Antioxidant network-based signatures cluster glioblastoma into distinct redox-resistant phenotypes
IntroductionAberrant reactive oxygen species (ROS) production is one of the hallmarks of cancer. During their growth and dissemination, cancer cells control redox signaling to support protumorigenic pathways. As a consequence, cancer cells become reliant on major antioxidant systems to maintain a b...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-04-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2024.1342977/full |
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| author | Yihan Yang Yihan Yang Yihan Yang Sanket More Sanket More Frederik De Smet Frederik De Smet Steven De Vleeschouwer Steven De Vleeschouwer Steven De Vleeschouwer Patrizia Agostinis Patrizia Agostinis |
| author_facet | Yihan Yang Yihan Yang Yihan Yang Sanket More Sanket More Frederik De Smet Frederik De Smet Steven De Vleeschouwer Steven De Vleeschouwer Steven De Vleeschouwer Patrizia Agostinis Patrizia Agostinis |
| author_sort | Yihan Yang |
| collection | DOAJ |
| description | IntroductionAberrant reactive oxygen species (ROS) production is one of the hallmarks of cancer. During their growth and dissemination, cancer cells control redox signaling to support protumorigenic pathways. As a consequence, cancer cells become reliant on major antioxidant systems to maintain a balanced redox tone, while avoiding excessive oxidative stress and cell death. This concept appears especially relevant in the context of glioblastoma multiforme (GBM), the most aggressive form of brain tumor characterized by significant heterogeneity, which contributes to treatment resistance and tumor recurrence. From this viewpoint, this study aims to investigate whether gene regulatory networks can effectively capture the diverse redox states associated with the primary phenotypes of GBM.MethodsIn this study, we utilized publicly available GBM datasets along with proprietary bulk sequencing data. Employing computational analysis and bioinformatics tools, we stratified GBM based on their antioxidant capacities and evaluated the distinctive functionalities and prognostic values of distinct transcriptional networks in silico.ResultsWe established three distinct transcriptional co-expression networks and signatures (termed clusters C1, C2, and C3) with distinct antioxidant potential in GBM cancer cells. Functional analysis of each cluster revealed that C1 exhibits strong antioxidant properties, C2 is marked with a discrepant inflammatory trait and C3 was identified as the cluster with the weakest antioxidant capacity. Intriguingly, C2 exhibited a strong correlation with the highly aggressive mesenchymal subtype of GBM. Furthermore, this cluster holds substantial prognostic importance: patients with higher gene set variation analysis (GSVA) scores of the C2 signature exhibited adverse outcomes in overall and progression-free survival.ConclusionIn summary, we provide a set of transcriptional signatures that unveil the antioxidant potential of GBM, offering a promising prognostic application and a guide for therapeutic strategies in GBM therapy. |
| first_indexed | 2024-04-24T07:57:02Z |
| format | Article |
| id | doaj.art-51648ebd66524c48826526b1a807c73d |
| institution | Directory Open Access Journal |
| issn | 1664-3224 |
| language | English |
| last_indexed | 2024-04-24T07:57:02Z |
| publishDate | 2024-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj.art-51648ebd66524c48826526b1a807c73d2024-04-18T04:48:36ZengFrontiers Media S.A.Frontiers in Immunology1664-32242024-04-011510.3389/fimmu.2024.13429771342977Antioxidant network-based signatures cluster glioblastoma into distinct redox-resistant phenotypesYihan Yang0Yihan Yang1Yihan Yang2Sanket More3Sanket More4Frederik De Smet5Frederik De Smet6Steven De Vleeschouwer7Steven De Vleeschouwer8Steven De Vleeschouwer9Patrizia Agostinis10Patrizia Agostinis11Research Group Experimental Neurosurgery and Neuroanatomy, Department of Neurosciences, KU Leuven, Leuven, BelgiumLaboratory of Cell Death Research & Therapy, Department of Cellular and Molecular Medicine, KU Leuven, Leuven, BelgiumVlaams Instituut voor Biotechnologie (VIB) Center for Cancer Biology Research, Leuven, BelgiumLaboratory of Cell Death Research & Therapy, Department of Cellular and Molecular Medicine, KU Leuven, Leuven, BelgiumVlaams Instituut voor Biotechnologie (VIB) Center for Cancer Biology Research, Leuven, BelgiumDepartment of Imaging and Pathology, KU Leuven, Leuven, BelgiumLeuven Institute for Single-Cell Omics (LISCO), Leuven, BelgiumResearch Group Experimental Neurosurgery and Neuroanatomy, Department of Neurosciences, KU Leuven, Leuven, BelgiumDepartment of Neurosurgery, University Hospitals Leuven, Leuven, BelgiumLeuven Brain Institute (LBI), KU Leuven, Leuven, BelgiumLaboratory of Cell Death Research & Therapy, Department of Cellular and Molecular Medicine, KU Leuven, Leuven, BelgiumVlaams Instituut voor Biotechnologie (VIB) Center for Cancer Biology Research, Leuven, BelgiumIntroductionAberrant reactive oxygen species (ROS) production is one of the hallmarks of cancer. During their growth and dissemination, cancer cells control redox signaling to support protumorigenic pathways. As a consequence, cancer cells become reliant on major antioxidant systems to maintain a balanced redox tone, while avoiding excessive oxidative stress and cell death. This concept appears especially relevant in the context of glioblastoma multiforme (GBM), the most aggressive form of brain tumor characterized by significant heterogeneity, which contributes to treatment resistance and tumor recurrence. From this viewpoint, this study aims to investigate whether gene regulatory networks can effectively capture the diverse redox states associated with the primary phenotypes of GBM.MethodsIn this study, we utilized publicly available GBM datasets along with proprietary bulk sequencing data. Employing computational analysis and bioinformatics tools, we stratified GBM based on their antioxidant capacities and evaluated the distinctive functionalities and prognostic values of distinct transcriptional networks in silico.ResultsWe established three distinct transcriptional co-expression networks and signatures (termed clusters C1, C2, and C3) with distinct antioxidant potential in GBM cancer cells. Functional analysis of each cluster revealed that C1 exhibits strong antioxidant properties, C2 is marked with a discrepant inflammatory trait and C3 was identified as the cluster with the weakest antioxidant capacity. Intriguingly, C2 exhibited a strong correlation with the highly aggressive mesenchymal subtype of GBM. Furthermore, this cluster holds substantial prognostic importance: patients with higher gene set variation analysis (GSVA) scores of the C2 signature exhibited adverse outcomes in overall and progression-free survival.ConclusionIn summary, we provide a set of transcriptional signatures that unveil the antioxidant potential of GBM, offering a promising prognostic application and a guide for therapeutic strategies in GBM therapy.https://www.frontiersin.org/articles/10.3389/fimmu.2024.1342977/fulloxidative stressGBMbioinformaticsantioxidant phenotypesignaturescanonical GBM classification |
| spellingShingle | Yihan Yang Yihan Yang Yihan Yang Sanket More Sanket More Frederik De Smet Frederik De Smet Steven De Vleeschouwer Steven De Vleeschouwer Steven De Vleeschouwer Patrizia Agostinis Patrizia Agostinis Antioxidant network-based signatures cluster glioblastoma into distinct redox-resistant phenotypes Frontiers in Immunology oxidative stress GBM bioinformatics antioxidant phenotype signatures canonical GBM classification |
| title | Antioxidant network-based signatures cluster glioblastoma into distinct redox-resistant phenotypes |
| title_full | Antioxidant network-based signatures cluster glioblastoma into distinct redox-resistant phenotypes |
| title_fullStr | Antioxidant network-based signatures cluster glioblastoma into distinct redox-resistant phenotypes |
| title_full_unstemmed | Antioxidant network-based signatures cluster glioblastoma into distinct redox-resistant phenotypes |
| title_short | Antioxidant network-based signatures cluster glioblastoma into distinct redox-resistant phenotypes |
| title_sort | antioxidant network based signatures cluster glioblastoma into distinct redox resistant phenotypes |
| topic | oxidative stress GBM bioinformatics antioxidant phenotype signatures canonical GBM classification |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2024.1342977/full |
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