Multi-Transcriptomic Analysis Reveals GSC-Driven MES-Like Differentiation via EMT in GBM Cell–Cell Communication

<b>Background</b>: Glioblastoma (GBM) is the most malignant brain tumor, with a cellular hierarchy dominated by glioma stem cells (GSCs). Understanding global communications among GSCs and other cells helps us identify potential new therapeutic targets. In this study, multi-transcriptomic analysis was utilized to explore the communication pattern of GSCs in GBM. <b>Methods</b>: CellChat was used to quantitatively infer and analyze intercellular communication networks from GBM single-cell RNA-sequencing (scRNA-seq) data. Gene set enrichment analysis (GSEA) was conducted to identify specific biological pathways (epithelial-mesenchymal transition, EMT) involved in the communication pattern of GSCs. Spatial transcriptomic database was used to support the relationship between EMT and GSC proliferation. Single-sample GSEA (ssGSEA) was employed to assess which GSC state exhibited the strongest association with the EMT signature. <b>Results</b>: The cell communication pattern of GSCs is mostly related to EMT. Multiple EMT-related genes are highly expressed in GBM, particularly in GSCs, which are associated with poor prognosis. In addition, EMT-related genes are most enriched in mesenchymal-like (MES-like) GSCs. Tumor patients with MES-like GSC-enriched signatures demonstrate the most unfavorable prognosis compared to those harboring proneural-like (PN-like) or classical-like (CL-like) GSCs. <b>Conclusions</b>: This study suggests that GSCs facilitate GBM progression through intercellular communication in the pattern of EMT. EMT-associated genes may drive the differentiation of GSCs toward a MES-like phenotype, thereby leading to poorer clinical outcomes. Consequently, targeting EMT-related pathways could represent a novel therapeutic strategy for GBM treatment.

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Publication Details

Journal
Biomedicines
Published
2025-05-26
DOI
https://doi.org/10.3390/biomedicines13061304
Primary Topic
MicroRNA in disease regulation
Type
article
Field-Weighted Citation Impact
0.00

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article

Multi-Transcriptomic Analysis Reveals GSC-Driven MES-Like Differentiation via EMT in GBM Cell–Cell Communication

Po Zhang, Wei-Chi Wu, Kejun He, Dongsheng Li
Biomedicines
MicroRNA in disease regulation
article

Multi-Transcriptomic Analysis Reveals GSC-Driven MES-Like Differentiation via EMT in GBM Cell–Cell Communication

Po Zhang, Wei-Chi Wu, Kejun He, Dongsheng Li
article en

Abstract

<b>Background</b>: Glioblastoma (GBM) is the most malignant brain tumor, with a cellular hierarchy dominated by glioma stem cells (GSCs). Understanding global communications among GSCs and other cells helps us identify potential new therapeutic targets. In this study, multi-transcriptomic analysis was utilized to explore the communication pattern of GSCs in GBM. <b>Methods</b>: CellChat was used to quantitatively infer and analyze intercellular communication networks from GBM single-cell RNA-sequencing (scRNA-seq) data. Gene set enrichment analysis (GSEA) was conducted to identify specific biological pathways (epithelial-mesenchymal transition, EMT) involved in the communication pattern of GSCs. Spatial transcriptomic database was used to support the relationship between EMT and GSC proliferation. Single-sample GSEA (ssGSEA) was employed to assess which GSC state exhibited the strongest association with the EMT signature. <b>Results</b>: The cell communication pattern of GSCs is mostly related to EMT. Multiple EMT-related genes are highly expressed in GBM, particularly in GSCs, which are associated with poor prognosis. In addition, EMT-related genes are most enriched in mesenchymal-like (MES-like) GSCs. Tumor patients with MES-like GSC-enriched signatures demonstrate the most unfavorable prognosis compared to those harboring proneural-like (PN-like) or classical-like (CL-like) GSCs. <b>Conclusions</b>: This study suggests that GSCs facilitate GBM progression through intercellular communication in the pattern of EMT. EMT-associated genes may drive the differentiation of GSCs toward a MES-like phenotype, thereby leading to poorer clinical outcomes. Consequently, targeting EMT-related pathways could represent a novel therapeutic strategy for GBM treatment.

BiomedicinesVol. 13(6)
Union Hospital (HK), Central South University (CN), Sun Yat-sen University (CN), The First Hospital of Changsha (CN), The First Affiliated Hospital, Sun Yat-sen University (CN), Huazhong University of Science and Technology (CN)
National Natural Science Foundation of China
No poverty
Openalex Percentile: Top 84%
MicroRNA in disease regulation
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