Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Genome-wide profiling of methylation identifies novel targets with aberrant hypermethylation and reduced expression in low-risk myelodysplastic syndromes.

ABSTRACT: This SuperSeries is composed of the following subset Series: GSE41130: Expression profiling of Low-Risk Myelodysplastic Syndromes (MDSs) GSE41215: Methylation profiling of Low-Risk Myelodysplastic Syndromes (MDSs) Refer to individual Series

ORGANISM(S): Homo sapiens

SUBMITTER: Javier De Las Rivas

PROVIDER: E-GEOD-41216 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Genome-wide profiling of methylation identifies novel targets with aberrant hypermethylation and reduced expression in low-risk myelodysplastic syndromes.

del Rey M M O'Hagan K K Dellett M M Aibar S S Colyer H A A HA Alonso M E ME Díez-Campelo M M Armstrong R N RN Sharpe D J DJ Gutiérrez N C NC García J L JL De Las Rivas J J Mills K I KI Hernández-Rivas J M JM

Leukemia 20120831 3

Gene expression profiling signatures may be used to classify the subtypes of Myelodysplastic syndrome (MDS) patients. However, there are few reports on the global methylation status in MDS. The integration of genome-wide epigenetic regulatory marks with gene expression levels would provide additional information regarding the biological differences between MDS and healthy controls. Gene expression and methylation status were measured using high-density microarrays. A total of 552 differentially ...[more]

PMID: 22936014

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Project description:Genome-wide expression and methylation profiling identifies novel targets with aberrant hypermethylation and reduced expression in low-risk myelodysplastic syndromes (MDSs). Gene expression profiling signatures may be used to classify the subtypes of Myelodysplastic syndrome (MDS) patients. However, there are few reports on the global methylation status in MDS. The integration of genome-wide epigenetic regulatory marks with gene expression levels would provide additional information regarding the biological differences between MDS and healthy controls. Gene expression and methylation status were measured using high-density microarrays. A total of 552 differentially methylated CpG loci were identified as being present in low-risk MDS; hypermethylated genes were more frequent than hypomethylated genes. In addition, mRNA expression profiling identified 1005 genes that significantly differed between low-risk MDS and the control group. Integrative analysis of the epigenetic and expression profiles revealed that 66.7% of the hypermethylated genes were underexpressed in low-risk MDS cases. Gene network analysis revealed molecular mechanisms associated with the low-risk MDS group, including altered apoptosis pathways. The two key apoptotic genes BCL2 and ETS1 were identified as silenced genes. In addition, the immune response and micro RNA biogenesis were affected by the hypermethylation and underexpression of IL27RA and DICER1. Our integrative analysis revealed that aberrant epigenetic regulation is a hallmark of low-risk MDS patients and could have a central role in these diseases. Low-risk MDS patients and age-matched controls without haematological malignancies were included in the study. Mononuclear cells were isolated from bone marrow samples of low-risk MDS patients and controls by density gradient (Ficoll). A cohort of 18 patients with low-risk MDS and seven controls were included in a simultaneous integrative study of methylation (using Methylated CpG Island Amplification and Microarrays, MCAM) and expression (using Affymetrix microarrays HG-U133 Plus 2), while the whole series was used as a control group of expression data.

Dataset Information

Genome-wide profiling of methylation identifies novel targets with aberrant hypermethylation and reduced expression in low-risk myelodysplastic syndromes.

Publications

Genome-wide profiling of methylation identifies novel targets with aberrant hypermethylation and reduced expression in low-risk myelodysplastic syndromes.

Similar Datasets

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