A multiparameter flow cytometry immunophenotypic algorithm for the identification of newly diagnosed symptomatic myeloma with an MGUS-like signature and long-term disease control.

Achieving complete remission (CR) in multiple myeloma (MM) translates into extended survival, but two subgroups of patients fall outside this paradigm: cases with unsustained CR, and patients that do not achieve CR but return into a monoclonal gammopathy of undetermined significance (MGUS)-like status with long-term survival. Here, we describe a novel automated flow cytometric classification focused on the analysis of the plasma-cell compartment to identify among newly diagnosed symptomatic MM patients (N=698) cases with a baseline MGUS-like profile, by comparing them to MGUS (N=497) patients and validating the classification model in 114 smoldering MM patients. Overall, 59 symptomatic MM patients (8%) showed an MGUS-like profile. Despite achieving similar CR rates after high-dose therapy/autologous stem cell transplantation vs other MM patients, MGUS-like cases had unprecedented longer time-to-progression (TTP) and overall survival (OS; ~60% at 10 years; P<0.001). Importantly, MGUS-like MM patients failing to achieve CR showed similar TTP (P=0.81) and OS (P=0.24) vs cases attaining CR. This automated classification also identified MGUS patients with shorter TTP (P=0.001, hazard ratio: 5.53) and ultra-high-risk smoldering MM (median TTP, 15 months). In summary, we have developed a biomarker that identifies a subset of symptomatic MM patients with an occult MGUS-like signature and an excellent outcome, independently of the depth of response.