ArticleTranslational cancer research2023
Novel cuproptosis-related lncRNAs can predict the prognosis of patients with multiple myeloma.
Article in Translational cancer research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- RNA-Based Therapeutic Strategies in Multiple Myeloma: From Molecular Targets to Delivery and Clinical Translation.International journal of molecular sciences · 2026Review
- Cuproptosis in lung cancer: a nexus of ncRNA regulation, epigenetics, and tumor microenvironment Remodeling.Clinical and experimental medicine · 2025Review
- Cuproptosis: A Review on Mechanisms, Role in Solid and Hematological Tumors, and Association with Viral Infections.Mediterranean journal of hematology and infectious diseases · 2025Review
- lncRNAs as prognostic markers and therapeutic targets in cuproptosis-mediated cancer.Clinical and experimental medicine · 2024Review
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Cuproptosis-related long-stranded non-coding RNAs (lncRNAs) have several implications for the prognosis of multiple myeloma (MM). This research aimed to construct a prognostic risk model for MM patients and explore the potential signaling pathways in the risk group. Methods: Cuproptosis-related lncRNAs were obtained from the co-expression analysis of cuproptosis-related genes and lncRNAs. Subsequently, twelve cuproptosis-related lncRNAs were selected to construct a prognostic risk model of MM patients by the least absolute shrinkage and selection operator (LASSO) regression. Then, the clinical data of these patients were randomly divided into the training group and the testing group. Next, patients were divided into the low- and high-risk groups according to the median risk score. The Kaplan-Meier survival analysis was performed to clarify the prognostic differences between risk subtypes. Besides, the Cox analysis was conducted to identify whether the risk score can be used as an independent prognostic factor. In addition, the receiver operating characteristic (ROC) curve analysis and the concordance index (C-index) curve analysis were performed to elucidate the value of risk score as a prognostic indicator. Finally, the differential risk analysis and functional enrichment analysis were carried out to identify the potential signaling pathways in the low- and high-risk groups. Results: The results demonstrated that the overall survival (OS) of patients in the high-risk group was shorter than that in the low-risk group. There were significant differences in the expression of genes in MM patients between the high- and low-risk groups. The Gene Ontology (GO) analysis results showed that the differentially expressed risk-related genes (DERGs) were mainly concentrated on the collagen-containing extracellular matrix. According to the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis results, the DERGs may be related to the neuroactive ligand-receptor interaction and mitogen-activated protein kinase (MAPK) signaling pathway, indicating that they may be involved in the progression of tumors. Conclusions: The findings of this study suggest that cuproptosis-related lncRNAs may be effective biomarkers for predicting the prognosis of MM patients, which is anticipated to contribute to the improvement of clinical outcomes.
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