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Series GSE159907 Query DataSets for GSE159907
Status Public on Mar 09, 2021
Title DNA methylation analysis of acute myeloid leukemia (AML)
Organism Homo sapiens
Experiment type Methylation profiling by genome tiling array
Summary 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.
 
Overall design Genomic DNA was extracted from from bone marrow derived Mononuclear cells collectected from 272 patients with AML at diagnosis and a matched relapse sample from 28 patients. Following bisulfite conversion the samples were hybridised to the Infinium methylationEPIC assay following standard protocol. Additional samples are matched diagnosis and relapse samples from an additional 8 patients.
 
Contributor(s) Giacopelli B, Oakes C
Citation(s) 33707228
Submission date Oct 23, 2020
Last update date May 19, 2021
Contact name Christopher OAKES
E-mail(s) christopher.oakes@osumc.edu
Phone 6146859284
Organization name The Ohio State University
Street address 400 W. 12th Avenue, Wiseman Hall, Suite 455
City Columbus
State/province OH
ZIP/Postal code 43210
Country USA
 
Platforms (1)
GPL21145 Infinium MethylationEPIC
Samples (316)
GSM4849759 Beat AML project [09-00705]
GSM4849760 Beat AML project [10-00136]
GSM4849761 Beat AML project [10-00507]
Relations
BioProject PRJNA670857

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE159907_Beta_values.csv.gz 1.1 Gb (ftp)(http) CSV
GSE159907_GSM5134137-GSM5134152_Beta_values.csv.gz 78.4 Mb (ftp)(http) CSV
GSE159907_GSM5134137-GSM5134152_Signal_Intensities.csv.gz 73.8 Mb (ftp)(http) CSV
GSE159907_RAW.tar 4.5 Gb (http)(custom) TAR (of IDAT)
GSE159907_Signal_Intensities.csv.gz 1.3 Gb (ftp)(http) CSV
Processed data are available on Series record

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