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Construction and experimental validation of a macrophage cell senescence-related gene signature to evaluate the prognosis, immunotherapeutic sensitivity, and chemotherapy response in bladder cancer

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Abstract

Tumor-associated macrophages (TAMs) are pivotal components of tumor microenvironment (TME), and senescent TAMs contribute to the alternation of the profiles of TME. However, the potential biological mechanisms and the prognosis value of senescent macrophages are largely unknown, especially in bladder cancer (BLCA). Based on the single-cell RNA sequencing of a primary BLCA sample, 23 macrophage-related genes were identified. Genomic difference analysis, LASSO, and Cox regression were used to develop the risk model. TCGA-BLCA cohort (n = 406) was utilized as the training cohort, and then, three independent cohorts (n = 90, n = 221, n = 165) from Gene Expression Omnibus, clinical samples from the local hospital (n = 27), and in vitro cell experiments were used for external validation. Aldo-keto reductase family 1 member B (AKR1B1), inhibitor of DNA binding 1 (ID1), and transforming growth factor beta 1 (TGFB1I1) were determined and included in the predictive model. The model serves as a promising tool to evaluate the prognosis in BLCA (pooled hazard ratio = 2.51, 95% confidence interval = [1.43; 4.39]). The model was also effective for the prediction of immunotherapeutic sensitivity and chemotherapy treatment outcomes, which were further confirmed by IMvigor210 cohort (P < 0.01) and GDSC dataset, respectively. Twenty-seven BLCA samples from the local hospital proved that the risk model was associated with the malignant degree (P < 0.05). At last, the human macrophage THP-1 and U937 cells were treated with H2O2 to mimic the senescent process in macrophage, and the expressions of these molecules in the model were detected (all P < 0.05).

Overall, a macrophage cell senescence-related gene signature was constructed to predict the prognosis, immunotherapeutic response, and chemotherapy sensitivity in BLCA, which provides novel insights to uncover the underlying mechanisms of macrophage senescence.

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Data availability

The followed data used to support the conclusions of this study are available and the code would be supplied from the corresponding author upon request: The Cancer Genome Atlas (TCGA, https://portal.gdc.cancer.gov/), accessed 5 May 2022 (Colaprico et al. 2016); GEO (https://www.ncbi.nlm.nih.gov/geo/), accessed 5 May 2022 (Barrett et al. 2011); CellAge (http://genomics.senescence.info/cells), accessed 5 May 2022; and MSigDB (https://www.gsea-msigdb.org/gsea/msigdb/), accessed 5 May 2022 (Drake et al. 2016).

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Acknowledgements

Special thanks for the contribution of TCGA, GEO, CellAge and MSigDB databases.

Funding

This study is supported by National Natural Science Foundation of China (NO. 82101684 and NO. 81772257) and President Foundation of The Third Affiliated Hospital of Southern Medical University (KT202203020002).

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Author notes

  1. Qijun Jiang and Junhao Zhou contributed equally to this work.

Authors and Affiliations

  1. Department of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, 510000, China

    Qijun Jiang, Junhao Zhou, Qi Chen, Cheng Yang & Cundong Liu

  2. Department of Nephrology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, 510000, China

    Yuliang Huang

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  1. Qijun Jiang
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Contributions

Qijun Jiang was mainly responsible for conceptualization, methodology, software, and writing original draft. Junhao Zhou prepared formal analysis and wrote the manuscript text. Qi Chen and Cheng Yang were responsible for data curation and investigation. Yuliang Huang completed IHC validation and visualization. Cundong Liu was corresponding author for supervision, project administration, and funding acquisition.

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Correspondence to Cundong Liu.

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The study received approval from the Ethics Committee of the Third Affiliated Hospital of Southern Medical University (Guangzhou, China) (ID: 2023ER024). Method and results were conducted following the Declaration of Helsinki.

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Supplementary information

ESM 1

Supplementary Table 1: A total of 279genes extracted from CellAge. Supplementary Table 2: clinical information of the TCGA-BLCA, GSE31684, GSE13507, GSE32894 datasets. (PDF 762 kb)

ESM 2

Supplementary Figure 1: The quality control (QC) of single-cell datasets. Supplementary Figure 2: NMF clusters defined through MSR signatures with 63 patients from GSE19423. Supplementary Figure 3: The TME cell infiltration score assessment. Supplementary Figure 4: MSRs served as an independent prognostic factor. Supplementary Figure 5: Results from CellChat ligand-receptor pairs outcomes prediction among MSR macrophage and immune cells or malignant cells in bladder TME. Supplementary Figure 6: Measurement of secreted cytokines in U937 cells and THP-1 cells following exposure to H2O2 for 48 hours by ELISA Kit. (PDF 1733 kb)

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Jiang, Q., Zhou, J., Chen, Q. et al. Construction and experimental validation of a macrophage cell senescence-related gene signature to evaluate the prognosis, immunotherapeutic sensitivity, and chemotherapy response in bladder cancer. Funct Integr Genomics 23, 228 (2023). https://doi.org/10.1007/s10142-023-01163-4

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