Multiple Myeloma Subgroups Research Articles

Combined Inhibition of Chk1 and Wee1 As a New Therapeutic Strategy for High-Risk Multiple Myeloma Patients

Multiple myeloma (MM) is the second most common hematological malignancy characterized by an abnormal clonal proliferation of malignant plasma cells. Despite introduction of novels agents that have significantly improved clinical outcomes, most patients relapse and develop drug resistance. Therefore, novel therapeutic strategies to overcome chemotherapy resistance are needed in clinical settings.MM is characterized by genomic instability and high level of replicative stress that arise during the disease's pathogenesis. In response to replicative and DNA damage stress, MM cells activate various DNA damage signaling pathways that include the kinases ATR, Chk1 and Wee1. Chk1 is activated by ATR after DNA damage or replicative stress and promote cell cycle arrest through the regulation of S and G2 checkpoints. Wee1 kinase plays a central role in the proper timing of cell division cycle controlling entry into mitosis and DNA replication during S phase. Interestingly, experimental studies have identified that Chk1 inhibitors are strongly synergistic with Wee1 inhibitors in various cancer models. Furthermore, Chk1 and Wee1 inhibitors are currently under clinical investigation.Here, we investigated the therapeutic interest of Chk1 and Wee1 in MM.First we investigated the prognostic value of Chk1 and/or Wee1 gene expression in MM patients. Both Chk1 and Wee1 were significantly overexpressed in human myeloma cell lines (HMCLs, n= 40) compared to bone marrow plasma cells (BMPCs, n=5) (P<001 and P<001 respectively). Chk1 and Wee1 expression were significantly higher in the poor prognosis “proliferation” MM subgroup (P<001 and P<001 respectively).High Chk1 expression and high Wee1 expression could predict for shorter overall survival (OS) in 4 independent cohorts of newly-diagnosed patients (P<0.001 and P=0.007 in the HM cohort (N=206), P<0.001 and P=0.008 in UAMS-TT2 cohort (N=345), P<0.001 and P<0.001 in Hovon cohort (N=282) and P=0.002 and P<0.001 in UAMS-TT3 cohort (N=186)). Same results were obtained for event free survival (EFS). Moreover, Chk1 and Wee1 high expression are associated with a poor prognosis in a cohort of 242 patients treated by Bortezomib monotherapy (Mulligan Cohort, P<0.001 and P=0.001 respectively).Interestingly, combined high expression of Chk1 and Wee1 are associated to significantly shorter survival compared to high expression of Chk1 or Wee1 alone in the 4 independent cohorts investigated. Same results were obtained for event free survival (EFS).According, to these results, we investigated the therapeutic interest of Chk1 and Wee1 inhibitors (AZD7762 and MK-1775) alone and in combination in MM.Chk1 inhibitor (AZD7762) induced a dose dependent cell growth inhibition in 13 HMCLs with a median IC50 of 179nM (range 69-366nM). A correlation between HMCLs sensitivity and P53 mutation was observed (r =0.7, P<0.01).Wee1 inhibitor (MK-1775) induced also a dose dependent inhibition of cell growth in all investigated HMCLs (n=10) with a median of IC50 of 450nM (range 100-800nM).Combination treatment of Wee1 inhibitor IC20 with various doses of Chk1 inhibitor was performed in 4 HMCLs. We identified a high synergy (combination index range 0.4-0.7) associated with a significant and remarkable reduction of Chk1 inhibitor (AZD7762) IC50 (198nM to 20nM for XG6; 166nM to 25nM for AMO1; 386nM to 18nM for XG7 and 163nM to 21nM for OPM2) in all the tested HMCLs. Chk1 and Wee1 inhibitors combination demonstrated a significant increase in apoptosis induction, proliferation inhibition and DNA damage induction compared to Chk1i or Wee1i alone in 3 HMCLs.We investigated the effects of Chk1i, Wee1i and Chk1i/Wee1i combination on primary MM cells of patients (n = 5) co-cultured with their bone marrow microenvironment. After 4 days of treatment, cells were enumerated and the fraction of viable myeloma cells (CD138+) and non-myeloma cells (CD138-) were determined by flow cytometry. Chk1i/Wee1i combination significantly and specifically induced a higher toxicity on myeloma cells of patients compared to Chk1i or Wee1i alone. This toxicity is specific of MM cells since normal bone marrow cells were significantly less affected by the combination treatment (P < 0.01).Taken together, these data suggest that association of Chk1i and Wee1i may represent a promising therapeutic approach in high-risk MM patients characterized by high Chk1 and Wee1 expression. DisclosuresBruyer:Diag2tec: Employment. Martin:Diag2tec: Employment. Cartron:Celgene: Consultancy, Employment; Sanofi, BMS, Jansen, celgene, Roche, Gilead: Equity Ownership; Roche: Consultancy, Equity Ownership, Honoraria, Research Funding. Hose:EngMab: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; Sanofi: Research Funding.

Light Chain-Predominant Multiple Myeloma Subgroup; Impaired Renal Function Correlates with Decreased Survival in this Subgroup

Background: Patients with light chain-predominant multiple myeloma have been shown to exhibit shorter survival. Retrospective comparison of clinical and laboratory data was undertaken to ascertain the likely cause(s) of this observation. Methods: Records of multiple myeloma patients seen at one institution revealed 316 cases of conventional and 71 cases of light chain-predominant multiple myelomas with secretion of intact immunoglobulins. Laboratory and clinical findings in the two groups were compared. Findings: Patients with light chain-predominant multiple myeloma had a significantly higher death rate, higher rate of chronic dialysis, and a lower eGFR and serum albumin, a significantly higher urine protein concentration, and a significantly higher prevalence of hypertension and blood transfusion requirements. Other clinical and laboratory parameters surveyed were not significantly different between the two groups. Interpretation: The shorter survival of patients with light chain-predominant multiple myeloma is likely to be due to renal damage caused by the excess free immunoglobulin light chains. Renal damage might be ameliorated by early aggressive treatment with chemotherapy, plasmapheresis and dialysis; a multi-institutional prospective controlled trial would be needed to test this hypothesis. Funding Statement: None to declare. Declaration of Interests: Dr. Singh serves as a consultant to Diazyme Inc. and HealthTap. All other authors have nothing to declare. Ethics Approval Statement: The study protocol was reviewed and approved by the institutional review board.

Genome-Wide Somatic Alterations in Multiple Myeloma Reveal a Superior Outcome Group.

PURPOSEMultiple myeloma (MM) is accompanied by heterogeneous somatic alterations. The overall goal of this study was to describe the genomic landscape of myeloma using deep whole-genome sequencing (WGS) and develop a model that identifies patients with long survival.METHODSWe analyzed deep WGS data from 183 newly diagnosed patients with MM treated with lenalidomide, bortezomib, and dexamethasone (RVD) alone or RVD + autologous stem cell transplant (ASCT) in the IFM/DFCI 2009 study (ClinicalTrials.gov identifier: NCT01191060). We integrated genomic markers with clinical data.RESULTSWe report significant variability in mutational load and processes within MM subgroups. The timeline of observed activation of mutational processes provides the basis for 2 distinct models of acquisition of mutational changes detected at the time of diagnosis of myeloma. Virtually all MM subgroups have activated DNA repair–associated signature as a prominent late mutational process, whereas APOBEC signature targeting C>G is activated in the intermediate phase of disease progression in high-risk MM. Importantly, we identify a genomically defined MM subgroup (17% of newly diagnosed patients) with low DNA damage (low genomic scar score with chromosome 9 gain) and a superior outcome (100% overall survival at 69 months), which was validated in a large independent cohort. This subgroup allowed us to distinguish patients with low- and high-risk hyperdiploid MM and identify patients with prolongation of progression-free survival. Genomic characteristics of this subgroup included lower mutational load with significant contribution from age-related mutations as well as frequent NRAS mutation. Surprisingly, their overall survival was independent of International Staging System and minimal residual disease status.CONCLUSIONThis is a comprehensive study identifying genomic markers of a good-risk group with prolonged survival. Identification of this patient subgroup will affect future therapeutic algorithms and research planning.

Evaluation of the Role of Plerixafor in Peripheral Blood Progenitor Cell Mobilization and Collection in Autologous Donors with Multiple Myeloma and Non-Hodgkin Lymphoma

Purpose Autologous hematopoietic stem cell transplantation is commonly used as treatment for patients with Multiple Myeloma (MM) or Non-Hodgkin Lymphoma (NHL). The mobilization and collection of peripheral blood progenitor cells (PBPC) to reach the required cell dose for transplantation is problematic for some patients when standard mobilization agents such as G-CSF, alone or combined with chemotherapy, are used. These patients are considered poor mobilizers with &lt; 20 CD34+ cells /μl on the planned day of collection and the optimal strategy to collect a sufficient number of PBPC in poor mobilizers is still not fully known. Plerixafor, a CXCR4 inhibitor, when added to the standard mobilization regimen, has been shown to improve mobilization and increase the probability of collecting a PBPC graft &gt; 2 X106CD34 /kg in standard mobilizers. In our center, Plerixafor became available in October 2012. However, how best to use plerixafor to improve care for poor mobilizers while ensuring the most cost-effective use of health care resources for this patient population remains an important question. To begin answering this question, we evaluated the impact of plerixafor usage in our population of poor mobilizers in our institution using a historical cohort for comparison. Material and method The population of poor mobilizers in the setting of MM or NHL (defined as &lt; 20 CD34 / μl on the planned day of collection) between January 2009 and December 2017 at Hôpital de l'Enfant Jesus (HEJ) du CHU de Québec was retrospectively studied and analyzed. To ensure that all poor mobilizers were included, we screened all flow cytometry CD34+ cell count results &lt; 50 /μl on the planned day of collection and reviewed all the charts of patients with &lt; 20 CD34 / μl regardless of whether they were collected or not. This chart review allowed a comprehensive description of the characteristics of our poor mobilizers, a comparison of the capacity to collect an adequate PBPC with or without plerixafor and to evaluate its impact on different variable with regard to PBPC collection and subsequent engraftment. The data were compiled in an ACCESS database using a retrospective review of digital patient charts. The data was analyzed by the Centre de Recherche du CHU de Quebec (CRCHUQ). Data were stratified by disease type and CD34 level on the planned day of PBPC collection. Results 207 patient charts were reviewed; 70 poor mobilizers with 95 mobilizations attempts, 30 of them using plerixafor, were included. The baseline characteristics of both groups were similar as well as the length of hospitalization for transplant and relapse free survival at one year. The addition of Plerixafor to our management of poor mobilizers did not significantly increase the proportion of patients proceeding to autologous PBPC transplant (80,4 vs 75% p=0,7599). During the mobilization attempts, the maximal CD34 /μl reached was similar in both groups (18,86 vs 15,4 p=0,1541). Plerixafor was associated with a superior collection efficiency (% of CD34 collected) (40,85 vs 60,91% p=0,007), but this can be explained by a greater use of central venous catheters for collection in this group (70 vs 95,1% p = 0,0275). Data stratified by initial diagnosis and CD34 level on the planned day of PBPC collection (&lt;10 c/μl versus [10c/μl - 20c /μl [) showed the same tendency. The collection duration was not significantly reduced in the plerixafor group, but there was a trend for a shorter mean duration of 22 minutes also explained by a greater use of central venous catheters in this group. The preplanned subgroups analyses have shown the same trend when stratified by diagnosis, with a reduction of 53 minutes in the multiple myeloma subgroup with a greater total CFU-GEM / kg per collect (46,35 vs 70,55 p=0,0163). Conclusion The use of plerixafor at HEJ did not improve significantly the proportion of poor mobilizers reaching an adequate PBPC graft and did not improve transplant outcomes compared to a historical control. Better strategies are needed to improve care for true poor mobilizers. The optimal use of plerixafor needs to be further studied. Table. Disclosures Blais-Normandin: Sanofi: Other: unrestricted research grant. Laroche:Sanofi: Other: unrestricted research grant.

Dissecting Heterogeneity of Tumor Cells and Their Microenvironment in Refractory Multiple Myeloma

Introduction: Despite significant improvements in therapy during the last decade, most multiple myeloma (MM) patients develop refractory disease over time. Treatment of refractory MM is a major challenge, likely due to the still poorly characterized inter- and intratumor heterogeneity at this stage of the disease, and the complex interplay of MM cells with the microenvironment (ME). In particular, there is an urgent need to unravel how these features of MM are linked to molecular mechanisms of drug resistance. Methods: We resolved the cellular composition, underlying transcriptional inter- and intra-patient heterogeneity and molecular treatment response of relapsed/refractory MM by single cell RNA sequencing (scRNA-seq). Using droplet-based microfluidics, ~230,000 single cell gene expression profiles from bone marrow (BM) aspirates of 21 patients sorted into CD138+and CD138- fractions were acquired, allowing for a comprehensive analysis of both MM cells as well as their ME. Patients had a median of 4 prior lines of therapy including both a proteasome inhibitor and an immunomodulator and were refractory to their immediate prior line of therapy at time of sampling. In addition, paired samples before either pomalidomide- or carfilzomib-based therapies were analyzed for 16/21 patients. Genomic aberrations in individual patients were mapped by interphase fluorescence in situ hybridization. Cells were clustered and CD138+ MM subtypes as well as immune cell-types of the ME were identified from their single cell transcriptomes and a copy number variation (CNV) analysis. As a reference for non-malignant cells and to construct a developmental B-cell trajectory the Human Cell Atlas BM scRNA-seq reference dataset was used. To characterize interactions of MM cells with their ME, the correlated expression of ligand-receptor pairs was exploited. Results: The analysis of inter- and intra-tumor heterogeneity of molecular MM subgroups revealed distinct transcriptome signatures with contributions that could be assigned to differences in heavy and light chain immunoglobulin expression as well as known genomic alterations, including t(11;14), t(4;14) and hyperdiploidy. MM cells from individual patients largely maintained a plasma cell specific gene expression profile but a partial loss of plasma cell identity was detected based on mapping to a developmental B-cell trajectory. It was characterized by the upregulation of subgroup transcriptome signatures associated with earlier stages of B-cell development in almost 50% of patients, such as a pre-B or mature B cell-like phenotype. Within individual samples, subclonal MM cell populations with specific gene expression programs were resolved based on the CNV analysis and included those characterized by expression of the immune-activator CD27 and the modulator of WNT signaling FRZB. The analysis of longitudinally collected samples revealed both changes in the cell subtype cluster structure as well as drug-specific adaptation of gene expression programs in distinct subpopulations persisting or emerging at relapse. These profile changes were characterized by e.g. downregulation of Myc target genes upon pomalidomide treatment or induction of heat shock proteins under carfilzomib. Within the ME of refractory MM patients, we observed that the fraction of B cells and CD4+ T cells was strongly reduced while CD14+ and CD16+ monocytes as well as dendritic cells expanded. Notably, the immune checkpoint protein PD-1H (aka VISTA) that inhibits T cell activation was highly expressed in cell types from the myeloid compartment in contrast to healthy donors. Further, a ligand-receptor analysis revealed that MM cells displayed the strongest interactions with monocytes, which were mediated by MIF, BAFF and other cytokines. Conclusions: Our study demonstrates the value of scRNA-seq analysis for identifying crucial transcriptome features that classify refractory MM subtypes and their evolution in response to treatment including regulation of drug resistance associated signaling pathways. Our data suggest that refractory MM cells shape the myeloid compartment in the BM to generate an immune suppressive ME. Understanding the evolution of MM cell heterogeneity and the bone marrow milieu in refractory disease will lead to novel treatment approaches and eventually improve patient outcome. Disclosures Müller-Tidow: MSD: Membership on an entity's Board of Directors or advisory committees. Goldschmidt:John-Hopkins University: Research Funding; Molecular Partners: Research Funding; Amgen: Consultancy, Research Funding; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; MSD: Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Dietmar-Hopp-Stiftung: Research Funding; Janssen: Consultancy, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; John-Hopkins University: Research Funding; Chugai: Honoraria, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive Biotechnology: Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Mundipharma: Research Funding.

Distinct Chromatin Accessibility Changes, Aberrant Transcription Factor Networks Combined with Novel Oncogenic Enhancers Characterise Myeloma-Initiating Genetic Events

In multiple myeloma (MM), a malignancy of the bone marrow plasma cells (BMPC), hyperdiploidy (HY) and oncogene over-expression via chromosomal translocation [including CCND1- t(11;14), MAF- t(14;16), MMSET-t(4;14)] are the primary myeloma initiating events (MIE) that drive distinct transcriptional programs. These are further shaped by secondary SNV and CNV events. This genetic heterogeneity converges, in most cases, to a functionally dichotomous state of CCND1 or CCND2 overexpression. The molecular mechanisms underlying each of the distinct myelomagenic transcriptomes and the CCND1 vs CCND2 dichotomy have not been defined. To address these questions, we obtained highly purified BMPC from 3 healthy donors and 30 MM patients (HY: 15; CCND1: 4; MMSET: 5; MAF: 2; other: 4), either at diagnosis or relapse, and mapped their chromatin accessibility and transcriptome profiles by ATAC-seq and RNA-seq, respectively. In total, we obtained ~300K regions with accessible chromatin in either MM or normal PC. Overall chromatin accessibility increased in myeloma compared to normal PC, particularly in MAF- and MMSET-translocated subtypes. Analysis of combined ATAC-seq/RNA-seq by Multi-Omics Factor Analysis (MOFA) resulted in a clearer samples distinction than either ATAC-seq or RNA-seq alone, with altered chromatin accessibility accounting for more of the variance than expression. Of the top five identified factors, the top two (one transcriptome driven, one accessibility driven) distinguished normal from MM samples, whilst two more separated MMSET, MAF and CCND1 subgroups. Ninety seven, 157, 256 and 348 overexpressed genes in the CCND1, HY, MMSET and MAF subgroups, respectively, were predicted to be regulated by differentially accessible enhancers. Twenty percent (165/858) of these genes were overexpressed in &gt;1 subgroup suggesting a process of chromatin accessibility-based convergence evolution. Enrichment analysis suggested direct or indirect involvement of Polycomb and chromatin remodellers; significant enrichment was also found for genes involved in neurogenesis. ATAC-seq footprinting predicted binding sites for 250 expressed transcription factors (TFs), 116 of which displayed higher binding frequency in myeloma than in normal PC and included both known (e.g., XBP1, RELA, IRF4, PRDM1) and potentially novel regulators of myeloma biology (e.g., CXXC1 and NFE2L1). The remaining 134 TF were predicted to be present in at least one MM subgroup, but absent in normal PC. Amongst them, as expected, MAF was active in the MMSET- and more so in the MAF-translocated subgroups. DepMap database analysis suggested myeloma cell dependency on 181/250 TF (CRISPR/Cas9 CERES score &lt; -0.1 in &gt;3/14 MMCL analysed). In dissecting the regulatory basis of CCND2 vs CCND1 dichotomy, one MOFA factor completely separated MAF from CCND1 samples, placing extreme opposite weights on the expression of CCND2 and CCND1 respectively. Interestingly, the same factor identified open-chromatin clusters upstream of CCND2 and linked them to its over-expression. These clusters were also open in the MMSET group and in CCND2-expressing HY samples. Conversely, no accessibility was detected in the CCND1 group, the CCND1-expressing HY samples or in normal PCs. Further, super-enhancer calling using the H3K27ac histone mark in MAF-translocated JJN3 cells identified the region of interest as a bona fide super-enhancer. Chromatin long range interactions, as assessed by Capture-HiC, demonstrated high frequency interactions of the CCND2 promoter with the constituent elements of the putative super-enhancer. Experimental validation using a CRISPR/Cas9i system confirmed the functional role of all 4 super-enhancer constituents tested in the regulation of CCND2 expression, while TF footprinting predicted MAF binding to the super-enhancer in MAF-translocated PC. In conclusion, we show that distinct oncogenic transcriptomes in MM are underpinned by extensive chromatin changes, accompanied by TF activity 're-wiring' that does not necessarily require transcriptional deregulation of the TF themselves. We identify novel, non-oncogene TF dependencies that suggest therapeutic opportunities in MM and we discover and characterise the critical super-enhancer that drives overexpression of the CCND2 oncogene in MM. Disclosures Auner: Amgen: Other: Consultancy and Research Funding; Takeda: Consultancy; Karyopharm: Consultancy. Hatjiharissi:Janssen: Honoraria. Caputo:GSK: Research Funding. Karadimitris:GSK: Research Funding.

Genome Wide Transcriptomic Analysis Identifies Dysregulated Splicing Factor Profile with Molecular and Functional Role in Multiple Myeloma

Alternative splicing (AS) is a critical post-transcriptional event, which affects the number of cellular processes. Aberrant splicing of some genes has been reported in multiple myeloma (MM). However, to date, whole-transcriptome-wide AS study has not been performed. We used deep RNA-sequencing data from 16 normal plasma cells (NPC) and 360 newly-diagnosed MM patients to describe the landscape of the alternative splicing events and the molecular mechanisms driving aberrant AS in MM. Global splicing analysis showed that mutually exclusive exon (MXE) (n=510) and Skipped Exon (SE) (n=417) are the most frequent splicing events in MM compared to NPC. Among these events, ~54% were observed in genes which are not differentially expressed between MM and NPC and 46% of the AS events (SE, MXE, retained intron, alternative 3'/5' sites) were observed in differentially expressed genes targeting 203 unique genes. AS affected RNA transcription regulation genes such as IKZF1, IKZF3, and key regulatory elements in MM including, IRF3, IRF4, or key transcription factors such as MEF2C, XPB1, STAT2, and ILF3. In general, AS targetted DNA replication, cell cycle, and apoptosis pathways. MM subgroups showed a heterogeneity for AS events. Monosomy 14, t(4;14), del1p and del17p had the highest number of unique (not observed in other subgroups) AS events compared to NPC.To understanding the molecular mechanisms driving aberrant alternate splicing we next investigated115 splicing factors (SF) in MM and associated them with AS events. We observed that ~40% of SF were dysregulated (dysregulated expression and/or copy number alteration) in MM compared to NPC, including SRSF, PCBP and RBM families. To understand the key binding regions, we have performed SF binding motif enrichment analysis around AS events and found that SRFS1, SRSF9, and PCB1 motifs to be enriched among the splicing events. Importantly, SRSF1 expression was linked with survival in two independent MM datasets.We therefore explored functional role of SRSF1 in MM with perturbation studies. While upregulation of SRSF1 expression significantly increased the cell growth and survival, conversely downregulation of SRSF1 inhibited the both. To dissect the mechanisms of SRSF1-mediated MM growth induction, we utilized SRSF1 mutants lacking either of the 2 RNA-recognition motifs or the serine/argine-rich C-terminal domain involved in protein-protein interactions, and recruitment of spliceosome components. We also utilized a C-terminal fusion of SRSF1 with the nuclear-retention signal of SRSF2 (NRS1 mutant), to force SRSF1 retention in the nucleus and assess the role of its nuclear versus cytoplasmic functions. These studies suggested that SRSF1-regulated AS effects MM cell proliferation. We surprisingly also found that even NRS1 mutant failed to promote MM growth, suggesting an important role of cytoplasmic SRSF1 in promoting MM cells proliferation.We next investigated alternative splicing pattern changes induced by SRSF1 knock down.When analyzing cellular functions of SRSF1-regulated splicing events, we found that SRSF1 knock down affect's genes in the RNA processing pathway as well as genes involved in cancer-related functions such as mTOR, E2F and MYC-related pathways. Splicing analysis was corroborated with immunoprecipitation (IP) followed by mass spectrometry (MS) analysis of T7-tagged SRSF1 MM cells.Finally, using genome wide chromatin and transcription landscape mapping techniques, we have found SRSF1 to be under the transcriptional control of oncogenic E2F1 in MM cells. Consistent with these findings, we observed greater in vitro loss of viability in a large panel of MM cell lines compared with PBMCs from healthy volunteers, following exposure to the splicing modulator pladeniolide. In summary, this study for the first time reports a detailed splicing landscape in myeloma and highlights the biological and clinical importance of alternative splicing events. Moreover, these results indicate a functional role and clinical significance of a gene involved in regulation of alternate splicing in MM, highlighting the need to further understand the splicing pattern in myeloma initiation and progression. Disclosures Anderson: Takeda: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau; Oncopep: Other: Scientific Founder; Sanofi-Aventis: Other: Advisory Board; Bristol-Myers Squibb: Other: Scientific Founder. Avet-Loiseau:takeda: Consultancy, Other: travel fees, lecture fees, Research Funding; celgene: Consultancy, Other: travel fees, lecture fees, Research Funding. Munshi:Adaptive: Consultancy; Abbvie: Consultancy; Takeda: Consultancy; Janssen: Consultancy; Oncopep: Consultancy; Amgen: Consultancy; Celgene: Consultancy.

The Landscape of Genome Wide Somatic Alterations Identifies a Good-Risk Group in Newly Diagnosed Multiple Myeloma

Multiple Myeloma (MM) is a plasma cells malignancy with number of recent therapeutic options that has improved outcomes with median survival now stretching beyond 8 years. There has been an intense search to identify genomic and laboratory correlates of outcome for high risk patients. However, a subgroup of patients have a long survival but genomic segmentation of this important group which can be potentially cured has not been identified. We here described first such attempt at identifying a subset of patients with long survival. We have analyzed data from 205 newly-diagnosed uniformly-treated MM patients using both deep whole genome (WGS) (80x) and whole transcriptome sequencing (RNAseq). Median number of SNVs, small insertion and deletion per megabase were 2.18 [0.49 - 14.52], 0.077 [0.024 - 0.17] and 0.12 [0.03 - 0.26] respectively. MM subgroups defined by FISH or copy number alterations (CNAs) had significantly different mutational load (Kruskal-Wallis p-value = 0.003). In general, Hyperdiploid MM (HMM) patients had lower SNV load compared to other subgroups and t(14;16) had the highest mutational load per megabase (Dunn test FDR &lt; 0.25). These subgroups also showed significant differences for mutational process utilization. Mutational processes associated spontaneous deamination of 5-methylcytosine to thymine was significantly high in HMM, APOBEC activity was very strong in t(14;16) MM and DNA repair was significantly different in t(6;14), del17p and t(11;14). Importantly, the mutations associated with clonal cell population and thus in early phases of MM cell progression were driven by spontaneous or enzymatic deamination (Signature 1), somatic hypermutation in lymphoid cells (Signature 9) and Signature 17 (ANOVA p value &lt; 1e-16) and surprisingly APOBEC activity was constant among the clones (ANOVA p value &gt; 0.05). However, mutations associated with homologous recombination (HR) and nucleotide excision repair (NER) activity were significantly enriched in the subclonal mutations (ANOVA p value &lt; 1e-16) suggesting their role in later stages of MM progression. Based on this information, we next calculated the homologous recombination repair defects using copy number alterations from WGS data. We identified that HR score generated using WGS copy number information predicted outcome in newly diagnosed myeloma. Further analysis of this data identified that newly diagnosed MM patients with hyperdiploid MM (HMM) and no HR- repair deficiency have superior outcome with 6 year overall survival (OS) probability for this of 100% in IFM/DFCI 2009 cohort (Logrank test p value = 0.0012). We next validated this finding using MMRF CoMMpass dataset and we confirmed 6-yr OS probability of 95% (Logrank test p value = 0.0016) in this independent dataset (Figure 1). We further investigated RNAseq data between these genomically defined groups and identified that chromosome and telomere maintenance pathways (FDR &lt; 0.01) and low bone disease associated genes described by Zhan et al. (FDR = 0.004) were up regulated in low-risk group. Finally, patients who were able to maintain HR, had lower mutation rate for TP53 (0% vs 9%, FDR &lt; 0.05), CSMD1 (0% vs 6%, FDR &lt; 0.05), FAT3/FAT4 mutations (1.7% vs 15%, FDR &lt; 0.05), however surprisingly higher mutation rate for NRAS (42% vs 14%, p value &lt; 0.001). In addition, DNA damage associated processes predicted by SNVs trinucleotides were significantly lower in the low-risk group (12% vs. 20%, p value &lt; 1e-05) providing further support to this data. In conclusion, we report a detailed genomic profile using deep DNA and RNA sequencing and identify a genomically-defined sub group that is predicted to have a long survival. This study also identifies the role of HR in myeloma with potential for its translational application in both prognosis as well as therapy. Figure 1 Disclosures Richardson: Janssen: Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees. Moreau:Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria. Thakurta:Celgene: Employment, Equity Ownership. Anderson:Sanofi-Aventis: Other: Advisory Board; Bristol-Myers Squibb: Other: Scientific Founder; Oncopep: Other: Scientific Founder; Amgen: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau. Avet-Loiseau:celgene: Consultancy, Other: travel fees, lecture fees, Research Funding; takeda: Consultancy, Other: travel fees, lecture fees, Research Funding. Munshi:Takeda: Consultancy; Oncopep: Consultancy; Adaptive: Consultancy; Amgen: Consultancy; Celgene: Consultancy; Abbvie: Consultancy; Janssen: Consultancy.

WGS and RNA-Seq Is Superior to Conventional Diagnostic Tests in Multiple Myeloma: Ready for Prime Time?

Background: The diagnosis and risk stratification of multiple myeloma (MM) is based on clinical and cytogenetic tests. Magnetic CD138 enrichment followed by interphase FISH is the gold standard to identify prognostic translocations and copy number alterations. Gene expression (GEP) studies show that MM might consist of various subgroups with distinct clinical outcomes (Zhan et al., Blood 2006). Whole genome sequencing (WGS) and targeted sequencing studies have further shed light onto recurrent mutations in MM and clinical implications are being derived (Lohr et al., Cancer Cell 2014). We set up a single workflow to analyze MM by WGS and RNA-Seq to evaluate whether this diagnostic workup is superior to conventional diagnostic testing.Methods: The cohort comprised 211 patients (pts) diagnosed with MM at our institution from 2011 to 2017. For all pts FISH and WGS was performed on CD138 enriched cells. For WGS 150bp paired-end sequences where generated on Illumina HiseqX and NovaSeq 6000 (Illumina, San Diego, CA). A mixture genomic DNA from multiple anonymous donors was used as normal controls. To remove potential germline variants, each variant was queried against the gnomAD database, variants with global population frequencies >1% where excluded. 47 genes recurrently mutated in MM were selected for evaluation (Kortüm et. al., Blood 2016). Copy number alterations (CNAs) were called using GATK4 and structural variations (SVs) were called using MANTA accounting for missing matched-normal samples. For transcriptome analysis total RNA was sequenced and the resulting estimated gene counts were pre-processed and normalized, applying trimmed mean of M-values normalization method.Results: WGS allowed us to detect 98/102 (96%) translocations that had previously been identified by FISH. Specifically we confirmed 24/24 of t(4;14), 6/7 of t(6;14), 11/12 of t(8;14), 51/53 of t(11;14) and 6/6 of t(14;16) cases by WGS. Moreover, by conventional FISH 12 pts had an IGH (n=4) or MYC (n=8) translocation with an unknown partner chromosome. We identified all 12 translocations by WGS. By WGS we also identified 679/740 (92 %) copy number alterations (CNA) detected by FISH. In detail these were 100/103 del(13q), 17/21 del(17p), 10/10 del(1p) and 79/87 +1q. Concordance rates for trisomies 3, 5, 9, 11, 15 and 19 were 80/91, 75/87, 92/97, 87/97, 53/55 and 86/92, respectively.Zhan et al. defined 7 MM subgroups (CD-1, CD-2, HY, MF, MS, LB, PR) based on GEP. 4 groups (CD-1/CD-2, MF, MS) were genetically defined by recurrent translocations and 1 by hyperploidy (HY). They used 700 probes to separate the groups of which 400 transcripts were recovered in our RNA-Seq analysis (GEPSeq). Supervised clustering grouped all 211 pts at the following frequencies: CD-1 (5%), CD-2 (25%), HY (30%), MF (5%), MS (11%), LB (14%), (PR 10%). 56/62 (90%) of pts that were allocated to CD-1/CD-2 had the characteristic translocation (t(11;14) or t(6;14)), while 23/24 (92%) of pts and 5/10 (50%) pts in GEPSeq group MS and MF had the respective t(4;14) or t(14;16). GEP allocates pts with hyperdiploidy to group HY and 51/63 (81%) pts in HY had a hyperdiploid karyotype by FISH. We specifically queried the WGS data for patients with discrepant FISH and GEPSeq results: WGS identified hyperdiploidy in 10/12 patients that were allocated to HY and could not be assigned by FISH due to insufficient material for complete testing, resulting in a 97% final concordance of GEPSeq and karyotype. One patient in group MS without FISH data for t(4;14) could be confirmed by WGS as harbouring the translocation (concordance 100%). Interestingly in 5/5 patients that were allocated to the MF group by GEPSeq 2 had an IGH-MYC or IGH-MYCN rearrangement respectively and 2 had another IGH rearrangement involving chromosome 8q. By WGS the most frequently mutated (mut) genes were KRAS (26%), NRAS (23 %), TP53 (8%), BRAF (4%) and ATM (2%), which is in line with published data (Lohr 2014). NRASmut was significantly associated with GEPSeq groups CD-2 and HY (p=0.001) and ATMmut with MF, MS and PR (p=0.047).Conclusion: RNA-Seq and WGS prove highly valuable in differentiating genetically distinct MM subgroups. The simultaneous analysis of gene mutations might have future implications for study design and selecting treatment options. A single workflow based on WGS and RNA-Seq provides a comprehensive genetic analysis in MM, is feasible and might substitute conventional diagnostic testing in the near future. DisclosuresHöllein:MLL Munich Leukemia Laboratory: Employment. Twardziok:MLL Munich Leukemia Laboratory: Employment. Walter:MLL Munich Leukemia Laboratory: Employment. Hutter:MLL Munich Leukemia Laboratory: Employment. Hernández:MLL Munich Leukemia Laboratory: Employment. Meggendorfer:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

Preclinical Validation Studies Support Causal Machine Learning Based Identification of Novel Drug Targets for High-Risk Multiple Myeloma

IntroductionRegardless of significant advances in the therapy of multiple myeloma (MM) there is still a lack of effective treatment options for patients with high-risk disease. In this context, we recently developed a network of high-risk disease based on more than 30 000 genomic and clinical variables from 645 patients of the CoMMpass dataset (Gruber et al., ASH 2016). Validation of these findings has been performed in the IFM/DFCI 2009 trial dataset (Furchtgott et al., ASH 2017). This comprehensive computational approach revealed a network of 17 genes driving high-risk (defined as progression or myeloma-related death within 18 months). Here, we performed preclinical validation of potential novel drug targets to confirm the utility of in silico guided target discovery in high-risk MM.MethodsTTK (CFI402257, BAY-1217389), PLK4 (CFI400945, Centrinone), MELK (OTSSP167) and CDK1 (CPG71514) inhibitors were studied in a panel of human MM cell lines (n=11) for their activity in cell viability, cell growth, cell cycle, apoptosis, colony formation, drug combination and co-culture experiments. PKMYT1, TTK and PLK4 were targeted with doxycycline-inducible shRNAs. Analysis of gene expression (GEP) data (GSE24080) was used to link candidate genes to certain MM subgroups.ResultsThe network of 17 genes driving high-risk disease contained eight kinases that serve as attractive drug targets (AURKA, NEK2, CDK1, BUB1B, MELK, TTK, PKMYT1, and PLK4), all of them involved in cell cycle regulation. Accordingly, expression levels of all kinases (except PKMYT1) were enriched in the GEP-defined proliferation associated subgroup of MM and thus linked to poor outcome. To study the interconnectedness of the individual network genes we first investigated the impact of previously reported CDK1 and MELK inhibitors on other network members. This demonstrated rapid loss of CDK1, NEK2, MELK, PKMYT1 and FOXM1 protein levels.We then selected TTK and PLK4 as putative novel MM targets with available inhibitors undergoing clinical testing in solid tumors. Protein and mRNA expression of both genes was confirmed in all MM cell lines. Two selective compounds per gene were used for preclinical studies. All four inhibitors significantly reduced MM cell viability and single dose IC70 treatment impaired cell growth up to 10 days (60-98% reduction, P<0.01). This growth inhibitory effect was confirmed with inducible shRNAs. Mechanistically, growth impairment was linked to G2M cell cycle arrest followed by the accumulation of polyploid cells (15-90% of cells 72h post treatment) which is in line with the role of both genes in chromosome segregation. The formation of aberrant mitoses led to the induction of apoptosis 3-5 days post treatment (≤20% viable cells at day 5 post treatment with 3/4 inhibitors) and was accompanied by the presence of active caspase 3 and cleaved PARP. Importantly, the activity of these drugs persisted in the presence of BMSCs and showed potent activity in colony formation assays (DMSO: 168±15 and 131±57, BAY-1217389: 39±29 and 41±3, CFI-400945: 19±26 and 30±6 colonies in KMS12BM and OPM2 cells at day 14, P<0.05). Drug combination studies pointed to favorable activity in combination with dexamethasone and lenalidomide. Furthermore, confirmatory TTK knockdown with two independent shRNAs sensitized MM cells to dexamethasone.Finally, PKMYT1 was chosen as putative target based on its role as major driver of high-risk in our model. We transduced MM cells with three doxycycline-inducible PKMYT1-targeting shRNAs and observed an impressive impact on myeloma cell growth upon doxycycline induction compared to non-targeting control shRNA (up to 85% reduction at day 10, P<0.01). Furthermore, PKMYT1 knockdown led to the induction of apoptosis in all MM cell lines tested. Based on these encouraging results we currently perform in-depth in silico and in vitro analyses of the underlying PKMYT1 signaling network. Detailed results of these sub-studies will be presented at the meeting.ConclusionsOur results confirm the utility of computational based modelling of high-risk disease. This strategy not only revealed a genetic network closely associated to adverse prognosis, but also enabled the identification of so far unnoticed drug targets. Importantly, inhibitors of TTK and PLK4 are already in clinical testing and thus enable rapid clinical translation of our findings to MM patients in need of alternative therapeutic options. DisclosuresGruber:GNS Healthcare: Employment. Furchtgott:GNS Healthcare: Employment. Raut:GNS Healthcare: Employment. Wuest:GNS Healthcare: Employment. Runge:GNS Healthcare: Employment. Khalil:GNS Healthcare: Employment. Munshi:OncoPep: Other: Board of director. Hayete:GNS Healthcare: Employment. Ludwig:Amgen: Research Funding, Speakers Bureau; BMS: Speakers Bureau; Takeda: Research Funding, Speakers Bureau; Cilag-Janssen: Speakers Bureau; Celgene: Speakers Bureau.

Identification of a First-in-Class SETD2 Inhibitor That Shows Potent and Selective Anti-Proliferative Activity in t(4;14) Multiple Myeloma: T(4;14) Multiple Myeloma Cells Are Dependent on Both H3K36 Di and Tri-Methylation

t(4;14) chromosome translocations are found in 15% of newly diagnosed multiple myeloma (MM) cases and are associated with high risk. MM cells with t(4;14) over-express the histone methyltransferase (HMT), WHSC1/MMSET/NSD2, which leads to deregulation of gene expression due to increased di-methylation of Histone H3 at lysine 36 (H3K36me2). This activity has been shown to be essential for the survival of t(4;14) MM cells. In addition to WHSC1, another HMT, SETD2, has been shown to methylate H3K36. SETD2 is the only known enzyme capable of tri-methylation of H3K36 and has been reported to play a role in transcriptional elongation and alternative splicing. CRISPR pooled screening has shown that SETD2 activity is required for viability of a variety of cancer cell lines. This led Epizyme to develop small molecule inhibitors of SETD2 enzyme activity in order to understand the role of SETD2 in tumorigenesis. Through our drug discovery efforts, we identified EPZ-040414, a potent and selective inhibitor of SETD2 with low nM cell biochemical activity and broad selectivity against a panel of other HMTs. The proposed role of SETD2 in H3K36 methylation led us to test a panel of MM cells, including 6 t(4;14) cell lines with EPZ-040414. Inhibition of SETD2 resulted in reduced global tri-methylation of H3K36 in t(4;14) bearing MM cell lines. In contrast, there was no effect on global di-methyl H3K36 levels, indicating that WHSC1 activity is not affected by SETD2 inhibition. Moreover, 5/6 t(4;14) MM cell lines showed a cytotoxic response to treatment with EPZ-040414 with IC50s ranging between 60 and 200 nM, while all non-t(4;14) MM cell lines showed limited responses between 1 and 8 μM. Moreover, screening of a 280 cancer cell line panel with a SETD2 inhibitor showed minimal anti-proliferative activity in most cell lines tested. These findings show that t(4;14) MM cell lines require SETD2 activity for survival, suggesting that SETD2 inhibitors are strong candidates for the treatment of this high risk subgroup of MM. Efforts to further understand the interaction between SETD2 and WHSC1 in the molecular pathogenesis of t(4;14) myeloma will be presented. The current chemical series represented by EPZ-040414 is potent, selective, orally available, and currently under further evaluation for its therapeutic potential. [Display omitted] DisclosuresThomenius:Epizyme Inc.: Employment, Equity Ownership. Totman:Epizyme Inc.: Employment, Equity Ownership. Cosmopoulos:Epizyme Inc.: Employment, Equity Ownership. Brach:Epizyme Inc.: Employment, Equity Ownership. Ci:Epizyme Inc.: Employment, Equity Ownership. Farrow:Epizyme Inc.: Employment, Equity Ownership. Smith:Epizyme Inc.: Employment, Equity Ownership. Chesworth:Epizyme Inc.: Employment, Equity Ownership. Duncan:Epizyme Inc.: Employment, Equity Ownership. Tang:Epizyme Inc.: Employment, Equity Ownership. Riera:Epizyme Inc.: Employment, Equity Ownership. Lampe:Epizyme Inc.: Employment, Equity Ownership.

Global 3D-Epigenetic Dysregulation of Cyclin D1 and D2 Actively Controls Their Expression Pattern in Multiple Myeloma

Introduction: Multiple myeloma (MM) is characterized by the over-expression of D-cyclin genes and the expression is tightly linked to cytogenetic subgroups. For instance, overexpression of CCND1 in the t(11;14) and CCND3 in the t(6;14) is direct through IgH super-enhancer translocation, and CCND2 overexpression in t(4;14), t(14;16) and t(14;20) indirectly, presumably as a result of transcription factor or epigenetic regulation. In hyperdiploid MM, CCND1 is highly expressed in patients with trisomy of chr.11 and CCND2 in those without trisomy 11. Here, we combine DNA methylation with CTCF or super-enhancers (SE) binding and global histone profile to describe a novel perspective of epigenetic regulation of CCND1/2 expression in MM.Methods: Newly diagnosed MM patient CD138 sorted bone marrow plasma cells (PCs), consisted of those with a t(14;16) (n=17), t(14;20) (n=7), t(4;14) (n=9), t(11;14) (n=10) and hyperdiploidy (n=19, separated into D1-HRD (n=12) or D2-HRD (n=7), and were compared to PCs from healthy donors (n=4). A reduced representation bisulfite sequencing was performed to identify differentially methylated regions (DMRs). Histone modifications were determined using ChIP-seq in reference to KMS11 cells for t(4;14), U266 for t(11;14), and MM.1S for the MAF group patients. Additionally, enrichment of SEs in MM1.S and CTCF in Delta47 cells were determined to assess the collaborative epigenetic impact on altered CCND1/2 expression (FDR<0.05) in MM.Results: In the t(4;14) subgroup, CCND2 DMRs (n=21) at the promoter expressed marginal differences (<5%) in methylation compared to control, but showed enrichment for SEs/CTCF-binding. In contrast, of 15 DMRs in the body of CCND2, 7 showed significant demethylation (mean differential methylation; MDM: 16%; p<0.01), compared to the control. We also observed enriched activating H3K27Ac marks at the promoter and H3K4me1 and H3K36me3 at the body of CCND2 in KMS11. The prevalence of demethylation in the body and interactions from activating histone marks or SE/CTCFs was consistent with 3-fold increase in the expression, compared to control (6.92). The other CCND2 over-expressing groups, t(14;16) and t(14;20), also showed demethylation across the body and over-expressed by 5.21-fold in t(14;16) and 4.72-fold in t(14;20). We observed enrichment of activating H2K27Ac, H3K4me3, H3K4me1 or H3K36me3 marks in both the promoter and body of CCND2 in MM.1S. Moreover, the D2-HRD subgroup showed hypomethylated body and subtly hypermethylated promoter (MDM: 2%; p<0.01) with 8.82 fold increased expression of CCND2 than control.CCND1 showed a reducing hypomethylation gradient (MDM: 12% to 0.05%, p<0.01) across 24 DMRs, spanning from 5 kb upstream of the transcription start site (TSS), with an exception of a subtle increase in methylation across 6 DMRs (MDM>1%, p<0.01), spanning from 0.79-2.24 kb downstream of the TSS, compared to control. The rest of body contained 19 DMRs that were significantly hypomethylated. We also observed enrichment of H3K27Ac and H3K4me3 at the promoter and body of CCND1 in U266 cells. CCND1 hypomethylation from the promoter to exon 3 also coincides with strong signals from enhancer or CTCF sites, which was consistent with 7.41-fold increase in expression in the subgroup, compared to control (4.41). CCND1 was also upregulated by 4.07-fold in D1-HRD, however, unlike the t(11;14) samples the gene body was not exclusively hypomethylated.Conclusion: The disparities in CCND1/2 expression among MM subgroups are not the singular consequence from epigenetic events but broadly depends on other genotypic features such as alterations in copy number or chromosome structure. For instance, CCND1 DNA-demethylation does not always correlate with expression in t(4;14), D2-HRD, or the MAF cluster, implying that the predominant effect is through juxtaposition of the IgH-SE next to CCND1 in the t(11;14). In contrast, suppression of CCND2 expression in t(11;14), compared to t(4;14)/MAF may be explained by the enrichment of inactivating H3K27me3 marks at the body of CCND2 in the U266 cells. In summary, DNA hypomethylation at promoters or gene bodies facilitate the formation of open chromatin to enhance interactions with SE/CTCF or histones to constitute a three-dimensional epigenetic regulatory network, which potentially influence gene expression and identify novel variants in signaling pathways in MM, as evidenced here with CCND1/2. DisclosuresRoy Choudhury:University of Arkansas for Medical Sciences: Employment, Research Funding. Davies:MMRF: Honoraria; TRM Oncology: Honoraria; ASH: Honoraria; Abbvie: Consultancy; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria. Morgan:Janssen: Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria.

Activated Ral and Mutated RAS Are Independent Drivers of Multiple Myeloma Cell Survival.

IntroductionRAS-associated pathways are promising therapeutic targets in RAS-driven tumors because oncogenic RAS itself is not druggable. Alongside the pathways via PI3K/AKT and RAF/MAPK, the small GTPase RAL is considered to represent a third route for oncogenic RAS signaling, which mediates malignant transformation and tumor cell survival. We performed shRNA-mediated knockdown studies in multiple myeloma (MM) cells to investigate the functional role of RAL activity and to analyze the putative functional link between oncogenic RAS and RAL. Moreover, we used screening approaches to identify possible RAL effectors and interacting partners.MethodsFirst, we analyzed expression of the isoforms RALA and RALB in bone marrow biopsies (n=24) and in CD138+ selected primary MM cell samples (n=10) by immunohistochemistry and Western blotting, respectively. Next, we generated two isoform-specific shRNA expression vectors for each of the RAL isoforms to perform RNAi-mediated RAL knockdown and to analyze the functional consequences of RAL abrogation. Experiments were also carried out in combination with clinical anti-myeloma drugs. Furthermore, we treated MM cells with a recently developed pharmacological RAL inhibitor. MM cell survival and apoptotic cells were measured by flow cytometry with annexin V/propidium iodide staining. Changes in RAF/MAPK, PI3K/AKT or RAL pathway activation were detected by Western analysis. We then combined RAL pulldown and knockdown of mutated RAS to investigate the functional link between RAL activation and oncogenic RAS signaling. In addition, we compared RAS- and RAL-mediated gene expression profiles by RNA sequencing. Last, we used mass spectrometry to identify potential RAL effectors and interaction partners.ResultsRAL protein was detected in all MM cells tested, with RALA showing ubiquitously strong expression and RALB showing more heterogeneous stainings. In contrast, RALA and RALB expression was weak or absent in MGUS or normal plasma cells. MM cell survival was strongly impaired by shRNA-mediated RALA or RALB knockdown, with cell survival rates of 25% or 40 % in L-363 cells and 32% or 52% in MM.1S cells, respectively. No cross-activation between RAL and PI3K/AKT or RAF/MAPK pathways could be detected in MM cell lines. Pharmacological RAL inhibition was achieved in an MM subgroup at concentrations of 20 µM. Combining RAL knockdown and treatment with carfilzomib, pomalidomide, or ixazomib led to enhanced cell death induction. Of note, knockdown of oncogenic RAS also strongly reduced MM cell survival, but did not change constitutive RAL activation as detected by pulldown assay. Moreover, RNA sequencing after RAS or RAL knockdown produced differential gene expression profiles (1473 KRAS-regulated genes versus 771 RALA-regulated genes, with an overlap of 235 genes), again suggesting that both targets represent distinct signaling pathways. Using mass spectrometry, we identified novel RAL interaction partners which are currently being evaluated.ConclusionOur data indicate that the RAL signaling pathway constitutes a promising therapeutic target in MM and mediates MM cell survival and apoptosis independently of oncogenic RAS. Clinical translation of novel pharmacological RAL inhibitors may therefore be a future therapeutic strategy to tackle MM. DisclosuresNo relevant conflicts of interest to declare.

Differential Effect of Upfront Intensification Treatment in Genetically Defined Myeloma Risk Groups - a Combined Analysis of ISS, Del17p and SKY92 Scores in the EMN-02/HOVON-95 MM Trial

Differential Effect of Upfront Intensification Treatment in Genetically Defined Myeloma Risk Groups - a Combined Analysis of ISS, Del17p and SKY92 Scores in the EMN-02/HOVON-95 MM Trial

Identification of LEM-14 inhibitor of the oncoprotein NSD2.

The NSD family (NSD1, NSD2/MMSET/WHSC1, and NSD3/WHSC1L1) are histone lysine methyltransferases (HMTases) essential for chromatin regulation. The NSDs are oncoproteins, drivers of a number of tumors and are considered important drug-targets but the lack of potent and selective inhibitors hampers further therapeutic development and limits exploration of their biology. In particular, MMSET/NSD2 selective inhibition is being pursued for therapeutic interventions against multiple myeloma (MM) cases, especially in multiple myeloma t(4;14)(p16.3;q32) translocation that is associated with a significantly worse prognosis than other MM subgroups. Multiple myeloma is the second most common hematological malignancy, after non-Hodgkin lymphoma and remains an incurable malignancy. Here we report the discovery of LEM-14, an NSD2 specific inhibitor with an invitro IC50 of 132 μM and that is inactive against the closely related NSD1 and NSD3. LEM-14-1189, a LEM-14 derivative, differentially inhibits the NSDs with invitro IC50 of 418 μM (NSD1), IC50 of 111 μM (NSD2) and IC50 of 60 μM (NSD3). We propose LEM-14 and derivative LEM-14-1189 as tools for studying the biology of the NSDs and constitute meaningful steps toward potent NSDs therapeutic inhibitors.

Aurora kinase and FGFR3 inhibition results in significant apoptosis in molecular subgroups of multiple myeloma

Aberrant expression of proteins involved in cell division is a constant feature in multiple myeloma (MM), especially in high-risk disease. Increasingly, therapy of myeloma is moving towards individualization based on underlying genetic abnormalities. Aurora kinases are important mediators of cell cycle and are up regulated in MM. Functional loss of Aurora kinases results in genetic instability and dysregulated division leading to cellular aneuploidy and growth arrest. We investigated the role of Aurora kinase inhibition in MM, using a small molecule inhibitor A1014907. Low nanomolar A1014907 concentrations induced aneuploidy in MM cell lines independent of underlying cytogenetic abnormalities by inhibiting Aurora Kinases. However, A1014907 induced more pronounced and dose dependent apoptosis in cell lines with t(4;14) translocation. Translocation t(4;14) is observed in about 15% of patients with MM leading to constitutive activation of FGFR3 in two-thirds of these patients. Further investigation of the mechanism of action of A1014907 revealed potent FGFR3 pathway inhibition only in the sensitive cell lines. Thus, our results show that aurora kinase inhibition causes cell cycle arrest and aneuploidy with minimal apoptosis whereas inhibiting both aurora kinase and FGFR3 activity induced potent apoptosis in MM cells. These results support clinical evaluation of A1014907 in MM patients with t(4;14) translocation and/or FGFR3 expression.

Abstract 5324: Intragenic DNA-hypomethylation promotes overexpression of ITGB7 in MF subgroup of multiple myeloma

Abstract Integrin-β7 is part of an extensive family of glycoproteins and is overexpressed in the MF subgroups in Multiple Myeloma (MM), contributing to drug resistance and poor survival. ITGB7 promotes adhesion and proliferation of myeloma cells in bone-marrow stroma by supplementing growth factors like VEGF. Here, we investigate the possible epigenetic mechanism of ITGB7 overexpression in the MF subgroup, comprising of t(14;16) and t(14;20) myeloma. Newly diagnosed MM (NDMM) patient bone marrow aspirates underwent CD138 cell selection to enrich tumor cells to &amp;gt;98%. Samples consisted of those with a t(14;16) (n=17), t(14;20) (n=7), t(4;14) (n=9), t(11;14) (n=10) and hyperdiploidy (n=19, separated into D1 (n=12) or D2 (n=7 subgroups). NDMM patient samples were compared to plasma cells isolated from age-matched healthy donors (n=4), to determine differential changes in epitranscripts. We performed unbiased genome-wide reduced representation bisulfite sequencing (RRBS) to identify differentially methylated regions (DMRs) in CpG islands, which were validated by Infinium MethylationEPIC arrays (Illumina) in conjunction with gene expression array data (U133 Plus 2.0, Affymetrix) to determine the epitranscriptomic profile in all samples. RRBS was performed using 75 bp reads to a minimum of 20 M reads per sample. Data from MM cells at the Blueprint consortium were also used for annotation of epigenetic marks. Using the RRBS data we identified 26 hypomethylated, overexpressed genes in the MF group samples, which were not present in the other subgroups. In comparison, only 1 gene, FUT7, was hypermethylated and down-regulated in the MF cluster. Most interestingly, we identified ITGB7 amongst the hypomethylated, overexpressed genes. With an in-depth analysis we identified 4 significant (p&amp;lt;0.05) DMRs across intragenic regions of ITGB7, within a 2.5 kb region. Mean methylation across the DMRs reduced from 58% to 22% (p&amp;lt;0.01) in t(14;16) and 39% (p=0.02) in t(14;20) with concomitant overexpression of ITGB7 in the t(14;16), 19.5-fold increase, and the t(14;20), 23.4-fold increase, subgroups. These 4 DMRs belong to CpG islands, annotated to be the part of possible intragenic enhancer site with promoter like activity, and enriched for open chromatin structures. The DMRs also align with the hotspot of H3K4me1 marks and a putative binding site of activating transcription factors such as AP1/2 or Sp1. This suggests that the identified DMRs could be within the enhancer that regulates ITGB7 overexpression through DNA-hypomethylation. ITGB7 is a known oncogenic factor in high-risk MM, contributing to cell adhesion, migration and homing. Here we show using combined DNA methylation and expression data that ITGB7 is regulated through hypomethylation of the an enhancer region in the MF subgroup in MM. Citation Format: Samrat Roy Choudhury, Cody Ashby, Ruslana Tytarenko, Yan Wang, Purvi H. Patel, Aneta Mikulasova, Michael Bauer, Shayu Deshpande, Faith E. Davies, Gareth J. Morgan, Brian A. Walker. Intragenic DNA-hypomethylation promotes overexpression of ITGB7 in MF subgroup of multiple myeloma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5324.

Logic programming reveals alteration of key transcription factors in multiple myeloma

Innovative approaches combining regulatory networks (RN) and genomic data are needed to extract biological information for a better understanding of diseases, such as cancer, by improving the identification of entities and thereby leading to potential new therapeutic avenues. In this study, we confronted an automatically generated RN with gene expression profiles (GEP) from a cohort of multiple myeloma (MM) patients and normal individuals using global reasoning on the RN causality to identify key-nodes. We modeled each patient by his or her GEP, the RN and the possible automatically detected repairs needed to establish a coherent flow of the information that explains the logic of the GEP. These repairs could represent cancer mutations leading to GEP variability. With this reasoning, unmeasured protein states can be inferred, and we can simulate the impact of a protein perturbation on the RN behavior to identify therapeutic targets. We showed that JUN/FOS and FOXM1 activities are altered in almost all MM patients and identified two survival markers for MM patients. Our results suggest that JUN/FOS-activation has a strong impact on the RN in view of the whole GEP, whereas FOXM1-activation could be an interesting way to perturb an MM subgroup identified by our method.

Prediction of outcome in newly diagnosed myeloma: a meta-analysis of the molecular profiles of 1905 trial patients

Robust establishment of survival in multiple myeloma (MM) and its relationship to recurrent genetic aberrations is required as outcomes are variable despite apparent similar staging. We assayed copy number alterations (CNA) and translocations in 1036 patients from the NCRI Myeloma XI trial and linked these to overall survival (OS) and progression-free survival. Through a meta-anlysis of these data with data from MRC Myeloma IX trial, totalling 1905 newly diagnosed MM patients (NDMM), we confirm the association of t(4;14), t(14;16), t(14;20), del(17p) and gain(1q21) with poor prognosis with hazard ratios (HRs) for OS of 1.60 (P=4.77 × 10−7), 1.74 (P=0.0005), 1.90 (P=0.0089), 2.10 (P=8.86 × 10−14) and 1.68 (P=2.18 × 10−14), respectively. Patients with ‘double-hit’ defined by co-occurrence of at least two adverse lesions have an especially poor prognosis with HRs for OS of 2.67 (P=8.13 × 10−27) for all patients and 3.19 (P=1.23 × 10−18) for intensively treated patients. Using comprehensive CNA and translocation profiling in Myeloma XI we also demonstrate a strong association between t(4;14) and BIRC2/BIRC3 deletion (P=8.7 × 10−15), including homozygous deletion. Finally, we define distinct sub-groups of hyperdiploid MM, with either gain(1q21) and CCND2 overexpression (P<0.0001) or gain(11q25) and CCND1 overexpression (P<0.0001). Profiling multiple genetic lesions can identify MM patients likely to relapse early allowing stratification of treatment.

Search for rare protein altering variants influencing susceptibility to multiple myeloma.

The genetic basis underlying the inherited risk of developing multiple myeloma (MM) is largely unknown. To examine the impact of rare protein altering variants on the risk of developing MM we analyzed high-coverage exome sequencing data on 513 MM cases and 1,569 healthy controls, performing both single variant and gene burden tests. We did not identify any recurrent coding low-frequency alleles (1–5%) with moderate effect that were statistically associated with MM. In a gene burden analysis we did however identify a promising relationship between variation in the marrow kinetochore microtubule stromal gene KIF18A, which plays a role in control mitotic chromosome positioning dynamics, and risk of MM (P =3.6×10−6). Further analysis showed KIF18A displays a distinct pattern of expression across molecular subgroups of MM as well as being associated with patient survival. Our results inform future study design and provide a resource for contextualizing the impact of candidate MM susceptibility genes.