Monoclonal Gammopathy Of Undetermined Significance Samples Research Articles

B-075 Evaluation of patients with monoclonal gammopathy of undetermined significance using Optilite Freelite assays

Abstract Background Monoclonal gammopathy of undetermined significance (MGUS) is a pre-malignant disorder with a progression risk to multiple myeloma of 1% per year. Patients with MGUS may produce monoclonal intact immunoglobulins (Ig) and/or free light chains (FLC). The International Myeloma Working Group (IMWG) recommendations for the use of FLC measurements in MGUS are to establish the diagnosis of light chain only MGUS (LC-MGUS) and further to risk-stratify newly diagnosed MGUS. Once identified, MGUS is longitudinally monitored at intervals dependent on the risk of transformation. The IMWG recommends serum protein electrophoresis (SPEP) for monitoring of known MGUS with intact Ig, however others have published benefits of additionally monitoring with FLC. In this study, we evaluated the diagnostic sensitivity and specificity of the Optilite® Freelite® Kappa Free Kit and the Optilite Freelite Lambda Free Kit (The Binding Site, part of Thermo Fisher Scientific) in patients with MGUS, and the monitoring performance of Freelite results measured in serial samples from patients with clinically stable and progressive MGUS. Methods Serum samples from 234 patients with clinically diagnosed MGUS and 140 disease controls, taken at single time points, and serial samples (≥3) from 49 patients with MGUS were tested with the Freelite assays. Intact M-protein presence and isotype was confirmed in MGUS samples with immunofixation electrophoresis (IFE). In patients clinically diagnosed with LC-MGUS, the presence of detectable M protein on IFE was not required. The disease control cohort (non-MGUS) had disorders commonly associated with elevated polyclonal immunoglobulins (e.g autoimmune, liver, and renal diseases), confirmed by total IgG and/or IgA and/or IgM results and the absence of M-protein by IFE. Patients represented a diverse population from both European and US sources. Results The overall diagnostic sensitivity of the Optilite Freelite assays was 59.4%, calculated as the frequency of abnormal free light chain ratio (rFLC) in intact immunoglobulin MGUS, and abnormal rFLC with concurrent elevated involved FLC level in LC-MGUS. The diagnostic sensitivity was: 58.0% in non-IgM MGUS, 41.7% in IgM MGUS, 66.7% in biclonal MGUS and 100% in LC-MGUS. In intact (IgG/IgA/IgM) kappa MGUS, the diagnostic sensitivity was 67.5%, versus 41.5% in intact (IgG/IgA/IgM) lambda MGUS. The diagnostic specificity was 86.4%. In the 49 patients with serial samples, concentrations of involved FLC were stable in 93.3% of patients with clinically stable MGUS, whereas in patients with clinically progressive MGUS an increasing trend was seen in 50% of cases. Conclusions These results demonstrate that the Optilite Freelite Kappa and Lambda assays produce clinically relevant results that are useful in the evaluation of MGUS.

Single Nuclei Multiomics Analysis of Transcriptional and Chromatin Accessibility of Tumor Cells Uncovers Molecular Signatures and Regulatory Elements of Malignant Clonal Evolution in Multiple Myeloma

Category Multiple Myeloma and Plasma Cell Dyscrasias: Basic and Translational Introduction Multiple myeloma (MM) is a hematological cancer resulting from abnormal proliferation of plasma cells (PC) in bone marrow. The progression of the disease from Monoclonal Gammopathy of Undetermined Significance (MGUS), Smoldering Multiple Myeloma (SMM), to MM involves multiple drivers and dynamic interactions of premalignant/malignant cells. In the advancement of single-cell technologies, the same-cell readouts of nucleus RNA sequencing (snRNA-seq) and Assay for Transposase-Accessible Chromatin sequencing (snATAC-seq) provide a less biased measurement of gene expressions and chromatin accessible regions. Profiling and analyzing both omics data at different stages of MM may reveal essential molecular signatures and regulatory elements for microenvironmental modification and evolution. These insights could benefit MM patients as novel targets for early therapeutic intervention at different stages of progression. Methods Bone marrow aspirates were collected from 33 individuals: Healthy donors (n=3), patients with MGUS (n=2), SMM (n=5), MM (n=21), and Plasma Cell Leukemia (PCL; n=2). Viable mononuclear cells underwent CD138+ sorting and nuclei isolation prior to library preparation. Libraries were prepared with the Chromium Multiome kit (10X Genomics) and sequenced on NovaSeq S4 flow cells at UAMS. The clonal V(D)J arrangements of each sample and expression level from HD samples were used to distinguish malignant (MM) from normal plasma cells (PC). The MM data from snATAC-seq and snRNA-seq were integrated using Signac with the weighted nearest neighbor methods from Seurat. All inter- and intra-tumor clusters were evaluated for markers of high-risk disease, differential gene expression, differentially accessible regions, and transcription factor activities. Results We performed snRNA-seq and snATAC-seq sequencing to generate multi-stage, molecular classified-specific chromatin accessibility and transcriptional profiles of plasma cell neoplasms comprising 439,134 cells across 33 samples. The malignant plasma cells for each sample were extracted by the unique clonotypic signature of the immunoglobulin gene rearrangement. Of these, we detected the highest clonality in MGUS samples, suggesting clonal competition at the premalignant stage. Based on our primary microarray data, we detected the overexpression of molecular signatures for most cells in each sample, confirming the intratumor cell heterogeneity. Furthermore, we used the ratio of 70-gene signature of aggressive disease and proliferation signatures to investigate the clonal composition of MM cells corresponding to the risk of relapse. Surprisingly, the proportion of high-risk cells increased respectively from low to high-risk samples. The expansion of high-risk clonality might exhibit competition among malignant cell subpopulations regarding microenvironmental adaptation. The multiomics integration generated less distinct clusters between MGUS and SMM, indicating the gradual complex alterations of subclonal gene expression and chromatin accessibility in malignant transformation. Interestingly, most accessible regions were found in intronic/distal intergenic regions implying the long-range gene regulation from cis-regulatory elements. Based on the positive/negative correlation of binding motifs within differentially accessible regions, we identified unique enriched transcription factors for each disease stage, suggesting the mechanism patterns in the evolutionary process of malignant cells. Conclusion In the largest multiomics study to date of CD138+ cells, we demonstrate the malignant clonal evolution using gene expression and chromatin accessibility profiling from patients with early-stage disease to highly aggressive form. Throughout the time of disease progression, we found an increase in the proportion of malignant cells with high-risk signatures. Also, we uncover unique signatures of chromatin accessibility for each molecular classification that can further refine our understanding of functional heterogeneity in multiple myeloma. Collectively, our joint single nuclei profiling reveals additional insights into the malignant clonal evolution and investigates novel regulatory elements involved in disease progression.

Light Chain Amyloidosis Plasma Cells Show Specific Chromatin Accessibility and Transcriptome

Immunoglobin light chain amyloidosis (AL) is a monoclonal gammopathy characterized by the accumulation of malignant plasma cells (PC) in the bone marrow. These PCs secrete misfolded immunoglobulin light chains fibrils, which deposit in various organs, leading to organ dysfunction. Unlike other monoclonal gammopathies such as Multiple Myeloma, both its rarity and the lower BM PC burden has limited the deep study of the tumor population. The aim of this study was to analyze the transcriptome and epigenome of the PC from patients with AL amyloidosis to identify the role of chromatin modifications in the pathogenesis of the disease. Highly purified clonal PCs were obtained from bone marrow aspirates samples of 58 AL amyloidosis patients at diagnosis, 19 monoclonal gammopathy of undetermined significance (MGUS), 149 MM and 17 healthy donors. RNA was obtained from PCs and Illumina Stranded Total RNA-seq protocol was performed according to manufacturer's specifications. Accessible chromatin mapping was performed using FAST-ATACseq (Corces et al, 2016) with minor modifications. The data obtained were aligned with the GRCh38 version of the human genome and custom pipelines were used for computational analyses. Expression of immunoglobulin genes was removed for RNAseq analysis. Unsupervised principal component analysis of the RNAseq and ATACseq data showed a clear distinction between PCs from AL patients, MM and HD. To obtain a reliable measure of the magnitude of epigenomic and transcriptome changes in AL, we compared the RNAseq and ATACseq data of AL with MM or HD. The RNAseq analysis showed some clear transcriptional programs (TPs) related to AL and different from MM and HD (Figure 1): TP1 showed 89 genes upregulated and associated with positive regulation of protein kinases and TP2 showed 274 genes downregulated and correlated with immunoregulatory interactions and mitotic regulation. On the other hand, TP3 included 560 downregulated genes associated with glutamate pathway and glycosylation of proteins and TP4 revealed 362 upregulated genes linked with B cell activation. Both patterns were identified in AL patients and HD in comparison with MM patients. Regarding chromatin accessibility, we detected a similar number of ATAC peaks between the AL and MGUS samples and with a significant difference compared to the MM samples (p=0.00014), suggesting that AL and PCs from MGUS have a lower chromatin accessibility (Figure 2). These results provide evidence that the biological perturbations in the chromatin accessibility and transcriptome of PCs from AL patients are highly specific. Although the results depicted in Figure 1 demonstrate that AL patients clustered together by relatively homogenous chromatin accessibility and transcriptome, compared with MM patients, we further investigated whether there were any discernible differences among AL patients themselves. To address this, we conducted an analysis of chromatin accessibility and transcriptome in relation to various factors, including age, gender, organ affected, light chain isotype, percentage of tumoral PCs, presence of t(11,14) or amp1q. Remarkably, we identified differences in the transcriptome between AL patients with and without t(11;14), identifying, 46 upregulated genes linked with T cell and lymphocyte apoptosis and inflammatory cytokines production and 257 downregulated genes linked with FGFR family ligand binding and activation and protein ubiquitination and phosphorylation, in t(11,14) positive AL patients. These results suggest that t(11;14) may exert a significant modulation on the transcriptome of PCs of AL patients. Finally, scRNAseq was performed to address the heterogeneity of PCs. Preliminary analysis has shown a remarkable homogeneity in malignant PCs from AL patients with very limited transcriptional differences between PCs clusters. In summary, in this study we have characterized the PCs of AL patients revealing a homogeneous and specific chromatin accessibility and transcriptome that could contribute to explain the differences between AL and other gammopathies, such as MM. In addition, the identification of these epigenetic and transcriptomic alterations in AL will allow us to better understand the aberrant biology driving this disease, such as those AL with t(11;14). Moreover, these findings open new avenues for the development of innovative therapeutic strategies to improve the outcomes for AL patients.

Unveiling Novel Therapeutic Targets for CAR Therapy in Multiple Myeloma through Single-Cell RNA Sequencing

Multiple Myeloma (MM) is a hematological malignancy characterized by the clonal proliferation of plasma cells. Among the different therapeutic options in this setting, chimeric antigen receptor (CAR) T cells recently showed unprecedent achievements in term of progression free survival. However, despite advancements in current therapies, the disease's heterogeneity remains a major challenge and all patients unavoidably relapse, rendering innovative approaches to identify precise therapeutic targets eagerly awaited. Along this line, the revolution of single-cell (sc) technologies brings new opportunities to identify precise therapeutic targets, including abundant and unique surface proteins for CAR therapy. In this study, by analyzing individual cancer cells at sc level, we aim to identify novel surface targets, facilitating the development of novel personalized cellular therapies as well as treatment sequences. To this end, we used samples collected from 9 publicly available single-cell RNA sequencing (scRNA-seq) datasets (GEO accession numbers: GSE176131, GSE189460, GSE223060, GSE210079, GSE145977, GSE124310, GSE161801, GSE163278, GSE161722) obtained from 156 patients affected by monoclonal gammopathies (19 monoclonal gammopathy of undetermined significance (MGUS), 10 smoldering multiple myeloma (SMM), 78 MM and 25 relapsed/refractory multiple myeloma (RRMM)) and 24 normal bone marrows (NBM), to conduct an unbiased search for genes showing specific expression in plasma cells (PCs), regardless of disease status. We found 15 genes showing differential expression in PCs (adj.pval<0.01 and logFC>1) and coding for surface proteins: TNFRSF17(BCMA), SDC1 (CD138), FCRL5 (GPRC5D), TNFRSF13B (TACI), CD38, SLAMF7 (CS1), CD59, FCGR2B, FGFR3, SLC44A1 (CTL1), CD320, FCRL2, IL15RA, INSR and SLAMF1. As expected, most of these molecules already represent critical therapeutic targets. After completing our initial analysis, we compared PCs transcriptomes from MM/RRMM patients with NBM, MGUS, and SMM samples. Among previously identified genes, CD320 only was significantly overexpressed in MM PCs. Next, we investigated associations between cytogenetic-related cell subclusters and previously identified surface markers. Interestingly, we found a significant association between the expression levels of TACI/CD59 and the overexpression of CCND2 and MAF, both associated with the presence of t(14:16). Next, we decided to focus on the first five genes (according to expression ranking) that do not currently have an active clinical development program in advanced phases, namely: TNFRSF13B, CD59, FCGR2B, SLC44A1, and CD320 (Fig. 1 A, values dichotomized based on their median) to uncover their (potential) impact/association with patient's outcome. In our analysis of different available expression profiling datasets (GSE4204, GSE2658, GSE57317, GSE4581, GSE4452, GSE9782, the CoMMpass study NCT01454297) involving around 2000 MM patients, we observed TNFRSF13B, CD59, and FCGR2B expression correlated with improved outcome while CD320 and SLC44A1 expression associated with worse outcome (Fig. 1 B). In conclusion, we integrated results from both scRNAseq and bulk-RNAseq/microarray data to identify new targets genes to be used in the context of personalized medicine. Interestingly, CD320 emerges as a potential candidate biomarker useful for monitoring disease evolution and predicting worse outcomes. Additionally, this approach led us to identify a series of potential new targets for MM patients, depicting a new scenario where each patient could be “screened” to identify the best molecule to be targeted. While further investigation is necessary to assess off-target toxicity and confirm clinical relevance, our analyses significantly streamline the search for tumor markers with a method potentially applicable to different malignancies, bringing us closer to identifying the best candidates for effective CAR therapy.

Characterization of monoclonal gammopathy of undetermined significance progression to multiple myeloma through meta-analysis of GEO data

The etiology of monoclonal gammopathy of undetermined significance (MGUS) and multiple myeloma (MM) is still obscure as are the processes that enable the progression of MGUS to MM. Understanding the unique vs. shared transcriptomes can potentially elucidate why individuals develop one or the other. Furthermore, highlighting key pathways and genes involved in the pathogenesis of MM or the development of MGUS to MM may allow the discovery of novel drug targets and therapies.We employed STARGEO platform to perform three separate meta-analysis to compare MGUS and MM transcriptomes. For these analyses we tagged (1) 101 MGUS patient plasma cells from bone marrow samples and 64 plasma cells from healthy controls (2) 383 MM patient CD138+ cells from bone marrow and the 101 MGUS samples in the first analysis as controls (3) 517 MM patient peripheral blood samples and 97 peripheral blood samples from healthy controls. We then utilized Ingenuity Pathway Analysis (IPA) to analyze the unique genomic signatures within and across these samples.Our study identified genes that may have unique roles in MGUS (GADD45RA and COMMD3), but also newly identified signaling pathways (EIF2, JAK/STAT, and MYC) and gene activity (NRG3, RBFOX2, and PARP15) in MGUS that have previously been shown to be involved in MM suggesting a spectrum of molecular overlap. On the other hand, genes such as DUSP4, RN14, LAMP5, differentially upregulated in MM, may be seen as tipping the scales from benignity to malignancy and could serve as drug targets or novel biomarkers for risk of progression. Furthermore, our analysis of MM identified newly associated gene/pathway activity such as inhibition of Wnt-signaling and defective B cell development. Finally, IPA analysis, suggests the multifactorial, oncogenic qualities of IFNγ signaling in MM may be a unifying pathway for these diverse mechanisms and prompts the need for further studies.

Abstract 779: Clonal B-cell expansion and the potential challenges to blood-based early cancer detection

Abstract Introduction: Confounding signals originating from white blood cells (WBCs) have been reported as a potential source of false positives for blood-based early cancer detection and disease monitoring. Additionally, the level of aberrant signal originating from clonal expansion (CE) in precursor conditions, such as monoclonal B-cell lymphocytosis (MBL) and monoclonal gammopathy of undetermined significance (MGUS), is not well understood. To characterize CE in a potential screening population, we profiled samples from non-cancer (NC) participants and compared them to samples from participants with hematological precursor and neoplastic conditions (HPNCs). Methods: Using LymphoTrack IGH FR1 Assay (Invivoscribe, Inc), we sequenced DNA derived from WBCs from a subset of enrollees in the Circulating Cancer Genome Atlas study (NCT02889978) comprising NC participants, balanced for age and gender, and participants diagnosed with an HPNC (chronic lymphocytic leukemia [CLL], multiple myeloma [MM], MBL, or MGUS). Additional samples were titrated and processed to determine the limit of quantification (LoQ). Results: Using 12 titration samples, we determined the LoQ of detecting an unknown clone against a polyclonal background to be 0.1% of the total reads. The threshold used to determine evidence of CE was 2.5% of the total reads. We sequenced samples from 112 individuals, 67 of whom were NC participants (35 male of median [range] age 67 [33-85] years; 32 female of 60 [30-85] years). A large fraction of NC samples (10/67; 15%) showed evidence of CE: 9/10 (90%) were monoclonal with clonal percent total reads (PTR) ranging from 2.7% to 80.4% (median: 6.0%), and 7/9 had a mutation rate >2%, indicating somatic hypermutation (SHM). One sample exhibited oligoclonality with 2 clones (6.6% and 3.2%), and both had SHM. Most NC samples (57/67; 85%) lacked evidence of CE: median top clone PTR of 0.10% (mean: 0.18%; SD: 0.24%) and median Simpson clonality of 0.0021 (mean: 0.0030; SD: 0.0030). A positive correlation between the top clone PTR and age was also observed (⍴=0.41 all participants, ⍴=0.43 excluding 80.4% PTR). All CLL samples (9/11 monoclonal; 2/11 oligoclonal) and 3/4 MBL samples showed evidence of CE. Consistent with the observation that a limited number of plasma cells are expected to be in circulation, only 3/10 MM samples and 7/20 MGUS samples showed evidence of CE; 1 MM and 3 MGUS samples had a top clone PTR of >40%. Conclusion: A large fraction of NC samples (15%) had evidence of expanded lymphoid clones with SHM. The PTR of the top clone underscores the higher frequency of CE associated with increased age in asymptomatic participants. Clonal expansion of blood cell lineages can also carry genetic or epigenetic alterations that are similar to those associated with non-hematologic cancers. Thus, differentiating aberrant signals originating from various hematologic compartments is key for accurate early cancer detection. Citation Format: Jing Xiang, Qinwen Liu, Rita Shaknovich, Oliver Venn. Clonal B-cell expansion and the potential challenges to blood-based early cancer detection [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 779.

Single Cell Characterization of Myeloma and Its Precursor Conditions Reveals Transcriptional Signatures of Early Tumorigenesis

Our understanding of disease progression in multiple myeloma (MM) and its precursor conditions, monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM), is classically founded on bulk analysis studies. Low disease burden at the precursor stages has precluded comprehensive analyses of the transcriptomic events underlying malignant transformation. Here, we use single-cell RNA sequencing data from 29,387 bone marrow plasma cells from 26 patients with MGUS, SMM, or MM and 9 healthy controls to characterize the transcriptional transformation at each step of progression.Due to varying disease burdens, many samples contained a mixture of healthy and neoplastic plasma cells. We leveraged this impurity to perform a patient-specific characterization of the disease, comparing each patient's neoplastic and healthy plasma cells. This approach isolated the disease phenotype in each patient, which is usually confounded by biological and technical variability when comparing tumors to samples from healthy donors.We found that neoplastic cells from patients with MGUS and SMM already exhibit phenotypic changes similar to those of advanced myeloma. We observed upregulation of genes corresponding to known MM subtypes, such as CCND1 in patients with t(11;14) translocations and other known driver genes such as HIST1H1C. We also found universal downregulation of certain genes such as CD27, a member of the tumor necrosis factor receptor family associated with the differentiation of B cells into plasma cells, which may signify a common loss of a normal plasma phenotype across samples with different driver events and stages.Pathway analysis of differentially expressed genes further revealed that biological pathways related to myeloma were altered as early as MGUS. We observed that SMM patients with hyperdiploidy exhibit upregulation of ribosomal proteins, as reported in advanced disease. Upregulated genes in select MGUS and SMM samples were enriched for the eukaryotic translation initiation factor 3 (eIF3) complex, which plays important roles in translation, as well as proteasome activity, a function central to the survival of MM and targeted by therapies such as bortezomib. We observed enrichment of the E2F family of transcription factors in MGUS and SMM samples; these are master regulators of proliferation that have been suggested as therapeutic targets in myeloma. Five samples were enriched for genes associated with extracellular exosomes, which has been reported to play an important role in cancer cell signaling and to contribute to osteolysis and drug resistance in MM. Pathway enrichment of genes downregulated in neoplastic cell populations revealed weakened response to endoplasmic reticulum and oxidative stress, presumably allowing myeloma cells to tolerate high volumes of abnormal protein production without apoptosing.To further identify shared gene expression patterns across samples, we employed a Bayesian Non-Negative Matrix Factorization method to decompose our data into 31 gene signatures that capture its variability. In addition to recovering signatures corresponding to known MM subtypes, demonstrating that our method captures cohesive transcriptional networks, we find signatures that capture disease biology shared across subtypes. Most notably, we identified a signature that is active in healthy plasma cells across disease stages and dramatically lost in MM and precursor cells. The top genes in this signature include CD27 and CD79A, which are associated with the B cell lineage and whose downregulation may signify dedifferentiation of premalignant cells as early as MGUS, and JSRP1, CTSH, and HCST, genes as of yet unreported to be involved in plasma and MM cell biology. This phenotype would be obscured at early disease stages by bulk analysis. We validated the discovery and behavior of this signature in an external single-cell dataset from Ledergor et al. (Nature Medicine 2018).In summary, using single-cell RNA sequencing, we discovered that canonical MM pathways are altered as early as MGUS and identified a signature of genes which distinguishes healthy and neoplastic cells even at early disease stages. Our identification of patient-specific transcriptional changes as early as MGUS paves the way for future work exploring personalized treatment approaches prior to malignant disease. DisclosuresHaradhvala: Constellation Pharmaceuticals a MorphoSys Company: Consultancy. Zavidij: Constellation Pharmaceuticals: Current Employment. Sontag: curai health: Current holder of individual stocks in a privately-held company; Takeda Pharmaceuticals: Research Funding; Genentech: Research Funding; IBM: Research Funding. Ghobrial: AbbVie, Adaptive, Aptitude Health, BMS, Cellectar, Curio Science, Genetch, Janssen, Janssen Central American and Caribbean, Karyopharm, Medscape, Oncopeptides, Sanofi, Takeda, The Binding Site, GNS, GSK: Consultancy. Getz: IBM, Pharmacyclics: Research Funding; Scorpion Therapeutics: Consultancy, Current holder of individual stocks in a privately-held company, Membership on an entity's Board of Directors or advisory committees.

A Novel B Cell Antigen Designated Lambda Myeloma Antigen (LMA) Has Been Identified Using Two Fully Human Monoclonal Antibodies (Mabs) That Bind to Similar Epitopes on Plasma Cells from Patients with Plasma Cell Dyscrasias

Introduction:The novel kappa (κ) myeloma antigen (KMA) has been described and a specific monoclonal antibody KappaMab (formerly MDX-1097) developed which is currently in a Phase IIb clinical trial. In this study 2 human LambdaMabs (10B3 and 7F11) were shown to specifically bind to a conformational epitope in the lambda (λ) light chain constant region when it is held in non-covalent association with lipids in the cell membrane (LMA). The 10B3 Mab binds to all λ isotypes and 7F11 binds to isotypes 2 and 3; neither antibody binds κ light chain or immunoglobulin (Igλ or Igκ).Methods:To detect LMA on λ+ myeloma cell lines and on λ-restricted patient bone marrow (BM) samples, 7F11 and 10B3 Fab'2 fragments were conjugated to APC and R-PE and used to stain the λ myeloma cell lines LP-1, RPMI8226 and OPM-2 followed by flow cytometry analysis. KappaMab Fab'2 (KMA Fab'2) and the κ myeloma cell line JJN3 were used as a negative control and to identify KMA on κ-restricted patient BM samples.Patient BM samples (κ=43 and λ=22) included Monoclonal Gammopathy of Undetermined Significance (MGUS), untreated and treated multiple myeloma (MM) patients, AL amyloidosis, plasmacytoma and Waldenstroms macroglobulinemia (WM). Multiparametric FCM immunophenotyping was performed with the 10B3 Fab'2 fragments and CD38, CD138, CD269 (BCMA), CD319 (SLAM F7), CD56 and CD45 Mabs. Plasma cells (PCs) were identified by the co-expression of CD38 and CD138, then CD138+/CD38+ gated cells were analyzed for 10B3 or KMA, CD269, CD319, and CD56. KMA and LMA Fab'2 fragments were used as negative controls for each other. The antigen density of KMA or LMA versus BCMA on PCs in 55 samples was assessed using Quantibrite beads.Immunohistochemistry (ICH) tissue cross-reactivity studies using validated automated methods on tissue with whole antibody 7F11-biotin and 10B3-FITC were performed on MM cell lines, λ myeloma lung tissue (plasmacytoma) and a panel of 38 normal human tissues. Serial sections from snap frozen blocks were used to retain the conformational epitope and then stained with the λ Mabs and visualised by light microscopy.Results:The conjugated 10B3 Fab'2 fragment bound to LMA-expressing cell lines LP-1, RPMI8226 and OPM-2 (isotypes 1-3) and 7F11 bound to RPMI8226 and OPM-2, (isotypes 2-3); neither bound JJN3. KMA Fab'2 did not bind to λ myeloma cell lines but bound JJN3.Expression profiles for patient BM samples (Table 1) showed KMA was expressed on PCs from untreated (N=9/17; 53%) and treated (N=8/11; 73%) MM samples, whereas BCMA expression was 88% (N=15/17) and 82% (N=9/11) respectively. BM PCs from all 3 plasmacytoma cases and 1 WM case were positive for both KMA and BCMA. BM PCs from MGUS cases were all positive for BCMA and positive for KMA in half the cases studied. The expression of KMA and CD56 was highest on PCs from treated MM patient samples. Antigen density for KMA and BCMA was similar in the untreated patients. In treated patients KMA density was higher than BCMA, other samples had lower antigen density of both KMA and BCMA.LMA (Table 2) and BCMA were expressed on 50% and 90% of untreated MM samples and all LMA+ samples co-expressed BCMA but only 1 co-expressed CD56. All treated λMM samples expressed BCMA and 60% expressed LMA. LMA was positive on PCs from the 3 amyloidosis samples, BCMA was expressed weakly in only 1 of these whereas CD56 was always co-expressed with LMA. MGUS and WM samples did not express LMA. Similar to KMA, the antigen density of LMA and BCMA was equivalent in untreated patients but in treated patients LMA density was higher than BCMA. All 3 amyloidosis samples were λ isotype.IHC results showed that 10B3 and 7F11 bound to myeloma cell lines and 10B3 bound to PCs in λ plasmacytoma sections. Both Mabs bound occasional PCs or dendritic cells in the GI tract mucosa, tonsil and various secondary lymphoid organs. No off-target binding of 10B3 and 7F11 was observed and both antibodies bound occasional PCs in secondary lymphoid tissue.Conclusion:These studies used mostly myeloma samples and a small number of other plasma cell dyscrasias. Nevertheless expression of KMA and LMA was identified on PCs across the spectrum of disease. Within the treated patient cohort the antigen density of KMA or LMA was higher than that of BCMA and implies there is an enrichment of these novel antigens in relapsed refractory myeloma. No off-target binding was observed in normal human tissues and binding was limited to occasional leukocytes in secondary lymphoid tissue. [Display omitted] DisclosuresHu: HaemaLogiX Pty Ltd: Current Employment. Dunn: HaemaLogiX Pty Ltd: Current Employment.

A Whole Blood Gene Expression Signature Accurately Diagnoses Multiple Myeloma and Differentiates Patients in Remission from Those with Active and Progressive Disease

Introduction:A variety of multiple myeloma (MM) gene expression (GEP) signatures have been developed based on plasma cell transcriptomic analyses. Although generally prognostic, these have limited utility for separating overt MM from earlier stages of plasma cell dyscrasias such as monoclonal gammopathy of undetermined significance (MGUS). A disadvantage is they are invasive and require collection of plasma cells by bone marrow biopsy. We investigated the potential of a customized whole blood-based gene expression assay to provide an effective tool for diagnosing MM, differentiate active from progressive or in remission disease and examine the effect of treatment on the signature.Methods:A 26 gene-GEP was obtained from 15 individual MM peripheral blood transcriptomes. Gene transcripts were functionally linked and captured a number of biological processes such as angiogenesis, apoptosis, immune responsiveness, phenotype definition, protein processing (secretion), proliferation, RNA processing and survival. Gene expression was confirmed in 3 human MM cell lines (IM-9, MM1R and NCI-H929). Selective signature expression in MM was confirmed by screening blood of controls (n=26) and 106 MM patients. This signature was then prospectively tested in 67 MM patients (newly diagnosed or progressive, n=35; in remission following treatment, n=32, including 26 complete remissions), 7 MGUS and controls (n=29). Among MM patients, 52% had ISS stage 1 disease, 13% had stage 2 and 22% stage 3. FISH cytogenetic analysis was available in 82% of patients. Hyperdiploidy and chromosome 1 abnormalities were detected in 16 patients each (24%), del13q was present in 43% and high-risk aberrations such as del17p and t(4;14) were found in 12% and 9% of patients, respectively. Median time from diagnosis was 3.5 years. The majority (79%) of pretreated patients had received an autologous stem cell transplant; the median number of prior treatment lines was 1 (range, 1-13). MM mRNA measurement was by PCR withTaqMAN probes and GEP converted to a linear score (MMscore) ranging from 0-100 using the XBG algorithm. Statistical analyses: non-parametric testing (Mann-Whitney), ROC analysis, decision curve analysis, multiple and logistic regression.Results:MMscores were significantly elevated in all MM samples (46±13, p <0.0001) vs. controls (10±11; AUC=0.97, accuracy 96%) and MGUS (36±3, p=0.02; AUC=0.76). The GEP diagnostic accuracy for MM was >95% by Decision curve analysis. MMscores were not related to ISS stage. Scores were significantly lower with prior immunomodulatory therapy (p=0.04) or prior ASCT (p=0.002). MMscores were not correlated with any cytogenetic parameter except for elevation in the 9% with t(4;14) (57±8, p=0.008 vs. no translocation). Levels were significantly increased in active/progressive disease (54±10, p <0.0001: AUC: 0.81) compared to patients in remission following treatment (39±12). The difference between MGUS (36±3) and smoldering MM (SMM: 61±14) was statistically significant (p=0.002). Complete remission had the lowest scores (37±11) and was not significantly different to MGUS (0.36±0.03) but greater than controls (10±11). Multiple regression analysis identified the MMscore to be the only relevant parameter as a predictor of clinical status (F-ratio: 27.2, p <0.0001). The logistic model demonstrated that the MMscore and t(4;14) status accurately (AUC: 0.85) identified the clinical status at the time of blood draw.Conclusions:A blood-based GEP assay accurately (>95%) diagnosed multiple myeloma. This signature was not related to staging or cytogenetic abnormalities except the t(4;14) translocation. Levels accurately identified active and progressive disease differentiating these from complete remission. Of note, MGUS and SMM samples differed significantly. These data thus demonstrate that blood-based monitoring of multiple myeloma transcript levels may facilitate therapeutic management of myeloma disease. DisclosuresDrozdov:Wren Laboratories: Employment. Kidd:Wren Laboratories: Employment. Modlin:Wren Laboratories: Consultancy.

Whole Exome Sequencing of Plasma Cells Precancerosis MGUS and Malignant AL Amyloidosis Reveals Small Number of Shared Mutated Genes

Background: Immunoglobulin light chain amyloidosis (ALA) is a plasma cell dyscrasia that develops, similarly as multiple myeloma (MM), from clinically indistinguishable precancerous stage, monoclonal gammopathy of undetermined significance (MGUS). The specific mutations causing malignant transformation from MGUS to amyloidogenic immunoglobulin producing ALA are still unknown. The next generation sequencing (NGS) technology is a powerful tool that allows comprehensive description of the whole genome sequence. Previous studies have already shown highly overlapping phenotypic profile between ALA and both MGUS and MM and lack of unifying mutations in ALA patients (Paiva, 2016). Here we present whole exome NGS data of aberrant plasma cells (aPCs) obtained from patients with MGUS (n=10) and ALA (n=9). Further comparison of the exome sequences of the precancerosis and malignant stage will help to identify recurrently occurring mutations, novel oncogenic drivers and tumor suppressor genes. This will offer new prognostic markers to distinguish potential malignant plasma cell clones in MGUS that will ultimately lead to the development of fatal ALA.Aims: Revealing the mutational status of aPCs in MGUS and ALA using the whole exome NGS.Material and methods: aPCs and peripheral blood (to exclude germinal mutations) were collected from 9 ALA and 10 MGUS samples. aPCs were separated using fluorescence activated cell sorting and genomic DNA was isolated using AllPrep DNA/RNA Micro Kit (Qiagen) and amplified with REPLI-g Mini (Qiagen). DNA library was prepared using SureSelect Human All Exon V5 Kit and sequenced on Illumina HiSeq 4000 platform with average coverage 50x. Somatic variants were called against human genome version 38 using VarScan v2.0. Only non-synonymous mutations, indels and splice site alterations were considered for further investigation.Results: Using NGS we describe whole exome profile for 9 ALA and 10 MGUS patients. Total number of mutated genes for ALA was 554 (average 69 SNVs per patient) and for MGUS 558 (average 73 SNVs per patient). The number of shared mutated genes between both groups was only 26. Among these genes, we identified 4 functional groups: A) Killer-Cell Immunoglobulin Like Receptors (KIR2DL1, KIR3DL2), B) Mucins (MUC16, MUC3A, MUC6), C) Poly(A) Binding Cytoplasmic Proteins (PABPC1, PABPC3) and D) Serine Proteases (PRSS1, PRSS2, PRSS3). Genetic profiles in ALA and MGUS did not reveal any already known MM driver mutations (KRAS, NRAS, BRAF, FAM46C, TP53 and DIS3), with the exception of one ALA patient possessing mutated DIS3 gene. Importantly, we have observed a significant heterogeneity between the samples, as the number of mutated genes shared by all MGUS or ALA patients was only 7 and 3 genes, respectively.Conclusions: ALA develops from a precancerous stage MGUS. Whole exome sequencing of the aPCs showed comparable number of mutated genes between both disease stages (554 vs. 558). Nevertheless, the mutated genes in both groups were very distinct. We identified only 26 mutated genes shared in both ALA and MGUS. Interestingly, none of these genes was previously linked to tumorigenesis. Moreover, genetic profiles were very heterogeneous among individual patients. Future analysis of the presented data will include comparison with genomic profiles obtained from MM plasma cells to reveal additional insights into the mechanisms of clonal plasma cells development in monoclonal gammopathies.Acknowledgment: This work was supported by the Ministry of Health (15-29667A; DRO - FNOs/2014, DRO - FNOs/2016) and the Ministry of Education, Youth and Sports (Institutional Development Plan of University of Ostrava-IRP201550). DisclosuresHajek:Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy, Honoraria; Novartis: Consultancy, Research Funding; Pharma MAR: Consultancy, Honoraria; BMS: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Honoraria, Research Funding.

Transcriptome Alterations of Isolated Primary Bone Marrow Endothelial Cells Provide Insigt to MGUS and Multiple Myeloma Pathobiology

Multiple myeloma (MM) is characterized by an abnormal clonal expansion of plasma cells in the bone marrow, production of monoclonal immunoglobulins and finally organ damage (CRAB). The premalignant precursor of MM is Monoclonal gammopathy of undetermined significance (MGUS) and one percent of all MGUS patients progress to MM yearly. The bone marrow microenvironment is thought to play an important role in plasma cell growth, migration, and survival mainly via cytokine secretion and cell-cell interactions. Endothelial cells (ECs) are a major component in the bone marrow microenvironment, they regulate trafficking and homing of hematopoietic progenitor and stem cells. In MM increased bone marrow angiogenesis and recruitment of endothelial progenitors to the bone marrow niche has been reported. However, the specific EC contribution to myelomagenesis is not yet known. This study therefore aimed to investigate transcriptome alterations in prospectively isolated bone marrow ECs from MGUS and MM patients to identify possible disease-stage related changes. We isolated primary ECs from MGUS and MM patients undergoing diagnostic bone marrow aspirations and age-matched healthy donors by FACS. RNA from Lin- CD45- CD71- CD235a- CD271- CD31+ cells of MGUS (n=4) and MM (n=7) patients and healthy donors (n=6) was extracted. Sequencing was done using the Illumina® NextSeq 500/550 High Output Kit v2.5 (300 cycles). Gene expression analysis was performed in R. Differential gene expression analysis (DEseq2) identified 1,507 genes with p adjusted values below 1e-2 that were significantly differentially expressed between the three groups. Hierarchical clustering was done following Ward's method (ward.D2). Unsupervised clustering on the data showed that one MGUS-EC sample clustered with the healthy controls, and that one healthy control sample clustered with the MGUS samples. We therefore decided to restrict the analysis to those samples that clearly clustered separately, to be able to better depict the MGUS-, MM- and healthy EC specific profiles. Further clustering of differential expressed genes into 8 clusters revealed two especially interesting expression patterns. One cluster (#4) contained 102 genes that where higher expressed in the healthy controls with lower expression in MGUS and lowest expression in MM Samples. These genes thus reflect the downregulation during progression from a healthy bone marrow microenvironment to a reduced expression MGUS and further downregulation in MM. Another cluster (#6) showed the opposite pattern, with 105 genes being low or not expressed in healthy controls while the expression was higher in MGUS and highest in MM. Gene sets where further analyzed in the Database for Annotation, Visualization and Integrated Discovery (DAVID) v6.8. Cluster 4 showed a high number of downregulated transmembrane genes. Six genes of the major histocompatibility complex conserved site where identified might indicate a possible immunomodulating effect in disease progression. Furthermore, within cluster 4 we identified a cluster of genes involved in cell adhesion and receptor binding. Cluster 6 most strikingly showed a group of 6 genes of the melanoma-associated antigen (MAGE) gene family that were upregulated with disease progression. MAGE genes which belong to the cancer-testis group of germline genes have previously been reported in MM, as being involved in tumorigenesis, and plasma cell MAGE expression has been associated with chemotherapy resistance. Furthermore, cluster 6 contained a high number of extracellular matrix genes, and genes for proteins having an extracellular region, respectively, hinting towards a differential microenvironment composition upon MM development. Taken together RNA sequencing analysis of prospectively isolated bone marrow endothelial cells identified genes that were specifically upregulated/suppressed in MM-ECs compared to MGUS-ECs and healthy donor-ECs. These genes thus represent potential gene candidates involved in the disruption of normal microenvironment function, thus leading to disease development and progression. Accordingly, studies are underway to investigate selected transcriptional deregulation EC-MM microenvironmental functions in the context of the disease. Disclosures No relevant conflicts of interest to declare.

Network-based analysis of the molecular mechanisms of multiple myeloma and monoclonal gammopathy of undetermined significance.

The present study aimed to reveal the molecular mechanisms of multiple myeloma (MM) and monoclonal gammopathy of undetermined significance (MGUS). This was a secondary study on microarray dataset GSE80608, downloaded from the Gene Expression Omnibus database, which included 10 control samples, 10 MGUS samples and 10 MM samples. Differentially expressed genes (DEGs) were identified between control and MGUS samples, and between control and MM samples. A protein-protein interaction (PPI) network was built for studying the interactions between the DEGs. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was performed for the genes in a gene co-expression network. A microRNA (miRNA/miR)-gene network was built to the evaluate possible the miRNAs and genes involved in the diseases. The present study identified 136 common upregulated DEGs and 165 common downregulated DEGs between MM and MGUS. Pathway enrichment analysis of the genes in the gene co-expression network revealed that the complement and coagulation cascades pathway was significantly enriched for certain complement and coagulation-associated genes. Endothelin-1 (EDN1) was significantly enriched in the hypoxia inducible factor-1 (HIF-1) and tumor necrosis factor signaling pathways. EDN1 was an important node in the PPI network, and a target gene of let-7e, let-7b and miR-19a in the miRNA-gene network. The results of the present study indicate that complement and coagulation-associated genes, the complement and coagulation cascades pathway, EDN1, let-7e, let-7b-5p, miR-19a, and the tumor necrosis factor and HIF-1 signaling pathways may all be implicated in MM and MGUS.

Exome Sequencing To Define A Genetic Signature Of Plasma Cells In Systemic AL Amyloidosis

Systemic amyloid light chain amyloidosis (AL) is characterized by the deposition of immunoglobulin light chains as amyloid fibrils in different organs, where they form toxic protein aggregates. Most AL patients have relatively low levels of circulating free light chains and bone marrow plasmacytosis. The underlying disease is a plasma cell disorder, likely a monoclonal gammopathy, but limited data are available on the biology of the plasma cell clone underlying AL and existing studies have concentrated on chromosomal abnormalities. Many of the chromosomal abnormalities identified in AL are also seen in other plasma cell disorders, such as monoclonal gammopathy of undetermined significance (MGUS) and myeloma. These abnormalities include translocations involving the IGH locus, gains of 1q and deletions of 13q and 17p. Fluorescence in situhybridization studies have identified the translocation t(11;14) to be more frequent in AL and hyperdiploidy to be rare. The causal link between genetic changes in plasma cells and light chain instability remains unknown and progression to symptomatic myeloma is rare. We report the initial findings of the first exome sequencing to define the plasma cell signature in AL and compared this to MGUS and myeloma.CD138+ cells were selected using either EasySep (Stem Cell Technologies) or MACSort (Miltenyi) from the bone marrow of 18 AL patients and 5 MGUS patients. DNA was extracted from the CD138+ cells using the AllPrep kit (Qiagen). Non-involved DNA was isolated from peripheral white blood cells using the Flexigene kit (Qiagen). 200 ng DNA was subjected to exome sequencing using NEBNext kit (NEB) and SureSelect Human All Exon kit v5 and sequenced using 76-bp paired end reads. Fastq files were aligned to the reference genome using BWA and Stampy aligners. BAM files were recalibrated using the GATK and deduplicated using Picard. Paired tumour/normal BAMs were realigned together using the GATK indel realigner and SNVs were called using Mutect. Copy number data were estimated using the R package ExomeCNV. The median depth across all samples was 42x with 97% of the exome covered at 1x and 72% covered at 20x.Exome data to determine the cytogenetic groups of AL samples identified 42% hyperdiploid and 21% with t(11;14). The AL samples with t(11;14) did not contain any other copy number abnormalities. Exome sequencing on samples from patients with MGUS and myeloma was also performed to compare the genetic makeup and mutation spectrum of these well characterised plasma cell neoplasias with AL samples. MGUS samples had a median of 30 acquired nonsynonymous variants (range 24-189) and AL amyloidosis samples had a median of 17 acquired nonsynonymous variants (range 4-44). The AL samples had four recurrent mutations in PCMTD1 (n=3; L267F, P266S and M187I), C21orf33 (n=2; E72K), NLRP12 (n=2; L1018P, W959* ) and NRAS (n=2; Q61R, Q61H). In this small dataset, only 5 genes were mutated in both the MGUS and AL samples (DNMBP, FRG1, HIST1H1B, KRTAP4-11 and MCCC1). In order to assess the similarity (or differences) of plasma cells in AL to malignant plasma cells in general, we compared them to a random sampling of 20 multiple myeloma samples which had also been exome sequenced (median number of acquired nonsynonymous variants = 39 vs. 17 in AL samples). This revealed that the AL contained 21 mutated genes in common with the myeloma cohort, including DIS3 and NRAS. There were two DIS3 mutations in one AL sample at c.379D>E (p.D479E) and c.1999A>T (p.M667L), both of which were in the Ribonuclease II/R catalytic domain. Data on correlation of gene mutations and organ involvement in AL amyloidosis will be presented.We conclude that exome sequencing identifies a genetic signature of AL amyloidosis which is similar to other plasma cell disorders. This not only includes copy number abnormalities and translocations but also a similar number of nonsynonymous mutations to MGUS and fewer than the advanced myeloma samples. Study of further samples is in progress. Disclosures:No relevant conflicts of interest to declare.

Development Of a Serum Biomarker Panel That Predicts Imminent Risk Of Multiple Myeloma (MM) Progression From Premalignancy

Premalignant states are known to precede malignancy in many different cancers, including multiple myeloma (MM). Each year, 1% of Monoclonal Gammopathy of Undetermined Significance (MGUS) patients and 10% of Smoldering Multiple Myeloma (SMM) patients transition to symptomatic MM, which remains an incurable disease. By identifying patients at imminent risk (within 2 years) of progression to MM, treatment could begin early and potentially prevent full blown MM and associated morbidity and mortality. Multiple risk-factor models are currently utilized to identify patients at high-risk of developing MM. Commonly cited risk factors include percentage of bone marrow plasma cells, free light chain ratio, serum levels of M-protein, IgG subtype and levels of circulating plasma cells. These tests have individual and combined merit but there remains no consensus for measuring imminent risk of MM progression. To determine whether serum proteomics could help predict progression or provide information on relevant pathways involved in progression to MM, we evaluated 200 MGUS and SMM (187 non-IgM) patient samples on the Myriad DiscoveryMAP(r) platform (250+ serum proteins), supplemented by demographic and clinical information. Of the 187 non-IgM patients, 100 progressed to MM within 2 years (high-risk), and 87 did not progress to MM within 5 years (low-risk). We performed different subset analyses to screen for proteins that were informative and predictive of disease progression from MGUS/SMM to MM. First, a univariate Wilcoxon rank sum test was performed. The top 10 proteins that were found to be differential between high-risk/low-risk for all MGUS and SMM patients were IgM, Progesterone, MCP-2, Kallikrein-5, FGF4, EPO, MCP-4, MIP-1β, MCP-1, and TF. Interestingly, when analyzing MGUS and SMM patients separately, additional proteins that were important in distinguishing high-risk/low-risk patients included IgM, EN-RAGE, BAFF, and several others previously shown to be relevant in MM, as well as a handful of novel proteins with unidentified roles in MM. Second, to determine whether specific combinations of proteins could be utilized together to define high/low-risk, a classification tree was assembled. The combination of 8 features (IgM, Progesterone, Aldose Reductase, E-Selectin, Fas Ligand, Hemoglobin, Age and Creatine kinase-MB) appropriately classified 86% of the 187 patients into high/low-risk. Future analyses will include examining this high/low risk classifier in contrast to current risk factor models, and application to two additional sets of similar patient samples that serve as an independent validation set. Disclosures:No relevant conflicts of interest to declare.

Decorin is down‐regulated in multiple myeloma and MGUS bone marrow plasma and inhibits HGF‐induced myeloma plasma cell viability and migration

Decorin is a stromal-produced small leucine-rich proteoglycan known to attenuate tumour pro-survival, migration, proliferation and angiogenic signalling pathways. Recent studies have shown that decorin interacts with the hepatocyte growth factor (HGF) receptor c-Met, a potential key pathway in multiple myeloma (MM). Decorin levels in paired peripheral blood and bone marrow plasma samples from healthy volunteers (HV) (n=23), and patients with monoclonal gammopathy of undetermined significance (MGUS) (n=41) and MM (n=19) were determined by ELISA. Further, the ability of decorin to inhibit HGF-induced effects on MM cell lines were analysed in vitro using cell viability and Transwell migration assays. We found that decorin concentrations were significantly higher (P<0.05) in bone marrow (BM) plasma from HVs (median 35.2ng/mL; range, 15.3-99.1) compared with MGUS (median 22.5ng/mL; range, 11.1-59.5) and patients with MM (median 21.5ng/mL; range, 10.6-35.9). Decorin levels were higher in BM plasma than in peripheral blood in all groups, with a BM/PB ratio of 3.9, 3.4 and 2.5 for HV, MGUS and MM, respectively. A positive correlation (Spearman's ρ=0.51, P<0.05) was found between simultaneously measured levels of HGF and decorin in BM plasma in HVs, but not in MGUS or MM samples. Functionally, decorin inhibited HGF-induced migration and viability of INA-6 and ANBL-6 MM cell lines, independent of c-Met down-regulation. Our results show that decorin is down-regulated in MGUS and MM bone marrow plasma and that it inhibits HGF-induced viability and migration of myeloma cell lines in vitro.

Intraclonal heterogeneity is a critical early event in the development of myeloma and precedes the development of clinical symptoms

The mechanisms involved in progression from monoclonal gammopathy of undetermined significance (MGUS) and smoldering myeloma (SMM) to malignant multiple myeloma (MM) and plasma cell leukemia (PCL) are poorly understood but believed to involve the sequential acquisition of genetic hits. We performed exome and whole genome sequencing on a series of MGUS (n=4), high risk (HR)-SMM (n=4), MM (n=26) and PCL (n=2) samples, including four cases who transformed from HR-SMM to MM, to determine the genetic factors which drive progression of disease. The pattern and number of non-synonymous mutations show that the MGUS disease stage is less genetically complex than MM, and HR-SMM is similar to presenting MM. Intraclonal heterogeneity is present at all stages and using cases of HR-SMM, which transformed to MM, we show that intraclonal heterogeneity is a typical feature of the disease. At the HR-SMM stage of disease the majority of the genetic changes necessary to give rise to MM are already present. These data suggest that clonal progression is the key feature of transformation of HR-SMM to MM and as such the invasive clinically predominant clone typical of MM is already present at the SMM stage and would be amenable to therapeutic intervention at that stage.

MicroRNA expression in multiple myeloma is associated with genetic subtype, isotype and survival.

BackgroundMicroRNAs are small RNA species that regulate gene expression post-transcriptionally and are aberrantly expressed in many cancers including hematological malignancies. However, the role of microRNAs in the pathogenesis of multiple myeloma (MM) is only poorly understood. We therefore used microarray analysis to elucidate the complete miRNome (miRBase version 13.0) of purified tumor (CD138+) cells from 33 patients with MM, 5 patients with monoclonal gammopathy of undetermined significance (MGUS) and 9 controls.ResultsUnsupervised cluster analysis revealed that MM and MGUS samples have a distinct microRNA expression profile from control CD138+ cells. The majority of microRNAs aberrantly expressed in MM (109/129) were up-regulated. A comparison of these microRNAs with those aberrantly expressed in other B-cell and T-cell malignancies revealed a surprising degree of similarity (~40%) suggesting the existence of a common lymphoma microRNA signature. We identified 39 microRNAs associated with the pre-malignant condition MGUS. Twenty-three (59%) of these were also aberrantly expressed in MM suggesting common microRNA expression events in MM progression. MM is characterized by multiple chromosomal abnormalities of varying prognostic significance. We identified specific microRNA signatures associated with the most common IgH translocations (t(4;14) and t(11;14)) and del(13q). Expression levels of these microRNAs were distinct between the genetic subtypes (by cluster analysis) and correctly predicted these abnormalities in > 85% of cases using the support vector machine algorithm. Additionally, we identified microRNAs associated with light chain only myeloma, as well as IgG and IgA-type MM. Finally, we identified 32 microRNAs associated with event-free survival (EFS) in MM, ten of which were significant by univariate (logrank) survival analysis.ConclusionsIn summary, this work has identified aberrantly expressed microRNAs associated with the diagnosis, pathogenesis and prognosis of MM, data which will prove an invaluable resource for understanding the role of microRNAs in this devastating disease.ReviewersThis article was reviewed by Prof. Neil Smalheiser, Prof. Yuriy Gusev, and an unknown reviewer.

Evidence for ongoing DNA damage in multiple myeloma cells as revealed by constitutive phosphorylation of H2AX

DNA double-strand breaks (DSBs) are deleterious lesions that can lead to chromosomal anomalies, genomic instability and cancer. The histone protein H2AX has an important role in the DNA damage response (DDR) and the presence of phospho-H2AX (γH2AX) nuclear foci is the hallmark of DSBs. We hypothesize that ongoing DNA damage provides a mechanism by which chromosomal abnormalities and intratumor heterogeneity are acquired in malignant plasma cells (PCs) in patients with multiple myeloma (MM). Therefore, we assessed PCs from patients with the premalignant condition, monoclonal gammopathy of undetermined significance (MGUS) and MM, as well as human MM cell lines (HMCLs) for evidence of DSBs. γH2AX foci were detected in 2/5 MGUS samples, 37/40 MM samples and 6/6 HMCLs. Notably, the DSB response protein 53BP1 colocalized with γH2AX in both MM patient samples and HMCLs. Treatment with wortmannin decreased phosphorylation of H2AX and suggests phosphoinositide (PI) 3-kinases and/or PI3-kinase-like family members underlie the presence of γH2AX foci in MM cells. Taken together, these data imply that ongoing DNA damage intensifies across the disease spectrum of MGUS to MM and may provide a mechanism whereby clonal evolution occurs in the monoclonal gammopathies.

Utility of CD81 Flow Cytometry (FC) Assessment In Diagnostic Evaluation of Plasma Cell (PC) Disorders

AbstractAbstract 3011 Background:CD81 is a tetraspanin cell surface protein that regulates CD19 expression in B lymphocytes and enables hepatitis C virus infection of human cells. Immunohistochemistry and FC have showed that CD81 expression is downregulated in multiple myeloma and PC lines (Luo, 2010). It appears also that normal PCs are CD81+ at a high percentage (Rawstron, 2008). However, information about CD81 utility in phenotypic diagnosis of PC disorders is scanty. We assessed the frequency and the diagnostic value of the FC detection of CD81 surface expression in multiple myeloma (MM), monoclonal gammopathy of undetermined significance (MGUS) and non-hematological malignancy subjects. Patients-Methods:A total of 84 bone marrow aspirates were analyzed in this study. These included 52 diagnosis/disease progression MM samples, 8 samples from MGUS patients and 24 samples from reactive plasmacytosis and ITP patients. A 4-color FC technique was used for PC analysis. Based on the European Myeloma Network guidelines (Rawstron, 2008), we evaluated expression of CD19, CD27, CD56 and CD81 on PCs identified by the CD38/CD45/CD138 combination. At least 100,000 events/tube were acquired, leading to a sensitivity limit of 0.1%. FC positivity threshold for studied antigens was set at 20%. Any deviation from the normal PC phenotype (CD19+CD27+CD56-) was considered as abnormal. Diagnostic tests also included FBC, biochemistry, beta-2 microglobulin, IgA, IgG, IgM, kappa and lambda light chain serum levels, serum protein electrophoresis and immunofixation, bone marrow aspirate and skeletal survey where required. Results:Median PC percentage was significantly higher in the bone marrow aspirate when compared to FC as expected [15.5(3-96)% vs. 2(0.11-53)%, p<0.001]. CD81 positivity was identified in 19% (10/52) of MM samples and 50% of MGUS (4/8) and normal PC samples (12/24). CD81 plasma cell expression was significantly different between normal and MM samples (median: 16.8(1.9-52.4)% vs. 2.5(0-90.4)%, p<0.001) and between MGUS and MM patients (median: 14.4(1.5-53)% vs. 2.5(0-90.4)%, p=0.001). Mean fluorescence intensity of CD81 was similar in the 3 groups. A positive correlation was found between CD81 and CD19 expression (rho=+0.596, p<0.0001) and between CD81 and CD27 (rho=+0.358, p=0.001) while CD56 expression was negatively correlated with CD81 (rho=-0.291, p=0.007). Flow cytometry provided correct diagnosis in 87% (73/84) of cases; 8 samples were identified as false positive and 3 as false negative. Subsequently, a Receiver Operating Characteristic (ROC) curve analysis was performed in order to assess CD19, CD27, CD56 and CD81 antigens' sensitivity and specificity in discriminating normal from malignant PCs (Figure); although CD81 shared similar sensitivity and specificity with CD27, CD19 was shown to have the highest sensitivity and specificity in detecting correctly PC identity. Conclusions:This study provides laboratory evidence that CD81 expression in PCs is strongly correlated with CD19, CD27 and CD56 expression. CD81 surface detection seems to characterize normal PCs in reactive plasmacytosis, ITP and MGUS. However, it has an inferior sensitivity and specificity, in discriminating normal from malignant PCs, when compared to CD19. [Display omitted] Disclosures:No relevant conflicts of interest to declare.

Alterations in the antigen processing-presenting machinery of transformed plasma cells are associated with reduced recognition by CD8+ T cells and characterize the progression of MGUS to multiple myeloma

AbstractWe hypothesized that progression of monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma (MM) reflects the escape of transformed plasma cells from T-cell recognition because of impaired antigen processing-presenting machinery (APM). We studied plasma cells and CD8+ T cells from bone marrow of 20 MGUS patients, 20 MM patients, and 10 control patients. Immunofluorescence and flow cytometry revealed significantly different patterns of APM component expression in plasma cells from the 3 groups. Compared with control patients, MM samples had lower expression of proteasome subunits and peptide transporters and greater expression of chaperones, considering both percentages of stained cells and molecular equivalents of soluble fluorochrome. MGUS samples had intermediate percentages of stained cells but molecular equivalents of soluble fluorochrome similar to control patients. Real-time polymerase chain reaction documented that APM changes occurred at the transcriptional level. Cytotoxicity assays demonstrated that MGUS CD8+ T cells lysed autologous transformed plasma cells more than MM CD8+ T cells did. MGUS progression correlated directly with calnexin, calreticulin, and tapasin and indirectly with δ, LMP2, and LMP10 expression levels; MM disease status did not correlate with APM levels. APM changes may allow transformed plasma cells to elude immunesurveillance in the MGUS-MM pathogenetic sequence.