Identification Rate of Myeloma-Specific Clonotypes in Multiple Diagnostic Sample Types from Patients with Multiple Myeloma Using Next-Generation Sequencing Method

Background: Recent reports support the prognostic importance of minimal residual disease (MRD) levels in multiple myeloma (MM) patients and suggest that novel methods for MRD assessment can play a role in the evolving MM treatment paradigm (Martinez-Lopez et al., Blood 2014). The application of next-generation sequencing (NGS)-based MRD assessment has been previously demonstrated in multiple lymphoid malignancies (Faham et al., Blood 2012; Ladetto et al., Leukemia 2013). NGS-based MRD assessment requires a diagnostic sample for initial identification of the myeloma clonotype. In order for this MRD assessment approach to be clinically practical, it must allow for analysis of a diverse set of diagnostic samples. In this study, we assessed the rate of myeloma clonotype identification in 6 sample types at diagnosis: bone marrow (BM) aspirate slides, RNA extracted from CD138+ plasma cells, methanol-fixed BM cells, BM mononuclear cells, RBC-lysed BM cells, and DNA extracted from small numbers of CD138+ plasma cells.

Methods: Baseline samples were collected from 606 patients with MM. The following samples were provided at baseline: bone marrow aspirate (BMA) slides (164), RNA extracted from CD138+ plasma cells (402), methanol-fixed BM cells (30), BMA cell preparations using a Ficoll protocol (13), BMA cell preparations using an RBC lysis protocol (19), and DNA extracted from small numbers of CD138+ plasma cells (5). Samples with sufficient input DNA (>15ng) were included in the analysis, although this requirement was waived for samples from CD138+ cells. The Ficoll BMA cell preparations were divided into the mononuclear cell fraction and the lower Ficoll fraction, which is typically comprised of granulocytes and erythrocytes. Identification of myeloma clonotypes was performed using Sequenta's LymphoSIGHT™ method. Briefly, using universal primer sets, we amplified immunoglobulin heavy chain (IGH) and light chain (IGK) variable, diversity, and joining gene segments from genomic DNA. Amplified products were sequenced and analyzed using standardized algorithms for clonotype determination. Myeloma-specific clonotypes were identified for each patient based on their high-frequency (>5%) within the B-cell repertoire.

Results: The NGS assay identified a high-frequency myeloma clonotype in 555/606 (92%) of patients with MM. Myeloma clonotype identification rates were 141/164 (86%) in BMA slides, 375/402 (93%) in RNA extracted from CD138+ plasma cells, 30/30 (100%) in methanol cell preparations, 13/13 (100%) in Ficoll cell preparations, 18/19 (95%) in RBC lysis cell preparations, and 5/5 (100%) using small amounts of input CD138+ DNA (approximately 5000 cells). These applicability rates are consistent with previous reports of sequencing applicability in MM patients. In thirteen patients, we investigated the potential loss of myeloma-specific clonotypes due to Ficoll cell preparation. The variation in myeloma cell loss was typically low but ranged from essentially no loss to the loss of more than 90% of the myeloma cells in the PBMC of one patient compared to the RBC lysis preparation. The myeloma cells were detected in the typically discarded lower layer of the Ficoll preparation which explained the loss.

Conclusions: These results suggest that sequencing based MRD analysis is applicable in >90% of patients with MM. Multiple sample types, including archived BMA slides, can be used for identification of the myeloma clonotype. Further evaluation and optimization of sample processing methods is ongoing to enable application of the sequencing method for clinical MRD assessment in MM patients.