(PA-206) Comprehensive Characterization of Myeloma Genomes from Bone Marrow and Peripheral Blood Using a Novel Clinical Assay

Detecting genetic abnormalities is crucial for risk stratification and tailored interventions in multiple myeloma (MM) and its precursor conditions. This currently requires invasive bone marrow (BM) aspirates, which poses a challenge for serial monitoring of genomic evolution and causes discomfort to patients. The current standard for detecting genetic alterations in MM is fluorescence in situ hybridization (FISH), which cannot detect mutations and other clinically relevant events. As a result, the recently updated IMS-IMWG guidelines require next-generation sequencing for the classification of high-risk MM. Moreover, identification of mutations/deletions in therapeutic targets (e.g., BCMA, GPRC5D) is critical for guiding immunotherapies.

Here, we enable routine assessment of MM genomes by comprehensively and robustly characterizing with whole genome sequencing (WGS) a minimum of ~50 circulating tumor cells (CTCs) isolated from peripheral blood (PB), in a novel CLIA-approved Laboratory Developed Test called GenoPredicta. We demonstrate complete concordance between WGS on CTCs and BM tumor cells, corroborated by independent clinical FISH results on BM.


Methods: Tumor cells were isolated from paired BM and PB samples using fluorescence-activated cell sorting (FACS) (after CD138+ enrichment for PB) and subjected to WGS, from which we identified copy number alterations, structural variants, and single nucleotide variants and indels. For a subset of samples, the BM was also characterized by FISH, using a standard clinical panel for characterizing MM.

Results: In a retrospective cohort of >60 viably frozen samples from >30 patients, we show excellent concordance between genomic abnormalities detected in BM and PB, with all clinically relevant events (11 translocations and 125 CNVs) observed in BM recapitulated in PB (100% recall). These abnormalities included high-risk events not assayed by FISH, including

biallelic TP53 loss (Del 17p coupled with a deleterious TP53 mutation, observed in 4 patients) and MYC::IGL translocations (2 patients). Moreover, all events identified by FISH in 14 samples (8 translocations and 30 CNVs) were also identified in the BM and PB (100% recall), with 50 translocations and 30 CNVs not detected by FISH also absent in the WGS data (100% precision). Importantly, the sensitivity of our methods distinguished events that were subclonal in PB but clonal in the paired BM sample, suggestive of multi-focal or extramedullary disease. For example, we identified subclonal translocations (MYC::IGH) that were only detectable in PB, including in a longitudinal sample post-treatment, suggesting emergence of a resistant clone.

Conclusions:

We demonstrate that WGS-based characterization of MM from BM or CTCs is a viable replacement for FISH for clinical diagnosis, with blood-based measurements enabling more dynamic and minimally invasive monitoring of the myeloma cancer genome.