The study reveals that ferroptosis and cuproptosis risk model predicts clinical outcomes in gliomas, suggesting immune checkpoint involvement in therapy.
Background Ferroptosis and Cuproptosis are newly defined forms of cell death. Despite distinct mechanisms, both involve metabolic processes in the TCA cycle and downstream pathways, crucial for anticancer immunity. Methods We evaluated Iron (Fe) and Copper-induced cell death in lower-grade gliomas (LGG) using The Cancer Genome Atlas (TCGA) data by developing a metal-based ferroptosis and cuproptosis genes score (MBFCGs) risk model. Lasso regression and survival analyses assessed MBFCGs’ significance. An MBFCGs-based nomogram was created and its predictive performance verified. Signaling pathways, immune checkpoints, chemokines, and therapeutic response indicators were quantified using R/oncoPredict and Tidepay. Immunohistochemistry (IHC) examined candidate gene expression. Results The MBFCGs risk model, based on BACH1, CDCA3, and TIMP1, predicts LGG prognosis. High MBFCGs were associated with poor clinical outcomes. Functional enrichment analysis showed upregulation in neurotransmitter receptor regulation, KRAS signaling, and hedgehog signaling pathways in the high-risk group. High-risk LGG patients exhibited higher tumor mutation burden (TMB) and lower IDH1 mutation incidence. These patients also had increased stromal and immune scores, with elevated levels of T helper cells, B cells, macrophages, neutrophils, and NK cells. Immune checkpoint analysis indicated higher expression of CD274, PDCD1, and other inhibitory molecules, suggesting potential for targeted cancer immunotherapy. Conclusion The MBFCGs risk model is a promising prognostic tool for LGG, offering insights into underlying mechanisms and new directions for immunotherapy strategies. Assessment of MBFCGs for individual LGG patients may provide clues for developing new immunotherapy strategies.
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Saddozai et al. (2025) studied this question.
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