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Updated: Nov 25, 2025

Murine Prostate Micro-dissection and Surgical Castration
Published on: May 11, 2016
Regucalcin promotes dormancy of prostate cancer
Sambad Sharma1, Xinhong Pei2, Fei Xing1
1Department of Cancer Biology, Wake Forest Baptist Medical Center, Winston-Salem, NC, USA.
Abstract:
Prostate cancer is one of the leading causes of mortality in men. The major cause of death in prostate cancer patients can be attributed to metastatic spread of disease or tumor recurrence after initial treatment. Prostate tumors are known to remain undetected or dormant for a long period of time before they progress locoregionally or at distant sites as overt tumors. However, the molecular mechanism of dormancy is yet poorly understood. In this study, we performed a differential gene expression analysis and identified a gene, Regucalcin (RGN), which promotes dormancy of prostate cancer. We found that cancer patients expressing higher level of RGN showed significantly longer recurrence-free and overall- survival. Using a doxycycline-inducible RGN expression system, we showed that ectopic expression of RGN in prostate tumor cells induced dormancy in vivo, while following suppression of RGN triggered recurrence of tumor growth. On the other hand, silencing RGN in LNCap cells promoted its outgrowth in the tibia of mice. Importantly, RGN promoted multiple known hallmarks of tumor dormancy including activation of p38 MAPK, decrease in Erk signaling and inhibition of FOXM1 expression. Furthermore, we found that RGN significantly suppressed angiogenesis by increasing secretory miR-23c level in the exosomes. Intriguingly, FOXM1 was found to negatively regulate miR-23c expression in prostate cancer. In addition, we identified 11 RGN downstream target genes that independently predicted longer recurrence-free survival in patients. We found that expression of these genes was regulated by FOXM1 and/or p38 MAPK. These findings suggest a critical role of RGN in prostate cancer dormancy, and the utility of RGN signaling and exosomal miR-23c as biomarkers for predicting recurrence.
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