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Identification of cytokine-predominant immunosuppressive class and prognostic risk signatures in glioma

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Abstract

Purpose

The advent of immune checkpoint blockade (ICB) therapies this year has changed the way glioblastoma (GBM) is treated. Meanwhile, some patients with strong PD-L1 expression remain immune checkpoint resistant. To better understand the molecular processes that influence the immune environment, there is an urgent need to characterize the immunosuppressive tumor microenvironment and identify biomarkers to predict patient survival outcomes.

Patients and methods

Our study analyzed RNA-sequencing data from 178 GBM samples. Their unique gene expression patterns in the tumor microenvironment were analyzed by an unsupervised clustering algorithm. Through these expression patterns, a panel of T-cell exhaustion signatures, immunosuppressive cells, and clinical features correlates with immunotherapy response. The presence or absence of immune status and prognostic signatures was then validated with the test dataset.

Results

38.2% of GBM patients showed increased expression of anti-inflammatory cytokines, significant enrichment of T cell exhaustion signals, higher proportion of immunosuppressive cells (macrophages and CD4 regulatory T cells) and nine inhibitory checkpoints (CTLA4, PDCD1, LAG3, BTLA, TIGIT, HAVCR2, IDO1, SIGLEC7, and VISTA). The immunodepleted class (IDC) was used to classify these immunocompromised individuals. Despite the high density of tumor-infiltrating lymphocytes shown by IDC, such patients have a poor prognosis. Although PD-L1 was highly expressed in IDC, it suggested that there might be ICB resistance. There are many IDC predictive signatures to discover.

Conclusion

PD-1 is strongly expressed in a novel immunosuppressive class of GBM, but this cluster may be resistant to ICB therapy. A comprehensive description of this drug-resistant tumor microenvironment could provide new insights into drug resistance mechanisms and improved immunotherapy techniques.

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Data availability

Datasets analyzed during the current study are available in The Cancer Genome Atlas (TCGA) repository: https://portal.gdc.cancer.gov/, http://www.cgga.org.cn/.

Abbreviations

ICB:

Immune checkpoint blockade

GBM:

Glioblastoma

IDC:

Immune depletion class

CNS:

Central nervous system

FDA:

Food and drug administration

PD-1:

Programmed cell death protein 1

PD-L1:

Programmed death-ligand 1

GM-CSF:

Colony-stimulating factor

UCC:

Unsupervised consistent clustering

TCGA:

The cancer genome atlas

CGGA:

Chinese glioma genome atlas

ssGSEA:

Gene set enrichment analysis

TILs:

Tumor-infiltrating lymphocytes

GO:

Gene ontology

KEGG:

Kyoto encyclopedia of genes and genomes

Tex:

T cell exhaustion

OS:

Overall survival

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Acknowledgements

The authors thank all the participants for their cooperation.

Funding

The Scientific Research Planning Project of the Education Department of Jilin Province (Grant Nos. JJKH20181256KJ).

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Authors and Affiliations

  1. The Affiliated Hospital of Changchun University of Chinese Medicine, Changchun, 130117, China

    Ziyue Tian, Zhongyi Yang, Yuying Chai, Jinpu Wu, Miao Yang & Weimin Zhao

  2. The Third Affiliated Hospital of Changchun University of Chinese Medicine, Changchun, 130117, China

    Meng Jin

  3. School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, 511442, Guangdong, China

    Ran Ding

  4. School of Medical Informatics Engineering, Changchun University of Chinese Medicine, Changchun, 130118, Jilin, China

    Yuhan Wang

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  1. Ziyue Tian
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Contributions

ZT, RD. designed the study, performed the major data analysis, and drafted the manuscript; ZT. collected a part of data, performed a part of data analysis, and help to generated figures. ZY. performed a part of data analysis. MJ. helped to generate figures. WZ. provided funding source, designed, oversaw, and supervised the project and edited, reviewed, and finalized the paper. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Weimin Zhao.

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The only data used in this study are the original data of public databases, so no ethical approval is involved.

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Tian, Z., Yang, Z., Jin, M. et al. Identification of cytokine-predominant immunosuppressive class and prognostic risk signatures in glioma. J Cancer Res Clin Oncol 149, 13185–13200 (2023). https://doi.org/10.1007/s00432-023-05173-4

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