Does High Soluble BCMA Affect Treatment Efficacy in Myeloma?

Anita Boyapati, PhD

Soluble BCMA (sBCMA), a circulating form of a protein crucial for myeloma cell survival, has become a potential biomarker in the treatment of patients with multiple myeloma. However, its role and impact on therapy response remain under investigation.

Anita Boyapati, PhD, recently led a study exploring the relationship between soluble BCMA and disease burden in patients with relapsed/refractory multiple myeloma. The study looked at the relationship between sBCMA and M protein, and the response to treatment with linvoseltamab (REGN5458), a BCMA/CD3 bispecific antibody, in patients with relapsed/refractory multiple myeloma with high vs low baseline sBCMA.

Two clinical trials were utilized for baseline serum collection (NCT03761108 and NCT04083534; n = 302 for sBCMA analysis). Investigators assessed the correlation between baseline sBCMA and overall response rate (ORR) in patients treated with the recommended phase 2 dose of linvoseltamab (n = 117).

The findings revealed high variability in soluble BCMA levels, a modest correlation with individual disease parameters, and the identification of factors like urine protein, serum protein, and bone marrow plasma cell burden that influence sBCMA through machine learning analysis. Additionally, Boyapati revealed that even in those with high sBCMA concentrations, a high ORR can be reached with linvoseltamab 200 mg.

“Soluble BCMA has been an important biomarker and clinical trials, especially in BCMA-directed therapies. It has been useful to help understand dose response relationships and things, but our work shows that patients with high baseline disease, as read out by serum and protein, urine and protein, or bone marrow plasma cell burden, are highly correlated to soluble BCMA,” Boyapati, senior director of precision medicine at Regeneron Pharmaceuticals, told Targeted Oncology^TM, in an interview.

In the interview, Boyapati further discussed her research on the link between sBCMA and both disease burden and response to BCMA-targeted therapies in this patient population.

Targeted Oncology: Can you explain the rationale behind this research?

Boyapati: It has been hypothesized in the literature that circulating soluble BCMA is associated with disease burden in patients with multiple myeloma, and that it may impact response to myeloma targeting therapies, including BCMA-directed therapies. We therefore conducted an analysis to formally evaluate the relationship between soluble BCMA and patient’s disease, as well as response to linvoseltamab 200 mg.

Bone marrow aspirate cytology of multiple myeloma: ©David A Litman - stock.adobe.com

Can you give an overview of the methods and design you utilized in the research?

Our study involved 300 participants with relapsed/refractory multiple myeloma. In those [patients], we had baseline soluble BCMA measurements as well as their conventional disease parameters at baseline, as assessed in bone marrow, as well as in serum and urine. We then performed correlations between predose soluble BCMA concentrations, as well as all of these disease parameters. We then identified how these parameters explained the variability in circulating BCMA, which can be highly variable in patients. Finally, which was a key hypothesis, were the baseline levels associated with response to linvoseltamab, as reported for other therapies, that it may impact response. We did an association of response in soluble BCMA.

What were the main findings from this study?

We had 3 key main findings. Soluble BCMA is highly variable in patients with relapsed/refractory multiple myeloma. Second, we found that it is modestly correlated to individual disease parameters in the bone marrow, serum, and urine. These are routine measures that are measuring clinical trials, as well as in real-world practice. We did a machine learning study where we looked at what are the disease measures that are most correlated with soluble BCMA, and we found that urine and protein, as well as bone marrow plasma cell burden, explain a lot of the levels of soluble BCMA. Most importantly, we found that in patients treated with linvoseltamab 200 mg, there is a high overall response rate, even in patients with high baseline soluble BCMA, demonstrating that it works across patients with variable BCMA.

How did these data compare with findings previously observed?

Our study extends some work in newly diagnosed multiple myeloma and some literature reports of relapsed/refractory. It is 1 of the largest studies of soluble BCMA, a relationship to disease parameters, and comprehensive disease parameters. We looked in the bone marrow, we looked in the serum in the urine, because this disease disseminates across various disease compartments. So that is 1 thing that differentiates our study. The other aspect is that these are in heavily pretreated relapsed/refractory patients. It shows that even in heavily pretreated patients, what the concentrations are and how variable they are. I think the machine learning algorithm that we utilized is a new way to analyze what disease features are associated with soluble BCMA.

Moving forward in this space, how do you see machine learning growing or being utilized more?

Machine learning allows us to incorporate a lot of complex features and we are working in diseases where not only the diseases and the individual patients have heterogeneous disease and highly complex disease, but their disease is disseminated in a lot of different tissues. Combined with that complexity of the disease, but also the access to biomarkers, genomics and data in the bone marrow, and proteomics when we try to integrate all of this data and apply it to machine learning, it allows us to filter between the signal and noise. It also allows us, in the methodology we used in our study, to apply some significance of features, and avoid features that are highly correlated so that you are not selecting for the same feature over and over. So, I see machine learning being a mainstay, not only at the work we do at Regeneron in precision medicine, but also in the field of myeloma and related diseases, because in clinical trials and real-world investigators, we are all focused on better understanding the disease and characterizing the patients. I think that it is going to be a powerful and more routine method to understand these features and clinical outcomes.

For a community oncologist, what are the key takeaways from this research?

Soluble BCMA has been an important biomarker and clinical trials, especially in BCMA-directed therapies. It has been useful to help understand dose response relationships and things, but our work shows that patients with high baseline disease, as read out by serum and protein, urine and protein, or bone marrow plasma cell burden, are highly correlated to soluble BCMA. These routine labs that physicians are running to monitor their patients in practice can reflect high disease burden that is reflected by soluble BCMA. Even though they may not yet be commercially available soluble BCMA, the assays that they routinely monitor are going to reflect their patient's disease burden.

REFERENCE:

Boyapati A, Richter J, Suvannasankha A, et al. Association of baseline soluble BCMA with measures of disease burden and response to linvoseltamab: a comprehensive analysis in patients with R/R MM. Presented at: 20th Annual International Myeloma Society Meeting; September 27-30, 2023; Athens, Greece. P-005.