Dynamic trajectory and cell communication of different cell clusters in malignant progression of glioblastoma
10.19723/j.issn.1671-167X.2024.02.001
- VernacularTitle:胶质母细胞瘤恶性进展中不同细胞亚群的动态轨迹和细胞通讯网络
- Author:
Xiang CAI
1
;
Rendong WANG
;
Shijia WANG
;
Ziqi REN
;
Qiuhong YU
;
Dongguo LI
Author Information
1. 首都医科大学生物医学工程学院智能医学工程学学系,北京 100069
- Keywords:
Glioblastoma;
Single-cell sequencing;
Pseudo-time analysis;
Cell-cell interaction;
Cell communication
- From:
Journal of Peking University(Health Sciences)
2024;56(2):199-206
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To delve deeply into the dynamic trajectories of cell subpopulations and the communication network among immune cell subgroups during the malignant progression of glioblastoma(GBM),and to endeavor to unearth key risk biomarkers in the GBM malignancy progression,so as to provide a more profound understanding for the treatment and prognosis of this disease by integrating tran-scriptomic data and clinical information of the GBM patients.Methods:Utilizing single-cell sequencing data analysis,we constructed a cell subgroup atlas during the malignant progression of GBM.The Mono-cle2 tool was employed to build dynamic progression trajectories of the tumor cell subgroups in GBM.Through gene enrichment analysis,we explored the biological processes enriched in genes that significant-ly changed with the malignancy progression of GBM tumor cell subpopulations.CellChat was used to identify the communication network between the different immune cell subgroups.Survival analysis helped in identifying risk molecular markers that impacted the patient prognosis during the malignant pro-gression of GBM.This methodological approach offered a comprehensive and detailed examination of the cellular and molecular dynamics within GBM,providing a robust framework for understanding the disease's progression and potential therapeutic targets.Results:The analysis of single-cell sequencing data identified 6 different cell types,including lymphocytes,pericytes,oligodendrocytes,macrophages,glioma cells,and microglia.The 27 151 cells in the single-cell dataset included 3 881 cells from the pa-tients with low-grade glioma(LGG),10 166 cells from the patients with newly diagnosed GBM,and 13 104 cells from the patients with recurrent glioma(rGBM).The pseudo-time analysis of the glioma cell subgroups indicated significant cellular heterogeneity during malignant progression.The cell interaction analysis of immune cell subgroups revealed the communication network among the different immune sub-groups in GBM malignancy,identifying 22 biologically significant ligand-receptor pairs across 12 key bio-logical pathways.Survival analysis had identified 8 genes related to the prognosis of the GBM patients,among which SERPINE1,COL6A1,SPP1,LTF,C1S,AEBP1,and SAA1L were high-risk genes in the GBM patients,and ABCC8 was low-risk genes in the GBM patients.These findings not only provided new theoretical bases for the treatment of GBM,but also offered fresh insights for the prognosis assessment and treatment decision-making for the GBM patients.Conclusion:This research comprehensively and pro-foundly reveals the dynamic changes in glioma cell subpopulations and the communication patterns among the immune cell subgroups during the malignant progression of GBM.These findings are of significant im-portance for understanding the complex biological processes of GBM,providing crucial new insights for precision medicine and treatment decisions in GBM.Through these studies,we hope to provide more ef-fective treatment options and more accurate prognostic assessments for the patients with GBM.
