Evaluation of Immune Profile in Patients with Multiple Myeloma Using Cytof Technology

Introduction: CyTOF (time-of-flight mass cytometry) is a novel high-dimensional technology which permits immunophenotyping and analysis of signaling in single cells. This approach enables simultaneous evaluation of up to 40 parameters using antibodies tagged with distinct elemental isotopes, by combining flow cytometry with atomic mass spectrometry. Since multiple myeloma (MM) is characterized by immune dysfunction, we used CyTOF technology to define the complex immune profile in MM patient bone marrow (BM) samples.

Methods: We used 40 different markers to define various B, T, natural killer (NK) subsets, as well as cells of monocytic, granulocytic, erythroid and platelet lineages. Our preliminary data are results from 10 patients with MGUS/ smoldering MM (SMM); 10 newly diagnosed MM; 20 relapsed/refractory MM; and 15 WM patients (5 newly diagnosed and 10 receiving treatment) in comparison with age-matched healthy donors’ BM (HD). A significantly larger cohort of MM (N=150) and WM (N=50) patients is being similarly analyzed and will be presented. To evaluate phenotypic abnormalities in various B cell subsets, we used B lineage markers CD10, CD19, CD20, CD22, CD27, CD34, CD38, CD45, IgA, IgD, IgG and IgM to define B cells maturation stages from hematopoietic stem cells (HSC) to naïve to mature B lymphocytes (pro-B; pre-B-I; pre-B-II; immature B; and mature (naïve) B cells), as well as memory non-switched and memory switched B cells, plasmablasts, normal (CD138+CD38+CD19+CD45+) and clonal plasma cells (CD138+CD38+CD19-CD45-/low), which reside in the specific BM niche. Furthermore, natural killer (NK) subsets (such as NK and NKT cells) and T cells (such as memory CD4T, naive CD4T, memory CD8T, naive CD8T, T regulatory cells and Tg/d cells) were examined. High-dimensional data was obtained using CyTOF technology and analyzed by SPADE and viSNE software.

Results: Our data showed significantly decreased HSC in patients with newly diagnosed and relapsed/refractory MM compared to HD (P<0.025). A significant increase in pre-B-I cells was detected in relapsed/refractory MM vs. MGUS/SMM (P<0.028), but the opposite trend was observed in the pre-B-II subpopulation (P<0.005). No differences in immature B cell populations were observed in different stages of MM. However, a significantly higher percentage of immature B cells was present in relapsed/refractory MM compared to HD (P=0.008), and transitional B cells were significantly decreased in newly diagnosed MM compared to HD (P<0.001). Moreover, memory B cells were significant decreased in all MM stages compared to HD (P<0.003). Non-switched memory B cells were significantly increased in MGUS and SMM compared to newly diagnosed MM, while a significant increase of switched memory B cells was present in newly diagnosed MM compared to relapsed/refractory MM. A significant increase in plasmablasts was seen in relapsed/refractory MM in comparison with other MM stages (P<0.011) by CyTOF analyses. Malignant plasma cells (PC) were defined as CD19-, CD38++, CD45-/dim, CD138+ and either cyk or cyl positive. Importantly, a significant increase in clonal PC was found in all MM stages vs. HD, as well as in newly diagnosed MM compared to relapsed/refractory MM (P<0.01). The percentage of PC from CyTOF analyses correlated with % of PC obtained using flow cytometry by Bland-Altman method comparison. We also observed significant differences in T cell subsets including naïve, central memory, effector, and effector memory CD4+ and CD8+T populations between MGUS and newly diagnosed MM, but no significant changes in T regulatory and Tg/d cells. Furthermore, plasmacytoid dendritic (pDC) cells were significantly increased in newly diagnosed MM, and PD-1 expressed on pDC was significantly decreased in newly diagnosed MM compared to MGUS (P=0.007). Interestingly, PD-1 and its ligand PD-L1 were variably expressed on B cells (2-9% and 3-27%) and PC (0.5-46% and 3-41%) from MM BM samples. Other surface molecules including CD269 (4-32%), CD289 (1-8%), CD362 (0.5-1%) and CD329 (1-4%), were variably expressed in PC.

Conclusion: A better understanding of the neoplastic BM milieu will provide the framework for identifying and validating novel targeted therapies directed against MM. CyTOF technology represents a novel diagnostic tool to assess the status not only of MM, but also of host immunity, and may allow for the development of rational personalized therapies.