Fonseca, Rafaël

Abstract Background: Clonal cytogenetic aberrations define multiple myeloma (MM) into unique subsets of the disease each one with unique clinical and biologic features, associations with laboratory and pathologic markers and presumed differential influence on disease progression. While it is widely accepted that translocations represent primordial events in the pathogenesis of MM, it is controversial whether all translocations can be associated with disease stability and non-malignant behavior (i.e. in MGUS/SMM). We have found the translocations in cases of MGUS using dual fusion, cIg enhanced, interphase FISH, while others have found this translocation at lower prevalence using single fusion interphase FISH or the RT-PCR for IgH/MMSET. We thus sought to clarify by expanding the study of the t(4;14) among patients with MGUS and SMM. Materials and methods: We studied 210 patients who had the diagnosis of MGUS and SMM and entered into the Mayo Clinic Dysproteinemia database. Patients were excluded if they had active MM, extramedullary disease or plasmacytoma. Patients with isolated lytic bone lesions could be included if they had no overt evidence of progression. All studied patients had provided written informed consent for the collection of a research bone marrow aliquot that was collected at the time of routine bone marrow procurement. All patients had cytospin slides that were studied for a t(4;14) using cIg-FISH as previously described by us and using a double fusion FISH strategy. The importance of this is that the strategy will detect unbalanced t(4;14) with loss of der(14). Results: Twenty patients (9.5%) had evidence of the chromosome translocation. Detailed demographic data was available in 19; 14 were women (74%), 13 of 19 (68%) had SMM and there was no bias for heavy chain IgA (26%). Patients with t(4;14) were slightly younger than those without the abnormality (52 vs. 61 years), had similar hemoglobin concentrations, had slightly higher concentration of the serum M spike (2.0 vs 1.75 g/dl) and had overall slightly higher bone marrow plasmacytosis (median 23% vs 10%). Patients were followed since diagnosis for a median of 33 months (range 2–162 months). Three patients progressed to active MM at 12, 12 and 26 months after original diagnosis (all three originally having indolent/SMM). Conclusion: The t(4;14) can occur in patients with MGUS and SMM and without evidence of progression to MM. The prevalence is similar to that observed in MM, albeit slightly lower (9.5% versus 14%). In most “benign” plasma cell neoplasms the translocation is associated with greater plasmacytosis and thus enriched for in the smoldering MM category. It is also likely that the t(4;14) confers a higher risk of progression to MM given; a) its enrichment in SMM, b) the slightly higher prevalence of the translocation in MM as opposed to MGUS/SMM, and c) the well documented aggressive clinical course of MM with t(4;14).

Abstract Activation of NFkB has been noted in late B-cell malignancies, but no genetic basis for this activation has been shown except for rare mutations of the NFkB pathway in lymphoma and none have been described in MM. Bortezomib, highly tumoricidal in a subset of MM patients, inhibits NFkB suggesting it’s role as a therapeutic target. Here we show for the first time the critical importance of mutations that dysregulate this potential survival pathway in human myeloma cell lines (HMCL) and new diagnosis MM patients. We performed high-density oligonucleotide array CGH (Agilent 44k) on CD138+ selected MM cells from 68 patients and 42 unique HMCL. Initially we focused on small loci, bi-allelically deleted, as markers for inactivation of potential tumor suppressor genes. We next developed FISH probes for the identified loci to confirm the bi-allelic deletions seen by aCGH. We next sequenced all samples with monoallelic deletions, and additional unselected patients, and identified additional inactivating mutations. Multiple novel tumor suppressor genes (TSG) were identified and validated, whose loss of function (both in patients and HMCL) leads to activation of the non-canonical NFkB pathway including: TRAF2 (9q34), TRAF3 (14q32), BIRC2/BIRC3 (11q22) and CYLD (16q12). Functional studies showed that HMCL with deletion or mutations in these genes have markedly increased NFkB2 p52/p100 ratios relative to other HMCL (and for BIRC2/BIRC3 relative to an isogenic line that retains one copy of BIRC2/BIRC3), indicating genetic activation of the non-canonical NFkB pathway. Reintroduction of deleted TSG into HMCL inhibited cell growth and resulted in cell death (see data on abstract by J. Keats et al). We next focused our analysis (of combined aCGH and GEP data) on positive regulators of this pathway. Rare IgH translocations of NIK have recently been identified in MM. By aCGH we identified amplification and rearrangements of NIK. We identified dysregulated expression of TNF family receptors that activate the non-canonical pathway: CD40 (translocation), TACI (amplification) and LTBR. All of the HMCL with these mutations also showed increased NFkB2 p52/p100 ratios, consistent with activation of the non-canonical NFkB. These mutations correlate with a gene expression profile of NFkB activation that is detected in one half of patients. In summary, we have determined for the first time the genetic basis for constitutive NFkB activation - present in 19/42 HMCL, and we estimate in at least one quarter of newly diagnosed patients (approximately one half of those with evidence of NFkB activation by GEP). We propose a mechanism in which positive (TACI, CD40, LTBR) and negative regulators (TRAF2, TRAF3, BIRC2/BIRC3, CYLD) of the pathway converge on NIK to mediate the processing of NFKB2 p100 to p52. The preponderance of genetic evidence suggests that drugs that target the non-canonical NFkB pathway, will be most effective in treating the 50% of MM patients with NFkB activation.

Abstract Introduction: The analysis of what goes awry in a malignant cell has focused primarily on mutations of protein-encoding genes and their regulatory sequences. However, recent work on microRNA (miRNA) has shed light on the possible involvement of miRNA genes in human disease. miRNA are small “noncoding” or “non-messenger” RNAs of about 21–25 nucleotides in length that function as regulators of gene expression essentially by pairing to the mRNA of protein-coding genes to initiate mRNA degradation or repression of translation. We are interested in characterizing miRNA expression profiles in human myeloma cell lines (HMCLs) and myeloma patient samples. Multiple myeloma (MM) is a plasma cell tumor characterized by frequent chromosomal translocations. Materials and methods: The expression of miRNA in HMCLs, primary MM cells (hyperdiploid samples) and normal plasma cells was determined using human microRNA chips. The GenoExporerTM Human microRNA chips were developed by GenoSensor (Tempe, AZ) and the microarray contains 226 human microRNA sequences in addition to control sequences. The DNA oligo probes are synthesized and immobilized on the chips (1”x 3” standard glass microslide). The probes are designed based on the active mature miRNA sequences and some of their flanking sequences. Our analysis included seven myeloma patients (hyperdiploid MM), eight different HMCLs (MM1, 8226 with t(14;16); SKMM2, U266, INA-6 with t(11;14) and H929, KMS11, UTMC-2 with t(4;14)), and eight normal human plasma cells. The normal human plasma cells were collected at Mayo Clinic Rochester from bone samples of patients undergoing orthopedic surgery. For the assay 5–10 μg of total RNA per sample were used at a concentration of 1 μg/μL. The RNA is directly labeled with biotin and used as a target for the on-chip hybridization assays. A streptavidin-Alexa dye is used to stain the hybridized targets and the fluorescent signals are captured and analyzed. The gene signal intensities were normalized to tRNA signal intensity. Results: The primary MM cells and HMCLs displayed a distinctive miRNA expression profile compared with normal plasma cells. Using the GeneSpring 7 (Agilent Technologies, Palo Alto, CA) for gene expression analysis we have identified miRNA genes with significant variation in expression levels between tumor and normal samples including miR-125b, miR-133a, miR1, and miR-124a (p<0.01). Recently defined algorithms were used to identify putative targets for the miRNA genes of interest such as leukemia inhibitory factor (LIF) as targets of miR-125b and Stat3 and angiopoietin-1 precursor as targets of miR-124a (Lewis et al. 2003). Of note, miR-15 and miR-16, previously identified to be downregulated in CLL, were expressed at low levels in some MM patients and HMCLs, but not in the normal plasma cells. Further analysis will be carried out to validate the data from miRNA profiling using northern blot analysis or real-time RT-PCR to measure expression levels of miRNA genes and that of their target genes. Conclusion: Analysis of miRNA expression pattern (along with aCGH and gene expression profiling studies) will undoubtedly refine our understanding of the various genotypic subtypes of multiple myeloma.

Abstract H-MM affects about 40–50% of patients, and a similar proportion of MGUS/SMM. The genetic evolution of the disease and the clinical implications of the co-existence of 13q- or t(14q32) are unknown. We conducted a global survey of genetic abnormalities in H-MM in order to describe genetic evolution pathways. H-MM cases from the Mitelman cancer genetic database were combined with cases from the Mayo Clinic MM genetic database. All abnormalities (regional/whole chromosome gains/losses, breakpoints and translocations) were plotted against a 344-chromosome band profile created in a matrix format, and the number of genetic abnormalities per tumor (NAPT) logged. The abnormalities present in more than 5% of tumors were considered recurrent and each karyotype was scored for the presence or absence of each of the recurrent abnormalities. To investigate the temporal pattern of acquisition of genetic abnormalities, all tumors with a given abnormality were selected and the distributions of NAPT plotted. The modes of these distributions were used as a value of ‘lateness’, referred to as time of occurrence (TO). The impact of co-existence of 13q- and t(14q32) on progression free survival (PFS) and overall survival (OS) in H-MM was determined for MM patients entered into an Eastern Cooperative Oncology Group chemotherapy trial. Four hundred and sixty-nine H-MM patients were included in the karyotypic analysis. The median chromosome number was 53 (range 48–74) and the median NAPT was 10 (range 1–25). The distribution of NAPT revealed a normal distribution, suggesting an obligatory acquisition of a given number of genetic abnormalities. The most common abnormalities were trisomies of chromosomes 3,5,7,9,11,15,19 and 21 affecting a third or more of the patients. Deletions and abnormalities of even-numbered chromosomes occur in 20% or less of patients. None of the more than 300 specific translocations detected were recurrent. However, 5 translocation breakpoints were recurrent including 14q32, 8q24 and 11q13. TO analysis suggest that for H-MM, the trisomies are early genetic events, translocations occur midway and deletions tend to be later events. Amongst the trisomies, correlation analysis does not suggest a particular order of acquisition. Clustering analysis using principal component analysis suggests that in H-MM, IgH translocations are secondary events associated with disease evolution rather than defining unique biological entities. Consistent with this, survival of H-MM patients is not affected by 13q- status but is negatively impacted by the presence of t(14q32) especially those with unknown partners (p<0.05). The data presented suggest that H-MM fit a proposed aneuploid model of cancer due to auto-catalytic chromosome reassortment (Duesberg et al Cell Cycle2003:2:202–210). The presence of tumor specific trisomies and the apparent similar phenotype induced by various combinations of trisomies are consistent with this model.

Abstract Introduction: Increased bone marrow angiogenesis is a characteristic feature of multiple myeloma (MM) and correlates with disease progression. Increased bone marrow angiogenesis at the time of diagnosis, measured in terms of microvessel density (MVD), is a powerful adverse prognostic factor for patients with MM. To better understand the biological basis of this phenomenon and to understand the mechanisms responsible for increased MVD in MM we compared the gene expression profiles of plasma cells from newly diagnosed MM patients with low and high MVD. Methods: Bone marrow biopsy sections from pts with newly diagnosed MM were studied using CD34 immunostaining and graded as low, intermediate, or high by MVD as previously described. 19 pts each, with low or high MVD were included for this study. RNA was isolated from CD138+ plasma cells of MM patients and analyzed using Affymetrix HG-U133A arrays. To examine differential expression, GC-RMA normalized data was analyzed using GeneSpring 7.2 software and genes with ≥ 2-fold differential expression between high and low MVD samples were identified. The Welch T-test was used to determine the significance of differential expression. Results and Conclusion: Expression of 42 transcripts was increased ≥ 2-fold in samples with high MVD in comparison to samples with low MVD. Of these transcripts, 14 were found to be significantly increased (P<0.05) using the Welch T-test (see Table 1). Expression of 16 transcripts was decreased ≥ 2-fold in samples with high MVD in comparison to samples with low MVD. Of these transcripts, 6 were found to be significantly decreased (P<0.05) using the Welch T-test (see Table 1). Genes differentially expressed include those involved in inhibiting apoptosis, facilitating IL-6 signaling, ion transport, extracellular matrix interaction, and regulating gene expression. Classical angiogenesis genes including VEGF, FGF, and IGF were not found to be differentially expressed (> 2-fold). In conclusion, the list of differentially expressed genes reveals many functions relevant to MM disease pathology including proliferation, apoptosis, regulation of gene expression, cytokine signaling, and adhesion. Current studies evaluating the expression and function of these genes in relation to MM may identify factors critical for angiogenesis and MM progression and provide insight for therapeutic intervention. Gene Description Fold Change COL1A2 collagen, type I, alpha 2 3.008 MCL1 myeloid cell leukemia sequence 1 (BCL2-related) 2.793 209183_s_at chromosome 10 open reading frame 10 2.541 VIL2 villin 2 2.478 IL6ST interleukin 6 signal transducer (gp130) 2.404 CLIC2 chloride intracellular channel 2 2.364 DEPDC6 DEP domain containing 6 2.35 PBXIP1 pre-B-cell leukemia transcription factor interacting protein 1 2.337 CLIC4 chloride intracellular channel 4 2.334 CYP51A1 cytochrome P450, family 51, subfamily A, polypeptide 1 2.095 LIMS1 LIM and senescent cell antigen-like domains 1 2.091 YWHAE tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, epsilon polypeptide 2.042 OAS1 2′,5′-oligoadenylate synthetase 1, 40/46kDa 2.031 S100A11 S100 calcium binding protein A11 2.018 222378_at unknown transcribed sequences 0.496 SLC5A3 mitochondrial ribosomal protein S6 0.463 213089_at unknown transcribed sequences 0.406 PDE4B phosphodiesterase 4B, cAMP-specific 0.454 SVIL supervillin 0.386 RIPX rap2 interacting protein x 0.383

Abstract Background: Thalidomide and dexamethasone combination has been shown to be an effective therapy for multiple myeloma (MM). In newly diagnosed patients with MM, the combination results in overall response rates of over 70% of patients. However, a considerable number of patients do not respond and will need to proceed to other therapies. The ability to identify patients who are unlikely to respond to particular therapies will allow tailoring of therapeutic approaches and in turn will reduce unnecessary toxicity and morbidity from lack of rapid disease control. With the availability of new technology such as gene expression profiling (GEP), this has become a possibility. We employed this approach to identify genes that can reliably predict lack of response to the thalidomide dexamethasone combination. Methods: Patient samples from the Eastern Co-operative Oncology Group clinical trial (E1A00), that compared thalidomide-dexamethasone combination with dexamethasone, and patient samples from the phase II Mayo Clinic study of thalidomide and dexamethasone, both for newly diagnosed MM, were used for this study. Thirty newly diagnosed patients who were evaluable for response were included in the analysis. GEP was performed using the Affymetrix U133A microarray platform as per manufacturer’s recommendation. The Affymetrix output (CEL files) was imported into Genespring 7.2 (Agilent Technologies) microarray analysis software, normalized across chips using GCRMA followed by per gene normalization to median. For the purposes of this study, responses were defined as reduction in the serum paraprotein (or the urinary M protein in the absence of a serum M protein) of >=50% (PR), 25 to 49% (MR), increase of >=50% (PD) and stable disease for the remaining. Results: Five of the 30 patients had no response to the thalidomide Dexamethasone therapy. Using the class prediction tool available in Genespring (Support Vector Machines), we identified 25 genes that reliable predicted non responders (PD, NC) from the responders (MR, PR, and CR). See table for a list of predictive genes with identified genes. Conclusion: Using a combination of two datasets we have identified a set of genes that can be used to reliably predict lack of response to thalidomide and dexamethasone in patients with newly diagnosed MM. We think that this represents a step towards creation of custom microarrays spotted with genes that are capable of predicting lack of response (or response) for the purpose of tailoring therapy to the patient. Gene Predictive strength hypothetical protein FLJ20719 1.655 Tubulin alpha 6 1.653 SEC3-like 1 (S. cerevisiae) 1.649 Ribosomal protein L18 1.546 Ribosomal protein L4 1.432 Tubulin alpha 6 1.409 cleavage stimulation factor 1.393 Tubulin, alpha, ubiquitous 1.393 CD99 antigen 1.38 hmel2 1.346 Leptin receptor 1.291 Integrin-linked kinaseSMC4 structural maintenance of chromosomes 4-like 1 1.269 Cornichon homolog 1.255 Williams-Beuren syndrome chromosome region 5 1.217 Ubiquitin specific protease 1 1.2 Sarcoma antigen NY-SAR-91 1.2

Abstract Waldenström’s macroglobulinemia (WM) is an incurable low-grade lymphoproliferative disorder characterized by bone marrow (BM) infiltration of a clonal population of small B-lymphocytes, plasmacytoid lymphocytes and plasma cells that secrete monoclonal IgM antibody. Because it is difficult to obtain tumor metaphases for karyotype studies, few recurrent chromosomal abnormalities have been reported and the genetic basis of the disease remains poorly defined. Therefore, we performed a comprehensive high-resolution study to identify genomic abnormalities involved in WM pathogenesis. Fifty-seven WM patients were analyzed using a combination of array-based comparative genomic hybridization (aCGH)(N=42); gene expression profiling (GEP)(N=22), DNA sequencing (N=24) and cIgM-FISH (N=57). Agilent 244A and Affymetrix U133 platforms were used in the aCGH and GEP experiments, respectively. An NF-κB index was calculated from GEP data, as a surrogate marker of NF-κB transcription activity. NFKB2 sub cellular localization was determined by immunofluorescence staining. Overall, 83% of samples have aCGH defined chromosomal abnormalities, with a median of 3 abnormalities per patient (range 0 to 27). We identified 16 recurrent regions of copy number change found in >5% (3 or more patients); 10 deleted and 6 amplified regions. The most common abnormality was the entire or partial deletion of 6q, identified in 40% of cases. Four nonoverlapped minimal deleted regions were identified on 6q (MDR1 to MDR4), each of them being present in at least 14 of 17 patients with the abnormality. Gain of 6p was the second most common abnormality (17%) and its presence was always concomitant with 6q loss. Other recurrent deletions were 13q14 (10%) and 7q22, 8p, 11q22-q23, 11q23-q24 and 17p11-p13 (7% each). Copy gains were identified as partial or entire gains of chromosomes 18 (17%), 4 (12%) and 3 (10%), 8q (10%) and Xq27.1-q28 (10%). Three patients had either homozygous deletions or LOH with mutations affecting both alleles of TRAF3 on 14q32. TRAF3 inactivation was correlated with an increased NF-kB transcriptional signature and it was associated with activation of the non-canonical NFkB pathway. Additionally, we identified the inactivation of TNFAIP3, another negative regulator of the NF-kB pathways, in one of 24 patients. Finally, interstitial deletions identified in 4 patients at 13q14 identified a 1.1 Mb MDR, including MIRN15A and MIRN16-1. These findings confirm that focal 13q14 deletion is not restrict to B-CLL and that the MIRN15A/MIRN16-1 abnormalities might be common to several indolent B-cell diseases. Overall, we identified TRAF3 and TNFAIP3 inactivation in 5.3% and 2.4%, respectively. To our knowledge, this is the first study showing the inactivation of bona fide tumor suppressor genes in WM patients. Furthermore, these genes are negative regulators of NF-kB signaling pathway, highlighting its biologic importance in sustaining and limiting growth in WM. Mutational activation of this pathway, which is normally activated by ligand-receptor interactions within the BM microenvironment, suggest a therapeutic role for inhibitors of NF-KB pathway activation in the treatment of WM.

Abstract The objective of this study was to analyze protein changes that occur a the molecular level with novel therapeutic agents used in MM in order to identify potential combinations for clinical trials. We employed antibody protein microarrays (BD Clonetech, CA) to measure changes in the patterns of protein expression in Kas 6/1 MM cell line after treatment with bortezomib, dexamethasone, CC-5013, and 17-AAG. The antibody array is a new technique that assays protein differences directly by hybridizing fluorescently labeled protein mixtures from cell extracts onto glass slides spotted with 512 different monoclonal antibodies specific for human proteins. Induction of apoptosis was assessed by Annexin/Propidium iodide FACS analysis at 24 and 48 hours using different concentrations of the inhibitors. Protein arrays were performed at concentrations and treatment times that did not induce more than 25% apoptosis to ensure adequate analysis of early changes in signaling pathways. Bortezomib 5nM at 10 hours, dexamethasone 100mM, CC-5013 250nM, and 17-AAG 1mM at 24 hours were used. Control cells were treated with vehicles ETOH or DMSO at the same concentrations as the inhibitors. To assess differential protein expression, the mean of the Cy5/Cy3 ratios for each sample and its control were analyzed using the Clontech software and an internally normalized ratio (INR) was calculated. INR values >1.3 or <0.77 were considered as valid changes in protein abundance for this study. All inhibitors induced the upregulation of apoptosis proteins including BAK, BIK, SMAC/DIABLO, and caspase 14. Several proteins were inhibited by all 4 inhibitors indicating common pathways affected by these agents. These included members of the PI3K pathway (PI3K-p85a, p70S6kinase, and cyclin dependent kinases), MAPKinases (ERK1 and 2), antiapoptotic protein Bclx, heat shock proteins Hsp70 and HSP60, and ubiqutin/NFkB pathway (Ubch6, IKKalpha, and IKBe). These results indicate that inhibitors of the PI3K pathway such as mTOR inhibitors, IKK inhibitors or MAPkinase inhibitors may be used in the future in combination with bortezomib, dexamethasone, CC-5013 or 17-AAG. Fatty acid synthetase was downregulated by bortezomib and dexamethasone indicating potential use of fatty acid synthase inhibitors in combination with bortezomib or dexamethasone in future clinical trials. These results suggest that antibody protein arrays may be used in the rational design of combinations of targeted therapies in MM.

Abstract Our understanding of the molecular pathogenesis of myeloma is largely based on observations made from the available human myeloma cell lines. Cell lines have proved invaluable to the characterization of the known immunoglobulin translocations, recurrent deletions and amplifications, and the development of novel therapies. However, it has long been perceived that the cell lines are not representative of patient samples as they often have complex genomes and not even a single cell line has been described with a typical hyperdiploid karyotype. The absence of a hyperdiploid model system is significant as conventional cytogenetic studies of myeloma patient samples has established that patients can be almost evenly split into two broad categories of hyperdiploid and non-hyperdiploid based on their chromosome counts, with the hyperdiploid patients having recurrent trisomies of chromosomes 3, 5, 7, 9, 11, 15, 19, and 21 plus periodic gains of 1q, 18, 20 and loss of 13. Though all of the cell lines have abnormal genomes none of the previously tested cell lines had the characteristic pattern of chromosomal gains seen in hyperdiploid patients and the majority have immunoglobulin translocations, which are more commonly associated with non-hyperdiploid patients. These observations have provided the basis for the assumption that the cell lines are only representative of the non-hyperdiploid patient population. Furthermore, even though very few cell lines have been directly compared to the patient sample from which they were derived it is widely believed that the cell line genomes are unstable and have diverged significantly from the patient samples from which they were derived. Therefore, we decided to compare patient-cell line pairs available from the Mayo Clinic using Agilent 244k array-based comparative genomic hybridization (aCGH) and Affymetrix U133Plus2.0 gene expression profiling and repeated the analysis of our previously studied 46 cell lines on the higher resolution Agilent 244k platform. To date we have completed the analysis of four patient cell line pairs (ALMC-1; ALMC-2; KP-6; KAS-6/1, KAS-6/2) and have repeated our entire cell line panel on the higher resolution array. Four additional patient-cell line pairs (DP-6, JMW-1, SPMC, and VPC-6) are currently being completed. The first compelling observation from this study was that the patient sample from which KP-6 was derived is a perfect match to the characteristic hyperdiploid karyotype with a CGH defined karyotype (51, XY, −1p, +1q, +3, +7, +11, −13, +15, −16q, −17p, +19, +21). The KP-6 cell line showed a similar aCGH defined karyotype (50, X, −Y, −1p, +1q, +3q, +7, −8p, +9p, +11, +15, −16q, −17p, +17q, +19, +21) with the most significant changes occurring on the trisomic chromosomes as many transitioned from trisomies to single arm gains. Therefore, KP-6 appears to be the first myeloma cell line derived from a patient with a characteristic hyperdiploid phenotype. The ALMC patient cell line series is comprised of patient samples at diagnosis and relapse and cell lines derived from both stages. The two patient-cell line pairs only show five and two aCGH definable changes, respectively. In comparison the two matched patient sample pairs have diverged at six regions in the genome. The KAS patient-cell line series is actually two cell lines derived from pre- (KAS-6/1) and post-transplant (KAS-6/2) samples and the KAS-6/2 matching post-transplant patient sample. The comparison of the paired patient sample and derived cell line shows only four aCGH detectable changes. Similarly, there are only three changes between the KAS-6/1 cell line and post-transplant patient sample suggesting that the evolution of this tumor in both the patient and tissue culture is very limited. In conclusion, this study has identified the first bona fide hyperdiploid cell line, thereby providing a valuable investigative tool to better understand the biological differences between the two broad genetic categories of myeloma. Moreover, we demonstrate that the genomes of myeloma cell lines are typically stable and highly representative of the patient sample that was placed into culture to establish the cell line thereby validating their use in the study of this disease.

Abstract Marginal zone B-cell lymphomas (MZL) represent a sub-group of indolent B-cell lymphomas, normally localized in the “marginal zone” of the secondary lymphoid follicles. Depending on the site of involvement, three distinct sub-types have been identified: extra nodal MZL of MALT type, splenic MZL (SMZL), and nodal MZL (NMZL). MALT lymphoma is the most frequent of the MZL subtypes, representing 70% of MZL and 7% to 8% of non-Hodgkin lymphomas. SMZL and NMZL comprise the remaining 20% and 10% of MZL, respectively, and account for less than 1% of NHL. The relative rarity of these lymphomas and difficulty in distinguishing them from other low-grade B-cell lymphoma subtypes like lymphoplasmacytic lymphomas (LPL), making therapeutic decisions difficult. The aim of this study was to perform a comprehensive high-resolution study to identify distinctive molecular markers in MZL and LPL, which would help to better define these lymphomas at genomic level and distinguish them from other types of low-grade B-cell lymphoma. We analyzed 119 patients, including 22 pulmonary MALT (pMALT), 20 non-pulmonary MALT (npMALT), 34 SMZL, 21 NMZL and 22 LPL (8 Waldenström’s Macroglobulinemia and 14 non-WM) cases. Human Agilent 244A platform was used by array-based comparative genomic hybridization (aCGH) analysis. Overall, 93% of patients have an altered genome. LPL had the highest amount of copy number abnormalities (median of 7.5 per patient; average of 11.7; range: 0–44), followed by npMALT (6.5; 7.6; 0–33), NMZL (5; 8.3; 0–31), SMZL (4; 7.1; 0–56) and pMALT (3.5; 4.3; 1–11). When the overall size of the abnormalities was considered, LPL was also the most affected disease with an average size of 245.15Mb included in copy number changes per patient, followed by NMZL (188.6Mb), npMALT (187.2Mb), SMZL (126.4Mb) and pMALT (109Mb). Deletions were more commonly observed than amplifications but the affected area was significantly smaller (average of 55.2Mb and 118.6Mb included in deletions and amplifications per genome, respectively). Partial or total gains of chromosome 3 and 18 were recurrently identified in all the entities, being the most common abnormalities in npMALT (60% and 50%, respectively) and pMALT (27% each). Trisomy 12 was also ubiquitously observed, ranging from 24% of NMZL to 9% of pMALT. Deletions in 6q were commonly identified in LPL (55%), npMALT (35%) and, in a less extent, in SMZL (12%) and NMZL (5%), but not in pMALT. Biallelic and focal monoallelic deletions at 6q23 clearly delineate a minimal deleted region (MDR) that includes TNFAIP3 as being the target gene of the abnormality. Deletions on 7q were found in SMZL and npMALT, thus delineating two MDR. Interstitial 11q deletions were found in LPL, NMZL and SMZL, but not in MALT. Chromosome 13 abnormalities were monosomies in NMZL and interstitial 13q14 deletions in LPL and SMZL, comprising MIRN15A and MIRN16-1 in the MDR. Partial X chromosome gains were common to all the entities but involving different areas: Xq27.3–q28 gains were recurrent events in LPL and NMZL, but not in SMZL and MALT, which were characterized by p arm gains or trisomies. Finally, some recurrent abnormalities were exclusive of specific entities: 1p deletions and 1q gains were only common in NMZL; a focal 2p gain including BCL11A and REL was found in npMALT and partial 8q gains were only identified in LPL. Trisomy 4 was only identified in the subgroup of LPL with WM, but not in the remaining LPL cases or in the remaining diseases. In this study we made a compendium of chromosomal abnormalities present in a group of related diseases, in which the molecular basis remains poorly defined. Using this high-resolution approach we were able to establish recurrent and disease-specific patterns of abnormalities and minimal deleted/amplified regions were redefined. Furthermore, TNFAIP3, a negative regulator of the NF-kB pathway, has been identified as being a commonly affected gene in MALT, LPL and NMZL, highlighting its potential role in pathogenesis.