Single-cell multiomic clonal tracking in myeloma identifies SMM clones that progress to MM and low frequency MM clones with resistance features enabling more precise application of targeted therapies.

Multiple myeloma (MM) is a cancer of plasma cells with approximately 200,000 new cases/year and a 54% 5-year overall survival rate. Myeloma arises from expansion of pre-existing clonal populations, referred to as either monoclonal gammopathy of uncertain significance (MGUS) or smoldering multiple myeloma (SMM), but only ~1% of individuals with these precursors will develop fulminant MM. As myeloma cells expand, 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. Being able to more comprehensively identify low-frequency subclones that may result in frank disease or resistance would enable more direct application of precision therapies. Here, we present proof of concept single-cell, multiomic data identifying the clonal populations that progress to frank myeloma or resistant disease.