Deciphering Genomic Complexity of Multiple Myeloma Using Optimized Optical Genome Mapping

Abstract

The genomic evaluation of multiple myeloma in routine diagnostics involves isolating plasma cells expressing CD138, usually followed by fluorescence in situ hybridization analyses. However, cell sorting often yields a limited number of cells, restricting the number of probes that can be used and limiting the analysis to a few markers required for minimal prognostic classification. Optical genome mapping is a high-resolution technology capable of identifying structural variants and copy number variations across the entire genome; however, it currently requires 1 million cells. To overcome this constraint, an innovative strategy was implemented in this work based on mixing CD138-positive and CD138-negative fractions from the same patient, optimizing the use of available CD138-positive cells for genome-wide analysis. First, dilution experiments demonstrated that a 50% CD138-positive mix was sufficient to achieve complete detection of clonal structural and copy number variants, while establishing a detection threshold of 24% for copy number variants. Using this optimized protocol, 13 additional samples from 13 patients were analyzed. Optical genome mapping achieved 93% (13/15) concordance with fluorescence in situ hybridization for clonal anomalies and revealed >22 additional genomic variations not detected by fluorescence in situ hybridization. This strategy consolidated multiple analyses into a single test, minimized material requirements, and addressed critical prognostic and increasingly described anomalies, providing refined stratification for patients with multiple myeloma.