Journal
GENES
Volume 13, Issue 3, Pages -Publisher
MDPI
DOI: 10.3390/genes13030428
Keywords
glioblastoma; transcriptome analysis; tumor heterogeneity; biomarkers; network
Categories
Funding
- Department of Health Research (DHR)-Human Resource Development for Health Research (HRD)
- Indian Council ofMedical Research [R.12014/52/2020HR (BT2021164DHRX008473)]
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This study analyzed single-cell transcriptome data of glioblastoma patients to understand the heterogeneity and prognosis mechanism of GBM, and identified potential disease-specific biomarkers.
Glioblastoma multiforme (GBM) is the most common infiltrating lethal tumor of the brain. Tumor heterogeneity and the precise characterization of GBM remain challenging, and the disease-specific and effective biomarkers are not available at present. To understand GBM heterogeneity and the disease prognosis mechanism, we carried out a single-cell transcriptome data analysis of 3389 cells from four primary IDH-WT (isocitrate dehydrogenase wild type) glioblastoma patients and compared the characteristic features of the tumor and periphery cells. We observed that the marker gene expression profiles of different cell types and the copy number variations (CNVs) are heterogeneous in the GBM samples. Further, we have identified 94 differentially expressed genes (DEGs) between tumor and periphery cells. We constructed a tissue-specific co-expression network and protein-protein interaction network for the DEGs and identified several hub genes, including CX3CR1, GAPDH, FN1, PDGFRA, HTRA1, ANXA2 THBS1, GFAP, PTN, TNC, and VIM. The DEGs were significantly enriched with proliferation and migration pathways related to glioblastoma. Additionally, we were able to identify the differentiation state of microglia and changes in the transcriptome in the presence of glioblastoma that might support tumor growth. This study provides insights into GBM heterogeneity and suggests novel potential disease-specific biomarkers which could help to identify the therapeutic targets in GBM.
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