Antioxidant network-based signatures cluster glioblastoma into distinct redox-resistant phenotypes

Front Immunol. 2024 Apr 18:15:1342977. doi: 10.3389/fimmu.2024.1342977. eCollection 2024.

Abstract

Introduction: Aberrant 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.

Methods: In 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.

Results: We 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.

Conclusion: In 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.

Keywords: GBM; antioxidant phenotype; bioinformatics; canonical GBM classification; oxidative stress; prognosis; signatures; transcription factors.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antioxidants* / metabolism
  • Brain Neoplasms* / genetics
  • Brain Neoplasms* / metabolism
  • Brain Neoplasms* / pathology
  • Computational Biology / methods
  • Gene Expression Profiling
  • Gene Expression Regulation, Neoplastic*
  • Gene Regulatory Networks*
  • Glioblastoma* / genetics
  • Glioblastoma* / metabolism
  • Glioblastoma* / pathology
  • Humans
  • Oxidation-Reduction*
  • Oxidative Stress
  • Phenotype*
  • Prognosis
  • Reactive Oxygen Species / metabolism
  • Transcriptome

Substances

  • Antioxidants
  • Reactive Oxygen Species

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. Research project funded by Kom op tegen Kanker (Stand up to Cancer). PA, SV, and FS are supported by the KotK grant. PA is supported by grants from the Flemish Research Foundation (FWO-Vlaanderen; G076617N, G049817N, G070115N), the EOS DECODE consortium N° 30837538, the EOS MetaNiche consortium N° 40007532, Stichting tegen Kanker (FAF-F/2018/1252) and the iBOF/21/053 ATLANTIS consortium.