Genetic Progression Factors in Multiple Myeloma and MGUS

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DESCRIPTION (provided by applicant): The long-term goal of this project is to identify mutations that contribute to myeloma disease progression and to develop treatment strategies based on individual patient genotypes. Multiple myeloma (MM) accounts for 2% of all cancer deaths in the United States and 3% of all cancer deaths in black/African-Americans. In collaboration with the Washington University Genome Sequencing Center (GSC), we propose to extend our current mutational profiling analyses to better our understanding of disease progression in MM. We will define tumor genotypes using bone marrow and skin (germline) DNA from patients with MM using largescale exonic re-sequencing of candidate genes. The R21 phase of this project will develop the translational research infrastructure and solve technical issues associated with mutational profiling. (1) We will capture epidemiological data, disease-related characteristics, prognostic factors, therapeutic information and outcomes for all patients diagnosed with multiple myeloma (MM) seen at the Barnes/Jewish Hospital/Siteman Cancer Center in our comprehensive clinical database. (2A) We will define the threshold level of mutation detection achievable by re-sequencing based on phi29 polymerase-whole genome amplified (WGA) genomic DNA. (2B) We will collect and bank genomic DNA from CD138-enriched myeloma cells and matched skin biopsy samples from 46 patients with newly diagnosed MM and will perform complete exonic re-sequencing often (10) candidate cytokine signaling genes (NRAS, KRAS, FGFR3, ARAF, RAF1, PTPN11, PIK3CA, LTK, INSR, and MERTK). Upon completion of defined milestones, the R33 phase of this project proceed with the following Aims: (3) We will functionally characterize novel gain-of-function mutations, identified in myeloma patient samples, using cell line transformation assays and in a disease model using murine bone marrow transduction/transplantation. (4) We will validate the clinical utility of mutation profiling by high-throughput re-sequencing of cytokine signaling gene mutations in myeloma patient samples collected at distinct stages of disease progression. Accomplishment of these Aims will provide the data necessary to test additional hypotheses requiring larger numbers of patients in a cooperative group setting. Sequencing analysis has, until now, been a relatively underutilized tool, but is a crucial component of a set of genomic technologies (including expression microarrays and proteomics) that will be required to improve outcome in myeloma patients.