Abstract
Epigenetic dysregulation, including aberrant methylation of cytosine residues in DNA, is a hallmark of cancer and clearly results in oncogenic cellular alterations such as transcriptional attenuation of tumor suppressors and genomic instability. A number of studies have examined DNA methylation alterations in patients with acute myeloid leukemia (AML) and have shown that analysis of multilocus methylation patterns can identify biologically distinct AML subclasses and can predict patient prognosis. In order to utilize the prognostic capability of methylation analysis in a clinical setting, we have developed a microsphere-based HpaII tiny fragment enrichment by ligation-mediated PCR (xMELP) assay to interrogate the methylation state of genomic multiple loci along with a random forest-based classification algorithm that correlates DNA methylation status with patient prognosis. These tools can be easily implemented in a clinical molecular pathology laboratory and can be utilized for more accurate risk stratification of AML patients.
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