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Tumor Heterogeneity and Molecular Characteristics of Glioblastoma Revealed by Single-Cell RNA-Seq Data Analysis

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 pro...

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Autores principales: Yesudhas, Dhanusha, Dharshini, S. Akila Parvathy, Taguchi, Y-h., Gromiha, M. Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8955282/
https://www.ncbi.nlm.nih.gov/pubmed/35327982
http://dx.doi.org/10.3390/genes13030428
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author Yesudhas, Dhanusha
Dharshini, S. Akila Parvathy
Taguchi, Y-h.
Gromiha, M. Michael
author_facet Yesudhas, Dhanusha
Dharshini, S. Akila Parvathy
Taguchi, Y-h.
Gromiha, M. Michael
author_sort Yesudhas, Dhanusha
collection PubMed
description 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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spelling pubmed-89552822022-03-26 Tumor Heterogeneity and Molecular Characteristics of Glioblastoma Revealed by Single-Cell RNA-Seq Data Analysis Yesudhas, Dhanusha Dharshini, S. Akila Parvathy Taguchi, Y-h. Gromiha, M. Michael Genes (Basel) Article 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. MDPI 2022-02-25 /pmc/articles/PMC8955282/ /pubmed/35327982 http://dx.doi.org/10.3390/genes13030428 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yesudhas, Dhanusha
Dharshini, S. Akila Parvathy
Taguchi, Y-h.
Gromiha, M. Michael
Tumor Heterogeneity and Molecular Characteristics of Glioblastoma Revealed by Single-Cell RNA-Seq Data Analysis
title Tumor Heterogeneity and Molecular Characteristics of Glioblastoma Revealed by Single-Cell RNA-Seq Data Analysis
title_full Tumor Heterogeneity and Molecular Characteristics of Glioblastoma Revealed by Single-Cell RNA-Seq Data Analysis
title_fullStr Tumor Heterogeneity and Molecular Characteristics of Glioblastoma Revealed by Single-Cell RNA-Seq Data Analysis
title_full_unstemmed Tumor Heterogeneity and Molecular Characteristics of Glioblastoma Revealed by Single-Cell RNA-Seq Data Analysis
title_short Tumor Heterogeneity and Molecular Characteristics of Glioblastoma Revealed by Single-Cell RNA-Seq Data Analysis
title_sort tumor heterogeneity and molecular characteristics of glioblastoma revealed by single-cell rna-seq data analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8955282/
https://www.ncbi.nlm.nih.gov/pubmed/35327982
http://dx.doi.org/10.3390/genes13030428
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