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Integration of multiomics analyses reveals unique insights into CD24-mediated immunosuppressive tumor microenvironment of breast cancer

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Abstract

Background

Tumor immunotherapy brings new light and vitality to breast cancer patients, but low response rate and limitations of therapeutic targets become major obstacles to its clinical application. Recent studies have shown that CD24 is involved in an important process of tumor immune regulation in breast cancer and is a promising target for immunotherapy.

Methods

In this study, singleR was used to annotate each cell subpopulation after t-distributed stochastic neighbor embedding (t-SNE) methods. Pseudo-time trace analysis and cell communication were analyzed by Monocle2 package and CellChat, respectively. A prognostic model based on CD24-related genes was constructed using several machine learning methods. Multiple quantitative immunofluorescence (MQIF) was used to evaluate the spatial relationship between CD24+PANCK+cells and exhausted CD8+T cells.

Results

Based on the scRNA-seq analysis, 1488 CD24-related differential genes were identified, and a risk model consisting of 15 prognostic characteristic genes was constructed by combining the bulk RNA-seq data. Patients were divided into high- and low-risk groups based on the median risk score. Immune landscape analysis showed that the low-risk group showed higher infiltration of immune-promoting cells and stronger immune reactivity. The results of cell communication demonstrated a strong interaction between CD24+epithelial cells and CD8+T cells. Subsequent MQIF demonstrated a strong interaction between CD24+PANCK+ and exhausted CD8+T cells with FOXP3+ in breast cancer. Additionally, CD24+PANCK+ and CD8+FOXP3+T cells were positively associated with lower survival rates.

Conclusion

This study highlights the importance of CD24+breast cancer cells in clinical prognosis and immunosuppressive microenvironment, which may provide a new direction for improving patient outcomes.

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Availability of data and material

The scRNA-seq data of GSE148673 was obtained from TISCH (http://tisch.comp-genomics.org/). Additional data and materials of TCGA-GDC- BRCA are available from the University of California, Santa Cruz (UCSC) Xena browser (https://xenabrowser.net/) and the Gene Expression Omnibus (GEO) with accession number GSE20685 (https://www.ncbi.nlm.nih.gov/geo/).

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Acknowledgements

We thank the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) Database and TISCH for sharing a large amount of data. Test-tube images used in Fig. 1 was obtained from Scidraw.io. Free vector woman figure with breast cancer and laboratory instruments images used in Fig. 1 were obtained from Freepik.com. We also thank TissueGnostics asia Pacific limited (Beijing, Chia) for their technical support in the analysis of multi-immunofluorescence staining images.

Funding

This study was funded by the National Natural Science Foundation of China (grant number 82003802 to TLZ), the Natural Science Foundation of Hunan Province (grant number 2019JJ50542 and 2023JJ50156 to TLZ, 2024JJ7455 to XFX), the Science and Technology Program of Hunan Health Commission (grant number 20201978 to TLZ), the China Scholarship Council (grant number 201808430085 to TLZ) and Clinical Research 4310 Program of the First Affiliated Hospital of the University of South China (grant number 20224310NHYCG04 to TLZ), Science and technology innovation Program of Hengyang City (grant number 202250045223 to TLZ).

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Author notes

  1. Haihong Hu, Hongxia Zhu and Wendi Zhan contributed equally to this work.

  2. Xuefeng Xu, Taolan Zhang contributed equally to this work.

Authors and Affiliations

  1. Department of Pharmacy, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China

    Haihong Hu, Hongxia Zhu, Wendi Zhan, Bo Hao, Jingdi Zhang & Taolan Zhang

  2. School of Pharmacy, Hengyang Medical College, University of South China, Hengyang, 421001, Hunan, China

    Haihong Hu, Hongxia Zhu, Wendi Zhan, Jingdi Zhang & Taolan Zhang

  3. Phase I Clinical Trial Center, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China

    Haihong Hu & Taolan Zhang

  4. Department of Breast and Thyroid Surgery, The First Affiliated HospitalH, engyang Medical School, University of South China, Hengyang, 421001, Hunan, China

    Ting Yan

  5. Department of Medical Oncology,The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China

    Siyu Wang

  6. Department of Function, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China

    Xuefeng Xu

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Contributions

TLZ, HHH and HXZ conceived and designed the study. HHH, HXZ and WDZ drafted the manuscript. HHH, HXZ, WDZ, BH, TY, SYW and JDZ conducted data analysis. TLZ, HHH and XFX strictly revised the manuscript. All authors read and approved the final manuscript.

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Correspondence to Taolan Zhang.

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Hu, H., Zhu, H., Zhan, W. et al. Integration of multiomics analyses reveals unique insights into CD24-mediated immunosuppressive tumor microenvironment of breast cancer. Inflamm. Res. 73, 1047–1068 (2024). https://doi.org/10.1007/s00011-024-01882-9

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