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Integrated analysis of single-cell and bulk RNA-sequencing identifies a signature based on T-cell marker genes to predict prognosis and immunotherapy response in bladder cancer

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Abstract

Background

T cells have been proven to play important roles in anti-tumor and tumor microenvironment shaping, while these roles have not been explained in bladder cancer (BLCA).

Methods

Single-cell RNA-sequencing (scRNA-seq) data were downloaded from the gene expression omnibus (GEO) database to screen T-cell marker genes. Bulk RNA-sequencing data and clinical information from BLCA patients were downloaded from the cancer genome atlas (TCGA) database to develop a prognosis signature. We analyzed the association of different risk groups with survival analysis, gene set enrichment analysis (GSEA), tumor mutational burden (TMB), and immunotherapy response.

Results

Based on 192 T-cell marker genes identified by scRNA-seq analysis, we constructed a prognostic signature containing 7 genes in the training cohort, which was further validated in the testing cohort and GEO cohort. The areas under the receiver operating characteristic curve at 1-, 3-, and 5 years were 0.734, 0.742 and 0.726 in the training cohort, 0.697, 0.671 and 0.670 in the testing cohort, 0.702, 0.665 and 0.629 in the GEO cohort, respectively. In addition, we constructed a nomogram based on clinical factors and the risk score of the signature. The low-risk group exhibited higher immune-related pathways, immune cell infiltration and TMB levels. Importantly, immunophenotype score and immunotherapy cohort (IMvigor210) analyses showed that the low-risk group had better immunotherapy response and prognosis.

Conclusions

Our study reveals a novel prognostic signature based on T-cell marker genes, which provides a new target and theoretical support for BLCA patients.

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Availability of data and materials

The datasets generated during and analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

We sincerely thank the cancer genome atlas databases and the gene expression omnibus database for providing open access.

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Authors and Affiliations

  1. Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, Henan, China

    Xuezhong Shi, Ani Dong, Yongli Yang, Guowei Zheng, Nana Wang, Chaojun Yang, Yuping Wang, Jie Lu & Xiaocan Jia

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  1. Xuezhong Shi
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Contributions

XZS and AND designed the study. XZS, AND, YLY, GWZ, JL and XCJ performed data collection and analysis. XZS and AND wrote this manuscript. YLY, GWZ, NNW, CJY, YPW and XCJ polished and revised this manuscript. All authors have approved the final manuscript.

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Correspondence to Xiaocan Jia.

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Shi, X., Dong, A., Yang, Y. et al. Integrated analysis of single-cell and bulk RNA-sequencing identifies a signature based on T-cell marker genes to predict prognosis and immunotherapy response in bladder cancer. J Cancer Res Clin Oncol 149, 9733–9746 (2023). https://doi.org/10.1007/s00432-023-04881-1

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