Using Single Cell Multi-Omic Clonal Tracking in SMM to Identify Clones That Progress to MM and Harbor Treatment Resistance Features

Introduction

Multiple myeloma (MM) arises from an oligoclonal expansion of plasma cells, referred to as either monoclonal gammopathy of uncertain significance (MGUS) or smoldering multiple myeloma (SMM), with approximately 200,000 new diagnoses each year and a 54% 5-year overall survival rate. Yet only approximately 1% of individuals with these precursor conditions will develop fulminant myeloma. Clonal genetic differences lead to relapse due to acquired resistance in nearly 100% of patients, suggesting that initial therapy is inadequate to eradicate the entire disease burden and mandating regular, long-term surveillance along with the development of many targeted therapies. From matched pairs of SMM/MM patient samples, we share data from the Mission Bio Tapestri platform identifying the clonal populations that progress to frank myeloma.

Methods

Sixteen (16) pairs of cryopreserved, CD138-enriched, matched SMM/MM patient samples were multiplexed in groups of three per run on the Mission Bio Tapestri platform, enabling simultaneous single cell quantification of subclones by single nucleotide variants (SNV), copy number variants (CNV), IgH/IgK/IgL clonotyping, and surface protein expression analysis for immunophenotyping or therapeutic target selection. Samples were thawed and stained with a 20-plex antibody-oligo cocktail to label myeloma-specific surface markers for sequencing analysis and processed with an 846-plex DNA amplicon panel that combined whole-genome CNV coverage with MM gene hotspots. From an average of 3,500 cells recovered per multiplexed specimen, raw sequencing data was analyzed using Mission Bio proprietary algorithms.

Results

In our 16-patient cohort, we quantitatively characterized multiple features from SMM clonal phylogenies (avg 3.4 clones/patient), identifying driver mutations leading one, typically minor, subclone to progress to frank MM at an average time to progression of 13 months. Tabular data output is customizable, but includes clonal architecture with BCR clonotyping, prognostic CNVs (hyperdiploidy, del(1p), gain (1q), del (6q), del(13), del (17p)), prognostic SNVs and relative protein expression levels. Expression of potentially targetable proteins (e.g. BCMA, FcRL5, GPRC5D) along with SNVs that might cause therapeutic resistance could possibly inform treatment decisions.

Conclusion

Clonal expansion of plasma cells is a common event, but only a small fraction of individuals progress to MM. However, the high clonal diversity leads to resistance and relapse over time in nearly every patient, which can be difficult to elucidate using bulk measures or single, non-therapeutic markers such as clonotyping alone. As the variety and application of precision therapies in myeloma continue to expand, the need to correlate multiple clonal features could inform better prognostics (and potential treatment) for the identification of putatively resistant subclones at the time of diagnosis or relapse, informing modifications to therapy meant to mitigate selection. Even from notoriously difficult cryopreserved MM specimens, Mission Bio’s Tapestri platform enables quantitative correlation of SNVs, CNVs, Ig clonotyping (including T-cell exhaustion), and protein expression from thousands of cells per specimen with a resolution unmatched by bulk sequencing methods and clinical actionability unmatched by flow cytometry or standalone VDJ clonotyping.