Single-Cell Atlas Reveals Immunosuppressive Microenvironment and Treg Cell Distribution in Recurrent Glioblastoma

Glioblastoma is the most aggressive brain tumor, with a very high recurrence rate and poor prognosis. Although many studies have explored the tumor microenvironment of this disease, the understanding of the immune microenvironment in recurrent glioblastoma remains very limited. In this study, the research team used single-cell RNA sequencing technology to reveal the immune microenvironment of recurrent glioblastoma, analyze potential biomarkers in cerebrospinal fluid, and compare the immune characteristics of tumors in different locations.

Research Background

Glioblastoma is a highly malignant and easily recurrent brain cancer characterized by features such as the specificity of the blood-brain barrier (BBB) and high heterogeneity. Treatment options for patients with recurrent glioblastoma are limited, as inherent molecular changes make the tumor resistant to conventional therapies. Understanding the molecular and cellular composition of these tumors can help broaden treatment options. Furthermore, immunotherapy, as an ideal treatment, can overcome the BBB targeting tumor cells. However, some initial immune cells in the tumor microenvironment will transform to support tumor cells in evading immune surveillance. A detailed understanding of these components will help reveal the complexity of recurrent glioblastoma.

The immunosuppressive microenvironment in recurrent glioblastoma has a significant impact on tumor recurrence and prognosis. Regulatory T cells (Tregs) play a key role in tumor immunotherapy. They promote tumor cell immune evasion by inhibiting the activity of effective T cells. Therefore, the role of regulatory T cells is a new direction in glioblastoma immunotherapy.

Research Source

This study was completed by the research team of the Department of Neurosurgery at the Northern Jiangsu People’s Hospital affiliated with Yangzhou University. The team includes researchers from Yangzhou University, Nanjing Medical University Affiliated Cancer Hospital, and Jiangsu Cancer Institute. This paper was published in the 2024 issue of the journal “Cancer Gene Therapy” and received approval from the Ethics Committee of Northern Jiangsu People’s Hospital.

Research Process

The researchers recruited two patients and collected their tumor and cerebrospinal fluid samples. Using single-cell RNA sequencing technology, the research team revealed the immune landscape of recurrent glioblastoma and its cerebrospinal fluid.

Data Collection and Processing

The researchers collected four samples from two patients: a malignant tumor sample and a cerebrospinal fluid sample from a recurrent glioblastoma patient, and a non-malignant tumor sample and a cerebrospinal fluid sample from a patient with a benign brain tumor. The samples were transported under low temperatures, and cell suspensions were prepared and libraries constructed using single-cell dissociation kits.

Single-Cell Sequencing and Analysis

Single-cell sequencing was performed using the 10x Genomics platform, revealing a total of 44,743 cells. Based on a reference marker set, the researchers identified 13 clusters related to the tumor microenvironment. Techniques such as differential gene expression analysis, enrichment analysis, pseudotime trajectory analysis, and inferred CNV analysis were used to comprehensively analyze cell types and marker genes in the samples.

Research Findings

1. Immune Landscape Analysis: The analysis found that malignant tumor samples were enriched with T cells, while Treg cells primarily populated the malignant cerebrospinal fluid samples, indicating an immunosuppressive microenvironment in recurrent glioblastoma. Additionally, macrophages and neutrophils were significantly enriched in malignant cerebrospinal fluid.

2. Biomarker Potential of S100A9: High expression of S100A9 was found in malignant cerebrospinal fluid, suggesting its potential as an effective biomarker for diagnosis and prediction of recurrence.

3. Cell Type and Characterization: The analysis revealed that astrocytes in tumor samples had higher CNV levels, and similar subgroup development trends were observed in both core and peripheral tumor positions.

4. Differential Gene Expression Analysis: Significant differences in DEGs expression patterns were found between different samples. Notably, S100A9 expression was significantly higher in malignant samples than non-malignant samples, highlighting its critical role in tumor progression.

5. Immune Microenvironment Heterogeneity: Despite no significant differences in immune composition in multifocal tumor samples, heterogeneity was observed between tumor and cerebrospinal fluid samples. This further confirms the potential of liquid biopsy in glioblastoma.

6. Single-Cell Metabolic Pathway Analysis: Metabolic analysis of macrophages and T cells revealed that T cell metabolic activity in malignant cerebrospinal fluid was significantly higher than in tumor samples, indicating that these cells might be more active and invasive in a malignant environment.

Conclusion and Significance

This study revealed the immune microenvironment of recurrent glioblastoma after chemotherapy and radiotherapy, and for the first time demonstrated the heterogeneity of tumor and cerebrospinal fluid samples at the single-cell level. The study proposes S100A9 as a new target for glioblastoma and confirms the prospect of liquid biopsy in tumor immunotherapy. The results provide new insights for the treatment and diagnosis of recurrent glioblastoma, particularly in exploring the mechanisms of immunosuppression in the microenvironment. Meanwhile, this study also emphasizes the unique advantage of cerebrospinal fluid samples in reflecting the tumor microenvironment, providing a theoretical basis for future glioblastoma research.

Summary

This study comprehensively revealed the immune microenvironment of recurrent glioblastoma using single-cell sequencing technology, deeply explored the complexity and heterogeneity of the tumor microenvironment, and proposed the potential of S100A9 as an important biomarker. These findings not only enrich the understanding of glioblastoma but also provide new directions for future diagnosis and treatment.