Comprehensive analysis of copper-metabolism-related genes about prognosis and immune microenvironment in osteosarcoma.

Autor: Lin Z; Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China., He Y; Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China., Wu Z; Department of Orthopaedics, The Second Xiangya Hospital, Central South University, Changsha, 410011, Hunan, People's Republic of China., Yuan Y; Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China., Li X; Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China., Luo W; Department of Orthopaedics, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, People's Republic of China. luowei0928@126.com.; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, China. luowei0928@126.com.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2023 Sep 12; Vol. 13 (1), pp. 15059. Date of Electronic Publication: 2023 Sep 12.
DOI: 10.1038/s41598-023-42053-w
Abstrakt: 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.
(© 2023. Springer Nature Limited.)
Databáze: MEDLINE
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