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A novel CD8+ T cell-related gene signature for predicting the prognosis and immunotherapy efficacy in bladder cancer

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Abstract

Objective

To identify CD8+ T cell-related molecular clusters and establish a novel gene signature for predicting the prognosis and efficacy of immunotherapy in bladder cancer (BCa).

Methods

Transcriptome and clinical data of BCa samples were obtained from the Cancer Genome Atlas (TCGA) and GEO databases. The CD8+ T cell-related genes were screened through the CIBERSORT algorithm and correlation analysis. Consensus clustering analysis was utilized to identified CD8+ T cell-related molecular clusters. A novel CD8+ T cell-related prognostic model was developed using univariate Cox regression analysis and Lasso regression analysis. Internal and external validations were performed and the validity of the model was validated in a real-world cohort. Finally, preliminary experimental verifications were carried out to verify the biological functions of SH2D2A in bladder cancer.

Results

A total of 52 CD8+ T cell-related prognostic genes were screened and two molecular clusters with notably diverse immune cell infiltration, prognosis and clinical features were developed. Then, a novel CD8+ T cell-related prognostic model was constructed. The patients with high-risk scores exhibited a significantly worse overall survival in training, test, whole TCGA and validating cohort. The AUC was 0.766, 0.725, 0.739 and 0.658 in the four cohorts sequentially. Subgroup analysis suggested that the novel prognostic model has a robust clinical application for selecting high-risk patients. Finally, we confirmed that patients in the low-risk group might benefit more from immunotherapy or chemotherapy, and validated the prognostic model in a real-world immunotherapy cohort. Preliminary experiment showed that SH2D2A was capable of attenuating proliferation, migration and invasion of BCa cells.

Conclusions

CD8+ T cell-related molecular clusters were successfully identified. Besides, a novel CD8+ T cell-related prognostic model with an excellent predictive performance in predicting survival rates and immunotherapy efficacy of BCa was developed.

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Availability of data and materials

The data presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding authors.

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Funding

The study was supported by the “Eyas Plan” Youth Top-notch Talent Project of Fujian Province (Grant number: SCYJHBJRC-XN2021) and Class B Talent Research Project of the First Affiliated Hospital of Fujian Medical University (Grant number: YJCRC-B-XN2022).

Author information

Author notes

  1. Fei Lin, Zhi-Bin Ke, Yu-Ting Xue and Jia-Yin Chen contributed equally to this work.

Authors and Affiliations

  1. Department of Urology, Urology Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China

    Fei Lin, Zhi-Bin Ke, Yu-Ting Xue, Jia-Yin Chen, Hai Cai, Yun-Zhi Lin, Xiao-Dong Li, Yong Wei, Xue-Yi Xue & Ning Xu

  2. Department of Urology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China

    Fei Lin, Zhi-Bin Ke, Yu-Ting Xue, Jia-Yin Chen, Hai Cai, Yun-Zhi Lin, Xiao-Dong Li, Yong Wei, Xue-Yi Xue & Ning Xu

  3. Fujian Key Laboratory of Precision Medicine for Cancer, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China

    Xue-Yi Xue & Ning Xu

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  1. Fei Lin
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Contributions

FL, Z-BK, Y-TX wrote the original draft. NX and X-YX reviewed and edited the original draft. J-YC and HC contributed to the methodology. FL and Y-ZL did the investigation. Z-BK and X-DL contributed to formal analysis. Y-TX and YW curated the data. FL contributed to the conceptualization and the visualization. NX supervised the project. X-YX administrated the project. All authors reviewed the manuscript.

Corresponding authors

Correspondence to Xue-Yi Xue or Ning Xu.

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All authors declared that there were no conflicts of interest.

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This study was approved by the Ethics Committee of the First Affiliated Hospital of Fujian Medical University and all patients provided written informed consent.

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Informed consent for publication of the manuscript was obtained from all authors.

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Supplementary Information

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11_2023_1772_MOESM1_ESM.tif

Supplementary file1 Supplemental Figure 1. Lasso regression analysis of key genes significantly related to CD8+ T cell infiltration (A-B). The 8‐year ROC curves of the risk model and other clinical characteristics in training cohort (C). Correlations between the two risk groups and TME score (D). The subgroup survival analysis between low-risk and high-risk groups in patients with age ≤65 and age >65 (E-G). The subgroup survival analysis between low-risk and high-risk groups in the female and male subgroups (H-J). *, P < 0.05; ***, P < 0.001. (TIF 21493 KB)

Supplementary file2 (DOCX 12 KB)

Supplementary file3 (DOCX 14 KB)

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Lin, F., Ke, ZB., Xue, YT. et al. A novel CD8+ T cell-related gene signature for predicting the prognosis and immunotherapy efficacy in bladder cancer. Inflamm. Res. 72, 1665–1687 (2023). https://doi.org/10.1007/s00011-023-01772-6

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