Genomic analysis of Multiple Myeloma using RNA Sequencing

Multiple Myeloma (MM) is a fatal proliferation of plasma cells that primarily affects elderly individuals, afflicting over 21,000 patients and accounting for over 10,000 deaths in the US each year. Most patients with MM relapse and ultimately become refractory to chemotherapy. Molecular and cytogenetic stratification of patients can identify patients at high risk of relapse, who have a particularly poor survival. Even though gene expression profiling (GEP) has been shown to be better than standard criteria and leads to better treatment stratification, a notable proportion of patients with high-risk gene expression signature can also achieve very good long-term survival, whereas some patients with low-risk gene expression signature myeloma (MM) can experience early relapse. Thus, newer molecular markers are needed for better risk stratification and most importantly newer therapeutic targets are desperately needed for patients with high-risk and relapsed disease. We hypothesize that integrative genomic analysis can define biologically and clinically distinct forms of myeloma beyond what can be gleaned by gene expression profiling alone, and by bringing together multiple types of molecular measures and understanding their relationships, we can reveal a more complete picture of multiple myeloma pathology and therapeutic opportunities. We are performing high-resolution genome-wide genomic, exome and transcriptome and epigenomic characterization of primary MM using next-generation sequencing and correlating these data with survival outcomes in a well-annotated cohort of patients treated at Mt. Sinai. We expect our results to yield novel insights into pathogenesis of relapsed MM, improved prognostic models and new therapeutic targets not identified by current technologies, and to identify approved therapies that could be repurposed for improving the treatment of relapsed MM.

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