Journal Article Epublish
PubMed: 40188324 DOI: 10.1186/s13062-025-00640-z
Large-scale bulk and single-cell RNA sequencing combined with machine learning reveals glioblastoma-associated neutrophil heterogeneity and establishes a VEGFA + neutrophil prognostic model.
Biol Direct 20(1):45
Authors: Yufan Yang, Ziyuan Liu, Zhongliang Wang, Xiang Fu, Zhiyong Li, Jianlong Li, Zhongyuan Xu, Bohong Cen
Affiliations
- Clinical Pharmacy Center, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, 510515, China. National Medical Products Administration Key Laboratory for Research and Evaluation of Drug Metabolism & Guangdong Provincial Key Laboratory of New Drug Screening & Guangdong-Hongkong- Macao, Joint Laboratory for New Drug Screening, School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, Guangdong, 510515, China.
- Department of Pharmacy, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, 510282, China. National Medical Products Administration Key Laboratory for Research and Evaluation of Drug Metabolism & Guangdong Provincial Key Laboratory of New Drug Screening & Guangdong-Hongkong- Macao, Joint Laboratory for New Drug Screening, School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, Guangdong, 510515, China.
- Department of Pathology, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, 510282, China.
- Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, 510515, China.
- Department of Orthopedic Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, 510515, China. Departments of Pediatrics, Weill Cornell Medicine, New York, NY, USA.
- Clinical Pharmacy Center, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, 510515, China. National Medical Products Administration Key Laboratory for Research and Evaluation of Drug Metabolism & Guangdong Provincial Key Laboratory of New Drug Screening & Guangdong-Hongkong- Macao, Joint Laboratory for New Drug Screening, School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, Guangdong, 510515, China.
- Clinical Pharmacy Center, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, 510515, China. National Medical Products Administration Key Laboratory for Research and Evaluation of Drug Metabolism & Guangdong Provincial Key Laboratory of New Drug Screening & Guangdong-Hongkong- Macao, Joint Laboratory for New Drug Screening, School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, Guangdong, 510515, China.
Abstract
BACKGROUND
Neutrophils play a key role in the tumor microenvironment (TME); however, their functions in glioblastoma (GBM) are overlooked and insufficiently studied. A detailed analysis of GBM-associated neutrophil (GBMAN) subpopulations may offer new insights and opportunities for GBM immunotherapy.
METHODS
We analyzed single-cell RNA sequencing (scRNA-seq) data from 127 isocitrate dehydrogenase (IDH) wild-type GBM samples to characterize the GBMAN subgroups, emphasizing developmental trajectories, cellular communication, and transcriptional networks. We implemented 117 machine learning combinations to develop a novel risk model and compared its performance to existing glioma models. Furthermore, we assessed the biological and molecular features of the GBMAN subgroups in patients.
RESULTS
From integrated large-scale scRNA-seq data (498,747 cells), we identified 5,032 neutrophils and classified them into four distinct subtypes. VEGFA +GBMAN exhibited reduced inflammatory response characteristics and a tendency to interact with stromal cells. Furthermore, these subpopulations exhibited significant differences in transcriptional regulation. We also developed a risk model termed the "VEGFA +neutrophil-related signature" (VNRS) using machine learning methods. The VNRS model showed higher accuracy than previously published risk models and was an independent prognostic factor. Additionally, we observed significant differences in immunotherapy responses, TME interactions, and chemotherapy efficacy between high-risk and low-risk VNRS score groups.
CONCLUSION
Our study highlights the critical role of neutrophils in the TME of GBM, allowing for a better understanding of the composition and characteristics of GBMAN. The developed VNRS model serves as an effective tool for evaluating the risk and guiding clinical treatment strategies for GBM.
CLINICAL TRIAL NUMBER
Not applicable.
MeSH
Cells, Neutrophils, Immunotherapy, Machine Learning, Glioblastoma, Learning, Rna