Peripheral blood immunoprofiling defines three distinct immune states associated with clinical and molecular axes in multiple myeloma
Authors
David G. Coffey¹, Anastasia Radko², Ivan Zubarev², Diana Lupova², Elina Ohanjanyan², Julia Alesse², Noel English², Roman Movsisyan², Ksenia Markova², Michael Goldberg², C. Ola Landgren¹
- University of Miami, Miami, FL, USA
- BostonGene Corporation, Waltham, MA, USA
Abstract
Background: Multiple myeloma (MM) cases are clinically and biologically heterogeneous. While immune dysregulation in the bone marrow has been extensively studied in MM, the architecture of peripheral blood immune compartments is less clearly defined. Given the increasing therapeutic complexity of MM, it is important to characterize the circulating immune states to gain insights into MM disease biology and clinical risk stratification.
Aims:
We aim to define distinct blood immune states in MM and smoldering multiple myeloma (SMM) and to assess their association with clinical parameters, cytogenetic risk, and therapy exposure.
Methods: Cryopreserved peripheral blood mononuclear cells (PBMCs) from patients with MM (n = 56) and SMM (n = 5) were profiled using high-dimensional multiparameter flow cytometry. Immune cell subsets were quantified as percentages of their parent populations. Association with clinical features, cytogenetic subtypes, therapy exposure, and clinical risk variables was assessed using non-parametric statistical testing. To capture coordinated immune variation, we aggregated biologically related subsets into composite immune state scores using z-scored frequencies. Pairwise Spearman correlation analysis was used to evaluate independence between these scores. Statistical comparisons were then performed across clinical and molecular subgroups.
Results:
Differential immune profiling across SMM/MM status, cytogenetic abnormalities, and therapy exposure revealed a significant association between multiple T-cell and myeloid populations with clinical and molecular variables (p<0.05). Three distinct composite immune states with low inter-score correlations (|ρ|≤0.25) emerged, each representing coordinated variation across biologically related subsets.
Immune state 1 was enriched in naïve T-cells, CD31+ CD4+ T cells, and CXCR5+ T-follicular helper cells. It was significantly more prominent in patients with SMM than those with MM (Δ median=0.86, p=0.003), in those with ≤4 prior lines of therapy (Δ median=0.43, p=0.008), and in patients last treated with lenalidomide (Δ median=0.53, p=0.005).
Immune state 2 was associated with high-risk cytogenetic abnormalities, including 1q amplification (Δ median=0.80, p=0.010) and 13q deletion (Δ median=0.78, p=0.016). It showed increased proportions of monocytes and proliferating Ki-67+ CD8+ T cells.
Immune state 3 was defined by skewing of non-naïve CD4+ T cells toward greater Th2 polarization, with elevated PD-1 and TIGIT expression on T cells. It was linked to high-risk cytogenetics: 11;14 translocations (Δ median=0.49, p=0.028), 17p deletions (Δ median=0.37, p=0.019), and >4 prior lines of therapy (Δ median=0.40, p=0.011).
Summary/Conclusion:
Peripheral blood immunoprofiling revealed three distinct immune states, each aligned with plasma cell dyscrasia subtypes, cytogenetic risks, and prior treatment history. These profiles reflect coordinated patterns of T-cell differentiation, polarization, and proliferation along with checkpoint enrichment and monocyte expansion across disease and treatment groups, rather than isolated immune alterations. Our findings show that peripheral immune architecture captures biologically and clinically meaningful heterogeneity in MM and supports blood-based immunoprofiling. Further analysis in expanded cohorts is required to better define its clinical utility and advance biological insight into disease evolution.
Aims:
We aim to define distinct blood immune states in MM and smoldering multiple myeloma (SMM) and to assess their association with clinical parameters, cytogenetic risk, and therapy exposure.
Methods: Cryopreserved peripheral blood mononuclear cells (PBMCs) from patients with MM (n = 56) and SMM (n = 5) were profiled using high-dimensional multiparameter flow cytometry. Immune cell subsets were quantified as percentages of their parent populations. Association with clinical features, cytogenetic subtypes, therapy exposure, and clinical risk variables was assessed using non-parametric statistical testing. To capture coordinated immune variation, we aggregated biologically related subsets into composite immune state scores using z-scored frequencies. Pairwise Spearman correlation analysis was used to evaluate independence between these scores. Statistical comparisons were then performed across clinical and molecular subgroups.
Results:
Differential immune profiling across SMM/MM status, cytogenetic abnormalities, and therapy exposure revealed a significant association between multiple T-cell and myeloid populations with clinical and molecular variables (p<0.05). Three distinct composite immune states with low inter-score correlations (|ρ|≤0.25) emerged, each representing coordinated variation across biologically related subsets.
Immune state 1 was enriched in naïve T-cells, CD31+ CD4+ T cells, and CXCR5+ T-follicular helper cells. It was significantly more prominent in patients with SMM than those with MM (Δ median=0.86, p=0.003), in those with ≤4 prior lines of therapy (Δ median=0.43, p=0.008), and in patients last treated with lenalidomide (Δ median=0.53, p=0.005).
Immune state 2 was associated with high-risk cytogenetic abnormalities, including 1q amplification (Δ median=0.80, p=0.010) and 13q deletion (Δ median=0.78, p=0.016). It showed increased proportions of monocytes and proliferating Ki-67+ CD8+ T cells.
Immune state 3 was defined by skewing of non-naïve CD4+ T cells toward greater Th2 polarization, with elevated PD-1 and TIGIT expression on T cells. It was linked to high-risk cytogenetics: 11;14 translocations (Δ median=0.49, p=0.028), 17p deletions (Δ median=0.37, p=0.019), and >4 prior lines of therapy (Δ median=0.40, p=0.011).
Summary/Conclusion:
Peripheral blood immunoprofiling revealed three distinct immune states, each aligned with plasma cell dyscrasia subtypes, cytogenetic risks, and prior treatment history. These profiles reflect coordinated patterns of T-cell differentiation, polarization, and proliferation along with checkpoint enrichment and monocyte expansion across disease and treatment groups, rather than isolated immune alterations. Our findings show that peripheral immune architecture captures biologically and clinically meaningful heterogeneity in MM and supports blood-based immunoprofiling. Further analysis in expanded cohorts is required to better define its clinical utility and advance biological insight into disease evolution.
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