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Updated: Jan 11, 2026

A Bioluminescent and Fluorescent Orthotopic Syngeneic Murine Model of Androgen-dependent and Castration-resistant Prostate Cancer
Published on: March 6, 2018
Unveiling oncogene-induced senescence: a new frontier in prostate cancer prognosis and therapy
YunZhen Peng1,2, Xin Qiu1,3, JunJie Cai4
1The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, China.
Background:
Prostate cancer (PCa) is the most common tumor in the male urogenital system. Radical prostatectomy, radiation, chemotherapy and endocrine therapy are common clinical treatment methods. Oncogene-induced senescence (OIS) is a special type of cellular senescence believed to have anti-tumor effects, may serve as an initial barrier for preventing tumor growth and development. As of yet, the effects of OIS on the occurrence, development, prognosis of prostate cancer and its related mechanisms are poorly understood, so further study is urgently needed.
Materials And Methods:
Gene transcriptomic data and clinical information data for PCa were downloaded from TCGA and GEO databases, OISGs were obtained from the Reactome database. We identified OIS-related subtypes based on consistent cluster analysis. Univariate Cox regression analysis was performed to identify PR-OISGs. LASSO regression analysis finally screened prognosis-related key genes and constructed a risk score model. Patients were classified into high-/ low-risk groups based on the median risk score. We assessed the TMB, immune cell infiltration level, immune checkpoint expression and drug sensitivity between high-/ low-risk groups. A nomogram was constructed and validated using calibration curves and clinical decision curves. RT-qPCR and IHC staining analysis were performed to verify the mRNA and protein expression levels of target genes.
Results:
The study identified two OIS-associated subtypes of PCa. We screened seven PRGs and established a risk model for PCa patients. It was found that BFS (biochemical recurrence-free survival) was significantly lower in high-risk group. Patients in the high-risk group showed greater immune infiltration and high expression of immune checkpoint, as well as higher TMB. Furthermore, stratifying the risk score appropriately allowed the predictive nomogram model to accurately predict the outcome of prostate cancer patients. Also, docetaxel and Olaparib sensitivity was higher in the high-risk group, whereas bicalutamide was more sensitive in the low-risk group. IHC and PCR confirmed CDK6 was highly upregulated in PCa.
Conclusion:
Our study screened seven genes with potential value for predicting long-term survival of patients with PCa and developed a prognostic model. These findings are expected to guide future development of effective therapies.
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