Publications by authors named "J Curfman"

Determining the pattern of methylation at CpG dinucleotides in a cell remains an essential component of epigenetic profiling. The correlations among methylation, gene expression, and accompanying disease have just begun to be explored. Many experiments for sensing methylation use a relatively inexpensive, high-throughput approach with a methyl-binding domain (MBD) protein that preferentially binds to methylated CpGs.

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High levels of microRNA-155 (miR-155) are associated with poor outcome in acute myeloid leukemia (AML). In AML, miR-155 is regulated by NF-κB, the activity of which is, in part, controlled by the NEDD8-dependent ubiquitin ligases. We demonstrate that MLN4924, an inhibitor of NEDD8-activating enzyme presently being evaluated in clinical trials, decreases binding of NF-κB to the miR-155 promoter and downregulates miR-155 in AML cells.

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DNMT3B encodes a DNA methyltransferase implicated in aberrant epigenetic changes contributing to leukemogenesis. We tested whether DNMT3B expression, measured by NanoString nCounter assay, associates with outcome, gene and microRNA expression and DNA methylation profiles in 210 older (⩾60 years) adults with primary, cytogenetically normal acute myeloid leukemia (CN-AML). Patients were dichotomized into high versus low expressers using median cut.

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Motivation: DNA methylation is an epigenetic change occurring in genomic CpG sequences that contribute to the regulation of gene transcription both in normal and malignant cells. Next-generation sequencing has been used to characterize DNA methylation status at the genome scale, but suffers from high sequencing cost in the case of whole-genome bisulfite sequencing, or from reduced resolution (inability to precisely define which of the CpGs are methylated) with capture-based techniques.

Results: Here we present a computational method that computes nucleotide-resolution methylation values from capture-based data by incorporating fragment length profiles into a model of methylation analysis.

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Purpose: Molecular risk stratification of acute myeloid leukemia (AML) is largely based on genetic markers. However, epigenetic changes, including DNA methylation, deregulate gene expression and may also have prognostic impact. We evaluated the clinical relevance of integrating DNA methylation and genetic information in AML.

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