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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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. |
format | Online Article Text |
id | pubmed-8955282 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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