Cuproptosis-related gene-based characterization and diagnostic biomarker screening in gliomas

Abstract

Aim: Glioma, the most common primary brain tumor, is known for its poor prognosis, limited treatment success, and high level of aggressiveness. Although cuproptosis-related genes have been linked to outcomes in other cancers, their role in glioma is still not well understood.

Methods: By leveraging the Cancer Genome Atlas (TCGA) and additional databases, we conducted Cox regression and Kaplan-Meier analysis to determine the predictive importance of cuproptosis-related genes in individuals with glioma. By utilizing data from Gene Expression Omnibus (GEO) and other relevant databases, we examined how the expression of cuproptosis-associated genes correlates with immune cell infiltration, immunological checkpoint status, pathological stage, and histological grade. Additionally, we analyzed the connection between gene expression linked to cuproptosis and the prognosis in glioma patients.

Results: Our newly developed cuproptosis-based glioma predictive model demonstrated promising prediction performance. Additionally, we identified glutaminase (GLS) in glioblastoma as a potential novel diagnostic indicator for glioma patients.

Conclusion: GLS holds the potential to provide novel perspectives on cancer management and serve as a valuable diagnostic predictor for glioma patients.

Keywords

Cuproptosis-related gene, diagnostic, glioma, GLS / biomarker

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