Integrated Analysis to Reveal Heterogeneity of Tumor‐Associated Neutrophils in Glioma
ABSTRACT Background Glioma, characterized by its cellular and molecular heterogeneity, presents formidable challenges in treatment strategy and prognostic assessment. The tumor microenvironment (TME) profoundly influences tumor behavior and treatment response, with tumor‐associated neutrophils (TANs...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-03-01
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| Series: | Cancer Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/cam4.70745 |
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| Summary: | ABSTRACT Background Glioma, characterized by its cellular and molecular heterogeneity, presents formidable challenges in treatment strategy and prognostic assessment. The tumor microenvironment (TME) profoundly influences tumor behavior and treatment response, with tumor‐associated neutrophils (TANs) playing a complex but understudied role. This study aimed to investigate the heterogeneity and role of TANs in glioma and to develop a prognostic model. Methods Analysis of scRNA‐seq data identified cellular subpopulations and differentially expressed neutrophil‐related genes (DE‐NRGs). Bulk RNA‐seq was obtained from four independent datasets. Molecular subtypes of glioma samples were determined by consensus clustering. WGCNA was conducted to elucidate the association between gene modules and subtypes. We developed a risk score model. Expression of selected genes was confirmed using immunohistochemistry (IHC). In vitro experiments were also performed for functional verification, including CCK8, EdU, Transwell, and TUNEL assays. Results A total of 108 DE‐NRGs for TANs were identified based on scRNA‐seq data. Two molecular subtypes were characterized, showing significant differences in prognosis and clinical features. Immune‐related analyses demonstrated varied immunological characteristics between subtypes. The risk score model was constructed with 7 genes, including AEBP1, CAVIN1, DCTD, DEPP1, DUSP6, FKBP9, and UGCG. It showed significant prognostic value and was validated across three external datasets. The mutation landscape highlighted higher IDH mutation prevalence in low‐risk groups. Drug sensitivity analysis indicated TMZ resistance in high‐risk groups. In vitro experiments showed that UGCG could promote glioma cell proliferation, migration, and invasion, while decreasing apoptosis. Conclusion This study explored the heterogeneity of TANs and developed a prognostic model, providing insights for prognostic prediction and guiding personalized treatment strategies in glioma. Declaration of Generative AI in Scientific Writing: The authors declare nonuse of generative AI and AI‐assisted technologies in the writing process. |
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| ISSN: | 2045-7634 |