Whole Genome DNA Methylation Analysis of Commpass Identifies Biomarkers of Multiple Myeloma Survival

Abstract Multiple myeloma is a malignancy of terminally differentiated, antibody secreting B cells known as plasma cells. Normal B cell differentiation and cell fate are coupled to epigenetic and transcriptional reprogramming, including a proliferation-dependent global loss of DNA methylation (Barwick et al., 2016, 2018). However, relatively little is known about the epigenetic changes that underlie myelomagenesis and how these may contribute to pathogenesis. To this end, we are analyzing the DNA methylome of myeloma specimens from the MMRF CoMMpass trial (NCT01454297), which has already characterized the mutational, structural, and transcriptional landscape of nearly 1,000 myelomas from newly diagnosed patients. CoMMpass specimens were obtained from a centralized biobank with approval from the CoMMpass Tissue Use Committee and Emory IRB. DNA isolated from CD138+ myeloma specimens was subjected to reduced representation bisulfite sequencing (RRBS) or whole genome bisulfite sequencing (WGBS). In total, DNA methylation was derived for over 24 million CpGs with an average of 18x coverage. WGBS data from normal B cells and plasma cells was obtained with permission from the BluePrint project (Agirre et al., 2015) via the European Genome Archive. DNA methylation levels were associated with PFS and OS using a cox proportional regression. We have determined the DNA methylome for 36 primary myeloma specimens and an additional 84 specimens are currently being sequenced. Relative to normal B cells that had an average DNA methylation level of 89.1%, plasma cells and myelomas exhibited a progressive demethylation with mean levels of 71.3% and 43.7%, respectively. While this is consistent with previous observations (Agirre et al., 2015; Salhia et al., 2010), WGBS revealed that myeloma in particular was characterized by large hypomethylated domains. These large hypomethylated domains encompassed genes that were devoid of gene expression whereas DNA methylation remained unchanged in the bodies of genes that were highly expressed. Although the majority of these hypomethylated domains were common across myelomas, there existed many regions where methylation levels varied between myelomas and these differences commonly corresponded with local gene expression differences. To understand if these specific patterns of DNA methylation were indicative of disease pathogenesis, DNA methylation levels were compared to PFS and OS. This identified 2,594 regions where the level of DNA methylation was prognostic of outcome (P≤0.001). Reduced DNA methylation corresponded with poor outcome at 88.5% (N=2,298) of these regions, which included loci proximal to cell cycle genes such as MYC, E2F3, CCND1, and CCNE1. Only 11.5% (N=296) of regions associated with outcome had higher levels of DNA methylation associated with poor prognosis. These regions tended to be proximal to genes involved in B cell receptor signaling, such as PLCG2 and VAV2. Although the expression of several of these genes was also prognostic of survival, the majority were not, indicating that the epigenetic state contains a unique prognostic value. These data indicate that myeloma undergoes profound epigenetic remodeling that is co-ordinate with changes in gene expression. Perhaps the most striking feature were megabase domains of hypomethylation. That DNA methylation was preferentially retained in the bodies of expressed genes suggests that a molecular mechanism and/or cellular selection occurs to maintain methylation at genes whose expression is required for myeloma cell survival. Despite the small number (N=36) of myeloma specimens analyzed thus far, the large number of regions associated with survival indicates the potential prognostic value of DNA methylation in myeloma. Furthermore, DNA methylation indicative of outcome only partially overlapped with the prognostic value of gene expression, indicating DNA methylation has independent value as a biomarker of outcome in myeloma. This may be due, in part, to the fact that DNA methylation is a very stable modification that not only reflects the current gene expression program, but is also indicative of the cell history and potential. Integrative genetic, epigenetic, and transcriptional analysis from WGBS of 120 CoMMpass myeloma specimens will be presented, including matched baseline and relapsed specimens from 25 patients. Disclosures Lonial: Amgen: Research Funding. Boise:Abbvie: Consultancy; AstraZeneca: Honoraria.

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Gene-expression profiling of Waldenström macroglobulinemia reveals a phenotype more similar to chronic lymphocytic leukemia than multiple myeloma

Blood ◽

10.1182/blood-2006-02-005488 ◽

2006 ◽

Vol 108 (8) ◽

pp. 2755-2763 ◽

Cited By ~ 122

Author(s):

Wee J. Chng ◽

Roelandt F. Schop ◽

Tammy Price-Troska ◽

Irene Ghobrial ◽

Neil Kay ◽

...

Keyword(s):

Gene Expression ◽

Multiple Myeloma ◽

B Cells ◽

Chronic Lymphocytic Leukemia ◽

B Cell ◽

Plasma Cells ◽

Cell Clone ◽

Expression Profiles ◽

Mapk Signaling ◽

Lymphocytic Leukemia

Abstract Waldenström macroglobulinemia (WM) is a B-cell malignancy characterized by the ability of the B-cell clone to differentiate into plasma cells. Although the clinical syndrome and the pathologic characteristics are well defined, little is known about its biology and controversy still exists regarding its cell of origin. In this gene-expression study, we compared the transcription profiles of WM with those of other malignant B cells including (chronic lymphocytic leukemia [CLL] and multiple myeloma [MM]) as well as normal cells (peripheral-blood B cells and bone marrow plasma cells). We found that WM has a homogenous gene expression regardless of 6q deletion status and clusters with CLL and normal B cells on unsupervised clustering with very similar expression profiles. Only a small gene set has expression profiles unique to WM compared to CLL and MM. The most significantly up-regulated gene is IL6 and the most significantly associated pathway for this set of genes is MAPK signaling. Thus, IL6 and its downstream signaling may be of biologic importance in WM. Further elucidation of the role of IL-6 in WM is warranted as this may offer a potential therapeutic avenue.

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Dissecting the Epigenetic Landscape of Smoldering, Newly Diagnosed and Relapsed Multiple Myeloma Revealed IRAK3 As a Marker of Disease Progression

Blood ◽

10.1182/blood-2018-99-115046 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 3896-3896

Author(s):

Mahshid Rahmat ◽

Nicholas Haradhvala ◽

Romanos Sklavenitis-Pistofidis ◽

Jihye Park ◽

Daisy Huynh ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Multiple Myeloma ◽

Disease Progression ◽

Plasma Cells ◽

Whole Genome ◽

Newly Diagnosed ◽

Promoter Regions ◽

Healthy Donors ◽

Precursor States

Abstract Introduction. Multiple myeloma (MM) is a complex and heterogeneous malignancy of plasma cells that has two precursor states: monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). MGUS and SMM are asymptomatic states that eventually give rise to overt MM, with some patients progressing, while others do not. Recent studies in MM pathobiology have highlighted epigenetic alterations that contribute to the onset, progression and heterogeneity of MM. Global hypomethylation of DNA, including tumor suppressor genes, and hypermethylation of B-cell specific enhancers, abnormal histone methylation patterns due to the overexpression of histone methyltransferases such as MMSET, and deregulation of non-coding RNAs along with mutations in different classes of chromatin modulators underline a potential for epigenetic biomarkers in disease prognosis and treatment. This study aimed to define epigenetic pathways that lead to the dynamic regulation of gene expression in MM pathogenesis. Methods. We performed ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) and RNA-seq on 10 MM cell lines and CD138+ plasma cells isolated from bone marrow aspirates of 3 healthy donors, 9 SMM, 8 newly diagnosed MM (NDMM) and 9 relapsed (RRMM) patients. ATAC-seq reads were trimmed of adapters, aligned to hg19 using bowtie2, and filtered for mapping quality >=Q30 using the ENCODE ATAC-seq pipeline. Reads mapping to promoter regions, defined as -400 to +250 bases from a refseq transcription start site, were counted using bedtools for each sample. Promoter read counts were then normalized by the total number of reads in promoters in the sample, scaled to 1 million total reads, and converted to log10(x+1) space. Results. To characterize the epigenetic contribution to disease progression in MM, we first identified accessible promoter regions in normal plasma cells (NPC), SMM, NDMM and RRMM patients and found regions displaying differential accessibility in MM progression. Next, we intersected the list of differential accessible regions (DARs) with matched transcriptome data and observed two main clusters: genes with unaltered transcription profiles and genes in which the dynamics of open chromatin regions (OCRs) correlated with gene expression. Transcriptomic analysis revealed that a large portion of the differentially expressed (DE) genes in SMM remain DE in NDMM as compared to NPCs (882 genes out of 1642 and 1150 DE genes in SMM and NDMM, respectively). Those genes were significantly enriched for pathways like epithelial mesenchymal transition, cell cycle checkpoints and mitosis, KRAS signaling and interleukin-JAK-STAT pathways. To investigate the genes that behaved differently among the stages of disease, we looked at differential accessibility and expression in NDMM and SMM samples, and integrated them with Whole-Genome Bisulfite-Sequencing and 450K DNA-methylation data from MM patients and healthy donors (BLUEPRINT). This analysis led to the identification of novel genes in MM progression, such as the transcriptional repressor ZNF254 and IRAK3, a negative regulator of the TLR/IL1R signaling pathway. Although gene expression data for these genes showed comparable mRNA levels in SMM and NPCs, followed by a significant decrease in NDMM/ RRMM, ATAC-seq revealed a striking drop in promoter accessibility in SMM, NDMM and RRMM cases. Comparison of ATAC-seq peaks to DNA methylation and ChIP-seq data revealed that the altered OCR of IRAK3 is actually hypermethylated in MM patients and marked by H3K4me3, a marker of active promoters, in MM cell lines. Hypermethylation of IRAK3 has been described in hepatocellular carcinoma, where it is associated with poor prognosis. Together, our data suggest that the identified IRAK3 OCR may act as a bivalent domain that loses accessibility in the precursor states and gains DNA methylation in MM progression. Hence, IRAK3 methylation could be a novel prognostic marker in MM. Conclusion. We have generated a global epigenetic map of primary tumors from patients at the smoldering, newly diagnosed and relapsed/refractory stage of multiple myeloma. Integrative analysis of ATAC-seq data with DNA methylome, transcriptome and whole-genome map of active and repressive histone marks in our study led to the identification of IRAK3 as a novel epigenetic biomarker of disease progression. Disclosures Licht: Celgene: Research Funding. Ghobrial:Takeda: Consultancy; BMS: Consultancy; Celgene: Consultancy; Janssen: Consultancy.

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Molecular Profiling Identifies Plasmablasts as the Cells of Origin of Activated Diffuse Large B Cell Lymphoma.

Blood ◽

10.1182/blood.v114.22.621.621 ◽

2009 ◽

Vol 114 (22) ◽

pp. 621-621

Author(s):

Cassandra L. Jacobs ◽

Patricia L. Lugar ◽

Qingquan Liu ◽

Jenny Zhang ◽

Peter Lipsky ◽

...

Keyword(s):

Gene Expression ◽

Multiple Myeloma ◽

B Cells ◽

B Cell ◽

Germinal Center ◽

Plasma Cells ◽

B Cell Lymphoma ◽

Plasmacytic Differentiation ◽

Expression Of Genes ◽

B Cell Subsets

Abstract Abstract 621 The classification of leukemias and lymphomas is based upon the state of differentiation of hematopoietic cells from which the malignancy is derived. These malignancies frequently preserve aspects of their lineage and lineage-specific markers are a standard in the pathology diagnosis of these tumors. Diffuse large B cell lymphoma (DLBCL) is the most common form of non Hodgkin lymphoma and comprises at least 2 different molecular subsets. The first subset is derived from germinal center B cells (GCB DLBCL) and is characterized by a relatively good prognosis when treated with standard chemotherapy. The second subset, activated B cell like (ABC) DLBCL, is characterized by higher expression of plasmacytic genes (IRF4, PRDM1 and XBP1), an activated phenotype and poorer prognosis. Unlike multiple myeloma, ABC DLBCLs lack the morphology and phenotype of plasma cells. The normal B cell counterpart of ABC DLBCLs is unknown. Thus, there are 2 major aspects of the molecular phenotype ABC DLBCLs—first, ABC DLBCLs demonstrate features of plasma cell differentiation, suggesting that they are derived from post-germinal center cells that are undergoing plasmacytic differentiation. Second, ABC DLBCLs are characterized by high activity of the NF-KB pathway, which is responsible for their activated phenotype. The etiology of NF-KB activation is not known, but is thought to result from acquired mutations in genes that encode the NF-KB pathway. Although plasmablasts have been studied extensively in vitro, using a variety of techniques to induce plasmacytic differentiation, comprehensive studies of in vivo, lymph node-derived human plasmablasts have been lacking. Methods and Results: Using flow cytometry for a standard set of B cell markers (CD19, CD20, IgD, CD38, CD27, CD10, CD138), we identified mature B cell subsets including naive, germinal center (GC), memory, plasmablast (PB) and plasma cells (PC) from healthy patients undergoing routine tonsillectomy. These subsets were profiled for gene expression at the whole genome-level and we constructed Bayesian predictors to distinguish these subsets. These gene expression-based predictors could distinguish the normal B cell subsets perfectly. We then applied these Bayesian predictors to identify the lineage of 350 tumors from patients with DLBCL and 125 patients with multiple myeloma. Tumors with ABC and GCB DLBCLs were distinguished based on their gene expression profiles. Using the Bayesian gene expression predictors, we found that GCB DLBCLs were classified as germinal center B cells, whereas ABC DLCBLs were classified as plasmablasts and multiple myeloma cases were classified as plasma cells. We found over 90% concordance between the lineage-based (PB vs GC) predictor and the previously defined gene expression-based predictor that distinguishes ABC from GCB DLBCL (P<1E-10, chi-squared test). Notably, PBs demonstrated lower expression of BCL6 and CD10, and higher expression of IRF4 and PRDM1 compared to GC cells. The expression pattern was reversed when compared to plasma cells. Thus, the gene expression profile of PBs was intermediate between germinal center (GC) and plasma cells (PC), with regard to expression of genes related to plasmacytic differentiation (p=0.008, Figure 1A). We further investigated the expression of the NF-KB pathway in these B cell subsets and DLBCL and multiple myeloma. We found that higher expression of NF-KB in ABC DLBCL compared to GCB DLBCL and multiple myeloma reflects the differences in NF-KB activity of their normal counterparts, results that were highly statistically significant (p=0.009, Figure 1B). Thus the higher expression of genes related to plasmacytic differentiation as well as NF-KB activation in ABC DLBCL appears to be directly related to their origin from plasmablasts. Conclusion: The key aspects of the molecular phenotype of ABC DLBCLs, i.e. plasmacytic differentiation and NF-KB expression, are a direct reflection of their normal counterpart B cells. Our data provide the basis for a better understanding of the pathogenesis of DLBCL. Disclosures: No relevant conflicts of interest to declare.

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DNA Methyltransferase 1 Contributes to Epigenetic Signatures and Biological Phenotype during Normal B-Cell Differentiation and Lymphomagenesis.

Blood ◽

10.1182/blood.v110.11.685.685 ◽

2007 ◽

Vol 110 (11) ◽

pp. 685-685 ◽

Cited By ~ 1

Author(s):

Rita Shaknovich ◽

Leandro Cerchietti ◽

Maria E. Figueroa ◽

Ari Melnick

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

B Cells ◽

B Cell ◽

Germinal Center ◽

Dna Methyltransferase ◽

Critical Role ◽

Epigenetic Programming ◽

Differential Digestion ◽

Epigenetic Signatures

Abstract Normal hematopoiesis requires incremental changes in gene expression in order to establish cellular phenotypes with specialized functions. We are particularly interested in the transcriptional and epigenetic programming of germinal center (GC) B-cells, which acquire unusual biological features normally associated with cancer. Specifically, GC B-cells (i.e. centroblasts - CB) undergo rapid DNA replication while at the same time undergoing genetic recombination, and give rise to a majority of B-cell lymphomas. We hypothesized that epigenetic programming would play a critical role in the CB stage of development, and that gene-specific and genome-wide DNA methyltransferase activity is critical for these cells. We first examined the CpG methylation levels of 24,000 gene promoters in five sets of primary human B-cells just prior to (i.e. naïve B-cells - NBC) and upon entering the GC reaction (i.e. CBs). This was achieved using the HELP (HpaII tiny fragment Enrichment by Ligation-mediated PCR) assay, which relies on differential digestion of genomic DNA by the isoschizomer enzymes HpaII and Msp. HELP is a robust and reproducible method that provides accurate and quantitative measurement of DNA methylation levels throughout the genome. Remarkably, we found that the DNA methylation profile of B-cells undergoes a significant shift as readily appreciated by hierarchical clustering. The epigenetic signatures of NBC and CB are differentiation-stage dependent and do not vary significantly between individuals. The coefficient of correlation between individuals was 0.98, as compared to the NBC vs. CB fractions 0.92–0.95. Supervised analysis demonstrated that 266 genes (P<0.001) were differentially methylated upon entry of NB-cells into the GC reaction. We further correlated the methylation status of these genes with their gene expression level. The most heavily affected pathways by differential methylation and concordant expression in naïve B-cells were the Jak/STAT and MAP3K signaling pathways, while in CBs the p38 MAPK pathway and Ikaros family of genes were most affected. Given the epigenetic reprogramming observed in CBs vs. NBCs, along with the need for maintenance of methylation during rapid replication, we predicted that DNA methyltransferase (DNMT) enzymes play a critical role in centroblasts. By performing QPCR and Western blots on isolated fractions of human tonsilar lymphocytes and anatomical localization by immunohistochemistry, we found that DNMTs have a complex temporal and combinatorial expression pattern whereby DNMT1 was the main methyltransferase detectable in centroblasts. Additionally we studied 10 DLBCL cell lines and a panel of primary DLBCL (n=176 for mRNA and 70 for protein) for DNMTs expression. Spearman Rank correlation analysis revealed that DNMT1 was preferentially highly expressed in GCB vs. ABC primary DLBCLs, as well as in BCR vs. OxPhos DLBCLs. Taken together, our data suggest that i) dynamic changes in epigenetic programming contribute to formation of GCs, ii) that DNMT1 may play both a de novo and maintenance methylation role in GC cells, iii) that DNMT1 is markedly upregulated in normal centroblasts and in DLBCLs with the BCR or GCB gene expression profiles and iv) specific therapeutic targeting of DNMT1 rather than non-specific global inhibition of DNA methylation could be a useful anti-lymphoma strategy for germinal center-derived DLBCLs.

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The proliferative history shapes the DNA methylome of B-cell tumors and predicts clinical outcome

10.1101/2020.02.06.937383 ◽

2020 ◽

Cited By ~ 2

Author(s):

Martí Duran-Ferrer ◽

Guillem Clot ◽

Ferran Nadeu ◽

Renée Beekman ◽

Tycho Baumann ◽

...

Keyword(s):

Dna Methylation ◽

B Cells ◽

B Cell ◽

De Novo ◽

Genetic Alterations ◽

Cell Tumor ◽

Patient Specific ◽

Maturation Stage ◽

Cell Of Origin ◽

Dna Methylome

AbstractWe report a systematic analysis of the biological and clinical implications of DNA methylation variability in five categories of B-cell tumors derived from B cells spanning the entire maturation spectrum. We used 2056 primary samples including training and validation series and show that 88% of the human DNA methylome is dynamically modulated under normal and neoplastic conditions. B-cell tumors display both epigenetic imprints of their cellular origin and de novo, disease-specific epigenetic alterations that in part are related to differential transcription factor binding. These differential methylation patterns were used by a machine-learning approach to create a diagnostic algorithm that accurately classifies 14 B-cell tumor entities and subtypes with different clinical management. Beyond this, we identified extensive patient-specific epigenetic variability targeting constitutively silenced chromatin regions, a phenomenon we could relate to the proliferative history of normal and neoplastic B cells. We observed that, depending on the maturation stage of the tumor cell of origin, mitotic activity leaves different imprints into the DNA methylome. Subsequently, we constructed a novel DNA methylation-based mitotic clock called epiCMIT (epigenetically-determined Cumulative MIToses), whose lapse magnitude represents a strong independent prognostic variable within specific B-cell tumor subtypes and is associated with particular driver genetic alterations. Our findings reveal DNA methylation as a holistic tracker of B-cell tumor developmental history, with implications in the differential diagnosis and prediction of the outcome of the patients.

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The IGLV3-21R110 Defines a Subset of Chronic Lymphocytic Leukemia with Intermediate Epigenetic Subtype and Poor Outcome

Blood ◽

10.1182/blood-2020-134786 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 43-44

Author(s):

Ferran Nadeu ◽

Romina Royo ◽

Guillem Clot ◽

Martí Duran-Ferrer ◽

Alba Navarro ◽

...

Keyword(s):

Gene Expression ◽

B Cells ◽

Chronic Lymphocytic Leukemia ◽

Rna Sequencing ◽

Prognostic Value ◽

Lymphocytic Leukemia ◽

Whole Genome ◽

Biological Features ◽

Mutational Status ◽

Bcr Signaling

Introduction: B-cell receptor (BCR) signaling is crucial for chronic lymphocytic leukemia (CLL) biology. IGLV3-21-expressing B-cells may acquire a single point mutation (R110) that triggers autonomous BCR signaling conferring aggressive behavior. Epigenetic studies have defined three CLL subtypes based on methylation signatures reminiscent of pre- and post-germinal center B-cells named naïve-like (n-CLL), intermediate (i-CLL) and memory-like CLL (m-CLL) with different biological features. i-CLL carry a borderline IGHV mutational load and a significant higher usage of IGHV3-21/IGLV3-21. The integration of these factors might translate into novel insights in CLL pathogenesis with implications on the proposed stratification of the patients. Aim: To determine the clinical and biological features of the IGLV3-21R110 in CLL in the light of the epigenetic subtypes and immunogenetic, genomic and transcriptomic landscapes of the tumors. Methods: We characterized the immunoglobulin (IG) gene of 584 CLL cases from whole-genome/exome and RNA sequencing using our recently developed algorithm IgCaller (Nadeu et al., Nat. Commun. 2020) and MiXCR, respectively. The genomic makeup of the tumors was obtained from whole-genome/exome sequencing while RNA sequencing data for 369 cases was used for gene expression analyses. Expression levels of WNT5A and WNT5B were verified by quantitative PCR with reverse transcriptase. Primary end points were time to first treatment (TTFT) and overall survival (OS) calculated from the date of diagnosis. All patients gave written informed consent. The study was approved by the Ethics Committee of the Hospital Clínic of Barcelona. Results: The IGLV3-21R110 was detected in 6.5% of cases being similarly distributed between mutated (6.5%) and unmutated (6.6%) IGHV cases (P=0.56). In contrast, the IGLV3-21R110 was found in 30/79 (38%) i-CLL compared to only 5/291 (1.7%) m-CLL and 1/189 (0.5%) n-CLL (P<0.001). All stereotyped subset #2 cases carried IGLV3-21R110 while 62% of IGLV3-21R110 i-CLL had non-stereotyped IG genes. IGLV3-21R110 i-CLL had a borderline IGHV mutational status (median 97.7%) that was higher than i-CLL lacking the IGLV3-21R110 (median 96.2%, P=0.005). IGLV3-21R110 i-CLL had significantly higher number of SF3B1 and ATM mutations, and total number of driver alterations. Nonetheless, the R110 mutation was the sole alteration in one i-CLL case and accompanied only by del(13q) in three. Although composite regarding IGHV mutational status, IGLV3-21R110 i-CLL transcriptomically resembled naïve-like/unmutated IGHV CLL and had a specific expression signature of 64 genes with overexpression of WNT5A and WNT5B as hallmarks. No differences were observed in the expression profile of subset #2 and non-subset #2 IGLV3-21R110 i-CLL tumors. On the other hand, i-CLL lacking the IGLV3-21R110 phenotypically mirrored memory-like/mutated IGHV cases. In relation to prognosis, IGLV3-21R110 i-CLL had a short TTFT and OS similar to n-CLL/unmutated IGHV cases whereas non-IGLV3-21R110 i-CLL had a good prognosis similar to memory-like/mutated IGHV. Therefore, i-CLL cases, which have been associated with an intermediate prognosis between m-CLL and n-CLL in previous studies, can be divided in two subgroups of cases with opposed clinical evolutions based on the IGLV3-21R110. Indeed, the IGLV3-21R110 and n-CLL subtype retained independent prognostic value in multivariate analyses while the i-CLL lost its prognostic prediction both for TTFT and OS. The prognostic value of the IGLV3-21R110 was also independent of the IGHV mutational status. In terms of applicability in the clinics, all n-CLL cases were classified as unmutated IGHV and 98% of m-CLL were mutated IGHV. Thus, either a complete IG characterization (IGHV mutational status and IGLV3-21R110) or the integration of the n-CLL subtype and IGLV3-21R110 identified virtually the same subset of patients with aggressive disease. Conclusions: The IGLV3-21R110 defines a CLL subset with borderline IGHV mutations, specific driver alterations, a gene expression signature including WNT5A/B overexpression, and an unfavorable prognosis independent of the IGHV mutational status and epigenetic subtypes. Our findings support the identification of IGLV3-21R110 CLL as a particular subgroup of the disease with relevance in the risk stratification of the patients. Disclosures Nadeu: Janssen: Honoraria. Campo:NIH: Consultancy, Other: Co-inventor on a patent related to the MCL35 assay filed at the National Institutes of Health, United States of America..

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Multiple Myeloma Includes Phenotypically Defined Subsets of Clonotypic CD20+ B Cells that Persist during Treatment with Rituximab

Clinical medicine Oncology ◽

10.4137/cmo.s615 ◽

2008 ◽

Vol 2 ◽

pp. CMO.S615 ◽

Cited By ~ 1

Author(s):

Linda M. Pilarski ◽

Eva Baigorri ◽

Michael J. Mant ◽

Patrick M. Pilarski ◽

Penelope Adamson ◽

...

Keyword(s):

Multiple Myeloma ◽

B Cells ◽

B Cell ◽

Plasma Cells ◽

Cell Subset ◽

Light Scatter ◽

Cell Compartments ◽

B Lineage ◽

B Cell Subsets ◽

Anti Cd20

Potential progenitor B cell compartments in multiple myeloma (MM) are clinically important. MM B cells and some circulating MM plasma cells express CD20, predicting their clearance by treatment with anti-CD20. Here we describe two types of clonotypic CD20+ B cell in peripheral blood of myeloma patients, identified by their expression of CD19 and CD20 epitopes, their expression of CD45RA and their light scatter properties. Thus, the circulating component of the MM clone includes at least two distinct CD19+ CD20+ B cell compartments, as well as CD138+CD20+ plasma cells. To determine whether either or both B cell subsets and the CD20+ plasma cell subset were depleted by anti-CD20 therapy, they were evaluated before, during and after treatment of patients with rituximab (anti-CD20), followed by quantifying B cell subsets over a 5 month period during and after treatment. Overall, all three types of circulating B lineage cells persist despite treatment with rituximab. The inability of rituximab to prolong survival in MM may result from this failure to deplete CD20+ B and plasma cells in MM.

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Genome-Wide DNA Methylation Landscape Defines IGHV Mutated and Unmutated B Cell Chronic Lymphocytic Leukemias

Blood ◽

10.1182/blood.v120.21.526.526 ◽

2012 ◽

Vol 120 (21) ◽

pp. 526-526

Author(s):

Junfeng Luo ◽

Justin Choi ◽

Lirong Pei ◽

Farrukh Awan ◽

Eun-Joon Lee ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

B Cells ◽

B Cell ◽

Dna Hypomethylation ◽

Excellent Correlation ◽

Methylation Analysis ◽

Promoter Regions ◽

Genome Wide ◽

Dna Methylation Analysis

Abstract Abstract 526 Chronic lymphocytic leukemia (CLL) is a biologically and clinically heterogeneous disease. The somatic hypermutation status of the immunoglobulin heavy chain variable (IGHV) genes has been identified as one of the most robust prognostic markers in CLL. Patients with unmutated IGHV status (U-CLL) typically experience an inferior outcome compared to those whose clones express mutated IGHV genes (M-CLL). We conducted a genome-wide DNA methylation analysis in CD19+ B-cells from a group of 43 CLL patients using reduced representation bisulfite sequencing (RRBS). Using base-pair resolution methylation sequencing, 2323 differentially methylated regions between CLL and normal B cells (CLL-specific DMRs) and 569 between M-CLL and U-CLL samples (IGHV-specific DMRs) were identified in the CLL genomes. The IGHV-specific DMRs are mostly unique when compared to the CLL-specific DMRs. Less than 10% of the IGHV-specific DMRs are located in promoter regions; however, more than half of these overlap with known DNase I hypersensitive sites, enhancer regions marked by histone modification (H3K4Me1 and H3K27Ac), and transcription factor binding sites in the ENCODE datasets, which indicates that these DMRs contain regulatory sequences. Distinctive DNA methylation patterns were observed in M-CLL and U-CLL samples. Overall, U-CLL was found to contain 50% more hypermethylated regions than M-CLL samples. The hypermethylated loci observed in the U-CLL samples also appear to be hypermethylated in normal naïve B cells as compared memory B cells, suggesting that M-CLL and U-CLL differ in differentiation status corresponding to normal B cell differentiation stages. RNA-seq analysis performed using matched samples (n=34), in which both DNA methylation and gene expression data were available, demonstrated excellent correlation between DNA methylation and gene expression. Several genes whose expression status was previously shown to be associated with CLL prognosis such as ZAP70, CRY1, LDOC1, SEPT10, LAG3, and LPL were differentially methylated in the promoter regions between M-CLL and U-CLL samples indicating that DNA methylation plays an important role in defining the gene expression patterns of these prognostic genes. We further validated 9 genes with IGHV-specific DMRs in the promoter regions using bisulfite pyrosequencing, and the results demonstrated excellent correlation between differential methylation and IGHV mutation status. These novel differentially methylated genes could be developed into biomarkers for CLL prognosis. In addition, DNA hypomethylation was observed in a significant number of genes involved in lymphocyte activation such as PDCD1, NFATc1, and CD5. DNA hypomethylation was observed in the proximal promoter and far up-stream enhancer regions of CD5, an important cell surface marker that uniquely identifies CLL. Overall, the DNA methylation landscape in CLL patients indicates that CLL B cells possess an active B-cell phenotype; at the same time, U-CLL and M-CLL are faithfully committed to their lineage resembling either naïve or memory B cells. In summary, this comprehensive DNA methylation analysis has identified a large number of novel epigenetic changes in CLL patients. The results from this study will further advance our understanding of the epigenetic contribution to molecular subtypes in CLL. Disclosures: No relevant conflicts of interest to declare.

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A Novel Role For Histone Deacetylase 11 (HDAC11) In Plasma Cell Differentation and Survival

Blood ◽

10.1182/blood.v122.21.1907.1907 ◽

2013 ◽

Vol 122 (21) ◽

pp. 1907-1907

Author(s):

Eva Sahakian ◽

Jason B. Brayer ◽

John Powers ◽

Mark Meads ◽

Allison Distler ◽

...

Keyword(s):

Gene Expression ◽

Multiple Myeloma ◽

Bone Marrow ◽

B Cells ◽

Plasma Cell ◽

Research Funding ◽

Plasma Cells ◽

Myeloma Cells ◽

Peripheral Blood Plasma

Abstract The role of HDACs in cellular biology, initially limited to their effects upon histones, is now appreciated to encompass more complex regulatory functions that are dependent on their tissue expression, cellular compartment distribution, and the stage of cellular differentiation. Recently, our group has demonstrated that the newest member of the HDAC family of enzymes, HDAC11, is an important regulator of IL-10 gene expression in myeloid cells (Villagra A Nat Immunol. 2009). The role of this specific HDAC in B-cell development and differentiation is however unknown. To answer this question, we have utilized a HDAC11 promoter-driven eGFP reporter transgenic mice (TgHDAC11-eGFP) which allows the monitoring of the dynamic changes in HDAC11 gene expression/promoter activity in B-cells at different maturation stages (Heinz, N Nat. Rev. Neuroscience 2001). First, common lymphoid progenitors are devoid of HDAC11 transcriptional activation as indicated by eGFP expression. In the bone marrow, expression of eGFP moderately increases in Pro-B-cells and transitions to the Pre- and Immature B-cells respectively. Expression of eGFP doubles in the B-1 stage of differentiation in the periphery. Of note, examination of both the bone marrow and peripheral blood plasma cell compartment demonstrated increased expression of eGFP/HDAC11 mRNA at the steady-state. These results were confirmed in plasma cells isolated from normal human subjects in which HDAC11 mRNA expression was demonstrated. Strikingly, analysis of primary human multiple myeloma cells demonstrated a significantly higher HDAC11 mRNA expression in malignant cells as compared to normal plasma cells. Similar results were observed in 4/5 myeloma cell lines suggesting that perhaps HDAC11 expression might provide survival advantage to malignant plasma cells. Support to this hypothesis was further provided by studies in HDAC11KO mice in which we observed a 50% decrease in plasma cells in both the bone marrow and peripheral blood plasma cell compartments relative to wild-type mice. Taken together, we have unveiled a previously unknown role for HDAC11 in plasma cell differentiation and survival. The additional demonstration that HDAC11 is overexpressed in primary human myeloma cells provide the framework for specifically targeting this HDAC in multiple myeloma. Disclosures: Alsina: Millennium: Membership on an entity’s Board of Directors or advisory committees, Research Funding. Baz:Celgene Corporation: Research Funding; Millenium: Research Funding; Bristol Myers Squibb: Research Funding; Novartis: Research Funding; Karyopharm: Research Funding; Sanofi: Research Funding.

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

Blood ◽

10.1182/blood.v124.21.3404.3404 ◽

2014 ◽

Vol 124 (21) ◽

pp. 3404-3404

Author(s):

Jana Jakubikova ◽

Efstathios Kastritis ◽

Danka Cholujova ◽

Teru Hideshima ◽

Ludmila M Flores ◽

...

Keyword(s):

Multiple Myeloma ◽

Flow Cytometry ◽

B Cells ◽

B Cell ◽

Natural Killer ◽

Plasma Cells ◽

Memory B Cells ◽

High Dimensional ◽

Newly Diagnosed ◽

D Cells

Abstract Introduction: CyTOF (time-of-flight mass cytometry) is a novel high-dimensional technology which permits immunophenotyping and analysis of signaling in single cells. This approach enables simultaneous evaluation of up to 40 parameters using antibodies tagged with distinct elemental isotopes, by combining flow cytometry with atomic mass spectrometry. Since multiple myeloma (MM) is characterized by immune dysfunction, we used CyTOF technology to define the complex immune profile in MM patient bone marrow (BM) samples. Methods: We used 40 different markers to define various B, T, natural killer (NK) subsets, as well as cells of monocytic, granulocytic, erythroid and platelet lineages. Our preliminary data are results from 10 patients with MGUS/ smoldering MM (SMM); 10 newly diagnosed MM; 20 relapsed/refractory MM; and 15 WM patients (5 newly diagnosed and 10 receiving treatment) in comparison with age-matched healthy donors’ BM (HD). A significantly larger cohort of MM (N=150) and WM (N=50) patients is being similarly analyzed and will be presented. To evaluate phenotypic abnormalities in various B cell subsets, we used B lineage markers CD10, CD19, CD20, CD22, CD27, CD34, CD38, CD45, IgA, IgD, IgG and IgM to define B cells maturation stages from hematopoietic stem cells (HSC) to naïve to mature B lymphocytes (pro-B; pre-B-I; pre-B-II; immature B; and mature (naïve) B cells), as well as memory non-switched and memory switched B cells, plasmablasts, normal (CD138+CD38+CD19+CD45+) and clonal plasma cells (CD138+CD38+CD19-CD45-/low), which reside in the specific BM niche. Furthermore, natural killer (NK) subsets (such as NK and NKT cells) and T cells (such as memory CD4T, naive CD4T, memory CD8T, naive CD8T, T regulatory cells and Tg/d cells) were examined. High-dimensional data was obtained using CyTOF technology and analyzed by SPADE and viSNE software. Results: Our data showed significantly decreased HSC in patients with newly diagnosed and relapsed/refractory MM compared to HD (P<0.025). A significant increase in pre-B-I cells was detected in relapsed/refractory MM vs. MGUS/SMM (P<0.028), but the opposite trend was observed in the pre-B-II subpopulation (P<0.005). No differences in immature B cell populations were observed in different stages of MM. However, a significantly higher percentage of immature B cells was present in relapsed/refractory MM compared to HD (P=0.008), and transitional B cells were significantly decreased in newly diagnosed MM compared to HD (P<0.001). Moreover, memory B cells were significant decreased in all MM stages compared to HD (P<0.003). Non-switched memory B cells were significantly increased in MGUS and SMM compared to newly diagnosed MM, while a significant increase of switched memory B cells was present in newly diagnosed MM compared to relapsed/refractory MM. A significant increase in plasmablasts was seen in relapsed/refractory MM in comparison with other MM stages (P<0.011) by CyTOF analyses. Malignant plasma cells (PC) were defined as CD19-, CD38++, CD45-/dim, CD138+ and either cyk or cyl positive. Importantly, a significant increase in clonal PC was found in all MM stages vs. HD, as well as in newly diagnosed MM compared to relapsed/refractory MM (P<0.01). The percentage of PC from CyTOF analyses correlated with % of PC obtained using flow cytometry by Bland-Altman method comparison. We also observed significant differences in T cell subsets including naïve, central memory, effector, and effector memory CD4+ and CD8+T populations between MGUS and newly diagnosed MM, but no significant changes in T regulatory and Tg/d cells. Furthermore, plasmacytoid dendritic (pDC) cells were significantly increased in newly diagnosed MM, and PD-1 expressed on pDC was significantly decreased in newly diagnosed MM compared to MGUS (P=0.007). Interestingly, PD-1 and its ligand PD-L1 were variably expressed on B cells (2-9% and 3-27%) and PC (0.5-46% and 3-41%) from MM BM samples. Other surface molecules including CD269 (4-32%), CD289 (1-8%), CD362 (0.5-1%) and CD329 (1-4%), were variably expressed in PC. Conclusion: A better understanding of the neoplastic BM milieu will provide the framework for identifying and validating novel targeted therapies directed against MM. CyTOF technology represents a novel diagnostic tool to assess the status not only of MM, but also of host immunity, and may allow for the development of rational personalized therapies. Disclosures No relevant conflicts of interest to declare.

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