How is The Immune System a “Critical Player” in NDMM Outcomes?

The immune system is a “critical player” in the emergence, therapeutic responses, and outcomes associated with newly diagnosed multiple myeloma (NDMM), according to Manoj Bhasin, PhD, MS.

Bhasin spoke with CancerNetwork^® about research that he and colleagues published in Nature Cancer describing a single-cell atlas that may effectively characterize the bone marrow immune microenvironment among patients with NDMM. By generating profiles of 1,397,272 single cells from the bone marrow of 337 patients with NDMM, investigators determined specific attributes that may correlate with tumor growth and factors that can help improve stratification for the prediction of survival.

In a breakdown of his team’s research, Bhasin highlighted different cytogenetic risk-based evaluations, signaling analyses, and other processes as part of a comprehensive investigation into the bone marrow immune microenvironment. Additionally, he outlined potential future initiatives aiming to translate these data into more comprehensive risk-stratification models and novel anti-myeloma therapies.

Bhasin is a professor in the Department of Pediatrics and in the Department of Biomedical Informatics at Emory University School of Medicine; and director of Genomics, Proteomics, Bioinformatics and Systems Biology and the Aflac Director of the Single Cell Biology Program at Children’s Healthcare of Atlanta.

CancerNetwork: What was the rationale for generating a bone marrow microenvironment Immune Atlas associated with NDMM?

Bhasin: If you look at the landscape of multiple myeloma, all the risk-staging and stratification is mainly tumor genetic-[centered]. We are mainly focused on the tumor part and some clinical features, whereas the extrinsic factors like the immune system are not taken in consideration when we are stratifying the patient into high risk or standard risk. The basis for this study was to figure out [if] the immune system is playing a role in the emergence of multiple myeloma, the therapeutic response, as well as the outcome. This was one of the first comprehensive studies where we profiled more than 1.4 million cells from newly diagnosed [patients with] myeloma before they were given any therapy. This was a study to answer some of the important questions because it was built up on the Multiple Myeloma Research Foundation (MMRF) CoMMpass registry study [NCT01454297]. That is a study with 8 to 10 years of follow up on the patients with very comprehensive tumor genetics along with the clinical information to understand if the immune system plays a role in multiple myeloma. This is the study we planned 5 years back.

What did findings show regarding the utility of this single-cell atlas? What did the cytogenetic risk-based analysis demonstrate?

What we learned from this study is that [the atlas] generated a comprehensive profile of the immune landscape of the bone marrow microenvironment in multiple myeloma. We profiled 106 different major cell types, subtypes, or states of immune cells, and then correlated them with the outcomes of multiple myeloma at broader level. What we learned is that the patients who have an accumulation of these dysfunctional effector T cells at baseline usually have poor outcomes. This is true for whether they have a standard risk or high risk based on tumor genetics. The immune system is a key player in driving the outcomes.

Broadly speaking, patients with multiple myeloma are put into 2 bins. One is high risk, and [another] is standard risk based on the cytogenetics of their lesions. What we learned is that cytogenetics affects the immune system, but [not] all high-risk cytogenetic lesions have the same effect. Most of the high-risk cytogenetic lesions have depletion of interferon type 1 response. But what we observed is that one of the high-risk lesions, which carry deletion of 17p13, these specific lesions have enrichment of interferon type 1 response. That looks counterintuitive, but what we learned is that T cells, myeloid cells, and the tumor cell themselves produce humongous amounts of this interferon 1, specifically in the lesions with 17p13 deletion. Then, if you look at the second major cytogenetic alteration-carrying myeloma lesions...these lesions have accumulation of these dysfunctional T cells, along with senescent and exhausted T cells, that are associated with the poor outcomes in these lesions. The cytogenetics of lesions seem to be [quite] different from each other. Not all the high-risk lesions have the same immune imprint.

What were the key findings from the signaling analyses? Are there any particular factors associated with potential tumor growth and survival?

The proinflammatory signaling and immune-expressive signaling in the bone marrow microenvironment, which is driven by interferon 1 or interferon gamma, activates T and NK cells. It also activates macrophages and monocytes. On one side, it is like putting an escalator on T and NK cells to make them anti-tumor. It also activates the macrophages to create an immunosuppressive environment. It’s like you’re putting a foot on both escalators as well as on the brake of a car. It is making the cells get exhausted, and that is associated with the poor outcomes.

There is a great thing going on where a proliferation-inducing ligand [APRIL] binds with a TACI receptor on the plasma cells. The monocytes and macrophages, which are enriched in high-risk patients and patients who show very rapid progression, produce more amounts of this APRIL receptor that binds with the TACI on the surface of plasma cells to make them survive and cause the therapeutic resistance. In the patients who have non-progressive disease, they produce B cell-activating factor [BAFF] instead of APRIL. When they produce BAFF, they bind with the B cells and make them differentiate. It can also bind with TACI on plasma cells, but with very low affinity. It looked like the balance of this signaling of APRIL, TACI and BAFF is shifted in the patients of high risk and the patients who are showing a rapid progression. That provides us a therapeutic opportunity; we can try to intervene into this interaction and try to design new therapies for multiple myeloma that fix the immune microenvironment.

How might integrating immune cell signatures with known tumor cytogenetics help with the prediction of survival in NDMM?

The current prognostic system or staging system is clinical feature driven and tumor genetic centric. What we learned from this study is that tumor-extrinsic factors like the immune system, the accumulation of these dysfunctional late effector T cells, are associated with poor outcomes. Adding those components into the staging system will improve the stratification of the patients. Right now, based on the current staging system, we observe that some of the high-risk patients don’t have progression of their disease, whereas some of the standard-risk patients show a rapid progression of the disease because the immune component is missing. Maybe adding that immune component will bring accuracy into our prognostication system.

In addition to looking at all the clinical parameters and all the tumor genetics parameters, maybe [we can] look into the immune compartment of bone marrow by doing some flow- or CyTOF-based immune profiling so that we can know if the patients have this dysfunctional T cell at baseline, they have a chance of rapid progression of disease. Taking the next step, how can we have a simple essay that can capture the immune microenvironment of bone marrow? Then, based on how the immune system is looking for a patient, a clinician can decide what the optimal therapy is. It is like we are trying to bring a personalized tumor genetics-, clinical-, and immune system-driven model for improving the progression-free survival, as well as overall survival, in multiple myeloma.

What are the next steps for further researching the immune microenvironment and potential factors correlating with survival in NDMM?

This study, Immune Atlas, is mainly focused on gene expression profiling, where we looked at the profile of each of the cells from the bone marrow. From genes, we need to move on to the protein. As a next step in this direction, we are focusing on profiling the proteome profile of each of these cells in the bone marrow microenvironment. We figured out from this study that these dysfunctional late effector T cells are the key drivers of outcomes of multiple myeloma. We need to further characterize them by doing functional assays, by doing some T-cell receptor sequencing or repertoire profiling, so that we can figure out what the clonality of these dysfunctional T cells look like.

Then, we are looking at the immune components of the bone marrow microenvironment. We also need to look into the stromal compartment that has these fibroblasts, hematopoietic stem cells, and the osteoblast. We need to start looking at endothelial cells. We should start looking into those cells because they might also be playing a key role, in addition to the immune system plus tumor genetics, on the outcomes. Then, [we are] converting this research grade assay into a clinical essay by using flow cytometry or by using another approach that can be quickly done with very high sensitivity in the clinical setting.

What do you hope your colleagues take away from this research?

Maybe the biggest thing we want to say from this study is that the immune system is a critical player in the outcome of multiple myeloma, its emergence, its therapeutic response, as well as the outcomes. It is not a byproduct; it is a major driver of the outcomes. We need to start working toward more comprehensive risk-stratification models that have tumor-intrinsic factors. We already have them, like genetics and clinical parameters, but then we need to add the immune component into it to further improve the stratification strategy. [Additionally], all high-risk multiple myeloma lesions are not same. They have very different immune imprints. We should look at the immune imprints of them, further comprehensively study them, and then help in designing immune therapies that fix the immune dysregulation that is associated with each cytogenetic alteration [instead of] thinking that all high-risk cytogenetic lesions of myeloma are all same.

Reference

Pilcher WC, Yao L, Gonzalez-Kozlova E, et al. A single-cell atlas characterizes dysregulation of the bone marrow immune microenvironment associated with outcomes in multiple myeloma. Nat Cancer. 2026;7:224-246. doi:10.1038/s43018-025-01072-4