Background: Multiple myeloma (MM) is a highly heterogeneous disease. Cuproptosis is a novel mode of death that is closely associated with several diseases, such as hepatocellular carcinoma. However, its role in MM is unknown.
Methods: MM transcriptomic and clinical data were obtained from UCSC Xena and gene expression omnibus (GEO) databases. Following MM samples were divided into different subtypes based on the cuproptosis genes, the differentially expressed genes (DEGs) among different subtypes, namely, candidate cuproptosis related genes were analyzed by univariate Cox and least absolute shrinkage and selection operator (LASSO) regression to construct a cuproptosis-related risk model. After the independent prognostic analysis was performed, a nomogram was constructed. Finally, Functional enrichment analysis and immune infiltration analysis were performed in the high- and low-risk groups, potential therapeutic agents were then predicted.
Results: The 784 MM samples in UCSC Xena cohorts were divided into three different subtypes, and 4 out of 346 candidate cuproptosis related genes, namely CDKN2A, BCL3, KCNA3 and TTC14 were used to construct a risk model. Risk score was considered a reliable independent prognostic factor for MM patients. It was investigated that the pathway of cell cycle was significantly enriched in the high-risk group. In addition, immune score, ESTIMATE score and cytolytic activity were significantly different between different risk groups, as well as 13 immune cells such as memory B cells. Nine drugs were predicted in our study.
Conclusion: A cuproptosis-related prognostic model was constructed, which may have a potential guiding role in the treatment of MM.
Keywords: Multiple myeloma; consensus clustering; cuproptosis; immune infiltration; prognosis.