PURPOSE Multiple myeloma (MM) is characterized by copy number abnormalities (CNAs), some of which influence patient outcomes and are sometimes observed only at relapse(s), suggesting their acquisition during tumor evolution. However, the presence of micro-subclones may be missed in bulk analyses. Here, we use single-cell genomics to determine how often these high-risk events are missed at diagnosis and selected at relapse. MATERIALS AND METHODS We analyzed 81 patients with plasma cell dyscrasias using single-cell CNA sequencing. Sixty-six patients were selected at diagnosis, nine at first relapse, and six in presymptomatic stages. A total of 956 newly diagnosed patients with MM and patients with first relapse MM have been identified retrospectively with required cytogenetic data to evaluate enrichment of CNA risk events and survival impact. RESULTS A total of 52,176 MM cells were analyzed. Seventy-four patients (91%) had 2-16 subclones. Among these patients, 28.7% had a subclone with high-risk features (del(17p), del(1p32), and 1q gain) at diagnosis. In a patient with a subclonal 1q gain at diagnosis, we analyzed the diagnosis, postinduction, and first relapse samples, which showed a rise of the high-risk 1q gain subclone (16%, 70%, and 92%, respectively). In our clinical database, we found that the 1q gain frequency increased from 30.2% at diagnosis to 43.6% at relapse (odds ratio, 1.78; 95% CI, 1.58 to 2.00). We subsequently performed survival analyses, which showed that the progression-free and overall survival curves were superimposable between patients who had the 1q gain from diagnosis and those who seemingly acquired it at relapse. This strongly suggests that many patients had 1q gains at diagnosis in microclones that were missed by bulk analyses. CONCLUSION These data suggest that identifying these scarce aggressive cells may necessitate more aggressive treatment as early as diagnosis to prevent them from becoming the dominant clone.

Multiple myeloma (MM) is a hematological malignancy characterized by the accumulation of tumor plasma cells (PCs) in the bone marrow (BM). Despite considerable advances in terms of treatment, patients’ prognosis is still very heterogeneous. Cytogenetics and minimal residual disease both have a major impact on prognosis. However, they do not explain all the heterogeneity seen in the outcomes. Their limitations are the result of the emergence of minor subclones missed at diagnosis, detected by sensible methods such as single-cell analysis, but also the non-exploration in the routine practice of the spatial heterogeneity between different clones according to the focal lesions. Moreover, biochemical parameters and cytogenetics do not reflect the whole complexity of MM. Gene expression is influenced by a tight collaboration between cytogenetic events and epigenetic regulation. The microenvironment also has an important impact on the development and the progression of the disease. Some of these determinants have been described as independent prognostic factors and could be used to more accurately predict patient prognosis and response to treatment.

Primary plasma cell leukemia (pPCL) is an aggressive form of multiple myeloma (MM) that has not benefited from recent therapeutic advances in the field. Because very rare and heterogeneous, it remains poorly understood at the molecular level. To address this issue, we performed DNA and RNA sequencing of sorted plasma cells from a large cohort of 90 newly diagnosed pPCL, and compared to MM. We observed that pPCL presents a specific genomic landscape with a high prevalence of t(11;14) (about half) and high-risk genomic features such as del(17p), gain 1q, del(1p32). In addition, pPCL displays a specific transcriptome when compared to MM. We then aimed at specifically characterize pPCL with t(11;14). We observed that this sub-entity displayed significantly fewer adverse cytogenetic abnormalities. This translated into better overall survival when compared to pPCL without t(11;14) (39.2 months vs 17.9 months, p=0.002). Finally, pPCL with t(11;14) displayed a specific transcriptome, including differential expression of BCL2 family members. This study is the largest series of patients with pPCL reported so far.