Keats, Jonathan J.

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 The availability of human myeloma cell lines (HMCLs) has drastically benefited out understanding of multiple myeloma (MM). They represent essential resources to the myeloma research community at large who use them to identify and more importantly validate oncogenic events in MM. Furthermore, they represent the front line tools in efforts to identify novel therapeutic agents for MM patients. However, the myeloma research community is not immune to problems of cell line contamination (mixed populations) or systemic errors where HMCLs are labeled incorrectly. As the community evolves towards the development of tailor medicine it is essential that our basic tools are both pure and correct. Otherwise, a potentially beneficial therapeutic agent designed for a specific patient subset maybe lost simply because of a simple laboratory mix-up at some point over the years. To that end we have developed a simple PCR based method that can be used to validate the purity and authenticity of HMCLs. First two reference collections of over 50 HMCL maintained at the NCI and Mayo Clinic Arizona were compared using microsatellite fingerprinting. This process identified several previously unnoticed discrepancies. First, in both labs several cell lines that reportedly originated from different patients had the same fingerprints. These include the following unexpected pairs; ANBL-6 and DP–6, CAG and ARP–1, KMS–11 and KMS–20, KMS–11 and KMS–21PE/BM, JIM3 and KPMM2. Second, both KP–6 and KAS6/1 showed a level of cross-contamination with ANBL–6. All of the discrepant cell lines were requested from the original contributor and those that were available were retested. After this step we had identified unique fingerprints for ANBL–6, DP–6, KMS–11, and KMS–20. Furthermore, pure populations of KP–6 and KAS6/1 were confirmed. However, CAG and ARP–1 still had an identical fingerprint. Since the use of microsatellite fingerprinting is an expensive task and the identification of cross-contamination is not very robust we set out to develop better method. We decided to use a simple qualitative PCR method, as the binomial presence or absence of a band makes the interpretation of the fingerprint extremely easy. Furthermore, the high sensitivity of a qualitative PCR can pick up a small amount of contamination in the culture that can be lost in microsatellite analysis. This method involves a multiplex PCR screen that simultaneously interrogates 10 regions of the human genome. The screen is divided into two reactions, one with a panel of highly polymorphic copy number variations (CNV) that are often completely absent in some individuals, and a second one based on known biologic events present in the cell lines. The integration of the results from the CNV and Biological Fingerprints will identify each HMCL as a unique entity. We validated the methodology by confirming that this qualitative screen could pick up the cross–contamination identified in the original KP–6 and KAS6/1 samples. As our understanding of myeloma increases and we strive to develop new therapies for specific biological entities it will be essential that groups confirm both the authenticity and purity of their test cultures. We hope that widespread use of this simple screening methodology will significantly improve the quality and reproducibility of assays carried out in labs around the world.

Abstract Genetic abnormalities are important in the pathobiology of myeloma and established prognostic factors. High-density aCGH allow global unbiased detection of genomic gains and losses. In this study, we attempt to identify survival critical genomic aberrations by correlating aCGH-defined abnormalities with survival in 2 different cohorts of patients. aCGH was performed in 64 MM patients treated with high dose therapy from the Mayo Clinic using Agilent’s 44k DNA microarray genechip. In addition, a publicly available aCGH dataset performed in 67 MM patients treated with total therapy from the University of Arkansas Medical School using the lower density Agilent 22k chip (Human 1A v2) was also analyzed. Base 2 logarithms of the ratios between red and green intensities (log-ratios) were treated as a primary measure of copy number ratio between tumor and normal samples. To detect the regions of genomic aberration, values of a sliding window of 15 consecutive log-ratios were compared with those of an artificial ‘reference’ chromosome using the Wilcoxon rank sum test. The reference chromosome, constructed for each sample, was assembled by collecting log-ratio values close to zero. For this, 15 randomly sampled log-ratios from autosomal regions whose p-value of Wilcoxon signed rank test against 0 was larger than 0.05 were recursively accepted until the number of log-ratios in the assembled reference chromosome reached 1000. The p-values and their corresponding false discovery rates (q-values) for the copy number gain or loss were calculated independently for each sliding window and assigned to the center position of corresponding sliding window. The survival difference was examined between samples that had gained or lost a chromosomal region (sliding window) and samples that had not using the method of Kaplan-Meier and the statistical significance was assessed by the log-rank test. The sliding window was identified as gained or lost if P-value < 10 −4 and Q-value < 10[suo]-3. Sliding windows whose gains or losses led to poor survival with log-rank test p-value < 0.5, corresponding q-value < 0.5, and happened to ≥ 10% of all samples were retained. Several regions of genomic gains and losses were significantly associated with poorer survival with 5 deletion hotspots common between the 2 datasets (Table). We validated the prognostic significance of these survival critical loci using FISH in an independent dataset of 169 patients treated with high dose therapy. Clustering of these survival critical loci revealed clusters of MM characterized by low, intermediate or high number of these abnormalities, which are independent of ploidy and translocations subtypes. These subgroups have significantly different survival. In addition, the clustering analysis suggests the chromosome 13 loss is an early event whereas chromosome 1 abnormalities are late events. Our strategy therefore identified novel regions of genomic aberration that are important prognostically. However, it is likely that these regions are manifestation of genomically unstable tumors with complex abnormalities that have poorer prognosis. Chr Start End Length Cytoband 1 74,137,824 75,972,544 1,834,720 p31.1 1 62,433,123 84,792,809 22,359,686 p31.3 – p22.3 20 4,100,452 6,189,410 2,088,958 p13 – p12.3 20 6,717,170 13,142,205 6,425,035 p12.3 – p12.1 20 4,708,668 10,566,333 5,857,665 p13 – p12.2

Abstract The use of high-resolution aCGH allows for whole genome screening for copy number changes even in tumors that rarely produce metaphase spreads. The aim of this study was to characterize the aCGH findings in B-CLL, lung MALT lymphoma, Waldenström’s Macroglobulinemia (WM), Multiple Myeloma (MM) and human myeloma cell lines (HMCLs). This study includes 301 B-cell malignancy samples (19 B-CLL, 19 MALT, 20 WM, 48 HMCLs and 195 MM) and an additional 76 melanoma samples. We found MM to have the highest number of abnormalities per karyotype, with 15.8±7.5 (mean ± SD) and 20.6±17.0 in hyperdiploid (H) and non-hyperdiploid MM (NH), respectively. The remaining diseases have a significantly lower number of abnormalities: 5.5±4.5 in B-CLL, 3.5±1.96 in MALT and 4±3.5 in WM. Aneuploidy and biallelic deletions were rare events in these three diseases. B-CLL has two highly recurrent abnormalities involving 11q22-q23 (29%) and 13q14.3 (33%). A minimal deleted region (MDR) of ∼108Kb was identified at 11q comprising ACAT1, NPAT and ATM. In 13q, a 280Kb MDR was recognized, including TRIM13, KCNRG, mir-15a and mir-16. The subgroup of MALT patients with t(11;18) had very few abnormalities and the majority are a consequence of unbalanced translocations (MALT, BIRC2 and BIRC3 deletions). In the remaining MALT samples, trisomy 3 and 18q gain were the most common abnormalities (31% each). The 6q16.3-q26 deletion was the most common abnormality in WM (45%). In 4 of 9 patients with 6q deletion there was an associated 6p gain. The same observation was found in 2 of 3 patients with 8p loss and concomitant 8q gain. Interestingly, 6p and 8q gain were not identified in patients without 6q and 8p deletions. Deletion of 17p was the most common recurrent abnormality observed in our panel of B-cell cancers, being identified in MM, WM and B-CLL. In B-CLL and WM, small mono and biallelic deletions of the NF-kB negative regulators, TRAF3 and NFKBIA, were identified, suggesting a potential involvement of this pathway in the pathogenesis of these diseases. Hierarchical clustering of the aCGH data in MM identified 3 distinct groups, NH-MM, H-MM and MM with deletions of chromosome 13 and 14. Interestingly, MGUS and SMM were more commonly clustered with H-MM. Several sub-clusters were observed in the H-MM group, the most prominent being made up exclusively of patients from TC class D1. This cluster was characterized by the presence of trisomy 11 and 21. The 11q13 TC group clustered and was highly associated with 11q amplifications due to unbalanced t(11;14). The 6q deletion defined a cluster with WM, MM and Melanoma patient with that abnormality. In the case of B-CLL and MALT, the only identifiable clusters were observed in cases with 13q loss and trisomy 3, respectively. These results highlight both, the common and unique aCGH findings in several B-cell cancers. By hierarchical clustering, MM was significantly divergent from the rest of the B-cell diseases. Due to the limited number of abnormalities in B-CLL/MALT/WM, the clustering of these groups was exclusively based on the common abnormalities. The use of aCGH has refined the MDRs of 11q and 13q in B-CLL. Additionally, the identification of deletions affecting the NF-kB pathway in B-CLL and WM has prompted us to hypothesize on the importance of constitutive NF-κB activation in these diseases.

Abstract MM is characterized by widespread genomic instability. Two broad genetic subtypes of MM defined by ploidy exist. Hyperdiploid MM (H-MM) is characterized by trisomies of chromosome 3, 5, 7, 9, 11, 15, and 19, and generally lacked primary translocations involving the immunoglobulin heavy chain locus (IgH) whereas the non-hyperdiploid MM (NH-MM) is characterized by primary IgH translocations such as t(11;14), t(4;14) and t(14;16). Using high-density array comparative genomic hybridization (aCGH, Agilent 44K array), we catalogued the different aberrations on each chromosome arm and also the total number of aberrations per tumor (NAPT), as an indication of the degree of genomic instability, in a large cohort of 194 MM patients. Both H-MM and NH-MM have high number of genomic aberrations, 15.8±7.5 (mean ± standard deviation) versus 20.6±17.0 respective. NH-MM has significantly more genomic losses (11.8±11.0 versus 4.1±3.8), whereas H-MM has slightly more genomic gains (11.7±5.0 versus 8.8±9.0). Most of the abnormalities in NH-MM are structural abnormalities whereas they are mainly whole chromosome abnormalities in H-MM. Based on these abnormalities, we cluster the patients using hierarchical clustering. The 2 main branch of the resulting dendogram delineate hyperdiploid and non-hyperdiploid patients. Sub-clusters of each ploidy subtype are apparent. For H-MM, a cluster with mainly trisomies, including that of chromosome 21, and another cluster with additional deletions (13, 16q, and less trisomy 21 and trisomy 11) were apparent. For NH-MM, a group with 1q amplification and 13 deletion, which also tend to have loss of chromosome 4, 6q, 16q and 14, and another group with little abnormalities or just 6q loss, and chromosome 13 and 14 loss were identified. We identified some genetic difference between NH-MM and H-MM in additional to known difference such as the trisomies and chromosome 13 deletion. Loss of chromosome 4 (18% versus 0.9%, p<0.0001), loss of chromosome 14 (33% versus 16%, p=0.02) and loss of chromosome 22 (21% versus 4%, p=0.0008) are more common in NH-MM. Based on the distribution of NAPT, a cut-off of 20 abnormalities per tumor segregate the patients into 2 groups with significantly different survival. Those with greater NAPT have significantly shorter survival (median overall survival of 20 months versus 88 months, Log-rank p=0.006). There is no correlation between NAPT and ploidy or presence of chromosome 1 abnormalities suggesting that genomic complexity itself is associated with survival. Our study showed that both H-MM and NH-MM are genomically unstable although the pattern of abnormalities is distinct. In addition, based on clustering analysis, new pattern of genetic abnormalities are observed that allow further refinement of the ploidy subtypes. In addition, genomic complexity is also an important prognostic factor.

AbstractObjectivesIn the TOURMALINE‐MM1 phase 3 trial in relapsed/refractory multiple myeloma, ixazomib‐lenalidomide‐dexamethasone (IRd) showed different magnitudes of progression‐free survival (PFS) benefit vs placebo‐Rd according to number and type of prior therapies, with greater benefit seen in patients with >1 prior line of therapy or 1 prior line of therapy without stem cell transplantation (SCT).MethodsRNA sequencing data were used to investigate the basis of these differences.ResultsThe PFS benefit of IRd vs placebo‐Rd was greater in patients with tumors expressing high c‐MYC levels (median not reached vs 11.3 months; hazard ratio [HR] 0.42; 95% CI, 0.26, 0.66; P < .001) compared with in those expressing low c‐MYC levels (median 20.6 vs 16.6 months; HR 0.75; 95% CI, 0.42, 1.2). Expression of c‐MYC in tumors varied based on the number and type of prior therapy received, with the lowest levels observed in tumors of patients who had received 1 prior line of therapy including SCT. These tumors also had higher expression levels of CD19 and CD81.ConclusionsPFS analyses suggest that lenalidomide and ixazomib target tumors with different levels of c‐MYC, CD19, and CD81 expression, thus providing a potential rationale for the differential benefits observed in the TOURMALINE‐MM1 study. This trial was registered at www.clinicaltrials.gov as: NCT01564537

8007 Background: We recently described mutations in multiple genes in MM patients that lead to the activation of the non- canonical NF-KB pathway. Among the mutated genes, TRAF3 is the most commonly affected, and is inactivated in about 20% of patients. In this study, we further defined the clinical significance of TRAF3 inactivation in MM. Methods: Deletion of TRAF3 was identified by array- based comparative genomic hybridization using Agilent Human Genome CGH 44k oligonucleotide array and confirmed by fluorescent in situ hybridization. Mutations were detected by sequencing. We use a TRAF3 gene expression cut-off (derived from 127 Mayo clinic patients) as a surrogate for TRAF3 inactivation to investigate its association with Translocations and Cyclin D genetic subtypes, response rates, and survival using 2 large gene expression dataset: UAMS dataset (559 newly diagnosed patients treated with Total therapy II and III) and Millenium datasets (213 relapsed patients entered into randomized study of bortezomib versus dexamethasone). Results: A normalized expression level of less than 0.6 identified all but three of the known TRAF3 inactivated cases in the Mayo dataset (p<0.0001). Using this cut-off, TRAF3 inactivated cases were enriched for t(4;14) (26%, p=0.00002) and rarely D1 (mostly hyperdiploid) (9%, p=9.6E-10) in all 3 datasets. TRAF3 inactivation did not affect survival of patients treated with transplant-based therapy (UAMS and Mayo dataset) but was strongly associated with bortezomib response (89% TRAF3 low versus 40% TRAF3 normal, p0.6 had similar PFS with the two treatment. Conclusion: Mutations resulting in TRAF3 inactivation are common, particularly in non-hyperdiploid MM, and predict for response to bortezomib and resistance to dexamethasone suggesting that inhibition of the non-canonical NF-KB pathway may be one of the principle mechanisms of action of proteasome inhibitors in MM. No significant financial relationships to disclose.

Abstract Background: MYC rearrangement is a recurrent somatic event in MM and results in super-enhancers repositioning within 3Kb (centromeric or telomeric) of the MYC locus. BRD4, a member of the bromodomain family, binds H3K27Ac and regulates enhancers activity, RNA polymerase II transcription initiation and elongation and in particular it regulates MYC transcription in MM cells. Immunomodulatory drugs (IMiDs) promote the proteasomal degradation of IKZF1/3 and the transcriptional repression of MYC and IRF4. However the exact mechanisms through which IMiDs downregulate MYC are not well understood. Methods and Results: Using a extended panel of 12 MM cell lines we have first confirmed our previous observartion that IMIDs universally degraded IKZF1/3, however unlike in IMiDs-sensitive cell lines it failed to downregulate MYC in resistant cells. Therefore, this finding suggests that MYC transcriptional regulation rather than IKF1/3 degradation is the "bottleneck" in IMiDs anti-myeloma activity or resistance. In addition, RNA-seq of paired and serially collected primary myeloma cells with acquired resistance to IMIDsconfirmed the enrichment of genes signatures associated with MYC at the time of acquired resistance. Of note, in a library of t(4;14) MM cell lines lenalidomide significantly downregulates FGFR3 while the expression of WHSC1 was not affected. As in t(4;14) cells FGFR3 is driven by the 3' IGH enhancer while WHSC1 is under the control of the intronic Em enhancer, and in view of the known role of IKZF1 in CSR, we posit that IKZF1 regulates plasma cells enhancer activity and hence MYC expression. To validate this hypothesis we first established the genome-wide distribution of IKZF1 in MM1S, RPMI8226 and OPM2 cells by ChIP-Seq. This analysis revealed the distribution of IKZF1 across the genome, predominantly to intronic an intragenic loci with only ~ 8% or reads mapping within +/- 5 kb of genes TSS. Importantly IKZF1 was also enriched at known myeloma cells enhancers or super-enhancers such as IGLL5, TXNDC5, BCL2L1, and DUSP22. We also mapped BRD4 binding to the genome in 8226 and MM1S cell lines and confirmed previously described mapping to known B-cell enhancers. Of note IKZF1 nearly universally overlapped with all BRD4 enhancers and superenhancers loci. These findings lead us to propose that IKZF1 depletion in response to IMiDs treatment will result in enhancer destabilization and displacement of BRD4 from enhancer loci. Indeed, Chip-Seq analysis of IKZF1 and BRD4 genomic distribution pre- and post- treatment with lenalidomide (10 uM for 4 or 8h) in IMiDs sensitive cell lines significantly depleted IKZF1 and BRD4 at superenhancer loci. In contrast, in IMiDs resistant cell lines (RPMI8226) and despite IKZF1 depletion, BRD4 was largely retained at these loci. These findings suggest that in IMiDs sensitive cells, IKZF1 is the major transcription factor mediating BRD4 recruitment to enhancer and superenhancer loci. In contrast, in IMiDs resistant cells and similar to BET-bromodomain inhibitor (JQ1) resistance, transcriptional plasticity or hyper-phosphorylation of BRD4 attributable to the phosphatase PP2A inactivation may also be mediating IMiDs resistance. Indeed the levels of p-BRD4 determined by western blotting were significantly higher in IMiDs resistant INA6 and RPMI8226 cells compared to MM1S cells. Furthermore, treatment of INA6 cells with the PP2A activator phenothiazine significantly sensitized INA6 cells to lenalidomide. Lastly, in order to investigate whether IMiDs resistance was associated with acquired new MYC rearrangements with an "IKZF1_resisant enhancer," we performed mate-pair sequencing of IMiDs resistance patients (18 post acquisition of IMIDs resistance and 7 pairs of pre- and post- acquisition of IMIDs resistance). MYC structural rearrangements (indels, translocations, inversions) were detected using DELLY and MANTA. Of note several MYC rearrangement were identified including MYC duplication in 1 patient, MYC structural rearrangement (±3Kb of TSS) in 9 patients (enhancer partner: TXNDC5, IGHa2, NSMCE2, IGLL5) and a newly acquired IRF4-IGH a2 rearrangement in 1 patient with pre-existing MYC-IGLL5 rearrangement. Conclusion:We have demonstrated that IMIDs alter enhancer activity in myeloma cells by depleting IKZF1 / IKZF3 and disrupting BRD4 binding to enhancers and super-enhancers, stalling of RNA polymerase II and MYC transcription. Disclosures Neri: Celgene and Jannsen: Consultancy, Honoraria. Bergsagel:Amgen, BMS, Novartis, Incyte: Consultancy; Novartis: Research Funding. Bahlis:Onyx: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Other: Travel Expenses, Research Funding, Speakers Bureau; BMS: Honoraria; Celgene: Consultancy, Honoraria, Other: Travel Expenses, Research Funding, Speakers Bureau.

Purpose: Multiple myeloma (MM) is a plasma cell (PC) malignancy with an increasing incidence in the US. Epidemiological studies demonstrate a 2-3 fold higher incidence of the pre-malignant monoclonal gammopathy of undetermined significance (MGUS) and MM with a ~4-year younger age of onset among African Americans (AA) compared to European Americans (EAs) (Fonseca, Leukemia, 2017). With equal access to care, AAs have better overall survival compared to EAs (Waxman, Blood, 2010). This disparity may be explained by ancestral-associated genetic predisposition of AAs to development of monoclonal gammopathies and to specific acquired, cytogenetically-defined subtypes. Using calculated genetic ancestry data, we have previously identified a higher prevalence of IgH translocations t(11;14), t(14;16) and t(14;20) in individuals with >80% African ancestry (Baughn, BCJ, 2018). Since SNP rs9344 encoding the CCND1 870G>A polymorphism has been reported in association with increased risk of t(11;14) (Weinhold, Nature Genetics, 2013), we investigated whether rs9344 correlates with African ancestry and with t(11;14) in our cohort of patients with plasma cell dyscrasias. Methods: We studied 898 patients with monoclonal gammopathies who had undergone uniform testing to identify MM-specific cytogenetic abnormalities. DNA from bone marrow samples was genotyped on the Precision Medicine Research Array and biogeographical ancestry was assessed using the Geographic Population Structure Origins tool (Elhaik, Nat Commun, 2014). Plasma cell proliferative disorder FISH of immunoglobulin (cIg)-stained positive plasma cells was performed as described (Baughn, BCJ, 2018). Individuals were divided into three ancestral groups: 1. EAs (<0.1% African ancestry and <30% Asian ancestry); 2. AAs (> 80% African ancestry); and 3. Other. Chi-squared test was used to determine the overall comparison between the 3 ancestral groups and also between ancestral groups 1 vs 2, and 2 vs 3 using pairwise comparison. All tests were two-sided with alpha level set at 0.05 for overall statistical significance. Pairwise comparison was considered statistically significant when p<0.025 based on Bonferroni method for multiple comparisons. Results: We identify increased risk of development of either a t(11;14), t(14;16) or t(14;20) in AAs (48.8%) compared to EAs (33.6%) (p-value=0.0051). To explore the genetic basis of increased t(11;14) specifically (37.4% AAs vs. 27.3% p-value=0.049), we evaluated the frequency of the G risk allele of rs9344 in relation to African ancestry. The frequency of the G risk allele was higher in AAs (0.81) compared to EAs (0.59) (p-value <0.0001) and also higher in t(11;14) cases (0.73) compared to non-t(11;14) controls (0.58) (p-value <0.0001). A multivariate model identified only rs9344 as significantly associated with t(11;14) after adjusting for age, gender and race group suggesting that it plays a role in the development of t(11;14) (p-value <0.001 for GG, p-value=0.005 for AG). To test if these results are replicable, we studied the MMRF CoMMpass cohort. This cohort includes individuals with newly diagnosed MM along with self-report race information and translocation data from long insert whole genome sequencing. Although t(11;14) was not enriched in self-reported Black individuals from this cohort (17.5% Black vs. 20.4% White, p-value=0.47), there was association between the rs9344 and self-reported Black race (p-value <0.0001) and with the presence of t(11;14) when the t(11;14) was analyzed by long insert whole genome sequencing (p-value=0.0001). Conclusions: To our knowledge, this study includes the largest group of African individuals with an abnormal plasma cell clone along with uniformly collected FISH, genotyping and ancestry data. We have identified in this diverse population the association of the CCND1 870G>A polymorphism (rs9344) with African ancestry and with t(11;14) suggesting that it plays a role in the development of t(11;14) plasma cell dyscrasias. Disclosures Elhaik: DNA Diagnostics Center: Consultancy. Baird:DNA Diagnostics Center: Employment. Cerhan:Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; NanoString: Research Funding. Bergsagel:Celgene: Consultancy; Ionis Pharmaceuticals: Consultancy; Janssen Pharmaceuticals: Consultancy. Dispenzieri:Alnylam: Research Funding; Akcea: Consultancy; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding. Kumar:Janssen: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Takeda: Research Funding.

Abstract As multiple myeloma tumors universally dysregulate cyclin D genes we conducted high-throughput chemical library screens for compounds that inhibit signaling pathways driving cyclin D2 promoter transactivation, assaying more than 4,000 compounds. The top-ranked compound from these studies was a natural triterpenoid, pristimerin. Pristimerin markedly suppressed cyclin D2 promoter activity (>90%) in 3T3 fibroblast cells and inhibited cyclin D1, D2 and D3 protein expression in myeloma tumor cells. Strikingly, the early (4 hour) transcriptional response of myeloma cells treated with pristimerin closely resembles cellular responses elicited by proteosome inhibitors (P<10−9) (Connectivity Map Build 2, www.broad.mit.edu/cmap), with rapid induction of heat shock proteins (HSP70 >90-fold), activating transcription factor (ATF) 3 and CHOP. Enzymatic assays performed with purified 20S proteosome, or with total cellular extract, confirm that pristimerin rapidly and specifically inhibits chymotrypsin-like 20S proteosome activity at low concentration (<100nM), causing sustained inhibition lasting >6 hours. Consistent with inhibition of proteosome function, pristimerin causes rapid and sustained accumulation of high molecular weight poly-ubiquitinated protein in myeloma cell lines. Notably, related cytotoxic triterpenoid drugs, such as the methyl ester of 2-cyano-3,12-dioxooleana-1,9(11)-dien-28-oic acid (CDDO-Me, RTA 402) or betulinic acid or the ginsenosides - all of which show promising anti-cancer activities and are currently in clinical trials for advanced lymphoma, leukemia or solid malignancies - commonly inhibit NF-kB activation via direct inhibition of IKKα or IKKβ. In contrast drugs that function as proteosome inhibitors also commonly suppress NF-kB function instead by impairing degradation of ubiquitinated IkB. Immunoblotting for phosphorylated IkB confirms that pristimerin, like other triterpenoids, acts upstream of IkB to inhibit its phosphorylation, although pristimerin simultaneously inhibits proteosome activity with marked potency to diminish the clearance of ubiquitinated IkB. As a result of this two-fold stabilization of IkB, pristimerin causes overt and specific suppression of NF-kB mediated transcription, measured by a panel of transcriptional reporters with synthetic promoters containing 5x repeats of generic binding sites for NF-kB, AP-1, CREB or TCF4. Importantly, specific suppression of constitutive NF-kB transcriptional activity was pronounced in myeloma cells with inherent NF-kB pathway activation resulting from bi-allelic deletion of the TRAF3 tumor suppressor. Constitutive activation of the NF-kB pathway occurs in a significant proportion of primary myeloma tumors, most commonly via inactivation of TRAF3. Selective silencing of NF-kB driven transcription in myeloma cells may mediate the potent suppression of cyclin D proteins induced by this compound. Significantly, multiple myeloma cells are exquisitely sensitive to both proteosome inhibition or NFkB pathway inhibition. Consistent with these twin vulnerabilities, pristimerin is potently and selectively lethal to primary myeloma cells from patients (IC50<100nM) grown in mixed lineage culture and inhibits the growth of xenografted human plasmacytoma tumors grown in mice, providing a strong rationale for pharmaceutical development of triterpenoid dual-function proteosome-plus-NF-kB pathway inhibitors as therapeutics for multiple myeloma and related human malignancies.