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<p>The improvement of the prediction of prostate cancer (PCa) is a major challenge in disease management. This study analysed a total of 147,856 cells and identified 15 distinct cell types using single-cell RNA-sequencing (scRNA-seq) and bulk RNA-seq data from TCGA and GEO databases. Of these cells, 31,256 exhibited a high telomere-related gene score and were predominantly composed of myeloid dendritic cells (mDCs). Simultaneously, pseudo-temporal analysis indicated that mDCs are in the later stages of the differentiation trajectory, suggesting the significant role of mDCs as telomere-active cells in the development of PCa. Analysis of cell-cell communication revealed significant differences, particularly an increase in communication between mDCs and CTLs, alongside a decrease in communication between mDCs and B cells. These variations may represent critical nodes influencing the development of PCa. Additionally, two hub genes were utilized to create risk models, with ROC curves confirming their predictive efficacy for 3-, 5-, and 10-year survival rates in patients. Functional analysis of these genes was conducted, and NPY siRNA transfection notably inhibited proliferation in LNCaP and DU145 cells. Furthermore, the models demonstrated that high-risk patients had poorer overall survival, greater immune infiltration, and reduced sensitivity to chemotherapeutic drugs.</p>

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Telomere-related gene risk model predicts prognostic and immune microenvironment alterations in prostate cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年4月25日

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  • Danfeng Zhao,
  • Zhenjie Zang,
  • Haodong Li,
  • Ruiyu Li,
  • Guanbo Wang,
  • Keqin Zhang,
  • Tongxiang Diao,
  • Qiang Fu

摘要

The improvement of the prediction of prostate cancer (PCa) is a major challenge in disease management. This study analysed a total of 147,856 cells and identified 15 distinct cell types using single-cell RNA-sequencing (scRNA-seq) and bulk RNA-seq data from TCGA and GEO databases. Of these cells, 31,256 exhibited a high telomere-related gene score and were predominantly composed of myeloid dendritic cells (mDCs). Simultaneously, pseudo-temporal analysis indicated that mDCs are in the later stages of the differentiation trajectory, suggesting the significant role of mDCs as telomere-active cells in the development of PCa. Analysis of cell-cell communication revealed significant differences, particularly an increase in communication between mDCs and CTLs, alongside a decrease in communication between mDCs and B cells. These variations may represent critical nodes influencing the development of PCa. Additionally, two hub genes were utilized to create risk models, with ROC curves confirming their predictive efficacy for 3-, 5-, and 10-year survival rates in patients. Functional analysis of these genes was conducted, and NPY siRNA transfection notably inhibited proliferation in LNCaP and DU145 cells. Furthermore, the models demonstrated that high-risk patients had poorer overall survival, greater immune infiltration, and reduced sensitivity to chemotherapeutic drugs.