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Objective <p>To develop a robust prognostic model for bladder cancer (BLCA) by integrating genes associated with CD8<sup>+</sup>T cell infiltration disparities and immune-related pathways.</p> Methods <p>Transcriptomic and clinical data for BLCA were acquired from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). Immune-related gene sets were curated from the ImmPort and InnateDB databases. Genes exhibiting differential expression correlated with CD8<sup>+</sup>T cell infiltration were identified via single-cell analysis using the TISCH database. Key candidates were selected by intersecting these CD8<sup>+</sup>T cell-associated differentially expressed genes with the immune-related gene list. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were performed to elucidate underlying molecular pathways and biological functions. Core prognostic genes were identified through univariate and multivariate Cox regression analyses coupled with Least Absolute Shrinkage and Selection Operator (LASSO) regression, culminating in the construction of a CD8<sup>+</sup>T cell-centric prognostic signature. The model’s capacity to predict immunotherapy response was evaluated using Tumor Immune Dysfunction and Exclusion (TIDE) scores and validated in the IMvigor210 cohort. Finally, gene expression levels were confirmed via quantitative real-time PCR (qRT-PCR).</p> Results <p>Intersection of CD8<sup>+</sup>T cell infiltration-associated differentially expressed genes with immune-related genes, leveraging both single-cell and bulk transcriptomic data, yielded 109 candidate genes. Subsequent Cox and LASSO regression analyses refined these into a ten-gene risk score signature: <i>ANXA1</i>,<i> ANXA6</i>,<i> APOBEC3G</i>,<i> CD3D</i>,<i> CSF3R</i>,<i> HSP90AB1</i>,<i> IFI30</i>,<i> RGS2</i>,<i> S100A8</i>, and <i>SBDS</i>. This model demonstrated robust prognostic performance across both TCGA and GEO cohorts, effectively stratifying BLCA patients based on Overall Survival (OS), Disease-Specific Survival (DSS), and Progression-Free Survival (PFS). The low-risk group exhibited an inflamed immune microenvironment characterized by elevated CD8<sup>+</sup>T cell infiltration, enhanced antigen presentation, and potent T cell co-stimulation signals, correlating with superior responsiveness to immunotherapy. Conversely, the high-risk group was associated with an immunosuppressive landscape and enrichment of extracellular matrix-related pathways. Validation in the IMvigor210 cohort and via TIDE analysis corroborated that low-risk patients derive greater benefit from PD-L1 blockade and exhibit prolonged survival. Furthermore, a nomogram integrating clinical parameters displayed high predictive accuracy, underscoring the potential utility of this CD8<sup>+</sup>T cell-related signature for prognosis assessment and immunotherapy guidance in BLCA.</p> Conclusion <p>Our study introduces a novel prognostic model based on CD8⁺ T cell marker genes, which demonstrates significant predictive power for prognosis and immunotherapy response in bladder cancer patients. This model offers a potential tool for improving patient stratification and personalizing treatment strategies.</p>

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A novel prognostic model based on CD8+T cell infiltration-associated differentially expressed genes and immune-related genes predicts survival in bladder cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年8月1日

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  • Changyong Zhao,
  • Mingshun Zuo,
  • Bo Yu,
  • Junyu Tian,
  • Yuyan Song,
  • Yilin Wang,
  • Neng Zhang

摘要

Objective

To develop a robust prognostic model for bladder cancer (BLCA) by integrating genes associated with CD8+T cell infiltration disparities and immune-related pathways.

Methods

Transcriptomic and clinical data for BLCA were acquired from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). Immune-related gene sets were curated from the ImmPort and InnateDB databases. Genes exhibiting differential expression correlated with CD8+T cell infiltration were identified via single-cell analysis using the TISCH database. Key candidates were selected by intersecting these CD8+T cell-associated differentially expressed genes with the immune-related gene list. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were performed to elucidate underlying molecular pathways and biological functions. Core prognostic genes were identified through univariate and multivariate Cox regression analyses coupled with Least Absolute Shrinkage and Selection Operator (LASSO) regression, culminating in the construction of a CD8+T cell-centric prognostic signature. The model’s capacity to predict immunotherapy response was evaluated using Tumor Immune Dysfunction and Exclusion (TIDE) scores and validated in the IMvigor210 cohort. Finally, gene expression levels were confirmed via quantitative real-time PCR (qRT-PCR).

Results

Intersection of CD8+T cell infiltration-associated differentially expressed genes with immune-related genes, leveraging both single-cell and bulk transcriptomic data, yielded 109 candidate genes. Subsequent Cox and LASSO regression analyses refined these into a ten-gene risk score signature: ANXA1, ANXA6, APOBEC3G, CD3D, CSF3R, HSP90AB1, IFI30, RGS2, S100A8, and SBDS. This model demonstrated robust prognostic performance across both TCGA and GEO cohorts, effectively stratifying BLCA patients based on Overall Survival (OS), Disease-Specific Survival (DSS), and Progression-Free Survival (PFS). The low-risk group exhibited an inflamed immune microenvironment characterized by elevated CD8+T cell infiltration, enhanced antigen presentation, and potent T cell co-stimulation signals, correlating with superior responsiveness to immunotherapy. Conversely, the high-risk group was associated with an immunosuppressive landscape and enrichment of extracellular matrix-related pathways. Validation in the IMvigor210 cohort and via TIDE analysis corroborated that low-risk patients derive greater benefit from PD-L1 blockade and exhibit prolonged survival. Furthermore, a nomogram integrating clinical parameters displayed high predictive accuracy, underscoring the potential utility of this CD8+T cell-related signature for prognosis assessment and immunotherapy guidance in BLCA.

Conclusion

Our study introduces a novel prognostic model based on CD8⁺ T cell marker genes, which demonstrates significant predictive power for prognosis and immunotherapy response in bladder cancer patients. This model offers a potential tool for improving patient stratification and personalizing treatment strategies.