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基于转录组学和孟德尔随机化研究的中心体复制相关基因在前列腺癌中的预后价值

Prognostic Value of Centrosome Replication-Related Genes in Prostate Cancer Based on Transcriptomic and Mendelian Randomization.

作者信息

Lu Qizhong, Wu Yufan, Yu Qiwei, Ouyang Jun

机构信息

Department of Urology, The First Affiliated Hospital of Soochow University, Suzhou, China.

Department of Urology, Kunshan Hospital of Traditional Chinese Medicine, Kunshan, China.

出版信息

Am J Mens Health. 2025 Mar-Apr;19(2):15579883251319125. doi: 10.1177/15579883251319125. Epub 2025 Mar 18.

Abstract

Prostate cancer (PCa) is a significant global health concern, with its incidence and mortality rates projected to rise due to population aging. In this study, we utilized PCa transcriptome data from public databases and applied bioinformatics methods to identify three prognostic genes (, , and ) related to centrosome duplication in PCa. is involved in cell cycle regulation, in deoxyribonucleic acid double-strand break repair, and in spindle assembly checkpoint function and cell proliferation. We constructed a risk model and a nomogram model, both demonstrating moderate to good predictive performance with area under the curve values ranging from 0.611 to 0.765 at different time points. Gene set enrichment analysis revealed that these genes were enriched in 64 pathways, including the cell cycle pathway, which is dysregulated in cancer. Furthermore, we analyzed the immune microenvironment and identified 13 differential immune cells and 13 differential immune checkpoints between high- and low-risk groups, providing insights into potential immunotherapy targets for PCa. In conclusion, this study contributes to a deeper understanding of PCa pathogenesis and lays important theoretical and experimental foundations for developing new diagnostic markers and treatment strategies. Future research requires more clinical samples and continued monitoring of the mechanism of these genes in PCa.

摘要

前列腺癌(PCa)是一个重大的全球健康问题,由于人口老龄化,其发病率和死亡率预计将上升。在本研究中,我们利用来自公共数据库的PCa转录组数据,并应用生物信息学方法来鉴定与PCa中心体复制相关的三个预后基因(、和)。参与细胞周期调控,参与脱氧核糖核酸双链断裂修复,参与纺锤体组装检查点功能和细胞增殖。我们构建了一个风险模型和一个列线图模型,两者在不同时间点的曲线下面积值范围为0.611至0.765,均显示出中等至良好的预测性能。基因集富集分析表明,这些基因在64条通路中富集,包括在癌症中失调的细胞周期通路。此外,我们分析了免疫微环境,并确定了高危和低危组之间的13种差异免疫细胞和13种差异免疫检查点,为PCa的潜在免疫治疗靶点提供了见解。总之,本研究有助于更深入地了解PCa的发病机制,并为开发新的诊断标志物和治疗策略奠定重要的理论和实验基础。未来的研究需要更多的临床样本,并持续监测这些基因在PCa中的作用机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c030/11920994/311ff08bd2ba/10.1177_15579883251319125-fig1.jpg

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