In an effort to predict accurately tumor behavior and to identify important oncogenic genes and biological pathways. These studies have revealed the presence of unique gene expression signatures distinguishing specific subgroups of cancers and have served to improve our understanding of the biology of these diseases. However, only part of the cellular information is contained at the messenger RNA level, and transcriptional activity is dependent on multiple factors. Among these factors are epigenetic marks, such as cytosine methylation and histone tail modifications, which help to determine and regulate chromatin structure and function including gene expression. Therefore, while gene expression studies using DNA microarrays have had a great impact in the study of cancer, it is important to recognize that there are limitations associated with this technique. Firstly, gene expression microarrays capture a snapshot of the cell’s transcriptome, detecting genes being actively Benzethonium Chloride transcribed at the time of RNA extraction, but they do not capture any information concerning the genes’regulatory states and consequently their potential for transcriptional changes in response to stimuli. For example, a locus such as the O6methylguanine DNA methyltransferase gene is not prognostically useful in terms of its basal expression state but the cytosine methylation status of its promoter provides an excellent indicator of how well gliomas will respond when treated by alkylating agents. We hypothesize that Lomitapide Mesylate biologically significant changes in expression can be missed by expression arrays due to technical limitations, but might be captured by epigenomic studies by identifying genes at which promoter cytosine methylation or H3K9 acetylation differ and testing them with highly-quantitative techniques. In order to test these hypotheses, we carried out genome-wide studies for DNA methylation and H3K9 acetylation as well as gene expression microarrays in patients with acute myeloid and lymphoblastic leukemia. These cell types were chosen so that we could test whether the technical approach we were exploring was feasible in typical clinical samples, using cell types that should be markedly distinctive. We show here that the integration of the information captured by these different platforms results in a more comprehensive detection of differentially regulated genes and an enhancement of the apparent biological relevance of the findings. Histone modifications and DNA methylation play a critical role in regulating gene expression by modifying the chromatin structure of genes and recruiting additional regulatory factors. Our work is based on the hypothesis that a truly integrated epigenomic analysis could yield superior insight 
into the transcriptional programming of cancer cells beyond that obtained by simply measuring abundance of mRNAs through expression microarrays, since epigenetic modifications will capture information not only from genes being actively transcribed, but they will also reflect the availability for transcription by informing on the chromatin structure at specific loci. As proof of principle, we selected two functionally validated epigenetic marks�Ccytosine methylation and histone 3 lysine 9 acetylation�Cin addition to standard gene expression arrays and tested their ability to identify gene regulatory differences between the AML and ALL cell types. First, we demonstrate that such multiplatform epigenomic studies can be readily performed in enriched leukemia cells from standard clinical trial patient specimens.