P-101: Single-cell RNA sequencing of 1.3 million plasma cells from patients with MGUS and SMM

Introduction: Patients with Monoclonal Gammopathy of Undetermined Significance (MGUS) and Smoldering Multiple Myeloma (SMM) exhibit variable risk of progression to full-blown Multiple Myeloma (MM), which cannot be fully explained by differences in tumor burden or genetic alterations. Therefore, characterizing non-genetic changes in malignant plasma cells may help to identify novel mechanisms of disease progression and improve prognostication.

Methods: Here, we performed single-cell RNA and V(D)J-sequencing on 245 samples from 36 patients with MGUS, 136 patients with SMM, 37 patients with MM, and 25 healthy donors. Libraries were prepared with the Chromium Single-cell 5’ Gene Expression and V(D)J enrichment kit by 10X Genomics and sequenced at the Genomics Platform of the Broad Institute of MIT and Harvard (Cambridge, MA).

Results: Overall, we sequenced 1,318,218 plasma cells, including 960,998 malignant and 357,220 normal plasma cells. By comparing tumor cells between patients and healthy donors, as well as between patients from different risk stages, we derived an expression signature that captures both the presence of malignancy and the tumor’s stage. This signature includes known culprits, such as IL6, as well as genes related to bone biology, hypoxia, metabolic activity, and cytomobility. We validated the capacity of this signature to identify disease and measure risk of progression in an independent gene expression profiling dataset (GSE6477) and showed a significant association with both progression-free survival (PFS) and overall survival (OS) in the CoMMpass dataset. Notably, this association remained significant when we accounted for the patient’s ISS stage and the tumor’s proliferative index, suggesting that this signature captures orthogonal aspects of the tumor’s aggressiveness. Furthermore, by comparing malignant and normal plasma cells within each patient, we were able to identify differentially expressed genes per tumor and assess how frequently each gene is dysregulated at scale. The most common upregulated genes were the oncogene MLLT3 (rank 1), the growth factor IGF1 (rank 2), and the proteasome regulator TJP1 (rank 3). This approach provides a rationale for the prioritization of novel targets, based on their rank, and can potentially uncover clinically meaningful differences between disease stages.

Conclusions: Our current understanding of transcriptomic alterations in patients with MGUS and SMM is based on bulk RNA-sequencing or microarray studies, which cannot distinguish between malignant and normal plasma cells, whose proportions vary across patients. This large single-cell RNA-sequencing cohort of patients with MGUS and SMM can help us gain novel insights into malignant plasma cell biology and nominate therapeutic targets for interception of progression.