Chng, Wee Joo

Abstract PURPOSE: Recent advances in understanding of the molecular alterations that occur at the genetic and epigenetic levels in Multiple Myeloma (MM) have led to major leaps in identifying molecular pathways that regulate progression and resistance to therapeutic agents. However, despite great scientific advances at the genomic level, studies to identify signaling pathways deregulated at the functional proteomic level in MM are limited. In this study, we used a rapid and reproducible antibody-based protein microarray technique to screen the functional differences between malignant plasma cells in samples obtained from patients with MM compared to normal plasma cells (NPC) from the bone marrow of healthy volunteers. METHODS: We determined the protein expression level of 512 polypeptides in 12 samples of newly diagnosed patients with MM using high-throughput proteomic analysis with antibody-based protein microarray. Primary CD138+ sorted MM cells were obtained from the bone marrow of patients after informed consent. MM1.S was used in this study. Using immunohistochemistry and immunoblotting were confirmed. Lentivirus was used to knockdown CRIK. Gene expression datasets from the Mayo Clinic (accession number GSE 6477) and the UAMS (accession number GSE 2658) were obtained from the Gene Expression Omnibus for analysis. The Mayo dataset was generated using Affymetrix U133A platform whereas the UAMS dataset was generated using Affymetrix U133plus 2.0 platform. RESULTS: We identified four subgroups of MM using unsupervised clustering analysis. We confirmed overexpression of some of these proteins including CRIK and CDK4 using immunohistochemistry and immunoblotting. Many of these proteins are known to be deregulated in MM, indicating that this technique can accurately identify proteins that are over or under-expressed in MM in a high-throughput fashion. In addition, we identified novel proteins that are not previously known to be differentially expressed in MM, including the small GTPase member of the Rho family, CRIK protein. We then showed using knockdown of CRIK that this novel protein specifically regulates migration and adhesion in MM. There was no effect on survival of MM cells using the CRIK knockdown. Analyzing the GEP data of the 15 NPC, 46 monoclonal gammopathy of undetermined significance (MGUS) or smoldering myeloma (SMM) and 101 MM samples from the Mayo Clinic, there was a significant increase in expression of CIT from NPC to MM. Among the 351 patients entered into TTII trials from UAMS, CIT expression was similar across the different TC class. Using a cut-off normalized expression level of 1.25 (a level above expression in NPC), MM with a high CIT expression (n=81) had a significantly shorter survival than the other patients. CONCLUSION: In this study, we show that MM cells express a high level of CRIK, and that inhibition of this protein leads to significant inhibition of adhesion and migration of MM cells. In addition, CRIK protein expression correlated with CIT gene expression, with high expression in MM samples compared to NPC. In addition, high CIT expression correlated with poor survival in patients with MM.

Abstract Although classified as marginal zone lymphomas under the WHO classification, the molecular relationship between splenic marginal zone lymphoma (SMZL), extranodal marginal zone B-cell lymphoma of mucosa-associated lymphoid tissue (MALT), and nodal marginal zone lymphoma (NMZL) has not been clarified. Furthermore, lymphoplasmacytic lymphoma (LPL) can show clinical morphologic and immunophenotypic overlap with these entities and may present a diagnostic challenge. In this analysis of gene expression data generated using the Affymetrix U133plus 2.0 chip from 32 SMZL, 25 MALTs (GI, salivary gland and lung), 23 NMZL and 25 LPL, we aim to identify the molecular relationship between these pathological entities using unsupervised methods, identify disease specific signatures and markers using supervised methods and also the functional implications of these signatures using a modified gene-set enrichment analysis. Using hierarchical clustering, MALT lymphoma forms a tight cluster regardless of tumor site. In addition, SMZL and NMZL form another large cluster. LPLs are divided into 2 main clusters with occasional samples interspersed amongst the SMZL and NMZL. There is no correlation between the percentage of CD20-positive B-cells, CD3-positive T-cells or CD138- positive plasma cells or tissue origin of the tumor and the way the samples are clustered. However, the separation of the LPLs into 2 major cluster correspond to the presence and absence of underlying Waldenstrom Macroglobulinaemia (WM), suggesting that the genes distinguishing the 2 clusters are potential markers for differentiating WM LPL from non-WM LPL. Next, using supervised analysis we identified a cluster of genes including MMP7, LTF and SFRP2 with high signals specific to MALTs, while other genes including PRDM1 (BLIMP1), XBP1 and TNFRSF17 (BCMA) were specifically over-expressed in LPL. These may therefore represent novel diagnostic marker differentiating these entities. Several of these are further validated at the protein level using immunohistochemistry on a tissue microarray. Consistent with the unsupervised analysis, SMZL and NMZL have little difference and share the over-expression of CD22 and WNT3 among other genes. Clustering of these samples based on the pathways and genesets that are enriched in the individual tumors as compared to their normal tissue counterpart showed a mutually exclusive pattern with significant enrichment of NFKB-related genesets and genes in LPL and MALT, and significant enrichment of B-cell receptor signaling genesets and genes in SMZL and NMZL. Our analysis, for the first time, describes the molecular relationship between these closely related lymphomas. In the process, we identified novel diagnostic markers that may differentiate these conditions and also new insights into molecular pathways that are differentially activated in the different conditions. These may represent potential therapeutic targets

Abstract Events mediating transformation from pre-malignant MGUS to MM is currently not well defined. Recurrent genetic abnormalities such as t(11;14), t(4;14), hyperdiploidy and chromosome 13 deletion are already present in MGUS at relatively similar frequency to MM. The unified deregulation of D-type cyclins is also already present in MGUS. Previous GEP studies have revealed little differences between MGUS and MM. A more recent study using a large patient cohort and new generation Affymetrix genechip identifies an MGUS signature but the functional and biological significance underlying this signature is unknown. In the current study, we analyze a cohort of 22 MGUS and 101 MM from the Mayo Clinic with GEP performed on Affymetrix U133A genechip using gene set enrichment analysis, a method that analyze differentially expressed gene between 2 phenotypes of interest in the context of published or curated genesets that represent specific biological, chemical, or molecular perturbation to cells. This method increases the sensitivity of identifying low but significant changes in gene expression. We made further modification to the original method that allows assessment in individual samples rather than the average across a phenotype further increasing the specificity of the output. In this analysis, 313 genesets were significant enriched for genes over-expressed in MM compared to MGUS, representing potential activated pathways that mediate transformation. When MM samples and genesets were clustered using the enrichment score for each genesets and samples, 4 cluster of genesets emerged, one including a number of MYC genesets, one including a number of cell cycle related genesets, one including genesets related to metabolic activity and another including a number of IFN related genesets. Further dissection of these correlated genesets to identify common enriched genes (leading edge genes) led to identification of a MYC core signature, tRNA core signature, Proteosome core signature and metabolic core signature which are highly correlated. From known literature and biology, it is likely that MYC activation leads to downstream activation of protein synthesis (tRNA signature), degradation (proteasome signature), and metabolic pathway (metabolic signature). This is verified by GEP results from in vitro modulation of MYC activation in cell lines. In addition, a cell cycle core signature and IFN core signature was identified. Activation of IFN and MYC core signatures accounts for almost 90% of MM patients. The remaining patients have a metabolic signature without MYC or IFN activation. The activation of the different core signatures is significantly correlated with certain TC classes when assessed by Chi-Square test. IFN activation is significantly correlated with D1 subtypes and negatively correlated with D2 subtypes. MYC activation is negatively correlated with t(11;14). Similar patterns were observed in a validation dataset of 351 MM patients from UAMS (GSE2677) with GEP performed on the U133plus2.0 chip. These results are validated at the protein level using IHC on TMA of the Mayo cohort. The activation of the IFN and MYC pathway may represent predominant mechanism in MGUS to MM progression.

Abstract Background Multiple myeloma (MM) is presently an incurable plasma cell (PC) malignancy which involves 16 000 new patients per year in US. In spite of the abundance of cytogenetic information, with more than 600 published karyotypes in Non-hyperdiploid MM (NHMM), very little is known about the mode of karyotypic evolution or of the presence of possible cytogenetic pathways. In our investigation, we have used 647 NHMM karyotypes, to identify the most frequently occurring imbalances. Patients and Methods The Mitelman database of Chromosome aberrations in cancer (Mitelman et al., 2007) was searched, and myelomas with modal chromosome number less than 48 were selected. All karyotypes were described using ISCN nomenclature (ISCN, 1995). Only the main clones were analyzed and incomplete karyotypes were excluded. The following information was obtained from each karyotype: chromosome number, imbalances including whole chromosome gains and losses; specific translocations and breakpoints, including add chromosomes. An Excel spreadsheet in which the rows of the first column were labeled to represent each band of a 360-band human chromosome ideogram was created as previously described (Hoglund et al., 2001; Horsman et al., 2003) All karyotypes were scored individually in successive columns for net gain and loss of each chromosome band. The total number of gains and losses affecting each chromosome band for the total cohort of karyotypes was then calculated using the Excel countif function. Recurrent abnormalities were defined as those that were involved in >5% of cases. Histograms of the number of abnormalities per tumor were then plotted, and the modal value extracted as variable called time to occurrence. Statistics correlation between the presence and absence of different abnormalities was analyzed using Spearman correlation matrices. P value of <0.05 was considered as statistical significant. Results In total 647 cases of newly diagnosed NHMM were included in the analysis. The median chromosome number was 43. Few cases had chromosome numbers under 40. The median NAPT was 12 (1–49) with a normal distribution (Fig 1). The most common abnormalities were monosomies of the chromosomes 13 and 14 (32.44% and 14.88% respectively). Out of 647 cases, more than 300 NHMM cases contained translocations in their karyotypes. The most common translocation was t(11;14), which occurs in 17% of cases followed by t(1;16) in 2.7% of cases and t(4;14) and t(8;14) in 1.5% respectively. The most recurrent breakpoints in our series include: 14q32 (32%), 11q13 (20%), 1q10 (10.5%), 1q12 (8%), 8q24 (6.9%), 1p11 (6.6%) and 1q21 (5.5%). Discussion Although only about 40% of MM has informative karyotypes, karyotyping has the advantage of representing global genetic changes at the cellular level. In this comprehensive survey, loss of chromosome 13 and 14 were the most common abnormalities. The NAPT analysis suggests that most NHMM patients have at least 12 abnormalities at diagnosis. It is possible that accumulation of abnormalities above a threshold results in malignant transformation. In our series the t(11;14) translocation appears to be the most recurrent translocation and exceeds the rate reported in Hyperdiploid-MM (17% vs 3.8%). Figure 1. NAPT Distribution in NH-MM Figure 1. NAPT Distribution in NH-MM

Abstract Table 1. Samples to p53 deletions p 53 deletion FISH aCGH FISH and aCGH MGUS 142 - - SMM 108 - - Newly diagnosed MM - 182 - Relapsed/refractory MM 62 156 19 HMCLs - 48 - Total 312 386 19 Background: Inactivation of p53 by mutation or allelic loss is a rare event in multiple myeloma (MM) at the time of disease diagnosis and believed to be more common in the late stages of the disease. Here we defined the prevalence of p53 deletions in monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM), newly diagnosed MM, relapsed MM and human myeloma cell lines (HMCLs). Indirect mechanisms of p53 inactivation such as amplification of MDM2, or deletion of CDKN2A (p14ARF) were also investigated. Patients and Methods: A total of 631 MM samples and 48 HMCLs were analyzed for p53 abnormalities (Table 1) and compared with a cohort of plasma cell leukemia (PCL) previously published by us. Interphase fluorescence in situ hybridization (FISH) and highresolution array-based comparative genomic hybridization (aCGH) were used to detect p53 deletions. MDM2 amplification and p14ARF loss were evaluated by aCGH. Overall survival (OS) was estimated through Kaplan Meier method. Results: The prevalence of p53 deletions was 1.4%, 3.7%, 8.9%, 20% and 87.5% in MGUS, SMM, newly diagnosed MM, relapsed MM and HMCLs respectively (Figure 1). Of interest patients in first relapse showed a p53 deletion prevalence of 18% in comparison with 33% for patients in second relapse or more. We obtained p53 deletion status in 8 patients noted to have deletion at the time of relapse and in whom we had previous samples stored. In 7 of 8 cases deletions had been acquired (absent in the previous samples). The median OS for relapsed MM patients with or without p53 deletion were 4.2 months and 37.8 months respectively (p <0.001). MDM 2 amplification and p14ARF loss was detected in 0.4% and 2% of new diagnosed MM, 0.6% and 5.1% of relapsed MM and 2% and 29% of HMCLs respectively. Discussion: Emergence of p53 deletion/mutations denotes progression genetic events in MM. Importantly we show for the first time the overriding importance of p53 deletions as prognostic markers in relapsed MM. A molecular staging system that is based on the presence of p53 inactivation may be more powerful than classifying patients based on the loss of p53. Other abnormalities involving p53 pathway regulators like MDM2 gain and p14ARF loss are infrequent events in MM, even in advanced disease. Figure 1. Prevalence of p53 deletions Figure 1. Prevalence of p53 deletions

Abstract Introduction: Clinical development of bortezomib in multiple myeloma (MM) included pharmacogenomic gene expression profiling (GEP) of pre-treatment tumor biopsies in order to evaluate the feasibility of developing predictive classifiers in prospective clinical trials and to better define the biological pathways related to drug sensitivity. By partitioning the samples into train (n=101) and test (n=80) datasets, statistically significant classifiers of response and survival were identified and then validated [Mulligan G, et al: Blood. 2007; 109:3177–88]. Here we describe specific genes and biological pathways associated with bortezomib efficacy in relapsed MM. Methods: Using tumor GEP data from 188 patients treated with single-agent bortezomib we identified genes associated with overall survival (OS), as well as genes associated with response (R) or progressive disease (PD) after bortezomib therapy. These clinical endpoints were also analyzed with biological pathway algorithms including GSEA [Subramanian A, et al: Proc Natl Acad Sci2005; 102:15545–50] Ingenuity Pathway Analysis and Gene Ontology/GATHER. These results were then compared to GEP data from a patient subset (n=76) treated with single-agent dexamethasone and also cell lines selected for differential sensitivity to bortezomib. Results: A comparison of R and PD highlighted numerous differentially expressed genes; approximately 200 were over-expressed in R and 500 were over-expressed in PD (t-test <0.01). R-associated genes include signaling molecules like TRADD, CFLAR and TANK, while PD-associated genes included oncogenes (NRAS), apoptotic regulators (DAP3) and cancer antigens (CTAG). Pathway tools helped to integrate and extend these observations, consistently identifying NFkB activation and overexpression of adhesion pathways as R-associated. Overexpression of protein synthesis and mitochondrial pathways were PD-associated. The overexpression of pathways such as NFkB, adhesion and cytokines appear linked specifically with bortezomib and not dexamethasone sensitivity. These approaches were also applied to patient survival. In contrast to analyses of single genes, the pathway tools highlighted links between response and survival, including adhesion and inflammatory cytokine pathway expression. Conclusions: This study highlights the diversity of biological pathways expressed in MM and the utility of clinical genomics to associate pathways with activity of single-agent bortezomib.

Abstract Multiple Myeloma (MM) is the second most prevalent haematological disorder in the US with great recent progress propelled by various technological and therapeutic advances. Nevertheless, the complexity of MM genomes remains inadequately characterized. We have combined high-resolution (44K Agilent) array comparative genomic hybridization (aCGH) and gene expression data with clinical outcomes in an initial attempt at indexing genomic complexity in MM and its clinical implication in 100 MM patients. We enumerated the Number of Aberrations per Tumor (NAPT) as defined by the ADM-1 algorithm available within CGH Analytics. There appear to be no difference in degree of genetic complexity between hyperdiploid and non-hyperdiploid myeloma. Generally, t(11;14) have low NAPT whereas D2 tumors have high NAPT. Amongst the high-risk genetic subtypes, tumors with maf translocations have relatively low NAPT whereas t(4;14) have high NAPT. Whilst a Multivariate Cox Proportional Hazards regression of survival outcome showed little statistical support for popular indicators such as ploidy and TC classification, results for NAPT were considerably more encouraging (p~ 0.07, median survival of 40 months in low complexity vs 18 months in high). Log-rank tests further supported prognosis based on NAPT independent of clinical status and ploidy. To characterize complexity, we clustered aCGH profiles by clinical status, ploidy and TC classification. Clear patterns of aggregation and recurrent aberration were observed suggesting that they were possibly instrument to aberrant gene expression. Indeed, expression of a large proportion of genes approximately 2Mb of the recurrent breakpoints varied significantly between patients carrying aberrations vis-a-viz others that did not. Comparison against known gene sets showed an enrichment for cell-cycle and apoptosis genes. We are presently characterizing several such breakpoint-associated genes for their functional significance.

Abstract Background B-cell chronic lymphocytic leukemia (B-CLL) is a well-defined clinical entity with heterogeneous molecular and cytogenetic features. Chromosome aberrations could be associated to specific CLL clinical features and outcomes and their impact on clonal evolution should have been addressed by using temporal analysis. In order to demonstrate the role of temporal analysis in CLL we conducted a comprehensive karyotypic survey of a large number of CLL cases with already known genetic aberrations to fully describe their meaning in terms of biological evolution. Methods A total of 1749 karyotypes were retrieved from the Mitelman Database of Chromosome Aberrations in Cancer. A matrix depicting the 360-band human chromosome ideogram was created. Regions that were either lost or gained in more than 3% of the cases were retained and identified as recurrent imbalances. Early and late imbalances were defined according to the appearance on the complex karyotypes. Descriptive statistics were used to summarize the genetic abnormalities. Results The median chromosome number and the median number of abnormalities per tumor (NAPT) were 46 and 1 respectively. (Figure 1 A and 1B) The most common abnormality seen was trisomy 12 which occurred in 29% (508 cases) followed by 13q14del (10.34%), 13q13del (6.63%) and add14q32 (6.63%). The temporal analysis revealed +12, 13q-, −17, 17p-, −Y and −X to be early imbalances (TO<5), followed predominately by a late loss with TO=5–10.5 (11q-). Hierarchical clustering suggested there are different groups including: trisomy 12, 13q-, 11q-, and 6q-, which at least in this clustering analysis appeared to be mutually exclusive. In summary, we can conclude that overall CLL is a neoplasia that shows remarkable chromosome stability even when only abnormal karyotypes are evaluated. Interestingly, clustering analysis suggests there are non-overlapping, unique subsets of CLL cases where trisomy 12 is the most common and along with 13q-emerged as early events on CLL clonal evolution. Figure 1A. Chromosomes distribution in chronic Lymphocytes Leukemia karyotypes Figure 1A. Chromosomes distribution in chronic Lymphocytes Leukemia karyotypes Figure 1b. Chronic Lymphocytes Leukemia and Number of Abnormalities Per Tumor (NAPT) distribution Figure 1b. Chronic Lymphocytes Leukemia and Number of Abnormalities Per Tumor (NAPT) distribution Figure Figure

Abstract The retinoblastoma 1 (RB1) gene is a frequent target of mutation or inactivation in neoplastic diseases. However, the current model for RB1-mediated malignancy requires inactivation of both alleles for tumor progression. Single–copy loss of RB1 has been shown to correlate with an approximate 50% reduction in RB1 mRNA expression in patients diagnosed with multiple myeloma and survival in this cohort of patients is significantly reduced. Using siRNA to reduce Rb protein levels to 50% and Rb-expressing adenovirus to restore RB1, variations in proliferation and cell cycle were observed. The KMS–11 adherent cell line with normal Rb protein expression was labeled with carboxyfluorescein succinimidyl ester (CFSE) for tracking of cellular division and RB1 siRNA added to silence 50% of protein expression. Transfection efficiency for siRNA was measured at 95% or greater. Flow cytometric analysis was performed at 72 hours to identify changes in proliferation between controls and Rb knock–down. Using CFSE proliferation analysis software, reduction of Rb protein levels by 50% caused an average increase in the proliferation index from 2.05 to 2.50. Additionally, reduction of Rb protein levels caused an increase in the percentage of cells in S–phase, from 24 to 29%. CFSE and cell cycle experiments were performed in triplicate. Conversely, addition of Rb–expressing adenovirus to MM.1R and U266 cell lines, with mono-allelic and bi-allelic loss of RB1 respectively, resulted in a decrease in proliferation assayed by CFSE and an average decrease in the percentage of cells in S-phase from 29 to 23% compared to controls. No changes in proliferation or cell cycle compared to untreated controls were observed following null adenovirus infection. Western blot and quantitative RT–PCR (qPCR) were used to confirm reduction or addition of RB1 to cell lines. Further, qPCR was used to identify potential activation of the interferon response following addition of siRNA and adenovirus. No changes in annexin V expression were observed following reduction or replacement of Rb as compared to controls. These results suggest the addition of proliferation advantages to tumors with single copy loss of RB1. For malignancies such as multiple myeloma characterized by deletion of 13q14 coupled with an extended period of development, the proliferation advantage associated with RB1 haploinsufficiency may contribute to decreased survival in the deletion 13 cohort.

Abstract From a high throughput RNAi screen of the human druggable genome targeting the KMS11 cell line, we identified the suppression of the vacuolar H+- ATPase (V-ATPase) family as cytotoxic to myeloma cells. In the screen, two oligos against each gene for the V-ATPase subunits ATP6V1A and ATP6V1B1 resulted in suppression of cell growth (50% and 60% inhibition of cell viability respectively). We further confirmed this result using both lentiviral shRNA knockdown and two small molecule inhibitors specific for V-ATPase. Silencing of ATP6V1A by lentiviral shRNA knock-down in KMS11 and in OPM1 myeloma cell lines caused 75–80% reduction of cell viability at 5 days post infection (measured by MTT assay). Consistent with this result, the V-ATPase specific inhibitors, bafilomycin A1 and REATA 203, both inhibited the growth of a genetically heterogeneous and standardized panel of 14 human myeloma cell lines in vitro with an IC50 ranging from 2.2 – 8.9 nM (mean 5.25 nM) for bafilomycin A1 and 46–1594 nM (mean 542.5 nM)) for REATA 203. We further demonstrated that patient samples (n=10) were sensitive to 20nM bafilomycin A1 which induced a mean of 58% of MM cells to undergo apoptosis (range 10% to 93%) after 24 hours of treatment. Similar to bafilomycin A1, treatment of primary patient-derived MM cells with 500 nM REATA 203 for 72 hours resulted in a mean 69% apoptosis (range 24% to 97%). In contrast, non-myeloma cells (the CD138- fractions of the bone marrow samples) were less sensitive - mean 9% apoptosis (range from 0% to 34%) under the same treatment conditions. Of high interest, however, unlike most drugs we have studied in pre-clinical myeloma models, the cytotoxicity induced by bafilomycin A1 in MM cell lines is abrogated by co-culture with patient bone marrow stromal cells but is not affected by IL-6 or IGF-1 treatment. Dexamethasone- or melphalan-resistant MM cell lines were also highly sensitive to both bafilomycin A1 and REATA 203. In a xenographic JJN3 mouse model, bafilomycin A1 suppresses and delays growth of tumor in a dose-dependent fashion. Gene expression analysis of normal-donor bone marrow plasma cells (n=19), primary tumor samples from MM patients (n=107) and normal somatic tissues demonstrates ubiquitous expression of most subunits of V-ATPase, however, some subunits are preferentially expressed in myeloma cells compared with normal plasma cells, including ATP6V1F (84% vs. 11%), ATP6V1E1 (29% vs. 5%), ATP6V1G2 (17% vs. 0%) and ATP6V0E 2 (36% vs. 16%). In conclusion, our data indicate that vacuolar H+-ATPase inhibitors are of interest as potential therapeutics for MM.