Dataset Information

Differential Analysis of Genetic, Epigenetic, and Cytogenetic Abnormalities in AML.

ABSTRACT: Acute myeloid leukemia (AML) is a haematological malignancy characterized by the excessive proliferation of immature myeloid cells coupled with impaired differentiation. Many AML cases have been reported without any known cytogenetic abnormalities and carry no mutation in known AML-associated driver genes. In this study, 200 AML cases were selected from a publicly available cohort and differentially analyzed for genetic, epigenetic, and cytogenetic abnormalities. Three genes (FLT3, DNMT3A, and NPMc) are found to be predominantly mutated. We identified several aberrations to be associated with genome-wide methylation changes. These include Del (5q), T (15; 17), and NPMc mutations. Four aberrations-Del (5q), T (15; 17), T (9; 22), and T (9; 11)-are significantly associated with patient survival. Del (5q)-positive patients have an average survival of less than 1 year, whereas T (15; 17)-positive patients have a significantly better prognosis. Combining the methylation and mutation data reveals three distinct patient groups and four clusters of genes. We speculate that combined signatures have the better potential to be used for subclassification of AML, complementing cytogenetic signatures. A larger sample cohort and further investigation of the effects observed in this study are required to enable the clinical application of our patient classification aided by DNA methylation.

SUBMITTER: Islam M

PROVIDER: S-EPMC5496127 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Differential Analysis of Genetic, Epigenetic, and Cytogenetic Abnormalities in AML.

Islam Mirazul M Mohamed Zahurin Z Assenov Yassen Y

International journal of genomics 20170620

Acute myeloid leukemia (AML) is a haematological malignancy characterized by the excessive proliferation of immature myeloid cells coupled with impaired differentiation. Many AML cases have been reported without any known cytogenetic abnormalities and carry no mutation in known AML-associated driver genes. In this study, 200 AML cases were selected from a publicly available cohort and differentially analyzed for genetic, epigenetic, and cytogenetic abnormalities. Three genes (FLT3, DNMT3A, and N ...[more]

PMID: 28713819

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Project description:BackgroundThe heterogenous cytogenetic and molecular variations were harbored by AML patients, some of which are related with AML pathogenesis and clinical outcomes. We aimed to uncover the intrinsic expression profiles correlating with prognostic genetic abnormalities by WGCNA.MethodsWe downloaded the clinical and expression dataset from BeatAML, TCGA and GEO database. Using R (version 4.0.2) and 'WGCNA' package, the co-expression modules correlating with the ELN2017 prognostic markers were identified (R2 ≥ 0.4, p < 0.01). ORA detected the enriched pathways for the key co-expression modules. The patients in TCGA cohort were randomly assigned into the training set (50%) and testing set (50%). The LASSO penalized regression analysis was employed to build the prediction model, fitting OS to the expression level of hub genes by 'glmnet' package. Then the testing and 2 independent validation sets (GSE12417 and GSE37642) were used to validate the diagnostic utility and accuracy of the model.ResultsA total of 37 gene co-expression modules and 973 hub genes were identified for the BeatAML cohort. We found that 3 modules were significantly correlated with genetic markers (the 'lightyellow' module for NPM1 mutation, the 'saddlebrown' module for RUNX1 mutation, the 'lightgreen' module for TP53 mutation). ORA revealed that the 'lightyellow' module was mainly enriched in DNA-binding transcription factor activity and activation of HOX genes. The 'saddlebrown' module was enriched in immune response process. And the 'lightgreen' module was predominantly enriched in mitosis cell cycle process. The LASSO- regression analysis identified 6 genes (NFKB2, NEK9, HOXA7, APRC5L, FAM30A and LOC105371592) with non-zero coefficients. The risk score generated from the 6-gene model, was associated with ELN2017 risk stratification, relapsed disease, and prior MDS history. The 5-year AUC for the model was 0.822 and 0.824 in the training and testing sets, respectively. Moreover, the diagnostic utility of the model was robust when it was employed in 2 validation sets (5-year AUC 0.743-0.79).ConclusionsWe established the co-expression network signature correlated with the ELN2017 recommended prognostic genetic abnormalities in AML. The 6-gene prediction model for AML survival was developed and validated by multiple datasets.

Dataset Information

Differential Analysis of Genetic, Epigenetic, and Cytogenetic Abnormalities in AML.

Publications

Differential Analysis of Genetic, Epigenetic, and Cytogenetic Abnormalities in AML.

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