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Comparative Analysis of the GNAI Family Genes in Glioblastoma through Transcriptomics and Single-Cell Technologies
SIMPLE SUMMARY: In this study, we aimed to address the critical need for a prognostic biomarker in the treatment of GBM. Various approaches and treatments have been examined in the recent literature; however, their effectiveness is limited due to the highly invasive, heterogeneous, and resistant nat...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10605456/ https://www.ncbi.nlm.nih.gov/pubmed/37894479 http://dx.doi.org/10.3390/cancers15205112 |
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author | Raza, Ahmad Yen, Meng-Chi Anuraga, Gangga Shahzadi, Iram Mazhar, Muhammad Waqar Ta, Hoang Dang Khoa Xuan, Do Thi Minh Dey, Sanskriti Kumar, Sachin Santoso, Adrian Wangsawijaya William, Bianca Tobias Wang, Chih-Yang |
author_facet | Raza, Ahmad Yen, Meng-Chi Anuraga, Gangga Shahzadi, Iram Mazhar, Muhammad Waqar Ta, Hoang Dang Khoa Xuan, Do Thi Minh Dey, Sanskriti Kumar, Sachin Santoso, Adrian Wangsawijaya William, Bianca Tobias Wang, Chih-Yang |
author_sort | Raza, Ahmad |
collection | PubMed |
description | SIMPLE SUMMARY: In this study, we aimed to address the critical need for a prognostic biomarker in the treatment of GBM. Various approaches and treatments have been examined in the recent literature; however, their effectiveness is limited due to the highly invasive, heterogeneous, and resistant nature of GBM tumors. TCGA, which is a database available online, was used to assess the role of guanine nucleotide-binding protein G(i) subunit alpha 3 (GNAI3), with a focus on analyzing its impact across different WHO grades. The results revealed that GNAI3 is associated with a poor prognosis and is involved in significantly important pathways, such as macrophage maturation and cytoskeleton arrangements. These findings suggest that GNAI3 may serve as a valuable prognostic biomarker for the GBM microenvironment and could provide actionable information for the treatment of GBM. ABSTRACT: Glioblastoma multiforme (GBM) is one of the most aggressive cancers with a low overall survival rate. The treatment of GBM is challenging due to the presence of the blood–brain barrier (BBB), which hinders drug delivery. Invasive procedures alone are not effective at completely removing such tumors. Hence, identifying the crucial pathways and biomarkers for the treatment of GBM is of prime importance. We conducted this study to identify the pathways associated with GBM. We used The Cancer Genome Atlas (TCGA) GBM genomic dataset to identify differentially expressed genes (DEGs). We investigated the prognostic values of the guanine nucleotide-binding protein G(i) alpha subunit (GNAI) family of genes in GBM using a Chinese Glioma Genome Atlas (CGGA) dataset. Within this dataset, we observed the association in the tumor microenvironment between the gene expression of GNAI subunit 3 (GNAI3) and a poor prognosis. MetaCore and gene ontology (GO) analyses were conducted to explore the role of GNAI3 in co-expressed genes and associated signaling pathways using a transcript analysis. Notable pathways included “Cytoskeleton remodeling regulation of actin cytoskeleton organization by the kinase effectors of Rho GTPases” and “Immune response B cell antigen receptor (BCR) pathway”. A single-cell analysis was used to assess GNAI3 expression in GBM. The results demonstrated that GNAI family genes, specifically GNAI3, were significantly associated with carcinogenesis and malignancy in GBM patients. Our findings suggest that the GNAI3 gene holds potential as a prognostic biomarker for GBM. |
format | Online Article Text |
id | pubmed-10605456 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-106054562023-10-28 Comparative Analysis of the GNAI Family Genes in Glioblastoma through Transcriptomics and Single-Cell Technologies Raza, Ahmad Yen, Meng-Chi Anuraga, Gangga Shahzadi, Iram Mazhar, Muhammad Waqar Ta, Hoang Dang Khoa Xuan, Do Thi Minh Dey, Sanskriti Kumar, Sachin Santoso, Adrian Wangsawijaya William, Bianca Tobias Wang, Chih-Yang Cancers (Basel) Article SIMPLE SUMMARY: In this study, we aimed to address the critical need for a prognostic biomarker in the treatment of GBM. Various approaches and treatments have been examined in the recent literature; however, their effectiveness is limited due to the highly invasive, heterogeneous, and resistant nature of GBM tumors. TCGA, which is a database available online, was used to assess the role of guanine nucleotide-binding protein G(i) subunit alpha 3 (GNAI3), with a focus on analyzing its impact across different WHO grades. The results revealed that GNAI3 is associated with a poor prognosis and is involved in significantly important pathways, such as macrophage maturation and cytoskeleton arrangements. These findings suggest that GNAI3 may serve as a valuable prognostic biomarker for the GBM microenvironment and could provide actionable information for the treatment of GBM. ABSTRACT: Glioblastoma multiforme (GBM) is one of the most aggressive cancers with a low overall survival rate. The treatment of GBM is challenging due to the presence of the blood–brain barrier (BBB), which hinders drug delivery. Invasive procedures alone are not effective at completely removing such tumors. Hence, identifying the crucial pathways and biomarkers for the treatment of GBM is of prime importance. We conducted this study to identify the pathways associated with GBM. We used The Cancer Genome Atlas (TCGA) GBM genomic dataset to identify differentially expressed genes (DEGs). We investigated the prognostic values of the guanine nucleotide-binding protein G(i) alpha subunit (GNAI) family of genes in GBM using a Chinese Glioma Genome Atlas (CGGA) dataset. Within this dataset, we observed the association in the tumor microenvironment between the gene expression of GNAI subunit 3 (GNAI3) and a poor prognosis. MetaCore and gene ontology (GO) analyses were conducted to explore the role of GNAI3 in co-expressed genes and associated signaling pathways using a transcript analysis. Notable pathways included “Cytoskeleton remodeling regulation of actin cytoskeleton organization by the kinase effectors of Rho GTPases” and “Immune response B cell antigen receptor (BCR) pathway”. A single-cell analysis was used to assess GNAI3 expression in GBM. The results demonstrated that GNAI family genes, specifically GNAI3, were significantly associated with carcinogenesis and malignancy in GBM patients. Our findings suggest that the GNAI3 gene holds potential as a prognostic biomarker for GBM. MDPI 2023-10-23 /pmc/articles/PMC10605456/ /pubmed/37894479 http://dx.doi.org/10.3390/cancers15205112 Text en © 2023 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 Raza, Ahmad Yen, Meng-Chi Anuraga, Gangga Shahzadi, Iram Mazhar, Muhammad Waqar Ta, Hoang Dang Khoa Xuan, Do Thi Minh Dey, Sanskriti Kumar, Sachin Santoso, Adrian Wangsawijaya William, Bianca Tobias Wang, Chih-Yang Comparative Analysis of the GNAI Family Genes in Glioblastoma through Transcriptomics and Single-Cell Technologies |
title | Comparative Analysis of the GNAI Family Genes in Glioblastoma through Transcriptomics and Single-Cell Technologies |
title_full | Comparative Analysis of the GNAI Family Genes in Glioblastoma through Transcriptomics and Single-Cell Technologies |
title_fullStr | Comparative Analysis of the GNAI Family Genes in Glioblastoma through Transcriptomics and Single-Cell Technologies |
title_full_unstemmed | Comparative Analysis of the GNAI Family Genes in Glioblastoma through Transcriptomics and Single-Cell Technologies |
title_short | Comparative Analysis of the GNAI Family Genes in Glioblastoma through Transcriptomics and Single-Cell Technologies |
title_sort | comparative analysis of the gnai family genes in glioblastoma through transcriptomics and single-cell technologies |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10605456/ https://www.ncbi.nlm.nih.gov/pubmed/37894479 http://dx.doi.org/10.3390/cancers15205112 |
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