active prostatic DHEA utilization might benefit from 3βHSD1 inhibitors as early intervention.

Authors

Xuebin Zhang, Zengming Wang, Shengsong Huang, Dongyin He, Weiwei Yan, Qian Zhuang, Zixian Wang, Chenyang Wang, Qilong Tan, Ziqun Liu, Tao Yang, Ying Liu, Ruobing Ren, Jing Li, William Butler, Huiru Tang, Gong-Hong Wei, Xin Li, Denglong Wu, Zhenfei Li

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Figure 4

Somatic mutations associated with prostatic 3βHSD1 activity.

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Somatic mutations associated with prostatic 3βHSD1 activity.
(A) Genomic...
(A) Genomic regions with marked recurrent somatic copy number variations (CNVs). Genomic DNA from biopsies was used for somatic mutation detection. (B and C) Heatmaps of somatic CNV burdens in biopsies. Results of all biopsies are shown in B, and separately displayed as benign patients and cancer patients in C. (D) Mutation burdens in biopsies with different metabolic features. (E) CNV in biopsies with different metabolic features. (F) Most frequent mutated genes in patients with different metabolic features at different disease stages. A patient would be identified as a carrier when a mutation was detected (regardless of its alternative allele fraction) in any of his biopsy samples, and the percentage of carriers was calculated in patients at different disease stages. (G) Most amplified genes in patients with different metabolic features at different disease stages. (H) Most deleted genes in patients with different metabolic features at different disease stages.

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ISSN: 0021-9738 (print), 1558-8238 (online)

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