ArticleCancer medicine2023
Identification of a copper metabolism-related gene signature for predicting prognosis and immune response in glioma.
Article in Cancer medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed, 26 citations in OpenAlex.
- Development of a fatty acid metabolism (FAM)-related gene signature for prognosis prediction and personalized therapy in lower grade gliomas.Translational cancer research · 2025Article
- A novel 5-protein kinase risk signature for predicting glioma prognosis and immunotherapy responsiveness.Scientific reports · 2025Article
- A novel golgi related genes based correlation prognostic index can better predict the prognosis of glioma and responses to immunotherapy.Discover oncology · 2025Article
- Review
- To explore the potential of LOXL2 as a biomarker in glioma and construct a genomic integrated clinical prognostic model.Frontiers in oncology · 2025Article
- Identification of TACSTD2 as novel therapeutic targets for cisplatin-induced acute kidney injury by multi-omics data integration.Human genetics · 2024Article
- The interplay between metal ions and immune cells in glioma: pathways to immune escape.Discover oncology · 2024Review
- Machine-learning developed an iron, copper, and sulfur-metabolism associated signature predicts lung adenocarcinoma prognosis and therapy response.Respiratory research · 2024Article
- Article
- Systematic analysis based on the cuproptosis-related genes identifies ferredoxin 1 as an immune regulator and therapeutic target for glioblastoma.BMC cancer · 2023Article
- Clinical and molecular analysis of cilia-associated gene signature for prognostic prediction in glioma.Journal of cancer research and clinical oncology · 2023Article
- Cuproptosis-related gene SLC31A1 expression correlates with the prognosis and tumor immune microenvironment in glioma.Functional & integrative genomics · 2023Article
- Identification of a copper metabolism-related gene signature for predicting prognosis and immune response in glioma.Cancer medicine · 2023Article
- Cuproplasia-related gene signature: Prognostic insights for glioma therapy.Neuro-oncology advancesArticle
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGliomas are highly refractory intracranial cancers characterized by genetic and transcriptional heterogeneity. However, therapeutic options are limited. In the last years, copper-induced cell death is becoming a prospective treatment strategy for gliomas and other solid tumors, but copper metabolism-related genes associated with cancer development remain unclear.
methodsWe first collected gene expression data from The Cancer Genome Atlas (TCGA) to identify significantly differentially expressed copper metabolism-related genes in gliomas. Using these genes, we performed COX regression and Least Absolute Shrinkage and Selection Operator (LASSO) regression to construct the prognostic model. The prognostic value of the model was further validated by CGGA testing set. Subsequently, functional analyses were carried out, including gene set enrichment analysis (GSEA), immune infiltration analysis, and mutation analysis. Finally, the expression levels of these genes were verified by immunohistochemical analysis.
resultsThe prognostic model consisted of 7 genes: CDK1, LOXL2, LOXL3, NFE2L2, SLC31A1, SUMF1 and FDX1. According to this prognosis model, glioma patients could be split into the high-risk group or low-risk group, and the low-risk group showed significantly better prognostic survival (p < 0.001). Moreover, the high-risk group had higher levels of immune cell infiltration, immune checkpoint genes expression, and higher tumor mutational burden (TMB), which indicates that they might benefit more from immunotherapy. Finally, we confirmed the expression level of FDX1, SUMF1, and SLC31A1 protein as significantly different in glioblastoma, lower-grade glioma, and non-tumor brain tissues by immunohistochemical analysis, and the high expression of FDX1 and SLC31A1 protein was related to poor survival in glioma patients.
conclusionsOur study could contribute to the prognosis prediction and decision-making in patients with gliomas.
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