Citations

Abstract Introduction: Multiple Myeloma (MM) is consistently preceded by pre-malignant asymptomatic monoclonal gammopathies (AMG). To date, our understanding of the pathogenesis of progression to MM remains incomplete. Genetic analyses of AMG cells compared to MM-derived plasma cells (PCs) have found few differences, suggesting that progression may be mediated in part by tumour-extrinsic mechanisms. To comprehensively examine the cellular and molecular complexities of MM pathogenesis, we performed an unbiased single cell RNA-sequencing (scRNA-seq) analysis of tumour cells as well as immune cells from the tumour microenvironment (TME) derived from transgenic mice transitioning from AMG to MM. Methods: We employed the Vk*MYC immune-competent mouse model of MM (C57BL/6/KaLwRij), which is a clinically and biologically faithful model of untreated disease that similarly progresses from AMG to MM with age. We established an age-based cohort of Vk*MYC mice to recapitulate a range of MM disease stages, generated single-cell suspensions from flushed bone marrow and subjected these cells to scRNA-seq profiling (10x Genomics). Results: Across 12 samples profiled to date, our scRNA-seq dataset contains 82,853 high-quality cells, expressing 17,922 genes. We employed dimensionality reduction and unsupervised graph-based clustering to visualize and group transcriptionally-similar cell populations, which revealed 42 clusters. Expression of known marker genes and computed correlation scores with bulk gene expression reference datasets enabled annotation of cell types, revealing both malignant cells and non-malignant immune cell populations. We first focused on single cell T/NK profiles in our data given the emerging utility of immune checkpoint inhibitors that target these populations. Although we did not observe numerical differences in the proportion of CD8+ T cells across disease stages, analysis of immune checkpoint receptor genes revealed increased expression of Pdcd1 (PD-1) and Lag3 in CD8+ T cells from mice with disease. Co-expression of LAG3 and PD-1 proteins was also confirmed using a Vk*MYC transplantable model, with a positive correlation between disease burden (%CD138+/B220- cells) and %PD1+LAG3+ CD8+ T cells by flow cytometry. Consistent with reports of PD-1 and LAG3 co-expression on non-functional exhausted T cells, CD8+ T cells from diseased mice demonstrated elevated T cell exhaustion scores in our scRNA-seq dataset. These observations suggest that T cell exhaustion may be mediated by multiple immune checkpoint receptors during disease evolution. Although combinatorial treatment with PD-1 and LAG3 antibodies failed to induce tumour regression in mice with established disease, the addition of cyclophosphamide (Cy) to these antibodies resulted in marked improvement in survival of the mice compared to Cy alone, presumably by promoting immunogenic cell death. Studies exploring the combination of LAG3 and PD-1 antibodies as a strategy to inhibit transition from AMG to MM in the Vk*MYC mice are ongoing and will be reported. We also performed subclustering analysis of 5,228 Sdc1+ (CD138) PCs in our scRNA-seq dataset revealing 11 distinct clusters, with evidence of inter- and intra-tumoural heterogeneity across all Vk*MYC mice. Differential gene expression analysis revealed a non-malignant PC (nPC) cluster as supported by lower Myc transgene and Ccnd2 expression. Moreover, this cluster was predominantly comprised of cells from age-matched control mice or mice with earlier disease. Single-cell chromosomal copy number analysis revealed loss of Chr5 in the majority of tumour cells from MM mice, but not in the nPC cluster. Loss of Chr5 was observed in tumor subclones from all AMG mice suggesting that it is an early and potentially unifying event in Vk*MYC mice during disease progression. Further, the data support the establishment of intratumoural heterogeneity early in disease evolution. Conclusions: Our approach of using scRNA-seq to characterize the pathogenesis of disease evolution in MM has enabled simultaneous measurement of intratumoural heterogeneity and immune cell phenotypes in the TME. In turn, this has provided insights into mechanisms that may contribute to transition from AMG to MM, including induction of T cell exhaustion and loss of mouse Chr5. Ongoing and future work aims to evaluate whether these mechanisms can be exploited therapeutically in pre-malignant AMG. Disclosures Sebag: Amgen Canada: Membership on an entity's Board of Directors or advisory committees; Janssen Inc.: Membership on an entity's Board of Directors or advisory committees; Celgene Canada: Membership on an entity's Board of Directors or advisory committees; Takeda Canada: Membership on an entity's Board of Directors or advisory committees. Pugh:Prosigna: Honoraria; N/A: Patents & Royalties: Hybrid-capture sequencing for determining immune cell clonality; N/A: Patents & Royalties: Combined hybrid-capture DNA sequencing for disease detection; Boehringer Ingelheim: Research Funding; Chrysalis Biomedical Advisors: Honoraria; Merck: Honoraria; DynaCare: Consultancy.

Abstract Monoclonal gammopathies, including multiple myeloma (MM), represent a group of plasma cell (PC) disorders that comprise of mostly incurable hematopoietic malignancies with an increasing incidence in the US. Previous epidemiological studies demonstrated a 2-3 fold higher incidence of monoclonal gammopathy of undetermined significance (MGUS) and a similarly higher incidence of MM along with a ~4-year younger age of onset among African Americans (AA) compared to European Americans (EAs) (Fonseca, Leukemia, 2017). This suggests a possible ancestral-associated genetic predisposition of AAs to the development of monoclonal gammopathies (Landgren, Blood, 2006). When access to care is equal, AAs have a better overall survival compared to EAs suggesting that AAs may have a genetic predisposition that renders them better responders to treatment or have more favorable cytogenetic subtypes of MM (Waxman, Blood, 2010). Previous efforts to understand this disparity have relied on self-reported race rather than genetic ancestry. We hypothesize that quantifying genetic ancestry is necessary to fully understand the genetic mechanisms of racial disparities of monoclonal gammopathies. We describe our study of 881 patients with monoclonal gammopathies who had undergone uniform testing to identify MM-specific cytogenetic abnormalities. DNA from the bone marrow samples was genotyped on the Precision Medicine Research Array. Biogeographical ancestry was assessed using the Geographic Population Structure Origins tool, which provides the ancestral breakdown of 36 admixture components for each individual representing different geographic regions and outputs admixture proportions corresponding to those ancestries (Elhaik, Nat Commun, 2014). We evaluated whether an increase in the percentage of African Ancestry altered the odds of any primary cytogenetic abnormality. We demonstrated that a 10% increase in the percentage of African ancestry was associated with a 6% increase in the odds of detecting either an t(11;14), t(14;16) or t(14;20) (odds ratio = 1.06, 95% CI: 1.02 - 1.11; p-value = 0.05). Although we observed an increase in the odds of each of the individual translocations with 10% increase in African ancestry, l t(11;14) (OR=1.03) t(14;16) (OR=1.11) and t(14;20) (OR=1.10), these three abnormalities were combined to achieve greater statistical power. The differences in cytogenetic abnormalities were most striking among individuals with ≥80.0% African (n=120) compared to individuals with <0.1% African ancestry (n=235). Using these cutoff values comparing the ≥80.0% and <0.1% African ancestry cohorts, there was a higher prevalence of t(11;14), t(14;16) and t(14;20) (51% vs. 33%, respectively, p-value=0.008) and a lower prevalence of trisomies (with or without IgH translocations) (48.3% vs. 61.3%, respectively, p-value=0.066). In addition, the ≥80% African ancestry cohort also displayed a slightly lower prevalence of monosomy 13/13q deletion compared to the cohort with <0.1% African ancestry (34.2% vs. 38.7%, respectively, p-value=0.021). Further, we observed a significantly higher prevalence in the proportion of females with monoclonal gammopathies among the ≥80% African ancestry cohort compared to the cohort with <0.1% African ancestry (56.7% vs. 42.1%, respectively, p-value=0.028). We complement our past studies that relied on self-reported race and characterized patients' demographic and uniformly collected cytogenetic data in relation to genetically defined African ancestry. We demonstrate the prevalence of having one of three specific subtypes (i.e., t(11;14), t(14;16), or t(14;20)) was significantly higher in those with highest (≥80%) compared to lowest (<0.1%) African ancestry demonstrating African ancestry is associated with a subtype distribution of MM that differs from non-African individuals. These differences were only revealed after analysis of individuals with the highest and lowest percentage of African ancestry. Since 38.3% of the individuals with ≥80% African ancestry have the favorable t(11;14) translocation (in comparison to 26.8% of <0.1% African individuals), this finding may explain improved survival with equal access to care. Understanding the genetic mechanisms of this disparity is a fundamental step to understanding differences in incidence and outcomes of patients with monoclonal gammopathies. Disclosures Elhaik: DNA Diagnostics Center: Consultancy. Baird:DNA Diagnostics Center: Employment. Cerhan:Jannsen: Other: Scientific Advisory Board; Nanostring: Research Funding; Celgene: Research Funding. Stewart:Amgen Inc., BMS, Celgene, Takeda, Roche, Seattle Genetics, Janssen, Ono: Consultancy; Amgen Inc., Celgene, Roche, Seattle Genetics: Research Funding. Dispenzieri:Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Kumar:Novartis: Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Research Funding.

Abstract Abstract 445 Background: Carfilzomib is a proteasome inhibitor that irreversibly binds its target and has a favorable toxicity profile that has shown significant activity in relapsed multiple myeloma (MM), leading to recent FDA accelerated approval. To achieve rapid and deep response in patients eligible for stem cell transplant, we combined carfilzomib with the regimen of cyclophosphamide-thalidomide-dexamethasone (CTD). We recently reported the results of the Phase I component of the trial (in which no MTD was reached) followed by the initial Phase II trial; however, with increasing evidence for the safe and effective use of higher doses of carfilzomib, we now report results from dose escalation extension of the Phase II trial. Methods: Newly diagnosed myeloma patients intended for stem cell transplant were eligible. All patients were treated on a 28 day cycle with Carfilzomib IV Days 1,2,8,9,15,16 (see Table 1 below for dosing per cohort) along with Cyclophosphamide 300 mg/m2 PO Days 1,8,15, Thalidomide 100 mg PO Days 1–28 and Dexamethasone 40 mg PO Days 1,8,15,22. We initially conducted a Phase I run in trial of 6 patients with no DLT observed before expanding to the Phase II portion of the study. The initial phase II regimen is shown below – as no DLTs were observed, we have now fully accrued to the Phase II dose level +1. Treatment was for 4 cycles with expected SCT post induction. The primary endpoint of the trial is the proportion of patients who have ≥very good partial response (VGPR) to treatment. All patients received herpes zoster prophylaxis and ASA daily. Results: A total of 38 patients have been accrued to the trial, 6 in the initial Phase 1, 21 in the initial Phase II, and the remaining at dose escalated cohorts. We are reporting the 27 patients who have completed therapy and will update with the dose escalated cohorts. Median age was 65 (range 27–74) and 52% were female. ISS Stage was advanced (II-III) in 56%. Best overall response rate during 4 cycles of CYCLONE at dose level 0 is 96%: CR 29%, VGPR 46%, PR 21% (1 pt achieved MR). Adverse events of grade 3 or higher at least possibly related to CYCLONE occurred in 12 (44%). Most commonly reported non hematological toxicities (all grades) included fatigue (67%), constipation (56%), lethargy (41%) somnolence (37%), malaise (30%) depressed level of consciousness (22%); however, grade 3/4 toxicities occurring in >5% were uncommon: thromboembolic event 11%) and muscle weakness (7%). Two cases of pneumonia required hospitalization. Eight patients (30%) developed grade 1 sensory neuropathy; no higher grade or painful neuropathy was evident. There were no cardiac events seen in greater than 5% of patients. Grade 3/4 hematological toxicities included neutropenia (15%) and lymphopenia (7%). All patients advancing to SCT successfully collected stem cells. One patient died on study from pneumonia. Conclusion: The 4 drug CYCLONE regimen is highly efficaceous with a response rate after only 4 cycles of 96% (75% ≥VGPR, 29% CR) at the current dosing level of carfilzomib IV 20/27 mg/m2 in newly diagnosed myeloma. Toxicities are manageable, with only grade 1 neuropathy and minimal cardiac or pulmonary toxicity. Increasing the dose of carfilzomib is feasible and updated results of dose escalated cohorts will be reported at 20/36 and 20/45 mg/m2. Disclosures: Bergsagel: onyx: Membership on an entity's Board of Directors or advisory committees. Stewart:Millennium Pharmaceuticals: Consultancy, Honoraria, Research Funding; Onyx: Consultancy; Celgene: Consultancy.

Abstract We have previously proposed the dysregulation of the D type cyclins by chromosome translocations to the IgH locus or by not fully characterized mechanisms in hyperdyploid patients as a unifying genetic event in the pathogenesis of Monoclonal Gammopathy of Uncertain Significance (MGUS) and multiple myeloma (MM). However, no experimental data are available to evaluate the direct consequences of cyclin Ds overexpression in plasma cells. Similarly, activating mutations of KRAS have been identified in 15% of MM patients, but never in MGUS, and have been proposed to contribute to the progression of MGUS to MM, but this hypothesis has never been experimentally validated. We evaluated the contribution of CyclinD1 and KRAS to the development and progression of monoclonal gammopathy (MG) that develops spontaneously in C57BL/6 mice. We aged a cohort of EuCCND1 mice, and lslKRASV12 mice crossed to three different CRE expressing mice: IgG1CRE, CD19CRE or Vk* CRE (KRAS/CRE). A cohort of Vk* MYC mice, Vk* MYC x EuCCND1 (MYC/CD1) and triple transgenic mice (CD1/KRAS/CRE) was also analyzed. Mice were bled every 10 weeks beginning at 30 weeks, and the presence of MG was evaluated by serum protein electrophoresis. The median Time To M-Spike (mTTS) detection was 97 weeks in C57Bl/6, 63w in EuCCND1, 54w in KRAS/CRE, 54w in Vk* MYC, 38w in CD1/KRAS/CRE and 36w in MYC/CD1 mice. This indicates that acceleration of the development of MG occurs in all these strain of mice. However, we noticed that the spontaneous MG in C57BL/6 wt, EuCCND1 or KRAS/CRE rarely progresses (as determined by detection of a M-spike >7 g/L), while in the other mouse strains it frequently progresses, with a mTTS >7 g/L around 65w. A clear progression of MGUS to MM was observed only in Vk* MYC mice, and was further accelerated in MYC/CD1 mice, which are characterized by extra-medullary disease and shorter overall survival. In conclusion, these data support our hypothesis that Cyclin Ds dysregulation in plasma cells is the initial transformation step leading to MGUS. Further oncogenic events, like activating mutations of KRAS are required to expand the monoclonal plasma cells. Among the oncogenes examined MYC provides the greatest acceleration of the MG in wildtype and EuCCND1 mice, and results in a disease with the malignant features of MM. Disclosures: No relevant conflicts of interest to declare.

Abstract Through the recent elucidation of molecular and cellular processes in multiple myeloma (MM) pathogenesis that effect well-defined proliferative and survival pathways, a number of molecular targets for anti-cancer agents have emerged. This includes proteins involved in cell cycle regulation. A recent model of early MM pathogenesis proposes that at least one of the cyclin D genes is dysregulated in all myeloma tumors facilitating activation of cyclin dependent kinase (CDK)4 (or CDK6), and transition from G1 to S phase. It is hypothesized that this renders myeloma cells more responsive to bone marrow (BM) derived proliferative stimuli including IL-6 that upregulates MYC expression in MM cells and cooperates with cyclin D to promote transit to S-phase. In addition, recent studies have established a causative role of MYC dysreguation in progression from monoclonal gammopathy to myeloma. Thus an approach targeting deregulated cell cycle progression and MYC may prove effective MM therapy. Purvalanol is a potent and selective inhibitor of CDK1, an important regulator of cell cycle progression and has been reported to induce MYC-dependent apoptosis. Activity of purvalanol against a panel of 14 standardized, annotated myeloma cell lines was measured in a 48 hour MTT viability assay. IC50-s of all 14 cell lines ranged between 5 uM to 7.5 uM. Western blot and real-time PCR analysis revealed variability of MYC protein and mRNA levels between the 14 myeloma cell lines. We compared potential therapeutic activity of purvalanol against 3 myeloma cell lines (U266, H929, KMS12PE) with low, intermediate, and high levels of c-MYC expression, respectively. All three cell lines demonstrated G2-M growth arrest however marked apoptosis as determined by PI/annexin V staining was observed only in the cell lines with the highest level of MYC expression. Exposure of MM patient-derived BM mononuclear cells to purvalanol preferentially induced apoptosis of CD138+ MM cells. In contrast, purvalanol was minimally cytotoxic to the non-myeloma cell fraction and to non-transformed fibroblast cell lines (MRC5, IMR90 and W138) and failed to inhibit normal bone marrow-derived CD34 colony formation. Recent studies have demonstrated that the BM microenvironment offers protection of myeloma cells from chemotherapeutic agents by common mechanisms. Myeloma cell lines were cultured in 3 different conditions to mimic the tumor’s protective microenvironment. Soluble factors produced by the BM, IL6 and IGF-1 induced a modest degree of resistance to purvalanol while co-culture on BM stroma cells was completely protective. Studies evaluating the in vivo efficacy of purvalanol in a novel Vk*myc transgenic mouse model that spontaneously develops myeloma with a low proliferative index are ongoing and will be presented. The CDK1 inhibitor, purvalanol demonstrates broad single agent activity against myeloma cells with enhanced activity against MYC overexpressing cells. However, the strong protective effect of the BM microenvironment suggest that combination with agents that can reverse cell-adhesion mediated drug resistance may prove beneficial in optimizing the efficacy of this class of drugs for the treatment of MM.

Background The precise molecular mechanism and targets of lenalidomide specific anti-Multiple Myeloma (MM) activity remain largely unknown, although, cereblon (CRBN) has been identified as a central mediator of activity with IRF-4 acting as a downstream molecule. Lenalidomide resistance in MM cells which, despite CRBN depletion, are able to restore their IRF-4 levels suggests the existence of alternative pathways. Methods To measure apoptosis and gene expression analysis 1x 106cells were incubated with 10μm to 50μm of lenalidomide for 24 to 96 hours before they were examined by annexin-PI and FACS analysis. Gene and protein expression were measured by RT-PCR, western blot, and immunohistochemistry. For lenalidomide followed bortezomib serial studies, cells were incubated with 10μm of lenalidomide for 48 hours and later treated with bortezomib for 24 to 48 hrs. CRBN and immunoglobulin light chain knock-down were performed by lentiviral mediated shRNA. Results We found lenalidomide induces Endoplasmic reticulum stress (ERS) via accumulation of intracellular immunoglobulin proteins, but only in the presence of CRBN in a panel of MM cell lines. This accumulation of intracellular proteins resulted in ERS as documented by western blot and RT-PCR in OPM2 and MMIS cell lines. We next utilized OPM2 cells knocked down for CRBN and control, non-target (NT), and treated with different doses of lenalidomide. After three days of treatment an ERS response was occurring in OPM2-NT cells but not in CRBN knockdown cells. Using Western blot we found decreased XBP-1u and increased XBP-1s, ERS marker proteins, in CRBN positive (NT) cells after 72 hours of lenalidomide treatment, but not in CRBN knock-down cells. Another ERS marker GRP78/BiP was also clearly accumulated after lenalidomide treatment in CRBN positive cells. Inactivation of the tumor suppressor p53 by degradation is a mechanism utilized by cells to adapt to ERS has been reported. We also found that p53 protein down regulated after lenalidomide treatment in CRBN positive OPM2 and MMIS cells. We have analyzed other isogenic cell lines MM1.S (lenalidomide-sensitive) and isogenic MM1.Sres (lenalidomide-resistant) HMCLs and found that lenalidomide induces ERS in MM1.S but not MM1.Sres cells. CRBN is important for lenalidomide to induce immunoglobulin protein accumulation and ERS was further proved by over-expressing CRBN in OCI-My5 MM cell line and subsequent lenalidomide treatment. To test the effect of light chain accumulation as ER stressors, we knocked down immunoglobulin light chain lambda in human MM cell line OPM2. Knock-down of lambda light chain in OPM2 cells resulted in lenalidomide resistance and it induced endoplasmic reticulum stress mediated anti-myeloma activity. Our preliminary data reveals that lenalidomide mediated progressive ERS can positively enhance bortezomib induced apoptosis in an in-vitro MM model. We pre-treated myeloma cell lines with lenalidomide and subsequently treated with bortezomib. MM cells pre-treated with lenalidomide for two days and there after treated with bortezomib clearly shown increased sensitivity to bortezomib induced apoptosis than non-pre-lenalidomide treated cells. Conclusion Here we show that lenalidomide causes accumulation of immunoglobulin light chains, inducing progressive ER stress, resulting in anti-myeloma activity and that effect depends on the presence of CRBN. Proteasome inhibitors such as bortezomib also sensitize MM cells to endoplasmic reticulum stress-mediated apoptosis. Our data demonstrated the synergistic effect of lenalidomide and proteasome inhibitors, likely due to the augmented protein stress. This data support the use of serial therapy utilizing pre-lenalidomide treatment followed by bortezomib or carfilzomib treatment. Disclosures: Fonseca: Medtronic: Consultancy; Otsuka: Consultancy; Celgene: Consultancy; Genzyme: Consultancy; BMS: Consultancy; Lilly: Consultancy; Onyx: Consultancy, Research Funding; Binding Site: Consultancy; Millennium: Consultancy; AMGEN: Consultancy; Cylene: Research Funding; Prognostication of MM based on genetic categorization of the disease: Prognostication of MM based on genetic categorization of the disease, Prognostication of MM based on genetic categorization of the disease Patents & Royalties.

Abstract Abstract 5093 A relative increase in proliferation is now accepted as the most important measure in risk stratification of myeloma. Attempts to include measures of proliferation in different stratification strategies have been met with obstacles largely influenced by their practicality and economic viability in the clinical setting. The plasma cell labelling index (PCLI) is the gold standard used in myeloma; however it is still only used in a minority of centers across the globe. New surrogate markers of proliferation, such as serum biomarkers and transcription-based methods, are under investigation but few have evolved to become part of a uniform strategy in the stratification of myeloma. The gene-expression based proliferation indices (gPI) described by Bergsagel et al, Shaughnessy et al and Hose et al all show similar correlation with PCLI. Studies comparing all currently available methods are lacking. In a cohort of 70 patients, PCLI and gPI were compared with two immunohistochemistry-based methods of measuring proliferation, Ki67 and a more specific measure of S-phase entry – phosphorylation of minichromosome maintenance protein 2 (pMcm2) at serine 40/41, combined with dual staining of CD138. We observed a similar correlation of gPI wth PCLI to that previously reported (r value; CI – 0.43;0.21–0.61). Both Ki67 and pMcm2 staining showed a stronger correlation with PCLI than with gPI and PCLI (r value; CI – 0.81;0.71–0.88 and 0.86; 0.78 – 0.91 respectively). PCLI and gPI have already been shown to be an independent predictor of time to progression and overall survival. Although this sample size was too small to test for time to progression or overall survival and thus independence, a logical extrapolation would indicate similar independence and predictions on survival and time to progression. As Ki67 is routinely used for more proliferative cancers in the clinic, the extension of its use as part of a new stratification system in myeloma provides interesting possibilities for further exploration. Disclosures: O'Dwyer: Novartis: Honoraria, Research Funding.

Abstract Background Carfilzomib is a proteasome inhibitor that irreversibly binds its target and has been validated as both relapse and upfront therapies for multiple myeloma. To optimize pre transplant response, we combined carfilzomib with the widely accessible backbone of cyclophosphamide-thalidomide-dexamethasone (CTD). We previously reported results of the Phase I component of the trial (in which no MTD was reached); we now report results for the MTD and fully accrued expansion cohorts at the MTD of the CYCLONE trial NCT01057225. Methods Newly diagnosed myeloma patients intended for stem cell transplant were eligible. All patients were treated on a 28 day cycle with carfilzomib IV Days 1,2,8,9,15,16 (see Table below for dosing per cohort) along with cyclophosphamide 300 mg/m2 PO Days 1,8,15, thalidomide 100 mg PO Days 1-28 and dexamethasone 40 mg PO Days 1,8,15,22. The initial phase I/ II regimen is shown below – as no DLTs were observed, we increased dosing of carfilzomib to 36 and then 45mg/m2 and have now nearly fully accrued to the Phase II dose level +1 (27mg/m2) and expansion MTD (36mg/m2). Treatment was for 4 cycles with planned SCT post induction. The primary endpoint of the trial is the proportion of patients who have ≥very good partial response (VGPR) to treatment. All patients received herpes zoster prophylaxis and ASA daily. Results A total of 54 patients have been accrued to the trial, 6 in the initial Phase 1, 21 in the initial Phase II (CFZ 27mg/m2), and 27 at CFZ 36-45mg/m2. Median age was 63 (range 27-77) and 52% were male. ISS Stage was advanced (II-III) in 57% The overall partial response rate or better following 4 cycles of CYCLONE at dose level 0 or greater is 91%: CR 18%, VGPR 58%, PR 16%, MR 2%, SD 4%. One patient withdrew from the trial after cycle 1. At dose level 2, 3/7 patients experienced dose-limiting toxicity in cycle 1 including: grade 3 alanine aminotransferase increase (possibly related); grade 3 infusion reaction (probably related); and grade 4 heart failure with grade 3 dyspnea, atrial fibrillation, and fatigue (all possibly related). No dose-limiting toxicity was observed in 6 patients at dose level 1 and thus DL1 was deemed the MTD. Across dose levels, adverse events are fully evaluable in 48 patients. AEs of grade 3 or higher at least possibly related to CYCLONE occurred in 26 (54%) – 35% non hematological and 33% hematological. Most commonly reported non hematological toxicities (all grades) included fatigue (63%), constipation (46%), elevated creatinine (27%), hyperglycemia (27%), lethargy (25%) peripheral sensory neuropathy (25% - all grade 1), and somnolence (21%); however, grade 3/4 toxicities occurring in >5% were uncommon: hypertension (8%), thromboembolic event (6%) and hyperglycemia (6%). Three cases of pneumonia required hospitalization. There were no cardiac events seen in greater than 5% of patients. Grade 3/4 hematological toxicities included lymphopenia (23%) and neutropenia (17%). All patients advancing to SCT successfully collected stem cells. One patient died on study from pneumonia. 90% completed at least 4 cycles. With median follow-up of 16 months (range 0-64), 1-year PFS was 90% and 1-year OS was 98%. Conclusion The 4 drug CYCLONE regimen is highly efficacious with an overall response rate after only 4 cycles of 91% (76% ≥VGPR) at the dosing level of carfilzomib IV 20/27-36 mg/m2 in newly diagnosed myeloma. Toxicities are manageable, with only grade 1 neuropathy and minimal cardiac or pulmonary toxicity. CYCLONE is a combination that results in rapid and deep responses with minimal neuropathy prior to stem cell transplant. Comparative studies of this regimen with longer duration of therapy (as induction or consolidation) at the defined MTD should be considered. Disclosures: Mikhael: Celgene: Research Funding; Onyx: Research Funding; Sanofi: Research Funding. Reeder:Millenium: Research Funding; Celgene: Research Funding; Novartis: Research Funding. Costa:Otsuka: Research Funding. Stewart:Celgene: Honoraria; Millenium: Honoraria, Research Funding; Onyx: Research Funding.

Abstract Abstract 2881 Multiple myeloma (MM) is characterized by a remarkable heterogeneity in outcome following standard and high-dose therapies. Significant efforts have been made to identify genetic changes and signatures that can predict clinical outcome and include them in the routine clinical care. Gene expression profiling (GEP) studies have achieved a central role in the study of multiple myeloma (MM), as they become a critical component in the risk-based stratification of the disease. To molecularly stratify disease-risk groups, we performed GEP on purified plasma cells (obtained from the immunobead selection of CD138+ cells) from 489 MM samples in different stages of the disease using the Affymetrix U133Plus2.0 array. A total of 162 probes were analyzed using an in house automated script to generate a GEP report with the most used risk stratification indices and signatures, including the UAMS 70-gene, UAMS class, TC classification, proliferation and centrosome signature, and NFKB activation indices. In a subset of 57 samples, IgH translocations were analyzed using FISH and results were correlated with GEP data. A macrophage index was calculated and used as a surrogate measurement of non-plasma cell contamination. A total of 49 samples (10%) were excluded from subsequent analysis as the macrophage index indicated a significant contamination with no plasma cells, hence potentially compromising the results. The percent of high-risk disease patients identified from different signatures ranged from 26.4% by using high proliferation index to 28.8% with high centrosome signature and 31.3% with high 70-gene index. This percent of high-risk cases based on the 70-gene index is similar to what was found in Total therapy 2 (TT2) and TT3 cohorts. A third of patients (33.2%) were classified as D1 in the TC class, followed by 11q13 (19.3%), D2 (16.4%), 4p16 (13.8%), MAF (6.1%), None (4.7%), D1+D2 (4.5%) and 6p21 (1.8%). The NF-kB pathway was likely activated in 45.5% to 59.5% of cases, depending on the index used for its calculation. High proliferation index and high centrosome signature significantly correlates with 70-gene high-risk group (p<0.0001). Conversely, the activation of NF-kB pathway was not significantly different between high- and low- risk subgroups. TC subgroups D1 (p<0.0001) and 11q13 (p=0.01) were significantly more common in the 70-gene low-risk group. Similarly, TC subgroups 4p16 (p=0.0004), Maf (p=0.02) and D2 (p=0.05) were enriched in the high-risk group. Translocations t(4;14)(p16;q32), t(11;14)(q13;q32) and t(14;16)(q32;q23) were precisely predicted by the TC classification (100% correspondence). Cases with IgH translocations with unknown partner were classified in subgroups D1 (33%), D2 (25%), 6p21 (25%) and Maf (16%). Here we summarized the associations between the most significant gene expression indices and signatures relevant to MM risk-stratification. The multiple variables simultaneously analyzed in an automated way, provide a powerful and fast tool for risk-stratification, helping in the therapeutic decision-making. Disclosures: Stewart: Celgene: Consultancy, Research Funding; Millennium: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Onyx Pharmaceuticals: Consultancy, Research Funding. Fonseca:Consulting :Genzyme, Medtronic, BMS, Amgen, Otsuka, Celgene, Intellikine, Lilly Research Support: Cylene, Onyz, Celgene: Consultancy, Research Funding.

Abstract Human myeloma cell lines (HMCL) provide both a discovery and validation platform to improve our understanding of the molecular pathogenesis of multiple myeloma. We have completed a project to characterize the underlying genetics of all commonly used HMCL with a primary goal of identifying appropriate model systems for findings from large scale patient studies like the multiple myeloma genomics initiative (MMGI). We first purchased all 37 commercially available HMCL from DSMZ, JCRB, ECACC, and ATCC. An additional, 32 non-commercial cell lines were obtained from Diane Jelinek and Leif Bergsagel. Subsequently each HMCL was thawed and cultured under strict parameters, which yielded cells for analysis, by comparative genomic hybridization, whole exome sequencing (Agilent SureSelect V4+UTR) and mRNA sequencing. The combination of these two assays provides a detailed map of the genetic complexity underlying this deadly disease. For variant discovery, alignment was done using BWA followed by realignment, quality recalibration and duplicate removal. High quality calls were identified using Mutect by requiring a minor allele frequency of 0.25 and a minimum depth of coverage of 10x. This identified a median of 81999 mutations per sample with 25th and 75thpercentile values of 76621 and 87440 respectively. To identify likely somatic mutations, we filtered out variants found in dbSNP, 1000 genomes project and the NHLBI Exome Sequencing Project when any of the SNPs within each database had a global minor allele frequency of greater than 0.1%. In addition, we included only those variants in gene space defined by RefSeq or GENCODE and targeted by Agilent exome capture V4+UTR. After these filtering steps a median of 1389 putative somatic mutations remained. To identify key events responsible for mutagenesis, we extracted non-synonymous variants in genes, which show substantially expression in RNASeq(FPKM>5). This identified a median of 371 and 135 variants per sample respectively. Overall, across all the 66 samples, there were at total of 9074 non-synonymous mutations in 4453 genes, which are significantly expressed. To identify potential oncogenes we focused on mutations that occurred at the same position in the genome or altered the same amino acid in expressed genes. This identified 63 genes including KRAS(n=16) and NRAS(n=11) as expected but also BRD9, CCNE1 and MAP2K3. To identify putative tumor suppressors, we looked for genes with homozygous mutations or genes with more than one mutation in the same sample. This identified 112 genes including TP53, TRAF3, FAM46C and DIS3 as expected along with LTB and KDM6B. Independently, to attempt to identify genes involved in MM pathogenesis, genes with mutations having a SIFT score of less than 0.05 which occurred in at least 5%(n>3) of the cell-lines were identified. This identified 185 genes of which 25 are in our putative oncogene list and 37 are in the tumor suppressor list. These study results provide the myeloma community with the unique resource of a fully characterized series of models that can be used for laboratory-based tests. To increase the utility of the dataset to the community all these data are freely available at www.keatslab.org or by request. Disclosures: No relevant conflicts of interest to declare.