ALBERT

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

Description: The Multiple Myeloma Research Foundation (MMRF) CoMMpass trial (NCT145429) is a longitudinal study of 1147 patients with newly-diagnosed multiple myeloma from clinical sites in the United States, Canada, Spain, and Italy. Each patient receives a treatment regimen containing a proteasome inhibitor, immunomodulatory agent, or both. Clinical parameters are collected at study enrollment and every three months through the eight-year observation period. To identify molecular determinants of clinical outcome each baseline and progression tumor specimen is characterized using Whole Genome Sequencing, Exome Sequencing, and RNA sequencing. Data available as of January 1, 2016 is included in this first formal interim analysis, which includes 995 enrolled patients of whom 851 are molecularly characterized. This cohort of patients includes 74 patients with at least two sequential samples, plus 15 patients with characterized tumor samples from the bone marrow and peripheral blood. The median follow-up of the cohort is 66 weeks, which identified a median PFS of 36 months for the cohort. The median OS was not reached but 76% are still alive at 3 years. Although the age at enrollment by gender is uniform, there is a significant difference in PFS and OS, with males performing worse than females, p=0.001 and p=0.0004 respectively. Analysis of the exome sequencing data from the 746 baseline BM localized tumors identified a median of 122 non-immunoglobulin related mutations per patient, with an interquartile range of 96-155. There is a group of highly mutated (〉481 mutations [mean+1SD]) patients who frequently have MAF family translocations (66%) and/or mutations in the DNA repair genes MSH2, MSH3, MSH4, MSH6, or ATM (38%). Across the cohort 21/53 of the DNA repair gene mutations reside in these 21 patients compared to 14/47 MAF family translocations. Analysis of the somatic mutations identified 20 significant genes, which are recurrently mutated and the mutated allele is detectably expressed; BRAF, CYLD, DIS3, FAM46C, FCF1, FGFR3, FUBP1, KRAS, MAX, NFKBIA, NRAS, PRKD2, RASA2, RB1, SAMHD1, SP140, TGDS, TP53, TRAF2, and TRAF3. Integration of the copy number data and the mutation data identified an association between TP53 deletion and mutation, suggesting many patients present with homozygous loss of TP53. Patients with one or two functional TP53 alleles had similar PFS and OS but the patients with zero functional alleles had a significantly reduced OS (p

Description: The Multiple Myeloma Research Foundation (MMRF) CoMMpass trial (NCT0145429) is a longitudinal study of 1000 patients with newly-diagnosed multiple myeloma. The study opened July 2011 and now includes over 650 patients from 91 sites in the United States, Canada and European Union. Each patient is required to receive an approved proteasome inhibitor, immunumodulatory agent, or both. Enriched tumor and matched constitutional samples are comprehensively analyzed using Long-Insert Whole Genome Sequencing (WGS), Whole Exome Sequencing (WES) and RNA sequencing (RNAseq). Clinical parameters, Quality of Life measurements and health care resource utilization values are collected at study entry and every three months for a minimum of five years. Additional bone marrow aspirates are collected and analyzed at each recurrence or progression of disease. An extensive clinical and molecular database, the MMRF Researcher Gateway (https://research.themmrf.org), has been developed to facilitate the rapid dissemination of the results and provides the myeloma community with a mechanism to analyze the data. In this current interim analysis, we report on 195 patients that are fully characterized at the molecular level. We focused this analysis on immunoglobulin translocations and inter-chromosomal fusion transcripts. As expected we detected the classic canonical t(4;14), t(6;14), t(11;14), and t(14;16) translocations targeting FGFR3/MMSET, CCND3, CCND1, and MAF respectively. Seven patients presented with t(8;14) rearrangements correlating with high expression of MYC. Novel translocations were detected targeting MAP3K14/NIK in two patients and NFKB1, TOP1MT, TXNDC2, APOL3, FCHSD2, PRICKLE1, and BCL2L1 in individual patients. Importantly, the matched RNAseq data confirmed the high expression of MAP3K14, NFKB1, TOP1MT, APOL3 and BCL2L1. Moreover, the anti-apoptotic isoform of BCL2L1, Bcl-xL, was the prominent transcript isoform detected. In several patients we detected multiple IgH translocations. For instance the BCL2L1 translocation occurred in a downstream class switch recombination region from one associated with a co-occurring t(11:14). We also analyzed the RNAseq dataset for inter-chromosomal fusion transcripts and leveraged the independent long-insert WGS data to validate the predicted fusions. The only recurrent fusion partner identified was IgH-MMSET created by t(4:14). Fusion transcripts were detected in individual patients between IgH elements and MYEOV and WWOX along with several of the novel IgH translocation partners; NFKB1, TOP1MT, and APOL3. Several genes are involved in multiple fusions but with different partners. Three independent fusions were detected between the highly expressed gene FCHSD2 and MYC, MAP3K14, and ANKRD55. Three additional fusions were detected between MAP3K14 and ELL, PLCG2, and CDC27, which produce hybrid MAP3K14 isoforms lacking the N-terminal negative regulatory domain. We also detected three independent fusions involving BRF1, which is typically not expressed in myeloma tumors. These appear to be markers of translocations occurring just centromeric of the strong 3’ IgH enhancers. Interestingly, two of the partners are located in a region of chromosome 12 harboring MDM2 and spiked expression of MDM2 was observed. Additional genes with multiple fusion events included NEDD9 and ARHGEF12. Integrating the WES and RNAseq datasets, we identified 3518 variants (median 14 per patient) where the variant allele detected by WES, was also detected in the RNAseq data, suggesting it is potentially biologically relevant. Of these, 44 distinct genes were mutated in at least 2% of patients. The most common mutations (〉7 patients) occurred in KRAS, NRAS, IGLL5, DIS3, BRAF, ACTG1, EGR1, FAM46C, TRAF3, DUSP2, FGFR3, and PRR14L. We also identified a deletion of IKZF3/Aiolos in a patient who progressed rapidly on lenalidomide-dexamethasone. Alterations in Ikaros family members like Aiolos have recently been reported as a potential mechanism of resistance to IMiDs. As the study continues to mature, we expect it will provide unprecedented molecular characterization and correlating clinical datasets that will help define the determinants of response to anti-myeloma agents and facilitate future clinical trial designs, thus serving as a stepping-stone toward personalized medicine for myeloma patients. Disclosures Lonial: Millennium: The Takeda Oncology Company: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Onyx Pharmaceuticals: Consultancy, Research Funding.

Description: The Multiple Myeloma Research Foundation (MMRF) CoMMpass trial (NCT145429) is a longitudinal study of 1000 patients with newly-diagnosed multiple myeloma from clinical sites in the United States, Canada, Spain, and Italy. Each patient receives a treatment regimen containing a proteasome inhibitor, immunumodulatory agent, or both. Clinical parameters are collected at study enrollment and every three months through the five-year observation period. To identify molecular determinants of clinical outcome each baseline and progression tumor specimen is characterized using Whole Genome Sequencing, Exome Sequencing, and RNA sequencing. This will be the first public presentation of the interim analysis seven cohort with 760 enrolled patients of whom 565 are molecularly characterized. This cohort of patients includes 14 patients with baseline and secondary samples along with 7 patients with characterized tumor samples from the bone marrow and peripheral blood. Although the median follow-up time for the cohort is only 260 days the patients on proteasome and IMiD based combinations are currently showing a PFS and OS benefit compared to those receiving combinations with each agent alone. From the raw mutational analysis we identified 24 significant genes that are recurrently mutated and the mutated allele is detectably expressed in all but one, DNAH5. Suggesting these mutations are likely contributing to myelomagenesis through an unconventional mechanism. Interestingly, DIS3 mutations are independent of KRAS, NRAS, and BRAF indicating a potential mechanistic link while PRKD2 mutations are associated with t(4;14). To identify events driving the initiation of myeloma we performed a detailed clonality analysis using a bayesian clustering method that corrects for copy number abnormalities and tumor purity to assign mutations into distinct clonal branches versus the initiating trunk mutations. On average 63.8% of mutations are trunk mutations and in 86.7% of patients at least one trunk mutation is associated with somatic hypermutation of an immunoglobulin gene as expected in a late stage B-cell malignancy. This identified many expressed trunk mutations that did not come out in the classic significance analysis like ATM, EGR1, and CCND1. To identify molecular subtypes we performed unsupervised clustering using a consensus clustering approach on independent discovery and validation cohorts, which identified 12 distinct subtypes, using a combination of silhouette score and cumulative distribution of consensus scores. This analysis identified two distinct groups associated with t(4;14) with mutations in FGFR3 and DIS3 being exclusive to one subgroup. In addition, this analysis separates patients with cyclin D translocations into three different groups, with one group having the second lowest PFS proportion. Three patients without CCND1 or CCND3 translocations were found to have IgH translocations targeting CCND2. The MAF subgroup was associated with the lowest OS and PFS proportion, and the three MAF/MAFB translocation negative patients in the subgroup all had MAFA translocations. The remaining 6 subgroups are associated with hyperdiploid copy number profiles and harbor the majority of the IgH-MYC translocation events. Two of the hyperdiploid groups are associated with a low level of NFKB activation compared to the remaining four, one of these is defined by the highest proliferation index but paradoxically the other has the second worst OS proportion. Another group is enriched with FAM46C and NRAS mutations. The genomic profiles of the paired tumors isolated from the peripheral blood and bone marrow are highly similar indicating these are not genetically distinct tumor compartments, at least in this subset of seven patients. Applying our bayesian clustering method to the serial samples resolved additional clonal clusters as mutations with similar cancer cell fractions at diagnosis clearly diverged at later timepoints. These analyses have identified tumor initiating mutations and new subtypes of myeloma, which are associated with distinct molecular events and clinical outcomes. Disclosures Jagannath: Novartis: Honoraria; Bristol Myers Squibb: Honoraria; Celgene: Honoraria; Merck: Honoraria; Janssen: Honoraria. Siegel:Celgene Corporation: Consultancy, Speakers Bureau; Amgen: Speakers Bureau; Takeda: Speakers Bureau; Novartis: Speakers Bureau; Merck: Speakers Bureau. Vij:Takeda, Onyx: Research Funding; Celgene, Onyx, Takeda, Novartis, BMS, Sanofi, Janssen, Merck: Consultancy. Zimmerman:Amgen: Honoraria, Speakers Bureau; Celgene: Honoraria, Speakers Bureau; Millennium: Honoraria, Speakers Bureau; Onyx: Honoraria. Niesvizky:Celgene: Consultancy, Speakers Bureau. Rifkin:Onyx Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Millennium Pharmaceuticals, Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Consultancy, Membership on an entity's Board of Directors or advisory committees. Lonial:Millennium: Consultancy, Research Funding; Onyx: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Celgene: Consultancy, Research Funding.