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Comprehensive analysis of cuproptosis-associated LncRNAs predictive value and related CeRNA network in acute myeloid leukemia
BACKGROUND: Acute myeloid leukemia (AML) is characterized by a high recurrence and mortality rate. Cuproptosis is involved in cell death regulation in in a variety of solid tumors. Long non-coding RNAs that regulate cuproptosis genes in the pathogenesis of acute leukemia have yet to be explored. MET...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10696213/ http://dx.doi.org/10.1016/j.heliyon.2023.e22532 |
Sumario: | BACKGROUND: Acute myeloid leukemia (AML) is characterized by a high recurrence and mortality rate. Cuproptosis is involved in cell death regulation in in a variety of solid tumors. Long non-coding RNAs that regulate cuproptosis genes in the pathogenesis of acute leukemia have yet to be explored. METHODS: First, cuproptosis genes with distinct expression levels were discovered by contrasting AML with normal samples from the TCGA and GTEx cohorts. Pearson correlation and univariate Cox-regression analysis were performed to identify cuproptosis-associated lncRNAs with significant prognostic values. Then the least absolute shrinkage and selection operator (LASSO) Cox regression was utilized to establish a multi-gene signature to predict AML prognosis. Next, Kaplan-Meier estimator, receiver operating characteristic curve, and a nomogram were performed to evaluate the predictive capacity of the risk signature. Functional enrichment analyses were employed to assess their function. Moreover, qRT-PCR testing of lncRNA expression in AML samples was conducted. The competing endogenous RNA (ceRNA) network was constructed to find the target genes. RESULTS: A risk model based on the signature of three cuproptosis-associated lncRNAs was developed. The results showed that the model possessed excellent prognostic potential. The nomogram raised the accuracy in predicting AML survival. In addition, functional enrichment analyses demonstrated an enrichment of inflammatory and immune-related pathways. Moreover, correlations between the risk signature and clinicopathological variables, tumor mutational burden, RNA stemness score, immune profile, and drug sensitivity were observed. Furthermore, we discovered that TRAF3IP2-AS1 may function as a ceRNA to regulate cuproptosis and ferroptosis gene expression. CONCLUSION: The risk signature established in this study could serve as a reliable biosignature for AML prognosis. And the findings presented here may facilitate research on cuproptosis in AML. |
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