Single-Cell Sequencing Reveals the Heterogeneity of Glioma and Identifies IGFBP2 as A Potential Therapeutic Target.

Overview

1. Department of Neurosurgery, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
2. Department of Neurosurgery, the Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China
3. Department of Oncology, Henan Provincial People’s Hospital, Zhengzhou, China
4. Biotherapy Center and Cancer Center, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
5. Department of Pathology, the Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, China

Abstract

Background: Glioma is among the most malignant brain tumors, and its heterogeneity contributes significantly to treatment failure. Comprehensive profiling of cellular and molecular heterogeneity across different glioma stages and recurrence states is crucial for understanding therapeutic resistance and identifying novel targets. Accordingly, this study sought to systematically characterize the cellular and molecular heterogeneity of glioma across different stages and recurrence states using single-cell RNA sequencing, and to identify prognostic subtypes and potential therapeutic targets. Methods: We integrated public single-cell RNA sequencing data from glioma specimens, including lower-grade glioma (LGG), glioblastoma (GBM), and paired primary and recurrent tumors. Using these datasets, we identified distinct cellular subpopulations and their molecular signatures. Based on these glioma cell subpopulations, we reclassified gliomas from The Cancer Genome Atlas (TCGA) database into molecular subtypes and constructed a prognostic model. The functional role of a key candidate gene, insulin-like growth factor binding protein 2 (IGFBP2), was validated using in vitro knockdown experiments in mouse and human tumor cells and in vivo therapeutic studies in murine models, including combination therapy with anti-programmed cell death protein 1 (anti-PD-1) immune checkpoint blockade. Results: This analysis revealed that T cells in GBM and recurrent samples were predominantly exhausted, characterized by upregulation of PD-1 and T-cell immunoglobulin and mucin-domain containing−3 (Tim3), while myeloid cells exhibited an immunosuppressive phenotype with elevated expression of macrophage migration inhibitory factor (MIF) and cluster of differentiation (CD)276. We identified 12 distinct glioma cell subpopulations with varying proliferative and hypoxic signatures. Based on these subpopulations, TCGA gliomas were reclassified into two major subtypes. One subtype, enriched with myeloid-derived suppressor cells (MDSCs) and regulatory T cells (Tregs), was associated with poorer patient prognosis. A prognostic model was successfully established using differentially expressed genes between the subtypes. Furthermore, IGFBP2 was highly expressed in glioma cells, and its expression negatively correlated with T cell infiltration. In vitro knockdown of IGFBP2 downregulated programmed death-ligand 1 (PD-L1) expression on tumor cells. In vivo, IGFBP2 knockdown significantly suppressed tumor growth (p < 0.01) and extended survival in tumor-bearing mice (p < 0.05), and its combination with anti-PD-1 therapy markedly enhanced antitumor efficacy. Conclusions: This study provides deeper insights into the cellular ecosystem and heterogeneity of glioma, linking specific cellular features to patient prognosis. We identify IGFBP2 may play a role in regulating immunosuppressive tumor microenvironment and a potential therapeutic target.

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Data

Datasets cited

• geo:GSE138794 — at NCBI GEO; found in the text, “Single-Cell Data Processing and Cell…”

Other data links

• ncbi.nlm.nih.gov/geo — NCBI; found in the text, “Single-Cell Data Processing and Cell…”

Availability of Data and Materials

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 6 authors, 4 keywords, 12 MeSH terms, 72 references.

Cite

This paper

Kang, J.-L., Xu, Y.-J., Zhao, Q.-T., Zhang, B., Xu, X., & Yang, B. (2026). Single-Cell Sequencing Reveals the Heterogeneity of Glioma and Identifies IGFBP2 as A Potential Therapeutic Target. Oncology research, 34(7), 23. https://doi.org/10.32604/or.2026.079221

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