A novel cuproptosis-related LncRNA signature: Prognostic and therapeutic value for acute myeloid leukemia - Li, Pian; Li, Junjun; Wen, Feng; Cao, Yixiong; Luo, Zeyu; Zuo, Juan; Wu, Fei; Li, Zhiqin; Li, Wenlu; Wang, Fujue (Frontiers in Oncology, 2022)
Background: Cuproptosis is a type of programmed cell death that is involved in multiple physiological and pathological processes, including cancer. We constructed a prognostic cuproptosis-related long non-coding RNA (lncRNA) signature for acute myeloid leukemia (AML). Methods: RNA-seq and clinical data for AML patients were acquired from The Cancer Genome Atlas (TCGA) database. The cuproptosis-related prognostic lncRNAs were identified by co-expression and univariate Cox regression analysis. The least absolute shrinkage and selection operator (LASSO) was performed to construct a cuproptosis-related lncRNA signature, after which the AML patients were classified into two risk groups based on the risk model. Kaplan-Meier, ROC, univariate and multivariate Cox regression, nomogram, and calibration curves analyses were used to evaluate the prognostic value of the model. Then, expression levels of the lncRNAs in the signature were investigated in AML samples by quantitative polymerase chain reaction (qPCR). KEGG functional analysis, single-sample GSEA (ssGSEA), and the ESTIMATE algorithm were used to analyze the mechanisms and immune status between the different risk groups. The sensitivities for potential therapeutic drugs for AML were also investigated. Results: Five hundred and three lncRNAs related to 19 CRGs in AML samples from the TCGA database were obtained, and 21 differentially expressed lncRNAs were identified based on the 2-year overall survival (OS) outcomes of AML patients. A 4-cuproptosis-related lncRNA signature for survival was constructed by LASSO Cox regression. High-risk AML patients exhibited worse outcomes. Univariate and multivariate Cox regression analyses demonstrated the independent prognostic value of the model. ROC, nomogram, and calibration curves analyses revealed the predictive power of the signature. KEGG pathway and ssGSEA analyses showed that the high-risk group had higher immune activities. Lastly, AML patients from different risk groups showed differential responses to various agents. Conclusion: A cuproptosis-related lncRNA signature was established to predict the prognosis and inform on potential therapeutic strategies for AML patients. Keywords: Cuproptosis-related Genes (CRGs), Long non-coding RNAs (LncRNAs), Acute myeloid leukemia (AML), Prognostic value, Chemotherapy and immunotherapy