S171: Molecular Clusters of Igm Monoclonal Gammopathies Present Distinct Biologic, Immune and Metabolic Features
Year: 2022
Type: article
Study design: Observational Study
Abstract: Background: IgM MGUS and Waldenstrom Macroglobulinemia (WM) represent a wide range of conditions whose management varies from observation to immunochemotherapy. The current classification relies solely on clinical features and does not explain the heterogeneity that exists within each of these conditions. Aims: To shed light on the biology that may account for the clinical differences, we performed the first comprehensive multi-omics analysis of IgM monoclonal gammopathies. Methods: We used bone marrow (BM) CD19+CD138+ sorted cells and matched BM plasma from 32 pts (7 IgM MGUS, 25 WM) and 5 healthy controls to perform whole exome sequencing, RNA-seq, proteomic and metabolomic analysis. 7 matched WM and 4 IgM MGUS pts were also evaluated using mass cytometry (CyTOF). Results: Applying principal component analysis to gene expression profiling, most of WM pts clustered together, while a small subset of them grouped separately with MGUS pts, suggesting a biologic dichotomy within WM. The controls formed a group distinct from most WM and MGUS pts. Fig1A We then applied a non-negative matrix factorization consensus clustering to the gene expression data and identified three robust clusters. Cluster 1 (C1) included only pts with WM, cluster 2 (C2) included pts with both WM and MGUS, and cluster 3 (C3) included all normal controls as well as a small number of WM and MGUS pts. Fig1B-C When mutations commonly identified in WM were analyzed, there was no difference among the three groups (excluding controls) in mutation burden of MYD88 L265P and CXCR4. Interestingly, aberrant expression of TNFAIP3 was a distinct feature of C1 as deletion of 6q (which encodes for TNFAIP3) and TNFAIP3 mutations were each significantly enriched in C1 (47%) compared to C2 (0%) and C3 (20%; p=0.04). Individual clusters associated with specific transcriptional signatures and clinical features. While C1 displayed enrichment of RNA processing, downregulation of inflammatory pathways and aggressive clinical behavior, C2 showed increased inflammatory signaling and senescence with indolent clinical behavior. C3 had intermediate features with combined proliferative and antigen response signatures. Fig1D In accordance with transcriptomics, the proteomic hallmark of C1 was upregulation of proteins involved in proliferation (eg AKT, MAPK) and downregulation of inflammatory proteins (eg IL4, IL10) while the opposite was observed in C2. Once more, C3 confirmed intermediate features with combined upregulation of proliferation and inflammatory proteins. The metabolism was rewired towards mitochondrial anabolism in C1 and C3, while towards glycolysis in C2. Accordingly, C1 and C3 showed undetectable concentrations of 3-hydroxybutyric acid as opposed to C2 which had increased levels of lactic acid, as end products of fatty acid oxidation and glycolysis respectively. Next, we explored whether C1 and C2 displayed a distinct immune profile. tSNE analysis showed that CD4+ T cells were more abundant in C2 compared to C1 while the opposite was observed for CD8+ T cells. Among CD4+ T cells, activated follicular helper (TFH; p=0.02) and regulatory (Treg; p=0.008) cells were predominantly expressed in C2. In contrast, C1 showed a higher expression of senescent T effector memory (TEM) cells. Fig1E In support of this, SPADE clustering analysis identified three clusters including TFH, Treg and TEM cells. Image:Summary/Conclusion: We have identified three molecular clusters in IgM monoclonal gammopathies with distinct clinical, proteomic, metabolomic and immune features, suggesting a potential biologic classification that may have therapeutic implications.
Source: HemaSphere
Institutions: Mayo Clinic, Mayo Clinic Hospital, Mayo Clinic in Florida
Language: English
Subfield: Genetics
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,480
OpenAlex ID: W4283380880