Perkins, Louise M.

Abstract In an effort to identify novel genetic abnormalities in multiple myeloma (MM) we analyzed an initial set, as part of the Multiple Myeloma Research Consortium (MMRC) Genomics Initiative, of 94 MM patient samples on high-resolution array-based comparative genomic hybridization (aCGH) and gene expression profiling (GEP) technologies. The MMRC Genomics Initiative is a three-year research program spanning a full-spectrum of genomic technologies with the goal of analyzing 250 MM patient samples by 2009. Raw data from the Initiative are released in near real time through the MMRC Multiple Myeloma Genomics Portal. This initial aCGH dataset from the Agilent 244K platform represents the highest resolution gene copy number analysis with corresponding GEP released to date in MM. It has confirmed the cytogenetic definitions of MM with the data set being split between patients with hyperdiploid and non-hyperdiploid MM. Furthermore, the 244K platform has helped to refine minimal regions of change present on 1p, 1q, 6q, 8p, 13q, 14q, and 16q. A comprehensive screen of the dataset for genes residing in regions of homozygous deletion identified 105 genes. The most commonly affected gene was CDKN2C(p18) (8.3%) while 12 other regions were recurrently targeted. Several of these regions were recently implicated in the pathogenesis of MM but the large majority represents novel observations. The aCGH and GEP data were integrated using two different programs developed by the core institutions (The Broad Institute of Harvard & MIT and Translational Genomics Research Institute). First, Genomic Identification of Significant Targets in Cancer (GISTIC), which identifies highly significant regions of change and a limited set of candidate genes within these regions, was used to identify 285 genes associated with DNA content alterations. Second, Breakpoint Expression Correlation (BEC), which identifies dysregulated genes on either side of a copy number alteration, was used to identify 194 genes with expression changes associated with a breakpoint. This latter gene list includes all known IgH translocation target genes identified to date in myeloma. Overlapping the gene lists generated by GISTIC, BEC, and the homozygous deletion screen identified a number of genes previously implicated in MM such as CDKN2C(p18), CYLD, BIRC2/BIRC3, and two novel genes, FAM46C and RNF6. Ongoing data integration with RNAi and high content sequencing projects of the current Initiative holds great promise in furthering our understanding of MM. The MMRC Genomics Initiative and resulting efforts from the myeloma research community will increase our understanding of MM at the molecular level, help to identify new targets, and ultimately lead to the development of better, more effective therapies for myeloma.

Abstract The Multiple Myeloma Research Consortium (MMRC) Genomics Initiative was instigated to harness the power of multiple genomic approaches to further the understanding of multiple myeloma. To date, 137 samples from patients with newly diagnosed and relapsed myeloma (out of an estimated final total of 250 by the end of the year) have been subjected to expression profiling and array comparative genomic hybridization. To identify regions of recurrent copy number alteration with a high degree of confidence, we have used the Genomic Identification of Significant Targets In Cancer (GISTIC) algorithm, which detects such regions and assigns a probability to each. Application of GISTIC to the MMRC collection identified 14 significant regions of amplification and 15 significant regions of deletion. The algorithm further detects peaks of copy number change that contribute to each region’s significance. Of genes that were expressed in our dataset, a total of 64 across the genome were found to lie within the boundaries of significant amplification peaks and 30 were found to lie within significant deletion peaks. Given the likelihood that this gene collection is highly enriched for genes important in the pathogenesis of myeloma and potential therapeutic targets, it has been prioritized for further validation with the amplified genes submitted for arrayed RNAi and the deleted genes expedited for re-sequencing. In order to define a poor prognosis group, we developed and applied a model based on the gene expression dataset of Shaughnessy and colleagues. To identify pathways activated in poor prognosis disease, we applied Gene Set Enrichment Analysis with the Molecular Signatures Database. This demonstrated enrichment of multiple canonical pathways within the poor prognosis group, including those associated with proliferation, cell cycle progression and DNA repair. A search for recurrent copy number events associated with poor prognosis disease revealed that by far the most significant event, and the only one surviving correction for multiple hypothesis testing, was mono- or bi-allelic deletion of CDKN2C (p18). Interestingly, the poor prognosis group also demonstrated higher expression of p18 in those samples without bi-allelic deletion and of CDKN2A (p16). Deletion and increased expression of p18 in high proliferation index myeloma samples has previously been described. However, our analyses demonstrate the pre-eminence of p18 loss for defining poor prognosis disease compared to other recurrent copy number changes. Furthermore, it expands on work in other tumors demonstrating feedback mechanisms between cyclin dependent kinase inhibitor pathways, suggesting a more complex model of interplay between the pathways than previously described. In conclusion, the MMRC reference collection is proving an important tool in the fight to understand key genetic events in multiple myeloma and would ultimately be anticipated to contribute towards development of improved therapy for the disease.

Abstract The Multiple Myeloma Research Consortium (MMRC) Genomics Initiative is a three-year program to analyze tumor tissue from hundreds of multiple myeloma (MM) patients via gene expression profiling (GEP), comparative genomic hybridization (aCGH), and exon re-sequencing. In addition, RNAi knockdown of selected genes in MM tumor cell lines is being evaluated to identify potential new targets. All genomic data generated is scheduled for placement in an open-access Multiple Myeloma Genomics Portal pre-publication and in near real-time (www.broad.mit.edu/mmgp). Additionally, samples are also destined for drug validation and correlative science on clinical protocols as this study moves forward. This comprehensive project is spearheaded by the MMRC and conducted via collaboration with the Eli and Edythe L. Broad Institute of MIT and Harvard, the Translational Genomics Research Institute (TGen), Mayo Clinic Arizona, and The Dana-Farber Cancer Center. The study is supported by the collection from member institutions of the MMRC of bone marrow aspirates and matched peripheral blood samples from over 1000 patients. Specific genomic technologies that are currently being employed across this sample set include GEP using Affymetrix Human Genome U133A 2.0 Plus Arrays, and, in parallel, efforts to identify regions of genomic gain and loss are using Agilent Human Genome CGH arrays. In contrast to other large-scale genomic projects based on exon-sequencing of targeted gene sets, this project will be the first to perform genome-scale single molecule sequencing (SMS) of DNA from patient specimens. Results will be targeted against candidate classes of genes (e.g. kinases, phosphatases, known oncogenes and tumor suppressors), and genes from GEP or within candidate regions of copy gain or loss identified by the aCGH experiments. Mutations will be further validated in an independent set of patient specimens. Finally we will attempt to identify points of vulnerability of MM through systematic loss-of-function screens in myeloma cell lines using high-throughput RNA interference (using both shRNA and siRNA platforms). Importantly, data generated from this genomics initiative will ultimately be made public pre-publication through the established MMRC Multiple Myeloma Genomics Portal. Data from all aspects of this project (sample collection and analyte isolation, GEP, aCGH, SMS, RNAi and bioinformatics) will be described in this presentation. The power of this study is the comprehensive collection of gene expression, CGH, and genome sequencing on a single reference set of clinically annotated samples. The addition of RNAi screens makes this a very important and unique data resource, which we hope will help expedite the discovery of novel targeted agents for MM scientific community.

Abstract Abstract 604 We have conducted a pilot study to interrogate both CpG hyper- and hypomethylation in Multiple Myeloma (MM) using the Illumina GoldenGate (GG) BeadArrayTM high-throughput assay. Specifically, we utilized the Illumina Methylation Cancer Panel I, which spans 1,505 CpG loci selected from 807 genes including known tumor suppressor genes and oncogenes. To date we have profiled 50 CD138+ MM specimens, 4 MM cell lines and 6 normal CD138+ plasma cell samples (each representing a pool of 3-5 individuals) obtained from the bone marrow of patients who have undergone hip or knee replacement surgeries. We have obtained highly reproducible and reliable DNA methylation profiles with an average r2 of greater than 0.98 when the β values were compared between technical replicates. Further, we generated an internal control panel for the array by performing methylation specific PCR (MSP) to determine the methylation status of several genes found on the array (CDKN2A, E-Cadherin, MGMT, hMLH1) in 4 MM cell lines. A differential methylation analysis was conducted between normal plasma cells and MM samples using the BeadStudio Methylation Module v3.2. Differential scores for each CpG locus on the array were generated that correspond to significant differences between groups. Scores greater than (hypermethylation) or less than (hypomethylation) 13 represent ‘Diff scores' that are statistically significant (p values < 0.05) and this cut-off threshold is used to determine differentially methylated loci. Globally, when comparing MM to normal plasma cells, hypomethylation occurred at 42% of probes on the array, and was more common than hypermethylation, which occurred at only 21% of probes. Interestingly, 77% of probes situated in non-CpG islands were hypomethylated compared to 26% or probes in CpG islands. On the contrary hypermethylation occurred mainly in CpG islands (26% of probes) whereas only 7.4% of probes in non-CpG islands were considered hypermethylated. A total of 946 CpG loci were differentially methylated between normal plasma cells and MM. Among the most significantly differentially methylated CpG loci between normal plasma cells and MM were FZD9, ALOX12, MMP-3, MMP-8, and p16. Array comparative genomic hybridization (aCGH) data availabel for this same sample set was used to generate a hyperdiploid index for each sample by identifying those samples with whole chromosome gains at minimally three odd numbered chromosomes. There were 751 CpG loci that were differentially methylated between hypderdiploid and non-hyperdiploid tumors with WEE1, FRZB, ELK1, CLDN4, and SHH being among the most significant. We also applied the pathway enrichment analysis tool GeneGo v5 (Agilent) to these data, which identified cell adhesion/ECM remodeling, developmental pathways and several immune response pathways as the most significantly enriched pathways between normal and plasma cells with ephrin signaling pathways in the context of cell adhesion as the most significantly enriched pathway between hyperdiploid and non-hyperdiploid tumors. We hope to integrate methylation data with orthogonal datasets including gene expression, aCGH, and DNA sequence data being developed as part of the MMRF Genomics Initiative. Further validation of hits will also be followed up by functional studies to assess the true biological relevance of differentially methylated genes. This study represents one of the first methylome interrogation studies in MM and points towards global hypomethylation as possibly an important mechanism driving myelomagenesis. Our data also suggest that differential methylation of genes may be a significant determinant of hyperdiploid biology. Determining the set of critical genes and pathways based on the myeloma methylome is likely to lead to an improved understanding of biological mechanisms involved in myelomagenesis, ultimately leading to new and improved methods of diagnosing and treating this disease. Disclosures: No relevant conflicts of interest to declare.

Abstract Abstract 601 A paucity of validated kinase targets in human multiple myeloma (MM) has delayed clinical deployment of kinase inhibitors in treatment strategies. We therefore conducted a kinome-wide small interfering RNA (siRNA) lethality study in MM tumor lines bearing common t(4;14), t(14;16) and t(11;14) translocations to identify critically vulnerable kinases in MM tumor cells without regard to preconceived mechanistic notions. Primary screening was performed in duplicate using an 1800-oligo siRNA library in a single-siRNA-per-well format. siRNA were transfected at low concentration (13nM) to minimize off-target effects using conditions that resulted in transfection of >95% cells and <5% background cytotoxicity. After 96 hours, viability was measured by ATP-dependent luminescence. Fifteen kinases were consistently vulnerable in MM cells, including AKT1, AK3L1, AURKA, AURKB, CDC2L1, CDK5R2, FES, FLT4, GAK, GRK6, HK1, PKN1, PLK1, SMG1, and TNK2. While several kinases (PLK1, HK1) were equally vulnerable in epithelial cells, others and particularly the G-protein coupled receptor kinase, GRK6, appeared selectively vulnerable in MM. GRK6 inhibition is selectively lethal to KMS11, OPM1, H929, KMS18 and OCI-MY5 myeloma cells and has minimal effect on 293, MCF7, SF767, A375 or A549 epithelial cells. Persistent expression of FLAG-GRK6 via cDNA rescued KMS11 cells from the lethal effect of a 3'UTR-targeted GRK6 siRNA, but not from control siRNA, validating identification of GRK6 as an essential myeloma survival kinase. Furthermore, concordant results were obtained using four different exon-based GRK6 siRNA, all of which induced GRK6 silencing and similar inhibition of KMS11 proliferation and viability. Significantly, GRK6 is ubiquitously expressed in lymphoid tissues and myeloma, but by comparison appears absent or only weakly expressed in most primary human somatic tissues. From co-immunoprecipitation experiments we demonstrate that GRK6 is highly expressed in myeloma cells via direct association with the HSP90 chaperone. Inhibition of HSP90 with geldanamycin blocks GRK6 protein expression. Importantly, direct GRK6 silencing causes rapid and selective suppression of STAT3 phosphorylation that is associated with sustained reductions in total MCL1 protein levels and MCL1 phosphorylation (within 24 hours), providing a potent mechanism for the cytotoxicity of GRK6 inhibition in MM tumor cells. GF109203X is an inhibitor of both protein kinase C and of GRK6 that causes near total inhibition of these kinases in vitro at distinct concentrations of 0.1μM and 1-10μM respectively. Notably, GF109203X was substantially cytotoxic to 10/14 myeloma tumor lines at concentrations most consistent with GRK6 inhibition (5-20μM), and was selectively more cytotoxic to myeloma tumor cells than to non-myeloma cell lines (P=0.01), highlighting the potential of GRK6 as a pharmaceutical target for selective therapeutic intervention in myeloma. As mice that lack GRK6 are healthy, inhibition of GRK6 represents a uniquely targeted novel therapeutic strategy in human multiple myeloma. Disclosures: Perkins: MMRC: Employment. Reeder:Celgene: Research Funding; Millennium: Research Funding. Fonseca:Otsuka: Consultancy; BMS: Consultancy; Amgen: Consultancy; Medtronic: Consultancy; Genzyme: Consultancy.

Abstract Abstract 832 We hypothesized that new therapeutic targets for multiple myeloma (MM) could be discovered through the integrative computational analysis of genomic data. Accordingly, we generated gene expression profiling and copy number data on 250 clinically-annotated MM patient samples. Utilizing an outlier statistical approach, we identified HOXA9 as the top candidate gene for further investigation. HOXA9 expression was particularly high in patients lacking canonical MM chromosomal translocations, and allele-specific expression analysis suggested that this overexpression was mono-allelic. Indeed, focal copy number amplifications at the HOXA locus were observed in some patients. Outlier HOXA9 expression was further validated in both a collection of 52 MM cell lines and 414 primary patient samples previously described. To further verify the aberrant expression of HOXA9 in MM, we performed quantitative RT-PCR, which confirmed expression in all MM patients and cell lines tested, with high-level expression in a subset. To further investigate the mechanism of aberrant HOXA9 expression, we interrogated the pattern of histone modification at the HOXA locus because HOXA gene expression is particularly regulated by such chromatin marks. Accordingly, immunoprecipitation studies showed an aberrantly low level of histone 3 lysine 27 trimethylation marks (H3K27me3) at the HOXA9 locus. H3K27me3 modification is normally associated with silencing of HOXA9 in normal B-cell development. As such, it appears likely that the aberrant expression of HOXA9 in MM is due at least in part to defects in histone modification at this locus. To determine the functional consequences of HOXA9 expression in MM, we performed RNAi-mediated knock-down experiments in MM cell lines. Seven independent HOXA9 shRNAs that diminished HOXA9 expression resulted in growth inhibition of 12/14 MM cell lines tested. Taken together, these experiments indicate that HOXA9 is essential for survival of MM cells, and that the mechanism of HOXA9 expression relates to aberrant histone modification at the HOXA9 locus. The data thus suggest that HOXA9 is an attractive new therapeutic target for MM. Disclosures: No relevant conflicts of interest to declare.

Abstract The plasma cell malignancy Multiple Myeloma (MM) is a rare but deadly form of cancer with 5 year survival rates of ∼30%. Epidemiological studies have suggested that MM exacts an especially heavy burden on African American (AA) patients. We examined a multi-ethnic cohort of MM tumors to assess potential differences in the frequency of molecular events in tumors derived from either African American (AA) or European American (EA) patients. The frequency of 14q32 translocation breakpoints at the IgH locus was compared among a series of data from 115 AA MM patients from three studies and EA MM from the Eastern Cooperative Oncology Group (ECOG). In addition, we analyzed matching genome-wide copy number and transcriptional data among 45 AA MM tumors and 196 EA MM tumors to determine differences in the frequency of molecular events in tumors from these populations. No differences were found for specific translocation subtypes; however, we detected a statistically significant difference in the overall frequency of IgH translocations between the two groups, which occurred more frequently in EA patients (52% vs. 40%; p = 0.032). When assessing genomic copy number events previously shown to be associated with poor outcome in MM, frequencies of alterations were not significant after correcting for multiple testing. Furthermore, there was not a significant difference in the association of high-risk disease using expression profiling. Our study represents the first comprehensive assessment of the frequency and distribution of molecular alterations in MM tumors from both AA and EA patients and could help shed light on possible biological features associated with population differences in incidence and outcome in MM. Citation Format: Angela S. Baker, Esteban Braggio, Susana Jacobus, Sungwon Jung, Dirk Larson, Terry Therneau, Angela Dispenzieri, Scott A. Van Wier, Gregory Ahmann, Joan Levy, Louise Perkins, Seungchan Kim, Kim Henderson, David Vesole, S. Vincent Rajkumar, Dianne F. Jelinek, John Carpten, Rafael Fonseca. Characterization of myeloma tumors from a multi-ethnic cohort using cytogenetics and genomic analysis. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2021. doi:10.1158/1538-7445.AM2013-2021

Key PointsIn this study, African American MM patients have a significantly lower frequency of IgH translocations than European American patients.

Abstract The plasma cell malignancy Multiple Myeloma (MM) is a rare but deadly form of cancer with 5 year survival rates of ∼30%. The disease exacts an especially heavy burden on African American (AA) patients. In fact, African Americans are twice a likely to be diagnosed with and die from MM as compared to Caucasian Americans. Although socio-economic factors likely influence this disparity, the role of biology has not been ruled out. We have profiled ∼250 MM tumors for somatic copy number alterations using array-based Comparative Genomic Hybridization (aCGH) and Gene Expression Profiling as part of the Multiple Myeloma Genomics Initiative. To determine if somatic alterations may play a role in the disparity in incidence and/or severity of MM in AA, we compared the frequency of specific chromosomal aberrations in genes and genomic regions previously found to be involved in progression and poor outcome in MM among a cohort of one hundred ninety-six (196) patients including 16 African Americans and 180 Caucasians. The frequency of occurrence (expressed as a percentage) was determined for each of the following aberrations: 1p deletion, homozygous deletion of p18, chromosome 13 deletion, and chromosome 13 monosomy. No significant difference was detected in the frequency of chromosome 13 deletion and chromosome 13 monosomy between the two groups. However, significant differences were observed for chromosome 1p alterations. Homozygous deletion at the p18 locus at 1p occurred in 12.5% (2/16) of tumors from AA patients and 2.8% (5/180) of CA patient tumors (p = 0.045). We further stratified tumors by hyperdiploid or non-hyperdiploid status using a-CGH profiles to determine ploidy status. Most significantly, p18 homozygous deletion was found in 25% (2/8) of AA patients with non-hyperdiploid tumors and in only 1.2% (1/83) of CA patients with non-hyperdiploid tumors (p=3.2 × 10-4). A nominally significant difference among non-hyperdiploid patients was also present for overall 1p deletion, which was observed in 2/8 (25%) of AA non-hyperdiploid tumors and 33/83 (40%) of CA with non-hyperdiploid tumors (p=0.05). No differences were observed for 1p deletion or p18 homozygous deletion among hyperdiploid tumors between AA and CA patients. These results suggest that deletions at 1p are more common among African American MM patients. Furthermore, homozygous deletion encompassing the p18 locus is more significantly common among AA MM patients, especially AA patients with non-hyperdiploid tumors. As 1p deletion and p18 homozygous deletion have been linked to poor outcome, our results suggest that the increased frequency of these alterations in tumors from AA patients may in part explain the disparity in unfavorable outcomes seen among AA MM patients Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4822.

Abstract Multiple myeloma (MM) is a cancer of the plasma cells in the bone marrow. Although rare, MM is a deadly form of cancer with a 5 year survival rate of only 37%. African Americans (AA) are twice as likely to be diagnosed with and die from MM as compared to European Americans (EA). Socioeconomic factors may contribute to this disparity, however, biological factors may also be an influence. We have identified somatic copy number alterations in MM as a part of the Multiple Myeloma Genomics Initiative by profiling 250 MM tumors using array-based comparative genomic hybridization (aCGH). Using this cohort, we identified 16 African American and 180 European American patients using a MMRC database that indicated the racial demographics of each patient. To determine if somatic alterations may play a role in the disparity in incidence and/or severity of MM in AA, we compared the frequency of specific chromosomal aberrations in genes and genomic regions found to be involved in progression and poor outcome. The number of events of occurring was calculated and a univariate analysis was conducted using the Fisher's exact test. P-values were used to determine statistical significance. Results revealed significant differences for chromosome 1 p alterations. Specifically, homozygous deletion at the p18 locus at 1 p occurred in 12.5% (2/16) of tumors from AA patients and 2.8% (5/180) of EA patient tumors (p = 0.045). Further stratification of tumors by hyperdiploid or non-hyperdiploid status revealed significant differences in p18 homozygous deletion. Homozygous deletion of p18 was found in 25% (2/8) of AA patients and only 1.2% (1/83) of EA patients with non-hyperdiploid tumors (p=3.2 × 10-4). A nominally significant difference among non-hyperdiploid patients was also present for overall 1 p deletion, which was observed in 2/8 (25%) of AA non-hyperdiploid tumors and 33/83 (40%) of EA with non-hyperdiploid tumors (p=0.05). No differences were observed for 1 p deletion or p18 homozygous deletion among hyperdiploid tumors between AA and EA patients. We then combined our AA dataset with an independent dataset of 8 AA MM patients generated at the Mayo Clinic, Scottsdale AZ and repeated the analysis. Interestingly, very little or no aberrations were found in the dataset from the Mayo Clinic, however, differences of p18 homozygous deletion and 16q deletion among AA and EA remained statistically significant. To determine the correlation between hemizygous and biallelic loss of p18 and poor prognosis we used the 70 gene signature (Shaughnessy, et al., 2007) as a surrogate to identify patients with poor prognosis within the Multiple Myeloma Genomics Initiative dataset. Genomic identification of significant targets in cancer (GISTIC) was used (Beroukhim et al., 2007) to identify regions of aberrant copy number that were over-represented among samples. A relationship between poor prognosis and biallelic loss was found to be statistically significant (p = 0002) while samples with hemizygous loss showed no relationship (p = 0.57). Although the size of the current AA cohort is small, these results suggest that homozygous deletions at the p18 locus may be more common among African American MM patients with non-hyperdiploid tumors which may help to explain the disparity in AA patients with MM. Array CGH is currently being conducted on an additional 40 tumors from AA MM patients for a more robust analysis. Citation Information: Cancer Epidemiol Biomarkers Prev 2010;19(10 Suppl):B64.