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<p>Ovarian cancer is characterized by a high recurrence rate, and platinum resistance often contributes to poor patient outcomes. Cellular senescence can influence the tumor microenvironment, metabolic status, and immune regulation. However, the role of senescence-associated genes (SAGs) in the heterogeneity, prognosis, and treatment-related features of ovarian cancer remains to be further clarified. This study integrated data from TCGA, GEO, and single-cell RNA sequencing to systematically analyze the expression patterns, single-cell distribution, molecular subtypes, and associations of SAGs with prognosis and the immune microenvironment in ovarian cancer. Consensus clustering was used to identify senescence-related molecular subtypes, and an SAG-related prognostic risk model was constructed and validated. Associations between the risk score and platinum response, tumor mutational burden (TMB), immune cell infiltration, and immune checkpoint expression were further evaluated. SAGs were differentially expressed between ovarian cancer and normal ovarian tissues and were mainly enriched in cell cycle, DNA damage response, and immune-related pathways. Single-cell analysis showed that senescence signals were mainly distributed in cancer-associated fibroblasts, malignant cells, and selected immune cell populations. According to SAG-based consensus clustering, patients were classified into three molecular subtypes with differences in metabolic activity, DNA repair, immune microenvironment, and genomic stability, although no significant differences in OS were observed among subtypes. An eight-gene senescence-related risk model showed prognostic relevance in the TCGA cohort, and additional analyses in two GEO cohorts supported the prognostic value of the selected SAGs. The high-risk group was associated with greater TMB, platinum resistance-related features, increased immune and stromal scores, reduced tumor purity, a lower proportion of CD8⁺ T cells, and higher expression of regulatory T cells, macrophages, and immune checkpoints, suggesting a link with an immunosuppressive tumor microenvironment. The current findings suggest that senescence-associated molecular features are associated with the biological heterogeneity, prognostic stratification, platinum response, and status of the immune microenvironment in ovarian cancer. The SAG-related risk model may provide clues for prognostic assessment and future studies on treatment-response stratification in ovarian cancer, but further experimental and clinical validation is required.</p>

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The role of cellular senescence in immune-metabolic features and prognosis of ovarian cancer: an integrated analysis based on single-cell sequencing and multi-omics data

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月2日

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  • Yuan Li,
  • Mengying Bai,
  • Ziqiong Zhou,
  • Wenbo Wu,
  • Haifeng Wu,
  • Shuyi Ling,
  • Liping Wang,
  • Yuehui Zheng

摘要

Ovarian cancer is characterized by a high recurrence rate, and platinum resistance often contributes to poor patient outcomes. Cellular senescence can influence the tumor microenvironment, metabolic status, and immune regulation. However, the role of senescence-associated genes (SAGs) in the heterogeneity, prognosis, and treatment-related features of ovarian cancer remains to be further clarified. This study integrated data from TCGA, GEO, and single-cell RNA sequencing to systematically analyze the expression patterns, single-cell distribution, molecular subtypes, and associations of SAGs with prognosis and the immune microenvironment in ovarian cancer. Consensus clustering was used to identify senescence-related molecular subtypes, and an SAG-related prognostic risk model was constructed and validated. Associations between the risk score and platinum response, tumor mutational burden (TMB), immune cell infiltration, and immune checkpoint expression were further evaluated. SAGs were differentially expressed between ovarian cancer and normal ovarian tissues and were mainly enriched in cell cycle, DNA damage response, and immune-related pathways. Single-cell analysis showed that senescence signals were mainly distributed in cancer-associated fibroblasts, malignant cells, and selected immune cell populations. According to SAG-based consensus clustering, patients were classified into three molecular subtypes with differences in metabolic activity, DNA repair, immune microenvironment, and genomic stability, although no significant differences in OS were observed among subtypes. An eight-gene senescence-related risk model showed prognostic relevance in the TCGA cohort, and additional analyses in two GEO cohorts supported the prognostic value of the selected SAGs. The high-risk group was associated with greater TMB, platinum resistance-related features, increased immune and stromal scores, reduced tumor purity, a lower proportion of CD8⁺ T cells, and higher expression of regulatory T cells, macrophages, and immune checkpoints, suggesting a link with an immunosuppressive tumor microenvironment. The current findings suggest that senescence-associated molecular features are associated with the biological heterogeneity, prognostic stratification, platinum response, and status of the immune microenvironment in ovarian cancer. The SAG-related risk model may provide clues for prognostic assessment and future studies on treatment-response stratification in ovarian cancer, but further experimental and clinical validation is required.