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Updated: Jul 1, 2025
An Orthotopic Murine Model of Human Prostate Cancer Metastasis
Published on: September 18, 2013
Comparative analysis of prognosis and gene expression in prostate cancer patients with site-specific visceral
Peng Zhang1, Tieding Chen1, Ming Yang1
1Department of Urology, Ningbo Medical Center Lihuili Hospital, Ningbo, Zhejiang, China.
Introduction:
Prostate cancer patients with visceral metastases often exhibited poor prognoses. Few researches had compared the prognostic impact and gene expression profiles among distinct visceral metastatic sites. Therefore, we conducted a comprehensive study utilizing data from the Surveillance, Epidemiology, and End Results (SEER) database and the Gene Expression Omnibus database.
Patients And Methods:
We analyzed the prostate cancer-specific mortality (PCSM) risk for 8,170 patients diagnosed with metastatic prostate cancer (mPCa) between 2000 and 2019, utilizing data from the SEER 17 registry database. Patients with metastatic disease in nonregional lymph nodes, bones, brains, livers, and lungs were identified. Competing risks regression was employed to evaluate the effect of visceral metastatic disease sites on PCSM. Differentially expressed genes (DEGs) between visceral metastases were assessed using data from the GSE6752 dataset. A relative protein-protein interaction (PPI) network was constructed based on STRING analysis. Furthermore, we explored the distribution of DEGs in various normal tissues and tumor tissues using the Human Protein Atlas and GEPIA.
Results:
Competing risks regression analysis revealed that liver and lung metastases had a substantial impact on PCSM (hazard ratio 2.24, 95% confidence interval 1.70-2.95, P < 0.001; hazard ratio 1.30, 95% confidence interval 1.06-1.59, P = 0.012, respectively). Seven significant DEGs were identified from samples of liver and lung metastases (HERV-FRD, NUDT12, FAM63A, SCGB3A1, CEACAM6, LOC440416, SFTPB) and were associated with respiratory gaseous exchange, pulmonary surfactant metabolism, and fibronectin matrix formation in PPI network analysis. Notably, the expression levels of the three DEGs significantly upregulated in lung metastases were also found to be higher in normal lung tissues compared to normal liver tissues.
Conclusion:
Patients diagnosed with mPCa and presenting with liver and/or lung metastases exhibit poorer prognoses. SCGB3A1, identified as a tumor suppressor gene, may contribute to the better survival prognosis observed in patients with prostate cancer lung metastases compared to those with liver metastases. The gene expression profiles in these two specific metastatic sites reveal a combination of both heterogeneity and homogeneity.
