Annals of medicine · 2024
Necroptosis-based glioblastoma prognostic subtypes: implications for TME remodeling and therapy response.
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Khan Muhammad, Huang Xiuting, Ye Xiaoxin, Zhang Donghui, Wang Baiyao, Xu Anan, Li Rong, Ren Anbang, Chen Chengcong, Song Jingjing, Zheng Rong, Yuan Yawei, Lin Jie
Аннотация
BACKGROUND: Glioblastoma (GBM) is an aggressive primary brain tumor with a high recurrence rate and poor prognosis. Necroptosis, a pathological hallmark of GBM, is poorly understood in terms of its role in prognosis, tumor microenvironment (TME) alteration, and immunotherapy.
METHODS & RESULTS: We assessed the expression of 55 necroptosis-related genes in GBM and normal brain tissues. We identified necroptosis-stratified clusters using Uni-Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression to establish the 10-gene Glioblastoma Necroptosis Index (GNI). GNI demonstrated significant prognostic efficacy in the TCGA dataset (n = 160) and internal validation dataset (n = 345) and in external validation cohorts (n = 591). The GNI-high subgroup displayed a mesenchymal phenotype, lacking the IDH1 mutation, and MGMT methylation. This subgroup was characterized by significant enrichment in inflammatory and humoral immune pathways with prominent cell adhesion molecules (CD44 and ICAM1), inflammatory cytokines (TGFB1, IL1B, and IL10), and chemokines (CX3CL1, CXCL9, and CCL5). The TME in this subgroup showed elevated infiltration of M0 macrophages, neutrophils, mast cells, and regulatory T cells. GNI-related genes appeared to limit macrophage polarization, as confirmed by immunohistochemistry and flow cytometry. The top 30% high-risk score subset exhibited increased CD8 T cell infiltration and enhanced cytolytic activity. GNI showed promise in predicting responses to immunotherapy and targeted treatment.
CONCLUSIONS: Our study highlights the role of necroptosis-related genes in glioblastoma (GBM) and their effects on the tumor microenvironment and patient prognosis. TheGNI demonstrates potential as a prognostic marker and provides insights into immune characteristics and treatment responsiveness.
METHODS & RESULTS: We assessed the expression of 55 necroptosis-related genes in GBM and normal brain tissues. We identified necroptosis-stratified clusters using Uni-Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression to establish the 10-gene Glioblastoma Necroptosis Index (GNI). GNI demonstrated significant prognostic efficacy in the TCGA dataset (n = 160) and internal validation dataset (n = 345) and in external validation cohorts (n = 591). The GNI-high subgroup displayed a mesenchymal phenotype, lacking the IDH1 mutation, and MGMT methylation. This subgroup was characterized by significant enrichment in inflammatory and humoral immune pathways with prominent cell adhesion molecules (CD44 and ICAM1), inflammatory cytokines (TGFB1, IL1B, and IL10), and chemokines (CX3CL1, CXCL9, and CCL5). The TME in this subgroup showed elevated infiltration of M0 macrophages, neutrophils, mast cells, and regulatory T cells. GNI-related genes appeared to limit macrophage polarization, as confirmed by immunohistochemistry and flow cytometry. The top 30% high-risk score subset exhibited increased CD8 T cell infiltration and enhanced cytolytic activity. GNI showed promise in predicting responses to immunotherapy and targeted treatment.
CONCLUSIONS: Our study highlights the role of necroptosis-related genes in glioblastoma (GBM) and their effects on the tumor microenvironment and patient prognosis. TheGNI demonstrates potential as a prognostic marker and provides insights into immune characteristics and treatment responsiveness.