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基于嘧啶代谢的前列腺癌分子亚型鉴定及预后特征预测免疫格局并指导临床治疗

Identification of pyrimidine metabolism-based molecular subtypes and prognostic signature to predict immune landscape and guide clinical treatment in prostate cancer.

作者信息

Yu Yu-Zhong, Xie Xiao, Cai Mao-Ping, Hong Ya-Ying, Ren Yang-Zi, Kang Xi, Yan Hai-Chen, Xiong Yang, Chen Hong, Wu Xing-Cheng, Luo Dao-Sheng, Zhao Shan-Chao

机构信息

Department of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.

Department of Urology, Nanfang Hospital, Southern Medical University, Guangzhou, China.

出版信息

Ann Med. 2025 Dec;57(1):2449584. doi: 10.1080/07853890.2025.2449584. Epub 2025 Jan 13.

Abstract

BACKGROUND

We previously described the enrichment of plasma exosome metabolites in CRPC, PCa, and TFC cohorts, and found significant differences in pyrimidine metabolites. The PMGs is associated with the clinical prognosis of several cancers, but its biological role in PCa is still unclear.

METHODS

This study extracted 98 reliable PMGs, and analyzed their somatic mutations, expression levels, and prognostic significance. Unsupervised clustering was applied to classify patients with PCa into clusters based on six PMGs that were related to the prognosis of PCa. The TME, gene mutations, and immune escape ability were compared among the clusters. A scoring algorithm based on prognostic PMGs, referred to as the PMGscore, was developed. TK1 was identified and the biological functions of TK1 were determined using loss-of-function experiments. RNA sequencing was subsequently performed to determine the molecules associated with the underlying mechanisms of TK1 function.

RESULTS

In total, six out of 98 PMGs simultaneously exhibited differential expression in PCa and were correlated with BCR. Patients were clustered into two clusters according to the expression levels of these six PMGs, which reflected distinct clinical outcomes and immune cell infiltration characteristics. Clinical features, tumor prognosis, and functional annotation were analyzed. Subsequently, we constructed a prognostic signature using these six PMGs. In combination with other clinical traits, we found that the six PMGs' prognostic signature was an independent prognostic factor for patients with PCa. Finally, we found that the expression of TK1 was higher in CRPC tissues than in PCa tissues in three GEO datasets. The results indicated that TK1 promotes the growth and metastasis of PCa cells.

CONCLUSIONS

We provide evidence for a PMG signature for PCa patients to accurately predict clinical prognosis. TK1 plays crucial roles in the progression of PCa cells and can be used as a potential therapeutic target for CRPC.

摘要

背景

我们之前描述了去势抵抗性前列腺癌(CRPC)、前列腺癌(PCa)和良性前列腺增生(TFC)队列中血浆外泌体代谢物的富集情况,并发现嘧啶代谢物存在显著差异。嘧啶代谢基因(PMGs)与几种癌症的临床预后相关,但其在前列腺癌中的生物学作用仍不清楚。

方法

本研究提取了98个可靠的PMGs,并分析了它们的体细胞突变、表达水平和预后意义。基于与前列腺癌预后相关的6个PMGs,应用无监督聚类将前列腺癌患者分为不同的簇。比较各簇之间的肿瘤微环境(TME)、基因突变和免疫逃逸能力。开发了一种基于预后PMGs的评分算法,称为PMGscore。鉴定了胸苷激酶1(TK1),并通过功能缺失实验确定了TK1的生物学功能。随后进行RNA测序,以确定与TK1功能潜在机制相关的分子。

结果

98个PMGs中共有6个在前列腺癌中同时表现出差异表达,并与生化复发(BCR)相关。根据这6个PMGs的表达水平,患者被分为两个簇,这两个簇反映了不同的临床结果和免疫细胞浸润特征。分析了临床特征、肿瘤预后和功能注释。随后,我们使用这6个PMGs构建了一个预后特征。结合其他临床特征,我们发现这6个PMGs的预后特征是前列腺癌患者的独立预后因素。最后,我们发现三个基因表达综合数据库(GEO)数据集中,CRPC组织中TK1的表达高于PCa组织。结果表明,TK1促进前列腺癌细胞的生长和转移。

结论

我们为前列腺癌患者提供了一个PMG特征,以准确预测临床预后。TK1在前列腺癌细胞的进展中起关键作用,可作为CRPC的潜在治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10bd/11731156/be85275cbf4e/IANN_A_2449584_F0001_C.jpg

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