CORE 3: Bioinformatics

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SUMMARY CORE 3 The goal of Bioinformatics core is to provide data management and bioinformatics support in a timely and efficient manner. The core will process, and analyze the data derived from P01 projects and provide bioinformatics support and expertise to the projects. We propose 3 objectives. The first objective will be to provide management, storage and sharing of the data. We will build a database to allow researchers to select samples and data tailored to specific questions. The database will be used as a platform for data analysis and integration. The second objective is to provide analytical support for the first 3 research projects. We will help to identify drivers mutations associated with melanoma progression. We will also provide a comprehensive extended (upstream regulators and downstream targets) annotation of the top hits (project 1). Whole genome methylation analysis (project 2) is expected, like all other research projects, to generate multiple hits across multiple regions. We developed powerful analytical tool that allows identification of the set of transcription factors whose downstream effects will be impeded by abnormal methylation. We will also provide bioinformatics support for gene expression analysis (project 3). We will construct regulatory network of the genes differentially expressed in long- term (>5 years) versus short-term (<5 years) bad survivors. We will provide comprehensive annotations of differentially expressed genes with the goal of the identification of molecular pathways associated with metastatic progression. Our third objective will be to provide bioinformatics support for data integration (project 4). We see two levels of integration: integration between the projects of the P01 and integration with the data and results generated outside if the P01. The first level of integration will be based on the assumption that melanoma progression is driven by a modulation of a single or a few biological functions and those functions can be modified by different mechanisms: germline and somatic mutations, modulation of the gene expression through genetic and somatic polymorphisms, methylation, and environmental exposures. We expect to find a stronger overlap between the results generated by different projects on the level of biological functions than on the gene level. Melanoma has been a hot research area and a lot of data and results related to the melanoma progression have been generated. We will combine the data generated by this P01 with TCGA, GEO, GTEx, ONCOMINE, Human Protein Atlas and other public sources. Using data from outside sources will allow us to test and refine key findings from this P01.