Identification and validation of a metabolism-related gene signature for predicting the prognosis of paediatric medulloblastoma

Medulloblastoma (MB) is a malignant brain tumour that is highly common in children and has a tendency to spread to the brain and spinal cord. MB is thought to be a metabolically driven brain tumour. Understanding tumour cell metabolic patterns and characteristics can provide a promising foundation f...

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Veröffentlicht in:Scientific reports 2024-03, Vol.14 (1), p.7540-7540, Article 7540
Hauptverfasser: Su, Jun, Xie, Qin, Xie, Longlong
Format: Artikel
Sprache:eng
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Zusammenfassung:Medulloblastoma (MB) is a malignant brain tumour that is highly common in children and has a tendency to spread to the brain and spinal cord. MB is thought to be a metabolically driven brain tumour. Understanding tumour cell metabolic patterns and characteristics can provide a promising foundation for understanding MB pathogenesis and developing treatments. Here, by analysing RNA-seq data of MB samples from the Gene Expression Omnibus (GEO) database, 12 differentially expressed metabolic-related genes (DE-MRGs) were chosen for the construction of a predictive risk score model for MB. This model demonstrated outstanding accuracy in predicting the outcomes of MB patients and served as a standalone predictor. An evaluation of functional enrichment revealed that the risk score showed enrichment in pathways related to cancer promotion and the immune response. In addition, a high risk score was an independent poor prognostic factor for MB in patients with different ages, sexes, metastasis stages and subgroups (SHH and Group 4). Consistently, the metabolic enzyme ornithine decarboxylase (ODC1) was upregulated in MB patients with poor survival time. Inhibition of ODC1 in primary and metastatic MB cell lines decreased cell proliferation, migration and invasion but increased immune infiltration. This study could aid in identifying metabolic targets for MB as well as optimizing risk stratification systems and individual treatment plans for MB patients via the use of a metabolism-related gene prognostic risk score signature.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-57549-2