磷代谢可能与肿瘤的发生和进展有关。我们的目的是筛选与膀胱癌相关的磷代谢基因并构建临床预后模型。用于分析的数据集来自TCGA数据库。随后将 GO 和 KEGG 富集分析应用于差异表达基因。利用共识聚类，比较不同聚类的肿瘤免疫微环境和其他特征。通过单变量Cox回归、LASSO回归和多变量Cox回归分析筛选出与预后相关的磷代谢相关基因，并构建列线图。分别使用TCGA数据集和GEO数据集验证列线图的性能。总体而言，TCGA数据库中鉴定出405个与磷代谢相关的差异表达基因，这些基因与磷酸化、细胞增殖、白细胞激活和信号通路相关。通过一致性聚类得到两个聚类。经过肿瘤免疫微环境分析，发现簇1和簇2之间的免疫细胞浸润存在显着差异。四种磷代谢相关基因（LIME1、LRP8、SPDYA 和 MST1R）与膀胱癌（BLCA）患者的预后相关。我们建立了一个预后模型，并将该模型可视化为列线图。校准曲线证明了该列线图的性能，与 ROC 曲线所示的一致。我们成功鉴定了四个与预后相关的磷代谢相关基因，为生物标志物和治疗提供了潜在靶标。开发了基于这些基因的列线图。尽管如此，这项研究是基于生物信息学，实验验证仍然至关重要。版权所有© 2024 He et al.由德黑兰医科大学出版。

Phosphorus metabolism might be associated with tumor initiation and progression. We aimed to screen out the phosphorus metabolism genes related to bladder cancer and construct a clinical prognosis model.The dataset used for the analysis was obtained from TCGA database. GO and KEGG enrichment analyses were subsequently applied to differentially expressed genes. Consensus clustering was utilized, and different clusters of the tumor immune microenvironment and other features were compared. The phosphorus metabolism-related genes involved in prognosis were screened out by univariate Cox regression, LASSO regression and multivariate Cox regression analysis, and a nomogram was constructed. The performance of the nomogram was validated using TCGA dataset and the GEO dataset, respectively.Overall, 405 phosphorus metabolism-related differentially expressed genes from TCGA database were identified, which were associated with phosphorylation, cell proliferation, leukocyte activation, and signaling pathways. Two clusters were obtained by consistent clustering. After tumor immune microenvironment analysis, significant differences in immune cell infiltration between cluster 1 and cluster 2 were found. Four phosphorus metabolism-related genes (LIME1, LRP8, SPDYA, and MST1R) were associated with the prognosis of bladder cancer (BLCA) patients. We built a prognostic model and visualized the model as a nomogram. Calibration curves demonstrated the performance of this nomogram, in agreement with that shown by the ROC curves.We successfully identified four phosphorus metabolism-related genes associated with prognosis, providing potential targets for biomarkers and therapeutics. A nomogram based on these genes was developed. Nevertheless, this study is based on bioinformatics, and experimental validation remains essential.Copyright© 2024 He et al. Published by Tehran University of Medical Sciences.