51. Identification of a copper metabolism‐related gene signature for predicting prognosis and immune response in glioma
- Author
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Ling Li, Wenyuan Leng, Junying Chen, Shaoying Li, Bingxi Lei, Huasong Zhang, and Huiying Zhao
- Subjects
bioinformatics ,cancer immunity ,copper metabolism ,diffuse glioma ,prognosis ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Abstract Background Gliomas 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. Methods We 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. Results The 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
- Published
- 2023
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