More than myeloma: the trouble with “normal” plasma cells Free

In this issue of Blood, Da Vià et al¹ use single-cell RNA sequencing combined with B-cell receptor sequencing to characterize and distinguish clonal plasma cells (cPCs) from polyclonal plasma cells (pPCs) in patients with multiple myeloma (MM), patients with MM precursor conditions, and healthy donors. Importantly, and in line with recent work,² the authors clearly identify how the combination of both of these sequencing techniques is superior to single-cell RNA sequencing alone, allowing for selective analysis of malignant and nonmalignant plasma cell populations in the marrow microenvironment.

Differentiating normal and tumor plasma cells is crucial. Single-cell RNA sequencing has enabled the characterization of normal cell transcriptomes,³ whereas innovative whole genome sequencing platforms have advanced the genomic profiling of normal B cells.^4,5 Because distinct genomic and transcriptomic alterations can also be detected in seemingly normal cells, these investigations are essential for understanding MM evolution and identifying the key events responsible for neoplastic transformation.

Today, patients with MM, and those with precursor conditions, are prognosticated by measuring tumor burden and identifying whether malignant cPCs carry cytogenetic abnormalities associated with high-risk disease.⁶ Although these models have good accuracy in detecting patients at imminent risk of progression, they have not shown strong sensitivity, highlighting the need for improved predictive tools that can better stratify patients with MM. In their article, Da Vià et al show that gene expression characteristics of healthy plasma cells differed among healthy individuals, those with precursor plasma cell disorders, and those with active MM, and that these differences can further stratify outcomes in patients with MM. Centrally, the authors have identified that some patients with MM displayed an inflamed pPC phenotype with increased interferon-γ signaling, and decreased functional capacity associated with clinical immunoparesis in affected patients. Analysis of cell interactions within the tumor microenvironment (TME) demonstrated that some of the inflammatory signals are driven by cPCs within the TME, providing new insight into how cPCs in patients with MM contribute to immune dysregulation in the bone marrow. Interestingly, the authors point out that the PETHEMA risk stratification model for smoldering myeloma (SMM) includes immunoparesis as a high-risk feature.⁷ Their finding in those with MM may be reflective of similar biology, with immunoparesis reflecting a more hostile “myeloma-like” TME in some patients with SMM that is predictive of early progression. Using these data, the authors go on to define a gene expression signature of healthy plasma cells most representative of healthy patients, and least representative of those with active MM.

Understanding the complex relationship between tumor cells and the immune environment is increasingly essential for developing effective immunotherapy strategies and early interception approaches for patients with SMM and monoclonal gammopathy of undetermined significance. Patients with MM exhibit clear alterations in the TME, often detectable at a lower scale in SMM and some cases of monoclonal gammopathy of undetermined significance.³ The idea that MM develops over decades, acquiring key genomic drivers years before progression and organ damage, suggests that immune control plays a critical role in containing already neoplastically transformed clones (see figure).^5,8 The loss of effective immune surveillance, not just at the T-cell level but also at the B-cell and plasma-cell levels, as shown by Da Vià et al, can severely affect a patient’s ability to develop or sustain a strong memory response. These concepts are supported by studies of responses to vaccinations in patients with MM and SMM.⁹ In addition, the reduction and alteration of pPCs during MM progression may further impair the ability to generate a sustained memory immune response after immunotherapy.

In the context of immunotherapy, investigators also found that GPRC5D expression was higher among cPCs than in pPCs, with no differences in TNFRSF17 (B-cell maturation antigen [BCMA]) expression when comparing cPCs and pPCs. Clinical studies have demonstrated that myeloma patients receiving bispecific antibodies are at a significantly increased risk of infection while on therapy, due to on-target, off-tumor killing of normal pPCs and subsequent hypogammaglobulinemia.¹⁰ However, this appears to be more common among patients receiving BCMA-directed bispecific antibodies like teclistamab or elranatamab than among patients receiving GPRC5D-directed bispecific antibodies like talquetamab. The authors note that cPCs had higher expression of GPRC5D than pPCs, whereas TNFRSF17 expression was largely similar between the 2 PC populations. This indicates a possible rationale for the decreased risk of infections seen in patients receiving talquetamab when compared with teclistamab or elranatamab.¹⁰ Again, this observation would have been very challenging to perform without single-cell RNA sequencing with B-cell receptor sequencing because this observation requires combining the 2 techniques.

In conclusion, the study by Da Vià and colleagues, along with other studies focused on immune dysregulation in patients with MM, seeks to use gene expression characteristics of nonmalignant leukocytes to identify signatures in patients with functionally high-risk MM that do not rely on characterization of features of myeloma cells themselves. What remains to be seen is whether these features ultimately originate from the plasma cells themselves, and whether specific genomic characteristics of myeloma cells can be identified as the source of pPC disruption.

Conflict-of-interest disclosure: F.M. is a consultant for Medidata and Sanofi. R.S.F. declares no competing financial interests.