Abstract
BACKGROUND: Cuprotosis is an emerging form of copper-dependent programmed cell death, while low-grade gliomas (LGGs) represent a common subtype of primary brain tumors. METHODS: Datasets from The Cancer Genome Atlas and TargetScan were utilized to identify cuprotosis-related microRNAs (CRMs). Univariate Cox and Lasso regression analyses identified CRMs linked to prognostic outcomes. Prognostic profiles for patients with LGG were constructed using multivariate Cox regression and validated for risk stratification in the CGGA external validation cohort. The study examined clinical features, mutational status, immune cell infiltration, signaling pathways, and immune checkpoint expression across different risk groups. Functional experiments assessed the biological significance of key model genes. RESULTS: Seven CRMs significantly associated with LGG prognosis were identified. The correlation between the CRM signature and poor prognosis in high-risk LGG cases was validated through Kaplan-Meier survival analysis, yielding a one-year area under the curve (AUC) of 0.849, indicating strong predictive accuracy. Risk scores were linked to 1p/19q co-deletion, IDH mutation, and tumor grade, with the model outperforming traditional clinicopathological criteria. Molecular enrichment analyses, including Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA), revealed significant associations between high-risk subgroups and pathways related to tumorigenesis and immune dysregulation. Increased tumor mutational burden and elevated IC expression were noted in high-risk cohorts. Furthermore, miR-93-5p was validated as a critical gene, with its disruption leading to significant reductions in GBM cell proliferation, migration, and invasion. CONCLUSION: The novel CRM signature enhances the prognostic landscape for patients with LGG, offering a new framework for evaluating immunotherapeutic efficacy.