Project description:Acute myeloid leukemia (AML) carrying MLL rearrangements. We applied WGBS and the informME analysis pipeline to investigate the role of DNA methylation stochasticity in MLL-rearranged AML.
Project description:The Illumina Human Methylation EPIC array was used to assess methylation status at initial diagnosis in bone marrow or peripheral blood specimens from children with acute myeloid leukemia.
Project description:We hypothesized that DNA methylation distributes into specific patterns in cancer cells, which reflect critical biological differences. We therefore examined the methylation profiles of 344 patients with acute myeloid leukemia (AML). Clustering of these patients by methylation data segregated patients into 16 groups. Five of these groups defined new AML subtypes that shared no other known feature. In addition, DNA methylation profiles segregated patients with CEBPA aberrations from other subtypes of leukemia, defined four epigenetically distinct forms of AML with NPM1 mutations, and showed that established AML1-ETO, CBFb-MYH11 and PML-RARA leukemia entities are associated with specific methylation profiles. We report a 15-gene methylation classifier predictive of overall survival in an independent patient cohort (p<0.001, adjusted for known covariates). Keywords: DNA methylation profiling DNA methylation profiling of a cohort of 344 AML patients from Erasmus Medical Center and enrolled in clinical trials from the Dutch-German cooperative group HOVON. Additionally, a control group consisting of 8 CD34+ bone marrow samples from healthy donors was also studied.
Project description:Acute myeloid leukemia (AML) is a molecularly complex disease characterized by heterogeneous tumor genetic profiles and involving numerous pathogenic mechanisms and pathways. Integration of molecular data types across multiple patient cohorts may advance current genetic approaches for improved sub-classification and understanding of the biology of the disease. Here we analyzed genome-wide DNA methylation in 649 AML patients using Illumina arrays and identified a configuration of 13 subtypes (termed ‘epitypes’) using unbiased clustering. Integration of genetic data revealed that most epitypes were associated with a certain recurrent mutation (or combination) in a majority of patients, yet other epitypes were largely independent. Epitypes demonstrated developmental blockage at discrete stages of myeloid differentiation, revealing epitypes that retain arrested hematopoietic stem cell-like phenotypes. Detailed analyses of DNA methylation patterns identified unique patterns of aberrant hyper- and hypomethylation among epitypes, with variable involvement of transcription factors influencing promoter, enhancer and repressed regions. Patients in epitypes with stem cell-like methylation features showed inferior overall survival along with upregulated stem cell gene expression signatures. We further identified a DNA methylation signature involving STAT motifs associated with FLT3-ITD mutations. Finally, DNA methylation signatures were remarkably stable at relapse for the large majority of patients, and rare epitype switching accompanied loss of the dominant epitype mutations and reversion to stem cell-like methylation patterns. These results demonstrate that DNA methylation-based classification integrates important molecular features of AML to reveal the diverse pathogenic and biological aspects of the disease.
Project description:Cytogenetically normal acute myeloid leukemia (CN-AML) comprise between forty and fifty percent of all adult acute myeloid leukemia (AML) cases. In this clinically diverse group molecular aberrations such as FLT3ITD, NPM1 and CEBPA mutations recently have added to the prognostic accuracy. Aberrant DNA methylation is a hallmark of cancer including AML. We investigated in total 89 CN-AML samples in a test and a validation cohort for genome-wide promoter DNA methylation with Illumina Methylation Bead arrays and compared them to normal myeloid precursors and global gene expression. IDH and NPM1 mutations were associated with different methylation patterns (p=0.0004 and 0.04, respectively). Genome-wide methylation levels were elevated in IDH mutated samples (p=0.006). We observed a negative impact of DNA methylation on transcription. Genes targeted by Polycomb group (PcG) proteins and genes associated with bivalent histone marks in stem cells showed increased aberrant methylation in AML (p<0.0001). Furthermore, high methylation levels of PcG target genes were independently associated with better progression free (OR 0.47, p=0.01) and overall survival (OR 0.36, p=0.001). In summary, genome wide methylation patterns show preferential methylation of PcG targets with prognostic impact in CN-AML. Genome wide methylation pattern study of cytogenetically normal AML
Project description:Label-free quantitation dataset from 44 representative Acute Myeloid Leukemia (AML) patients from the LAML TCGA dataset, and 6 healthy bone marrow derived controls including 3 lineage-depleted and 3 CD34+ selected bone marrows.
Project description:Acute myeloid leukemia (AML) is a clonal hematopoietic malignancy, characterized by expansion of immature leukemic blasts in the bone marrow. In AML, specific tyrosine kinases have been implicated in leukemogenesis, and are associated with poor treatment outcome. However, targeted therapy using kinase inhibitors (KIs) has had limited success, and may be improved by proper patient selection. We performed phosphotyrosine (pY) based, label-free phosphoproteomics to identify hyperphosphorylated, active kinases in two FLT3+ AML Pt samples.
Project description:A deep-scale proteome and phosphoproteome database from 44 representative Acute Myeloid Leukemia (AML) patients from the LAML TCGA dataset, and 6 healthy bone marrow derived controls including 3 lineage-depleted and 3 CD34+ selected bone marrows.