Genomics in multiple myeloma

Abstract

Multiple myeloma (MM) is a complex disease that is driven by numerous genetic and epigenetic alterations. Comprehensive oncogenomic analysis indicates the presence of many highly recurrent and highly focal amplifications and/or deletions in the MM genome. Integrated oncogenomic analyses of human MM have identified candidates resident within regions of amplification and/or deletions that are predicted to be involved in MM pathogenesis and progression. The biological behavior and clinical outcome in MM are dependent on these molecular determinants, which are also attractive therapeutic targets. The data obtained from extensive analysis of patient samples, with annotated clinical outcomes, are providing insights into molecular mechanisms of disease behavior, helping to develop sensitive prognostic models, identifying novel therapeutic targets, providing the framework for the development of molecularly based therapies, and, eventually, will help in developing individualized therapy to improve outcomes, with reduced toxicity.

Figure 1. Progression to Myeloma - Gene Expression Analysis

High-throughput gene expression profile identifies distinct pattern in myeloma and MGUS compared to normal plasma cells (above). Analysis of the expression profile data identifies a multistep model of progression from normalplasma cells to MGUS cells, and to multiple myeloma (MM) PCL- plasma cell leukemia. Figure adapted from Davies et al. Insights into the multistep transformation of MGUS to myeloma using microarray expression analysis. Blood. 2003;102:4504-4511. © the American Society of Hematology.

Figure 2. High-throughput genomic analysis spanning all regulatory checkpoints

Genomic information is translated through various processes including post-translational protein modification (middle row). Abnormalities at these various levels potentially play a role in development of malignant transformation and behavior of the cancer cell (bottom row). Various high -throughput genomic analysis methods and arrays spanning all regulatory checkpoints are available to identify these various genomic abnormalities to develop an integrated approach that will lead to understanding of the molecular pathogenesis of cancer, identification of novel targets and therapies, development of personalized medicine, and predictive models for outcome. * protein modification such as phosphorylation, acetylation, ubiqiitination, sumoylation etc.