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: Wen Wang, Junsheng Li, Qiheng He, Chenglong Liu, Siyu Wang, Zhiyao Zheng, Bojian Zhang, Siqi Mou, Wei Sun, Jizong Zhao
Format: Article
Language:English
Published: Wiley 2025-03-01
Series:Cancer Medicine
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Online Access:https://doi.org/10.1002/cam4.70745
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author Wen Wang
Junsheng Li
Qiheng He
Chenglong Liu
Siyu Wang
Zhiyao Zheng
Bojian Zhang
Siqi Mou
Wei Sun
Jizong Zhao
author_facet Wen Wang
Junsheng Li
Qiheng He
Chenglong Liu
Siyu Wang
Zhiyao Zheng
Bojian Zhang
Siqi Mou
Wei Sun
Jizong Zhao
author_sort Wen Wang
collection DOAJ
description 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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spelling doaj-art-e81e9ab9f4b2415a954064dc9761211a2025-08-20T02:05:21ZengWileyCancer Medicine2045-76342025-03-01145n/an/a10.1002/cam4.70745Integrated Analysis to Reveal Heterogeneity of Tumor‐Associated Neutrophils in GliomaWen Wang0Junsheng Li1Qiheng He2Chenglong Liu3Siyu Wang4Zhiyao Zheng5Bojian Zhang6Siqi Mou7Wei Sun8Jizong Zhao9Department of Neurosurgery Beijing Tiantan Hospital, Capital Medical University Beijing ChinaDepartment of Neurosurgery Beijing Tiantan Hospital, Capital Medical University Beijing ChinaDepartment of Neurosurgery Beijing Tiantan Hospital, Capital Medical University Beijing ChinaDepartment of Neurosurgery Beijing Tiantan Hospital, Capital Medical University Beijing ChinaDepartment of Neurosurgery Beijing Tiantan Hospital, Capital Medical University Beijing ChinaDepartment of Neurosurgery Beijing Tiantan Hospital, Capital Medical University Beijing ChinaDepartment of Neurosurgery Beijing Tiantan Hospital, Capital Medical University Beijing ChinaDepartment of Neurosurgery Beijing Tiantan Hospital, Capital Medical University Beijing ChinaDepartment of Neurosurgery Beijing Tiantan Hospital, Capital Medical University Beijing ChinaDepartment of Neurosurgery Beijing Tiantan Hospital, Capital Medical University Beijing ChinaABSTRACT 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.https://doi.org/10.1002/cam4.70745biomarkergliomaintroductionprognosisscRNA‐seqtumor‐associated neutrophil
spellingShingle Wen Wang
Junsheng Li
Qiheng He
Chenglong Liu
Siyu Wang
Zhiyao Zheng
Bojian Zhang
Siqi Mou
Wei Sun
Jizong Zhao
Integrated Analysis to Reveal Heterogeneity of Tumor‐Associated Neutrophils in Glioma
Cancer Medicine
biomarker
glioma
introduction
prognosis
scRNA‐seq
tumor‐associated neutrophil
title Integrated Analysis to Reveal Heterogeneity of Tumor‐Associated Neutrophils in Glioma
title_full Integrated Analysis to Reveal Heterogeneity of Tumor‐Associated Neutrophils in Glioma
title_fullStr Integrated Analysis to Reveal Heterogeneity of Tumor‐Associated Neutrophils in Glioma
title_full_unstemmed Integrated Analysis to Reveal Heterogeneity of Tumor‐Associated Neutrophils in Glioma
title_short Integrated Analysis to Reveal Heterogeneity of Tumor‐Associated Neutrophils in Glioma
title_sort integrated analysis to reveal heterogeneity of tumor associated neutrophils in glioma
topic biomarker
glioma
introduction
prognosis
scRNA‐seq
tumor‐associated neutrophil
url https://doi.org/10.1002/cam4.70745
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