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陆军军医大学(第三军医大学)第一附属医院病理学研究所,肿瘤免疫病理学教育部重点实验室,重庆
姚小红,E-mail:yaoxiaohong@tmmu.edu.cn
收稿日期:2025-04-27,
修回日期:2025-06-26,
纸质出版日期:2025-08-30
移动端阅览
陈涛,杨帆,王帅,等.基于多转录组测序的胶质母细胞瘤间质样肿瘤亚群缺氧特征及预后研究[J].陆军军医大学学报,2025,47(16):1904-1912.DOI:10.16016/j.2097-0927.202504111.
CHEN T,YANG F,WANG S,et al.Hypoxia characteristics and prognostic significance of glioblastoma MES-like subpopulation through multi-transcriptomics sequencing[J].J Army Med Univ,2025,47(16):1904-1912.DOI:10.16016/j.2097-0927.202504111.
陈涛,杨帆,王帅,等.基于多转录组测序的胶质母细胞瘤间质样肿瘤亚群缺氧特征及预后研究[J].陆军军医大学学报,2025,47(16):1904-1912.DOI:10.16016/j.2097-0927.202504111. DOI:
CHEN T,YANG F,WANG S,et al.Hypoxia characteristics and prognostic significance of glioblastoma MES-like subpopulation through multi-transcriptomics sequencing[J].J Army Med Univ,2025,47(16):1904-1912.DOI:10.16016/j.2097-0927.202504111. DOI:
目的
2
通过多转录组测序数据分析,解析胶质母细胞瘤(glioblastoma, GBM)的肿瘤细胞异质性组成特点和生物学功能,以探究GBM间质样(mesenchymal-like, MES-like)肿瘤亚群的缺氧特点、空间定位特征以及对GBM恶性生物学行为的影响。
方法
2
分析公共数据库18例GBM单细胞转录组测序(single-cell RNA sequencing, scRNA-seq)数据,以及GBM普通转录组测序(bulk RNA sequencing,bulk RNA-seq)和空间转录组测序(spatial transcriptomics,ST)数据,通过单细胞转录组定义GBM肿瘤亚群,基因本体论(Gene Ontology, GO)和基因集富集分析(gene set enrichment analysis, GSEA)进行功能富集。使用BayesPrism反卷积方法评估普通转录组的细胞亚群占比和定位,并收集2015年至2023年就诊于西南医院神经外科患者的12例符合胶质母细胞瘤病理学诊断标准的石蜡样本(男性10例,女性2例,平均年龄为53.50岁,中位年龄为54.50岁)进行免疫荧光验证。pySCENIC预测肿瘤细胞亚群特异转录因子。
结果
2
GBM肿瘤细胞具有高度异质性,主要分为4种亚群,即星形胶质细胞样(astrocyte-like,AC-like)、神经前体细胞样(neural progenitor-like,NPC-like)、少突前体细胞样(oligodendrocyte progenitor-like,OPC-like)和MES-like肿瘤亚群。差异基因分析发现MES-like肿瘤亚群高表达血管内皮生长因子A(vascular endothelial growth Factor A,VEGFA)、肾上腺髓质素(adrenomedullin, ADM)、N-myc下游调控基因1(N-myc downstream regulated 1,NDRG1)、胰岛素样生长因子结合蛋白 5(insulin like growth factor binding protein 5,IGFBP5)、A-激酶锚定蛋白 12(A-kinase anchoring protein 12,AKAP12)(
P
<
0.001)。pySCENIC转录因子预测发现,MES-like肿瘤亚群的高活性转录因子为AT-rich 交互域 3A(AT-rich interaction domain 3A,ARID3A)、FOS like 2, AP-1 转录因子亚基(FOS Like 2, AP-1 transcription factor subunit,FOSL2)、内皮 PAS 结构域蛋白 1(end
othelial PAS domain protein 1,EPAS1)、CCAAT增强子结合蛋白Delta(CCAAT enhancer binding protein delta,CEBPD)、CCAAT 增强子结合蛋白β(CCAAT enhancer binding protein beta,CEBPB)(
P
<
0.05)。GO和GSEA富集发现,MES-like肿瘤亚群富集于缺氧相关通路,如细胞对低氧水平的反应(NES=2.437,
P
<
0.001)。BayesPrism反卷积显示,MES-like肿瘤亚群主要存在于假栅栏样坏死区和坏死周围。GBM石蜡样本免疫荧光证实CD44
+
(CD44 antigen,CD44抗原)MES-like肿瘤亚群主要存在于HIF1α
high
(Hypoxia Inducible Factor 1 Subunit Alpha,缺氧诱导因子1α)的缺氧区域(
P
<
0.01)。多因素Cox回归显示MES-like肿瘤亚群与患者不良预后显著相关(
HR
=1.71,95%
CI
:1.38~2.11,
P
<
0.001)。
结论
2
GBM肿瘤细胞具有高度异质性,主要分为AC-like、NPC-like、OPC-like和MES-like肿瘤亚群,其MES-like肿瘤亚群具有缺氧特点,主要定位于假栅栏样坏死区和坏死周围,具有促进GBM恶性生物学行为的作用。
Objective To analyze the composition characteristics and biological functions of tumor cell subpopulations in glioblastoma (GBM) through multi-transcriptomics sequencing technology
and explore the hypoxia characteristics and spatial localization features of the mesenchymal-like (MES-like) tumor cell subpopulation in GBM and the influence on malignant biological behaviors. Methods Multi-transcriptomics sequencing data
including single-cell RNA sequencing (scRNA-seq) data (18 patients)
bulk RNA sequencing (bulk RNA-seq) and spatial transcriptomics (ST) data of GBM
were employed to define cell subpopulations in GBM
and Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) were utilized to analyze their functions. The proportions and locations of cell subpopulations in bulk RNA-seq data were evaluated with BayesPrism deconvolution. Immunofluorescence assay was conducted for verification on 12 paraffin samples of GBM from patients who visited the neurosurgical department of our hospital from 2015 to 2023 and met the pathological diagnostic criteria for GBM (10 males and 2 females
at an average age of 53.50 years and a median age of 54.50 years). pySCENIC was applied to predict sp
ecific transcription factors of tumor cell subpopulations. Results Tumor cells in GBM were highly heterogeneous
and could be mainly divided into 4 subpopulations: astrocyte-like (AC-like)
neural progenitor-like (NPC-like)
oligodendrocyte progenitor-like (OPC-like) and MES-like. Differential gene analysis found that the MES-like tumor cells highly expressed vascular endothelial growth factor A (VEGFA)
adrenomedullin (ADM)
N-myc downstream regulated 1 (NDRG1)
insulin like growth factor binding protein 5 (IGFBP5)
and A-kinase anchoring protein 12 (AKAP12) (
P
<
0.001). pySCENIC transcription factor prediction found that the high-active transcription factors of the MES-like tumor cells were AT-rich interaction domain 3A (ARID3A)
FOS like 2
AP-1 transcription factor subunit (FOSL2)
endothelial PAS domain protein 1 (EPAS1)
CCAAT enhancer binding protein delta (CEBPD)
and CCAAT enhancer binding protein beta (CEBPB) (
P
<
0.05). GO and GSEA enrichment analyses found that the MES-like tumor cells were enriched in hypoxia-related pathways
especially the pathway of cell responses to hypoxia levels (NES=2.437
P
<
0.001). BayesPrism deconvolution showed that the MES-like tumor cells mainly existed in PAN(Pseudopalisading cells around necrosis) and perinecrotic zone. Immunofluorescence assay confirmed CD44
+
(CD44 antigen) MES-like tumor cells were mainly located in hypoxia areas with highly expression of hypoxia inducible factor 1 subunit alpha (HIF1α) (
P
<
0.01). Multivariate Cox regression analysis indicated that the MES-like tumor cells were significantly correlated with the adverse prognosis of GBM patients (
HR
=1.71
95%
CI
: 1.38~2.11
P
<
0.001). Conclusion Tumor cells in GBM are of highly heterogeneity. They could be mainly divided into 4 subpopulations: AC-like
NPC-like
OPC-like and MES-like. MES-like tumor cells
mainly locating in PAN and perinecrotic zone
are charact
erized by hypoxia
which can promote the malignant progression of GBM.
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