ArticleTranslational cancer research2024
Expression of copper metabolism-related genes is associated with the tumor immune microenvironment and predicts the prognosis of hepatocellular carcinoma.
Article in Translational cancer research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Hydrated proton complexes supplementation for tumor microenvironment reprogramming: a bioenergetic strategy targeting the Warburg effect and mitochondrial dysfunction.Frontiers in oncology · 2025Pooled it
- Deep learning-based fusion of nuclear segmentation features for microsatellite instability and tumor mutational burden prediction in digestive tract cancers: a multicenter validation study.Briefings in bioinformatics · 2025Article
- Differences in Tissue Copper and Zinc Content Between Normal Livers and Those with Cirrhosis with or Without Hepatocellular Carcinoma.International journal of molecular sciences · 2025Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Copper metabolism dysfunction has been found to be associated with the progression of various malignant tumors. The aim of this study is to explore the prognostic value of copper metabolism-related genes (CMRGs) in hepatocellular carcinoma (HCC) and their impact on the immune microenvironment. Methods: We identified differentially expressed CMRGs in cancer and adjacent samples of HCC from The Cancer Genome Atlas (TCGA). Consensus clustering was performed to distinguish subgroups, and TIMER and CIBERSORT were applied to analyze the tumor immune microenvironment (TIME). We used the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis to establish a prognostic risk model for CMRGs. Gene set enrichment analysis (GSEA) was performed to elucidate potential signaling mechanisms associated with the risk group, as well as to determine and compare the tumor mutation burden (TMB), immune cell infiltration levels, and immune checkpoint of the identified risk groups. Results: Two subgroups with significantly different survival rates were identified, with a better prognosis associated with high immune scores, high abundance of immune-infiltrating cells, and a relatively higher immune status. A prognostic risk model based on five CMRGs was constructed, which showed significant prognostic value. When combined with clinical feature column charts, this model can predict the prognosis of patients with HCC. Functional enrichment analysis showed that the low-risk group was enriched in a large number of metabolic pathways, while the high and low-risk groups exhibited different TMB and differential expression of immune checkpoint genes. The established model was validated in an independent International Cancer Genome Consortium (ICGC) dataset. Conclusions: The results indicate that the expression of CMRGs is associated with the prognosis of HCC and the tumor microenvironment, and can serve as a predictive indicator for evaluating the prognosis of HCC.
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