Citations

The immune tumor microenvironment (iTME) plays a crucial role in disease biology of plasma cell (PC) dyscrasias, but remains poorly characterized in self-identified Black individuals, a population at increased risk. Mass cytometry and scRNA-seq of 128 bone marrow aspirates revealed significant changes in immune cell composition across the disease spectrum, including shifts from naïve to effector T cells with declines in B cells, MAIT, pDCs, and increases in monocytes with disease progression. Self-identified Black patients had higher relative proportions of terminally differentiated T cells and lower monocytes in newly diagnosed and treated multiple myeloma (MM). ScRNA-seq revealed genes overexpressed in self-identified Black individuals were enriched for E2F targets and G2-M checkpoints, while reduced genes were enriched for TNF-α/NF-kB, interferon and inflammatory responses pathways. These findings were supported by genetic ancestry and validated in an independent dataset of 286 patients with MM from the MMRF Immune Atlas. Self-identified race and African genetic similarity are significantly associated with remodeling the MM iTME, with potential implications for disease biology and treatment response.

Background: Beside fibril-forming proteins, amyloid deposits contain other proteins which can influence organ toxicity, disease initiation and clearance. We investigated the association between the amyloid plaque proteomic signature of diagnostic renal biopsies from patients achieving deep and sustained hematologic remissions and renal organ response in AL amyloidosis. Methods: Retrospective study of newly diagnosed AL amyloidosis patients between 2010-2020. Patients were eligible if; (1) they had a baseline renal biopsy which had undergone laser micro-dissection and mass spectrometry, (2) were assessable for renal response [RenR, non-selective proteinuria ≥1g /24 hours, predominantly albumin], (3) were not on renal replacement therapy and did not experience renal progression within 3-months of diagnosis and (4) had RenR measurements, at least twice annually in the first year from treatment and annually thereafter. Patients who did not obtain a renal complete response (RenCR) required a hematologic very good partial response (VGPR) or better within 6 months of treatment initiation, sustained for a minimum of 6 months. Hematological and renal responses were graded according to consensus criteria. Overrepresentation analyses of differentially expressed proteins were performed using the WebGestalt 2019 and the reactome pathway database. A false detection rate corrected p value <0.05 was used to identify significantly overrepresented proteins and pathways. Results: We defined two organ response categories, to capture the extreme ends of the spectrum: renal suboptimal responders (n=24), patients for whom the best renal response was ≤partial response (RenPR), and renal complete responders (n=29), patients who obtained a RenCR at best response. Overall, the median follow-up was 6.7 years (IQR: 5.4-9.2), 6.6 years (IQR: 5.4-8.1) for complete responders, and 8.4 years (IQR: 6.1-11.3) for suboptimal responders. Between renal suboptimal responders and complete responders there was no significant difference in median age (63 vs 63 years, p=0.7), lambda light chain isotype (66% vs 79%, p=0.3), first-line therapy received and renal stage (Stage III: 14% vs 8%, p=0.9). The median time to RenCR was 52-months (IQR: 31-63). Protein pathways over-represented in renal complete responders included 14-3-3 proteins (YWHAG, YWHAH, YWHAQ, YWHAZ), early components of the complement cascade and complement regulatory proteins (C3, C4A, C4B, C8A, complement factor H), keratins, cytoskeletal proteins (tubulin, actin, filamen) and collagen IV. Protein pathways over-represented in renal suboptimal responders included terminal/effector components of the complement cascade (C5, C6, C8B, C9), amyloid signature proteins (ApoA1 and E, vitronectin, clusterin), proteoglycans (heparan sulfate proteoglycan), transgelin and metallopeptidase inhibitor 3. Proteins with the highest-fold increase in renal complete responders included serine protease inhibitor (SERPINA3) and F-box and leucine rich repeat protein (FBXL6), 9.0 x 106 & 7.7-fold, respectively. Proteins with the highest-fold increase in renal suboptimal responders included complement 6 and 8B, 3.5 & 3.6-fold, respectively. Conclusion: This is the first study to identify proteomic determinants of organ response in AL amyloidosis. Molecular chaperones involved in protein aggregate homeostasis, such as the 14-3-3 proteins are upregulated in renal complete responders, similar to what we have shown in our prior work. This suggests that organ responders may have a more favorable microenvironment which “primes” them for organ response after the amyloidogenic light chain has been cleared from the circulation. Renal suboptimal responders (≤RenPR) have elevated levels of terminal complement proteins including membrane attack complex proteins and reduced levels of early components or complement regulatory proteins, which may be responsible for reno-toxic and reno-protective effects, respectively.

Abstract Multiple myeloma (MM) is the most common blood cancer in African American (AA) individuals. AAs have an increased risk of developing Monoclonal Gammopathy of Undetermined Significance (MGUS) and MM compared to non-Hispanic White (NHW) individuals. While several studies have shown a pivotal role for the immune tumor microenvironment (iTME) in MM pathogenesis, the composition of the iTME in AAs with MM is under investigated. Viably frozen whole bone marrow (BM) aspirates from 128 individuals (53 AA and 75 NHW) with either MM (n=65), MGUS (n=28), smoldering MM (SMM, n=13), or healthy controls (n=22) were evaluated by single cell RNA-sequencing (scRNA-seq) or mass cytometry (CyTOF). We characterized 34 (14 AA and 20 NHW) by scRNA-seq and 94 (39 AA and 55 NHW) by CyTOF. CyTOF samples were stained with Maxpar Direct Immune Profiling Assay Kit (Fluidigm), acquired on a Helios mass cytometer and analyzed in Cytobank. Data were analyzed by logistic equivalent regression model with p<0.05 for significance. ScRNA-seq samples were processed as in Yao, 2022. Data were normalized using scvi-tools and clustered by Uniform manifold approximation and projection (UMAP). Differentially expressed markers between clusters were identified using Model-based Analysis of Single-cell Transcriptomics (MAST) in Seurat R package at FDR < 0.05 and log2 fold change > 0.55. ScRNA-seq of the CD45+ non-tumor lymphocytes revealed 17 immune populations (HSC, erythroblast, MDSC, GMP, CD1c+ DC, CD4+ and CD8+ T cell, CD14+ M1 macrophage, CD16+monocyte, monocyte, pDC, naïve B, pre-B, pro-B, memory B, NK/MAIT). CD3E/D+cells were clustered into naïve/central memory (CCR7+, LEF1+, SELL+), memory (GZMK+), effector (GZMB+, GZMH+, FGFBP2+), g/d (TRDC+), MAIT (SLC4A10+, KLRB1+) and IFN CD8+ T cells (IFIT1+, IFIT2+,IFIT3+). Disease progression was associated with increases in median CD4+ and CD8+ GZMK+ T cells, memory B cells and a reduction in all monocyte clusters. Within the diseased cohort in comparison to NHW patients, AA patients had increased CD3+ T cells (CD4 and CD8+) (AA 57.5% vs. NHW 44.3%) and a reduction in overall monocytes (AA 10.5% vs. 26.5%). These results were validated by CyTOF, which confirmed an increase in CD3+ T cells (AA 53.7% vs. NHW 35.7%, p<0.001) including increases in CD8+ (AA 7.0% vs. NHW 3.2%, p<0.05) and CD4+ terminal effector T cells (AA 5.7% vs. NHW 2.7%, p<0.05) and a reduction in monocytes (AA 18.3% vs. NHW 26.6%) among AAs. After adjusting for age and sex, AAs retained an increase in T cells (OR 1.59 (95%CI 1.2-2.01, p=0.00023)) and a reduction in monocytes (OR 0.88 (95%CI 0.78-1, p=0.045)). Despite the increase in CD8+ T cells in AA patients, we identified reduced GZMK+ T cells and reductions in exhaustion markers (TIGIT, LAG3, TOX) in CD8+ T cells in comparison to NHWs. Nevertheless, the distribution of the immune populations was similar between healthy AA and NHW individuals. Our multiomics approach to characterize the iTME identified significant differences among AA compared to NHW patients with MM. Citation Format: Suganti Shivaram, Hongwei Tang, Huihuang Yan, Shulan Tian, Guyu Qin, Emilie Anderson, Neeraj Sharma, Abiola Bolarinwa, Cinthya Zepeda-Mendoza, Stacey Lehman, Felicia Gomez, Amit Mitra, Surendra Dasari, Taxiarchis Kourelis, Shaji Kumar, Linda Baughn. Characterization of the Immune Tumor Microenvironment in a Diverse Cohort of Patients with Multiple Myeloma [abstract]. In: Proceedings of the Blood Cancer Discovery Symposium; 2024 Mar 4-6; Boston, MA. Philadelphia (PA): AACR; Blood Cancer Discov 2024;5(2_Suppl):Abstract nr P06.

Background: It has been recently demonstrated that altered lipid metabolism involving increased free fatty acids (FFAs) uptake supports the growth and proliferation of MM cells (Panaroni et al. Blood 2022; Farell et al. Elife 2023). Whether the availability of FFAs in the bone marrow (BM) microenvironment is associated with the pathogenesis of MM from MGUS has not been previously evaluated. Thus, we evaluated if individual species of FAs or FA-containing lipids such as triacylglycerols (TAGs), diacylglycerols (DAGs), and monoacylglycerols (MAGs) are differentially present between the BM microenvironment of MGUS and MM patients. Methods: Lipid profiles of BM plasma samples (reflective of the BM microenvironment) from patients with a spectrum of plasma cell disorders (22 MGUS and 24 MM (15 newly diagnosed and 9 relapsed/refractory)) were acquired by liquid chromatography (LC)/tandem mass spectrometry (MS), and individual lipid species were quantified based on single-point quantification using 55 isotopically labeled internal standards. Concentration-based lipid species data was analyzed by the web-based tool MetaboAnalyst 5.0. Data was normalized by quantile normalization, log transformed and scaled by Pareto scaling. p values <0.05 were considered significant. Results: A total of 993 distinct lipid species were quantified by the MS-based targeted lipidomics assessment. Of these lipid species, the levels of individual mid-chain (≤50 carbon chain length) and long-chain (≥52 carbon chain length) polyunsaturated TAGs were the most differentially present in the BM plasma of MM compared to MGUS patients (Figure 1A). Even though a principal component analysis (PCA) involving all lipid species showed moderate separation of MM from MGUS patients, five MGUS patients (categorized as MGUS-other (MGO)) who clustered more towards MM patients compared to the remaining MGUS patients had a distinct pattern of individual mid and long-chain polyunsaturated TAG levels that were comparable to MM patients (Figure 1B). Furthermore, the proliferation rate of clonal plasma cells in the BM of these MM and MGUS as measured by the S-phase% was found to be directly correlated with the level of long-chain polyunsaturated TAGs. Conclusions: Mid and long-chain polyunsaturated TAGs are present in lower and higher levels, respectively, in the BM microenvironment of MM compared to MGUS patients. These findings continue to support the importance of FA-containing TAGs and other lipids in the pathogenesis of MM. Future confirmatory studies evaluating the biological significance of these differences are required to determine if they can be exploited for diagnostic and therapeutic purposes.

Background: Upfront autologous stem cell transplant (ASCT) is the standard-of-care for newly diagnosed multiple myeloma (MM) patients. However, relapse and the development of therapy-related myeloid neoplasms (t-MN) post ASCT results in considerable morbidity and mortality. We hypothesized that enrichment of abnormal myeloid progenitors and immune effector cells (IEC) in peripheral blood stem cells (PBSCs) of patients with MM is associated with a higher risk of relapse and development of t-MN. Methods: After institutional review board approval, we screened patients with active MM that were evaluated at Mayo Clinic, Rochester, MN between 01/01/2003 and 12/31/2020. Patients that underwent an ASCT and had cryopreserved PBSC product available for research were included. Using mass cytometry, we performed a comprehensive immunophenotyping of mobilized cryopreserved PBSCs from 54 MM patients undergoing 1 st ASCT, using validated antibody panel of 37 lymphoid- and myeloid-based markers each. Flow cytometry standard files were normalized and concatenated using the Fluidigm acquisition software. Flow cytometry standard files were uploaded to the OMIQ software from Dotmatics (www.omiq.ai, www.dotmatics.com), where transformation and cleaning (doublets, debris) were performed. To correct for between-sample technical variations (“batch effects”), we used fdaNorm within the omiq.ai platform. Clustering and visualization of normalized and concatenaded flowcytometry files were performed within the omiq.ai platform using PhenoGraph and UMAP, respectively. We performed principal component analysis (PCA) to identify major immunomic drivers of variability across patients. We explored the associations between immune subsets and the dichotomized clinical outcomes of interest: progression-free (PFS), myeloid neoplasm-free (MNFS) and overall survival (OS) from ASCT. A 2-sided false discovery rate adjusted P-value of <0.05 was considered significant when multiple comparisons were performed; otherwise, a P-value of <0.05 was considered significant. Results: The most abundant cell populations were T-cells (49% of the CD45 +) and myeloid cells (43% of the CD45 + cells). Clustering on the CD45 + cells revealed 30 unique lymphoid clusters and 27 unique myeloid clusters. Subclustering on NK-cells identified an additional 16 NK-cell clusters. On PCA, principal components-1 (PC-1) and 2 (PC-2) explained 15.2% and 12.5% of the variability in the data, respectively. A high PC-2 score was associated with inferior median PFS (20 vs. 52 months; P=0.005, Figure 1A), MNFS (52 vs. 85 months, P=0.03, Figure 1B) and OS (64 vs. 106 months, P=0.01) from ASCT. Immune subsets enriched in the high PC-2 cohort included the ‘NKT-like’ (CD56 +) T-cell subset which expressed the inhibitory CD159a receptor and TIGIT; a terminally differentiated (CD27/CD28 -, CD57/KLRG1 +) and exhausted (TIGIT/PD-1 +) T cell subset, 2 exhausted (TIGIT/PD-1 +) T cell subsets; an immunosenescent (CD27/CD28 -, CD57/KLRG1 +) T cell subset as well as a terminally exhausted (C27/C28 -, KLRG1/PD-1/TIGIT +) TCRgamma-delta subset. Immune subsets with high loadings within PC-1 (associated with improved clinical outcomes) consisted exclusively of CD4 + cells with early memory phenotypes (CD27/CD28/CD127 +). Abnormal expression of CD7 and HLA-DR expression on myeloid progenitor cell subsets was associated with an inferior PFS, MNFS, and OS. A NK-cell subcluster, characterized by an immature (CD56 high), inhibitory (CD159a +, NKG2A) phenotype, was enriched in patients developing t-MN (0.33% vs. 0.17%, P=0.006). Conclusion: We identify abnormal myeloid and immune effector cells in the PBSCs of patients with MM, even prior to ASCT. Patients with a PBSC product that is enriched in immunosuppressive T and myeloid cell subsets, and with a lower proportion of antigen presenting cells, progenitor populations, and anti-tumor macrophages have a shorter PFS and MNFS. This suggests that the predisposition to t-MN and inferior outcomes for MM are possibly determined early in the disease course. These findings need external validation and have the potential to guide sequencing of future treatment modalities.

As part of the Multiple Myeloma Research Foundation (MMRF) immune atlas pilot project, we compared immune cells of multiple myeloma bone marrow samples from 18 patients assessed by single-cell RNA sequencing (scRNA-seq), mass cytometry (CyTOF), and cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) to understand the concordance of measurements among single-cell techniques. Cell type abundances are relatively consistent across the three approaches, while variations are observed in T cells, macrophages, and monocytes. Concordance and correlation analysis of cell type marker gene expression across different modalities highlighted the importance of choosing cell type marker genes best suited to particular modalities. By integrating data from these three assays, we found International Staging System stage 3 patients exhibited decreased CD4+ T/CD8+ T cells ratio. Moreover, we observed upregulation of RAC2 and PSMB9, in natural killer cells of fast progressors compared with those of nonprogressors, as revealed by both scRNA-seq and CITE-seq RNA measurement. This detailed examination of the immune microenvironment in multiple myeloma using multiple single-cell technologies revealed markers associated with multiple myeloma rapid progression which will be further characterized by the full-scale immune atlas project. Significance: scRNA-seq, CyTOF, and CITE-seq are increasingly used for evaluating cellular heterogeneity. Understanding their concordances is of great interest. To date, this study is the most comprehensive examination of the measurement of the immune microenvironment in multiple myeloma using the three techniques. Moreover, we identified markers predicted to be significantly associated with multiple myeloma rapid progression.

AbstractAltered energy metabolism and changes in glycolytic and oxidative phosphorylation pathways are hallmarks of all cancer cells. The expression of select genes associated with the production of various enzymes and proteins involved in glycolysis and oxidative phosphorylation were assessed in the clonal plasma cells derived from patients with newly diagnosed multiple myeloma (NDMM) enrolled in the Multiple Myeloma Research Foundation (MMRF) CoMMpass data set. A scoring system consisting of assigning a point for every gene where their fragments per kilobase of transcript per million (FPKM) was above the median yielded a minimum of 0 and a maximum of 12 for the set of genes in the glycolytic and oxidative phosphorylation pathways to create a total energy metabolism molecular signature (EMMS) score. This EMMS score was independently associated with worse progression free survival (PFS) and overall survival (OS) outcomes of patients with NDMM. A higher EMMS score was more likely to be present in clonal plasma cells derived from Multiple myeloma (MM) patients than those from patients with monoclonal gammopathy of undetermined significance (MGUS). This was functionally confirmed by the clonal plasma cells from MM patients having a higher rate of mitochondrial and glycolysis‐derived ATP formation than clonal plasma cells from MGUS patients. Thus, this study provides evidence for the effect of energy metabolism within clonal plasma cells on pathogenesis and outcomes of patients with MM. Exploiting the energy‐producing metabolic pathways within clonal plasma cells for diagnostic and therapeutic purposes in MM should be explored in the future.

Abstract Introduction: Altered cellular metabolism is a hallmark of every cancer cell. Aerobic glycolysis ("The Warburg Effect") is one of the earliest recognized metabolic abnormalities in cancer cells whereby extracellular glucose is preferentially metabolized and eventually processed to generate lactate and energy in the form of ATP before the former is released extracellularly, irrespective of oxygen availability. While extracellular lactate produced and released from cancer cells has traditionally been considered a waste metabolic by-product, recent understanding of cell metabolism suggests that it can also serve as a primary metabolic fuel for cancer cells via uptake by monocarboxylate transporters (MCTs). Our goal was to evaluate this "Reverse Warburg Effect" phenomenon in multiple myeloma (MM) cells and determine if it can be exploited for therapeutic purposes. Methods: All HMCLs, MM1S, RPMI-8226 and U266, were grown in RPMI-1640 cell culture medium containing 11 mM glucose and supplemented with 10% dialyzed fetal bovine serum (FBS) and 2 mM Glutamine. Primary MM cells were extracted using magnetic bead CD138 positive selection from MM patient bone marrow aspirates. For 13C-labeling experiments, HMCLs and primary MM cells were suspended in RPMI-1640 cell culture media containing 13C-labeled isotopes. Isotopomer analysis of glycolytic and tricarboxylic acid (TCA) cycle metabolites from HMCL and primary MM cell pellets was performed using Agilent Technologies 5975C gas chromatography-mass spectrometry. Small molecule inhibitors, AZD3965 and syrosingopine, were purchased from Selleck Chemicals and Sigma respectively. Cellular viability and proliferation were measured using 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyl tetrasodium bromide (MTT) and CCK-8 assays respectively. MCT-1 and MCT-4 antibodies for western blotting were utilized to evaluate their cell membrane expression on HMCLs. Results: The HMCLs, MM1S and RPMI-8226 as well as primary CD138+ cells from MM patient bone marrow were cultured in cell culture media containing physiological levels (1 mM) of U-13C-Lactate. The incorporation of extracellular 13C into the intracellular glycolytic and TCA cycle metabolite pool was observed (Fig 1) based on the expected isotopomeric patterns, demonstrating the Reverse Warburg Effect in MM cells. The relative contribution of carbon substrate by extracellular lactate compared to extracellular glucose was assessed in the following HMCLs: MM1S, RPMI-8226 and U266 cells by culturing in cell culture media containing 3-13C-Lactate and U-13C-Glucose. Extracellular lactate (yellow bar) contribution to the formation of TCA metabolites equaled that of glucose (red bar) based on the expected isotopomer patterns, suggesting the relative importance of extracellular lactate as an essential nutrient like glucose (Fig 2). Since MCT-1 and MCT-4 are key bidirectional cell membrane transporters of lactate in and out of cells, we explored the clinical significance of their gene expression level on clinical outcomes using the COMMPASS dataset provided by the Multiple Myeloma Research Foundation (MMRF). When MM patients were dichotomized at above or below the median of the expression levels of fragments per kilobase of transcript per million (FPKM), MCT-1 and MCT-4 overexpression conferred a worse progression free survival and overall survival (Fig 3). The MCT-1/MCT-4 protein expression was detectable across the various HMCLs: MM1S, U266 and RPMI-8226 (Fig 4). Inhibition of MCT-1 by specific inhibitor AZD3965 was able to reduce proliferation but not affect viability of HMCLs at 48 hours (Fig 5). However, dual inhibition of MCT-1/MCT-4 using syrosingopine was able to significantly reduce proliferation and decrease viability of HMCLs in a dose dependent fashion (Fig 6). Finally, dual inhibition of MCT-1/MCT-4 using syrosingopine reduced the utilization of extracellular lactate into the TCA cycle pool by HMCLs in media containing 3-13C-Lactate (Fig 7). Conclusion: Utilization of extracellular lactate via Reverse Warburg Effect phenomenon appears highly active in MM cells. Disrupting the utilization of extracellular lactate by dual inhibition of both MCT-1 and MCT-4 appears therapeutic. In the future, dual inhibition of MCT-1/MCT-4 in combination with other anti-MM therapies should be evaluated to determine synergistic therapeutic potential. Figure 1 Figure 1. Disclosures Kumar: Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Carsgen: Research Funding; Sanofi: Research Funding; Novartis: Research Funding; Antengene: Consultancy, Honoraria; Beigene: Consultancy; Bluebird Bio: Consultancy; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Roche-Genentech: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding.

Abstract The immediate postautologous stem cell transplant (ASCT) period in multiple myeloma represents a unique opportunity for long-term disease control because many patients have eradicated most of their disease but also a challenge because it is characterized by the increase of immune subsets detrimental to tumor immunosurveillance. The impact of the tumor immune microenvironment (iTME) in post-ASCT outcomes is not known. In this study, we included 58 patients undergoing upfront ASCT and evaluated their cellular and humoral iTME with cytometry by time of flight (CyTOF) and luminex, respectively, at day +60 to 100 post-ASCT. We identified 2 cellular iTME patterns. Group 1 was enriched in T-cell subsets at the opposite ends of the spectrum of T-cell differentiation compared with the rest of the patients, that is, cells already terminally differentiated (immune senescent or exhausted) and naive T cells. This group had worse hematologic responses post-ASCT, inferior survival, and shorter time to hematologic progression independent of established risk factors. No differences in the humoral iTME were noted between the 2 groups. In addition, no differences in the cellular/humoral iTME were noted according to high-risk fluorescence in situ hybridization status, early or late relapse. Finally, males had higher levels of natural killer cells negative for CD16, a key receptor mediating antibody-dependent cell cytotoxicity, a major mechanism of antitumor efficacy by therapeutic antibodies such as elotuzumab. Our findings suggest that T-cell iTME dysfunction post-ASCT, some of which could be reversible (exhaustion), correlates with worse outcomes. These results could be used to guide rational selection of post-ASCT maintenance/consolidation approaches in these patients.