基于嘧啶代谢相关基因的膀胱癌分子分型及 其免疫微环境和预后价值分析

Molecular Subtyping of Bladder Cancer Based on Pyrimidine Metabolism-Related Genes and Its Immune Microenvironment and Prognostic Value

摘要: 基于TCGA-BLCA数据库获取膀胱癌转录组数据及临床信息，并结合MSigDB数据库筛选嘧啶代谢相关基因，采用一致性聚类方法对膀胱癌患者进行分子分型，系统分析不同亚型在免疫细胞浸润特征、免疫检查点基因表达、体细胞突变谱及药物敏感性方面的差异；同时通过差异表达分析和加权基因共表达网络分析(WGCNA)筛选关键基因，并利用Lasso回归构建预后风险模型以评估其预测性能。研究结果表明，基于嘧啶代谢相关基因可将膀胱癌患者分为两种具有显著生物学差异的分子亚型，两种亚型在免疫微环境特征、肿瘤突变负荷及预后方面存在明显差异，其中一类亚型呈现免疫活化特征，另一类亚型表现为免疫抑制微环境。进一步构建的预后风险模型能够有效区分高、低风险患者，且风险评分与患者总体生存显著相关。上述结果提示，嘧啶代谢相关分子分型有助于揭示膀胱癌的免疫异质性，并为预后评估及个体化治疗研究提供参考依据。

Abstract: Transcriptomic data and corresponding clinical information of bladder cancer were obtained from the TCGA-BLCA database, and pyrimidine metabolism-related genes were collected from the MSigDB database. Consensus clustering analysis was performed to identify molecular subtypes of bladder cancer, and differences in immune cell infiltration characteristics, immune checkpoint gene expression, somatic mutation profiles, and drug sensitivity between subtypes were systematically analyzed. In addition, differentially expressed genes and key modules were identified using differential expression analysis and weighted gene co-expression network analysis (WGCNA), and a prognostic risk model was constructed using Lasso regression to evaluate its predictive performance. The results demonstrated that bladder cancer patients could be classified into two distinct molecular subtypes based on pyrimidine metabolism-related gene expression, which exhibited significant differences in immune microenvironment characteristics, tumor mutation burden, and clinical prognosis. One subtype showed an immune-activated phenotype, whereas the other was characterized by an immunosuppressive microenvironment. Furthermore, the constructed prognostic risk model effectively stratified patients into high- and low-risk groups, and the risk score was significantly associated with overall survival. These findings suggest that pyrimidine metabolism-related molecular subtypes reflect the immune heterogeneity of bladder cancer and may provide valuable information for prognostic evaluation and individualized treatment research.