ArticleScientific reports2023
Comprehensive analysis of copper-metabolism-related genes about prognosis and immune microenvironment in osteosarcoma.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.
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- Identification and validation of prognostic genes associated with mitochondrial nuclear genes in gastric cancer.Clinical and experimental medicine · 2025Article
- Harnessing multi‑omics to revolutionize understanding and management of osteosarcoma: A pathway to precision medicine (Review).International journal of molecular medicine · 2025Review
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- Development of Novel PANoptosis-Related Gene Signatures to Predict the Prognosis of Patients With Stomach Adenocarcinoma.Human mutation · 2025Article
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- Prognostic Value of Centrosome Replication-Related Genes in Prostate Cancer Based on Transcriptomic and Mendelian Randomization.American journal of men's healthArticle
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite being significant in various diseases, including cancers, the impact of copper metabolism on osteosarcoma (OS) remains largely unexplored. This study aimed to use bioinformatics analyses to identify a reliable copper metabolism signature that could improve OS patient prognosis prediction, immune landscape understanding, and drug sensitivity. Through nonnegative matrix factorization (NMF) clustering, we revealed distinct prognosis-associated clusters of OS patients based on copper metabolism-related genes (CMRGs), showing differential gene expression linked to immune processes. The risk model, comprising 13 prognostic CMRGs, was established using least absolute shrinkage and selection operator (LASSO) Cox regression, closely associated with the OS microenvironment's immune situation and drug sensitivity. Furthermore, we developed an integrated nomogram, combining the risk score and clinical traits to quantitatively predict OS patient prognosis. The calibration plot, timeROC, and timeROC analyses demonstrated its predictable accuracy and clinical usefulness. Finally, we identified three independent prognostic signatures for OS patients: COX11, AP1B1, and ABCB6. This study confirmed the involvement of CMRGs in OS patient prognosis, immune processes, and drug sensitivity, suggesting their potential as promising prognostic signatures and therapeutic targets for OS.
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