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Magnetic Resonance Imaging Assessment of Carcinogen-induced Murine Bladder Tumors
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Macrophage Cell and Diagnostic Biomarkers in BLCA: Integrating Machine Learning With Single-Cell Analysis.

Guangliang Che1, Xuejun Zhao1, Rongtuan Luo1

  • 1Department of Urology, The Second People's Hospital of Pingdingshan, Pingdingshan, Henan, 467001, China.

Clinical Genitourinary Cancer
|October 26, 2025
PubMed
Summary

This study identifies seven key macrophage-associated genes to create a prognostic model for bladder cancer (BLCA). The model accurately predicts patient survival and highlights immune evasion in high-risk BLCA patients.

Keywords:
Bladder cancerImmune checkpoint inhibitorImmune evasionPrognosisSingle-cell sequencing

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Area of Science:

  • Oncology
  • Immunology
  • Genomics

Background:

  • Bladder cancer (BLCA) presents a significant clinical challenge with a poor prognosis.
  • Macrophages are closely linked to BLCA, but their specific roles and subtypes remain unclear.
  • Single-cell sequencing offers a powerful tool to explore macrophage heterogeneity and identify novel biomarkers in BLCA.

Purpose of the Study:

  • To investigate macrophage heterogeneity in bladder cancer using single-cell sequencing.
  • To identify key macrophage-associated genes for developing a prognostic model for BLCA.
  • To analyze immune infiltration and evasion in different risk groups within BLCA.

Main Methods:

  • Single-cell RNA sequencing data from BLCA and control samples were analyzed.
  • Scale-free network analysis (hdWGCNA) identified macrophage-associated genes.
  • LASSO and random forest analyses selected key genes for a prognostic model, validated on independent datasets.
  • Immune infiltration was assessed using CIBERSORT, ESTIMATE, and TIDE.

Main Results:

  • Nine distinct macrophage subtypes were identified in BLCA.
  • Seven key genes (MYO5A, KCNK6, DNAJB4, DEDD2, NFKBID, PSMB10, ITPRID2) were selected to build a prognostic model.
  • The model accurately predicted overall survival, with a high-risk group showing poorer outcomes.
  • High-risk BLCA patients exhibited increased immune evasion, suggesting impaired response to immune checkpoint inhibitors (ICIs).

Conclusions:

  • A 7-gene prognostic model demonstrates robust predictive performance for BLCA.
  • Enrichment of M2 macrophage phenotype in high-risk patients correlates with increased tumor invasiveness.
  • The findings suggest that high-risk BLCA patients may respond less effectively to ICI therapy.
  • DEDD2 emerges as a potential prognostic biomarker for bladder cancer.