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<p>Bladder cancer (BLCA) exhibits considerable heterogeneity, and research into its tumor microenvironment and prognostic biomarkers remains insufficient. This study aims to identify key prognostic genes and immune microenvironment factors to enhance clinical assessment. Primary tumor (PT) and lymph node metastasis (LNM) samples were obtained from patients with BLCA, and single-cell RNA sequencing (scRNA-seq) was conducted to analyze cellular composition and functional variations. Prognostic genes were identified based on integrated bulk transcriptomic data, leading to the development of a risk model. Functional enrichment analyses further elucidated the molecular characteristics of high- and low-risk cohorts. The scRNA-seq analysis revealed significantly elevated metabolic activity in epithelial cells of LNM. A subpopulation of epithelial cells, defined by 133 characteristic genes, was identified as pivotal in the lymphatic metastasis of BLCA. The prognostic model, derived from nine key genes (APOL1, CAST, DSTN, SPINK1, JUN, S100A10, SPTBN1, HES1, and CD2AP), demonstrated robust predictive performance. Functional enrichment analysis indicated that the high-risk group predominantly activated extracellular matrix (ECM) receptor interactions and the complement pathway, while the low-risk group was primarily associated with carbohydrate metabolism pathways. This study provides insights into the tumor heterogeneity and immune microenvironment of BLCA, introduces a high-precision prognostic model, and establishes a novel theoretical basis for personalized BLCA treatment.</p>

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Integration of Single-cell and bulk RNA sequencing data uncovers lymphatic metastasis-related prognostic genes and a predictive model in bladder cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月6日

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  • Bin Yang,
  • Yangbing Wei,
  • Shuqin Liu,
  • Jinyao Wang,
  • Xuwei Zhao,
  • Jingyu Wang,
  • Yongqiang Fu,
  • Changxi Wang,
  • Xiaofeng Yang

摘要

Bladder cancer (BLCA) exhibits considerable heterogeneity, and research into its tumor microenvironment and prognostic biomarkers remains insufficient. This study aims to identify key prognostic genes and immune microenvironment factors to enhance clinical assessment. Primary tumor (PT) and lymph node metastasis (LNM) samples were obtained from patients with BLCA, and single-cell RNA sequencing (scRNA-seq) was conducted to analyze cellular composition and functional variations. Prognostic genes were identified based on integrated bulk transcriptomic data, leading to the development of a risk model. Functional enrichment analyses further elucidated the molecular characteristics of high- and low-risk cohorts. The scRNA-seq analysis revealed significantly elevated metabolic activity in epithelial cells of LNM. A subpopulation of epithelial cells, defined by 133 characteristic genes, was identified as pivotal in the lymphatic metastasis of BLCA. The prognostic model, derived from nine key genes (APOL1, CAST, DSTN, SPINK1, JUN, S100A10, SPTBN1, HES1, and CD2AP), demonstrated robust predictive performance. Functional enrichment analysis indicated that the high-risk group predominantly activated extracellular matrix (ECM) receptor interactions and the complement pathway, while the low-risk group was primarily associated with carbohydrate metabolism pathways. This study provides insights into the tumor heterogeneity and immune microenvironment of BLCA, introduces a high-precision prognostic model, and establishes a novel theoretical basis for personalized BLCA treatment.