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Cuproptosis-related lncRNAs forecast the prognosis of acute myeloid leukemia
BACKGROUND: Acute myeloid leukemia (AML) is a highly heterogeneous cluster of hematologic malignancies. Leukemic stem cells (LSCs) are one of the culprits for the persistence and relapse of AML. The discovery of copper-induced cell death, namely cuproptosis, gives bright insights into the treatment...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10248575/ https://www.ncbi.nlm.nih.gov/pubmed/37304546 http://dx.doi.org/10.21037/tcr-22-2526 |
Sumario: | BACKGROUND: Acute myeloid leukemia (AML) is a highly heterogeneous cluster of hematologic malignancies. Leukemic stem cells (LSCs) are one of the culprits for the persistence and relapse of AML. The discovery of copper-induced cell death, namely cuproptosis, gives bright insights into the treatment of AML. Analogous to copper ions, long non-coding RNAs (lncRNAs) are not bystanders for AML progression, especially for LSC physiology. Uncovering the involvement of cuproptosis-related lncRNAs in AML will benefit clinical management. METHODS: Detection of prognostic relevant cuproptosis-related lncRNAs are carried out by Pearson correlation analysis and univariate Cox analysis with RNA sequencing data of The Cancer Genome Atlas-Acute Myeloid Leukemia (TCGA-LAML) cohort. After the least absolute shrinkage and selection operator (LASSO) regression and the subsequent multivariate Cox analysis, a cuproptosis-related risk score (CuRS) system was derived to weigh the risk of AML patients. Thereafter, AML patients were classified into two groups by their risk property which was validated with principal component analysis (PCA), risk curves, Kaplan-Meier survival analysis, the combined receiver operating characteristic (ROC) curves, and nomogram. Variations in biological pathways and divergences in immune infiltration and immune-related processes between groups were resolved by GSEA and CIBERSORT algorism, respectively. Response to chemotherapies were scrutinized as well. The expression profiles of the candidate lncRNAs were examined by real-time quantitative polymerase chain reaction (RT-qPCR) and the specific mechanisms of lncRNA FAM30A were determined by transcriptomic analysis. RESULTS: We fabricated an efficient prognostic signature named CuRS incorporating 4 lncRNAs (TRAF3IP2-AS1, NBR2, TP53TG1, and FAM30A) relevant to immune environment and chemotherapy responsiveness. The relevance of lncRNA FAM30A with proliferation, migration ability, Daunorubicin resistance and its reciprocal action with AUF1 were demonstrated in an LSC cell line. Transcriptomic analysis suggested correlations between FAM30A and T cell differentiation and signaling, intercellular junction genes. CONCLUSIONS: The prognostic signature CuRS can guide prognostic stratification and personalized AML therapy. Analysis of FAM30A offers a foundation for investigating LSC-targeted therapies. |
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