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Background <p>Bladder cancer is a common urinary system malignancy with a complex immune microenvironment that affects treatment outcomes. Single-cell RNA sequencing technology offers new opportunities to understand cellular heterogeneity within tumors, but systematic analysis of immune-related genes in bladder cancer remains limited.</p> Methods <p>We performed multi-omics analysis on bladder cancer samples using TCGA database analysis, single-cell RNA sequencing, cell clustering, immune gene expression analysis, and network pharmacology to study cellular heterogeneity and potential therapeutic targets.</p> Results <p>We identified 8 upregulated immune genes significantly associated with poor survival: CCL20, IL17RB, IL37, PLAU, INSL4, KNG1, SLURP1, and PAEP. Single-cell analysis revealed major cell types including B cells, T cells, dendritic cells, epithelial cells, fibroblasts, mast cells, monocytes, and smooth muscle cells. We identified 5 distinct fibroblast subgroups and 10 T cell subgroups with different functional characteristics. Network pharmacology analysis of the PLAU gene showed that traditional Chinese medicine compounds had good binding capacity with the PLAU protein, validated by molecular dynamics simulation.</p> Conclusion <p>This study identified 8 prognosis-related bladder cancer immune genes and revealed tumor microenvironment heterogeneity. The findings, particularly the PLAU therapeutic target, provide important evidence for bladder cancer immunotherapy and personalized treatment strategies.</p>

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Single cell RNA sequencing decodes cellular heterogeneity and identifies prognostic immune signatures in bladder cancer microenvironment

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月20日

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  • Kai Cao,
  • Yunfeng Shi,
  • Bin Wu,
  • Honglei Shi,
  • Zhong Lv,
  • Hongqian Guo,
  • Rong Yang

摘要

Background

Bladder cancer is a common urinary system malignancy with a complex immune microenvironment that affects treatment outcomes. Single-cell RNA sequencing technology offers new opportunities to understand cellular heterogeneity within tumors, but systematic analysis of immune-related genes in bladder cancer remains limited.

Methods

We performed multi-omics analysis on bladder cancer samples using TCGA database analysis, single-cell RNA sequencing, cell clustering, immune gene expression analysis, and network pharmacology to study cellular heterogeneity and potential therapeutic targets.

Results

We identified 8 upregulated immune genes significantly associated with poor survival: CCL20, IL17RB, IL37, PLAU, INSL4, KNG1, SLURP1, and PAEP. Single-cell analysis revealed major cell types including B cells, T cells, dendritic cells, epithelial cells, fibroblasts, mast cells, monocytes, and smooth muscle cells. We identified 5 distinct fibroblast subgroups and 10 T cell subgroups with different functional characteristics. Network pharmacology analysis of the PLAU gene showed that traditional Chinese medicine compounds had good binding capacity with the PLAU protein, validated by molecular dynamics simulation.

Conclusion

This study identified 8 prognosis-related bladder cancer immune genes and revealed tumor microenvironment heterogeneity. The findings, particularly the PLAU therapeutic target, provide important evidence for bladder cancer immunotherapy and personalized treatment strategies.