Abstract 2558 Background: The increasing use in the clinic of genome-wide analyses has placed a greater burden on, and need for novel informatics tools. Ideally such tools should be capable of reducing the vast amount of information generated per patient into integrated, simplified, intuitive, and preferably, visual data that can be easily translated into diagnostic, prognostic and theranostic actionable information. With the overarching goal of clarity and user-friendliness in mind we have co-opted a genome-wide representational tool used widely in non-clinical discovery genomics and tailored it to achieve its intended clinical use, i.e. simple graphical representation of complex data enabling clinicians to quickly derive meaning from robust clinical laboratory modalities, such as next-generation sequencing technologies and next-gen microarrays. Materials & Methods: For a proof of concept rendition, we collected cytogenetics, array CGH, and gene expression data on a subset of well-characterized core binding factor positive leukemias. Leukemias containing CBFA2 [t(8;21)(q22;q22)] or CBFB [inv(16)(p13q22)] fusion proteins were included in the study. Gene expression profiling data sets were extracted from Stanford Microarray Database. The associated karyotypes were obtained from the linked PubMed papers and directly from the authors. aCGH data sets were extracted from the SKY/M-FISH and CGH database at NCBI. All datasets for each case of CBF+ leukemia represented in this study were unified into a Microsoft Access Database, which contained the numeric coordinates of all genes included, and their associated cytogenetic band position. Results: By subjecting the data to customized subroutines, it was possible to extract and display relevant subsets of data into a customizable visually intuitive display, which allowed naïve observers to quickly assimilate all the clinically relevant genetic information on a particular AML case. From such a representation, heat maps of subsets of genes, structural and numerical chromosome abnormalities, copy-number changes and subsets of relevant point mutations could be displayed, all in a single integrated genome anchored image. Discussion: Our graphic user interface displays positionally-anchored genome-wide data and could be customized to represent CNVs, miRNA expression and DNA methylation patterns, associated phenotypes, etc, in addition to those shown in this study. Furthermore, any of these parameters can be segmented into functionally related groups to display, for instance, regulators of transcription, cell lineage or differentiation, proliferation, apoptosis, DNA repair, expression of genes that govern response or sensitivity to chemotherapy or entire signaling pathways. Conclusion: Integrated graphical representation of relevant genome-wide data facilitates and harmonizes communication among physicians with different expertise and facilitates patient stratification into defined risk groups, which is critically important in enabling risk-adapted and/or targeted therapies. Disclosures: No relevant conflicts of interest to declare.