P-047: Clonal evolution in multiple myeloma evaluated by Whole Exome Sequencing

Abstract

<h3>Background</h3> Multiple Myeloma (MM) is a plasma cell malignancy characterized by heterogeneous genomic and clinical profiles. Several molecular anomalies may arise clonally prior to diagnosis and continue to evolve temporally with disease progression. These evolving clones may follow either of the evolutionary patterns viz., stable /stable with loss of clone(s)/ linear with a gain of clone(s)/branching with both loss and gain of clone(s). While founder clones may initiate and drive the pathogenesis, the later (sub)clones may modulate response to therapy and facilitate relapse. This study was designed to investigate temporal changes in the prevalence of clonal mutations with time in MM and if any of these can be defined as actionable. <h3>Methods</h3> We have sequenced whole exomes of CD38+ enriched plasma cells obtained from 62 MM patients collected at two-time points, i.e., at diagnosis and on progression using Nextera Exome kit and HiSeq2500 sequencer (Illumina). Somatic variants were called using Illumina's Dragen somatic pipeline. <h3>Results</h3> A marked intraclonal heterogeneity was observed. Branching clonal evolution was observed as most common in more than 70% of patients followed by Linear and Stable with loss of clone in -15% patients each. Most of the patients with a branching pattern of clonal evolution also had low TMBs (<10) and 2 or 3 founder clones. This study has shown distinct changes in the clonal prevalence of driver genes including oncogenes and tumor suppressor genes during longitudinal follow-up. A few driver genes were found to increase in prevalence (e.g. CCND1, CYLD) while others reduced (e.g. ARID2, HIST1H1D, NCOR1) or remained consistent (e.g. RB1, IRF4) on progression. Similar changes in clonal prevalence were observed for a few actionable genes such as BRAF from diagnosis to progression. <h3>Conclusion</h3> These findings support the notion that evaluation of mutational landscapes in a time-phased manner may be important in discerning actionable mutations and decision-making for risk-adapted therapies.