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The bone marrow (BM) microenvironment actively promotes multiple myeloma pathogenesis, and therapies targeting both cancer cells and the niche are highly effective. We were interested in identifying novel signaling pathways supporting multiple myeloma–BM cross-talk. Mutations in the transmembrane receptor Roundabout 1 (ROBO1) were recently identified in patients with multiple myeloma; however, their functional consequences are uncertain. Through protein structure–function studies, we discovered that ROBO1 is necessary for multiple myeloma adhesion to BM stromal and endothelial cells and that ROBO1 knockout (KO) compromises BM homing and engraftment in a disseminated mouse model. ROBO1 KO significantly decreases multiple myeloma proliferation in vitro and intra- and extramedullary tumor growth in vivo. Mechanistically, the ROBO1 C-terminus is cleaved in a ligand-independent fashion and is sufficient to promote multiple myeloma proliferation. Vice versa, mutants lacking the cytoplasmic domain, including the human-derived G674* truncation, act dominantly negative. Interactomic and RNA-sequencing studies suggest that ROBO1 may be involved in RNA processing, supporting further studies.Significance:ROBO1 is highly expressed in t(4;14) multiple myeloma and supports homing and dissemination to the BM niche. ROBO1 knockout causes reduced tumor growth in intramedullary and extramedullary myeloma animal models, while the ROBO1 C-terminus is cleaved in multiple fragments and it is necessary and sufficient to sustain myeloma proliferation.

Supplementary Figure 1 showing ROBO1 expression in primary MM cells versus normal donor bone marrow plasma cells via gene expression profiling and immunohistochemistry. Supplementary Figure 2 showing distribution of ROBO1 expression in the CoMMpass database; ROBO1 expression in CoMMpass database according to cytogenetics; ROBO1 expression in IFM170 database according to cytogenetics; ROBO1 expression in t(4;14) cell lines WT or KO for MMSET. Supplementary Figure 3 showing ROBO1 protein down regulation after ROBO1 knock down via shRNA. Supplementary Figure 4 showing effects of shRNA4- and shRNA-5 mediated ROBO1 KD on cell viability across a panel of MM cell lines with western confirming proper protein down regulation. Supplementary Figure 5 showing successful ROBO1 KO across several KMS11 monoclones, but not H929 monoclones. Supplementary Figure 6 showing expression of ROBO1 FL construct in polyclonally and monoclonally-transduced OPM2 cells. Supplementary Figure 7 showing expression of FL ROBO1 addback in distinct KMS11 ROBO1 KO monoclones. Supplementary Figure 8 showing radiographic images of WT versus KO ROBO1 mu-SCID mice. Supplementary Figure 9 showing adhesion defect in ROBO1 KO KMS11 cells that is fully rescued by FL ROBO1 addback. Supplementary Figure 10 showing Kaplan-Meier survival curve of disseminated mouse model injected with ROBO1 KO versus FL OPM2 cells. Supplementary Figure 11 showing cleaved cytosolic ROBO1 fragments in 293T cells transduced with FL ROBO1 tagged with C-LAP tag and in WT MM.1S cells. Supplementary Figure 12 showing interacting partners of ROBO1 cytosolic domain as deconvoluted via STRING database. Supplementary Figure 13 showing differentially expressed genes in ROBO1 WT versus KO plasmacytoma represented via Volcano plot. Supplementary Figure 14 showing gene set enrichment analysis of differentially expressed genes in ROBO1 WT versus KO plasmacytoma. Supplementary Figure 15 showing schema of patient-derived ROBO1 mutation and expression of G674 truncation in WT and KO ROBO1 OPM2 cells. Supplementary Table 1 showing clinical annotation of newly diagnosed MM parents used in Supplementary figure 1.

Supplementary Methods

High-dose melphalan (HDM) improves progression-free survival in multiple myeloma (MM), yet melphalan is a DNA-damaging alkylating agent; therefore, we assessed its mutational effect on surviving myeloma cells by analyzing paired MM samples collected at diagnosis and relapse in the IFM 2009 study. We performed deep whole-genome sequencing on samples from 68 patients, 43 of whom were treated with RVD (lenalidomide, bortezomib, and dexamethasone) and 25 with RVD + HDM. Although the number of mutations was similar at diagnosis in both groups (7137 vs 7230; P = .67), the HDM group had significantly more mutations at relapse (9242 vs 13 383, P = .005). No change in the frequency of copy number alterations or structural variants was observed. The newly acquired mutations were typically associated with DNA damage and double-stranded breaks and were predominantly on the transcribed strand. A machine learning model, using this unique pattern, predicted patients who would receive HDM with high sensitivity, specificity, and positive prediction value. Clonal evolution analysis showed that all patients treated with HDM had clonal selection, whereas a static progression was observed with RVD. A significantly higher percentage of mutations were subclonal in the HDM cohort. Intriguingly, patients treated with HDM who achieved complete remission (CR) had significantly more mutations at relapse yet had similar survival rates as those treated with RVD who achieved CR. This similarity could have been due to HDM relapse samples having significantly more neoantigens. Overall, our study identifies increased genomic changes associated with HDM and provides rationale to further understand clonal complexity.

Immunoglobulin M (IgM) multiple myeloma (MM) is a rare disease subgroup. Its differentiation from other IgM-producing gammopathies such as Waldenström macroglobulinemia (WM) has not been well characterized but is essential for proper risk assessment and treatment. In this study, we investigated genomic and transcriptomic characteristics of IgM-MM samples using whole-genome and transcriptome sequencing to identify differentiating characteristics from non–IgM-MM and WM. Our results suggest that IgM-MM shares most of its defining structural variants and gene-expression profiling with MM, but has some key characteristics, including t(11;14) translocation, chromosome 6 and 13 deletion as well as distinct molecular and transcription-factor signatures. Furthermore, IgM-MM translocations were predominantly characterized by VHDHJH recombination-induced breakpoints, as opposed to the usual class-switching region breakpoints; coupled with its lack of class switching, these data favor a pre–germinal center origin. Finally, we found elevated expression of clinically relevant targets, including CD20 and Bruton tyrosine kinase, as well as high BCL2/BCL2L1 ratio in IgM-MM, providing potential for targeted therapeutics.

Long noncoding RNAs (lncRNAs) can drive tumorigenesis and are susceptible to therapeutic intervention. Here, we used a large-scale CRISPR interference viability screen to interrogate cell-growth dependency to lncRNA genes in multiple myeloma (MM) and identified a prominent role for the miR-17-92 cluster host gene (MIR17HG). We show that an MIR17HG-derived lncRNA, named lnc-17-92, is the main mediator of cell-growth dependency acting in a microRNA- and DROSHA-independent manner. Lnc-17-92 provides a chromatin scaffold for the functional interaction between c-MYC and WDR82, thus promoting the expression of ACACA, which encodes the rate-limiting enzyme of de novo lipogenesis acetyl-coA carboxylase 1. Targeting MIR17HG pre-RNA with clinically applicable antisense molecules disrupts the transcriptional and functional activities of lnc-17-92, causing potent antitumor effects both in vitro and in vivo in 3 preclinical animal models, including a clinically relevant patient-derived xenograft NSG mouse model. This study establishes a novel oncogenic function of MIR17HG and provides potent inhibitors for translation to clinical trials.

SUMMARYLong noncoding RNAs (lncRNA) can drive the tumorigenesis and be susceptible to therapeutic intervention. To define the landscape of therapeutically actionable lncRNA dependencies in multiple myeloma (MM), we coupled our extensive lncRNA transcriptomic profile with lncRNA targeted CRISPR interference viability screen and identified RNA Regulator of Lipogenesis (RROL) as a leading lncRNA dependency in MM. RROL shares its origin with the microRNA locus MIR17HG, however supports the proliferation and survival of MM cells in a microRNA- and DROSHA- independent manner. We found that RROL provides a chromatin scaffold for the functional interaction between c-MYC and WDR82 to promote the regulation of the lipogenic pathways via the transcriptional control of the rate-limiting enzyme ACC1 in MM cells. Inhibition of RROL with clinically applicable antisense molecules disrupts its transcriptional and functional activities causing potent anti-tumor effects both in vitro and in vivo in two pre-clinical animal models. This study establishes lncRNA RROL as a therapeutically actionable dependency with a unique mechanism of action in support of myeloma cell growth.

The bone marrow (BM) microenvironment actively promotes multiple myeloma pathogenesis, and therapies targeting both cancer cells and the niche are highly effective. We were interested in identifying novel signaling pathways supporting multiple myeloma–BM cross-talk. Mutations in the transmembrane receptor Roundabout 1 (ROBO1) were recently identified in patients with multiple myeloma; however, their functional consequences are uncertain. Through protein structure–function studies, we discovered that ROBO1 is necessary for multiple myeloma adhesion to BM stromal and endothelial cells and that ROBO1 knockout (KO) compromises BM homing and engraftment in a disseminated mouse model. ROBO1 KO significantly decreases multiple myeloma proliferation in vitro and intra- and extramedullary tumor growth in vivo. Mechanistically, the ROBO1 C-terminus is cleaved in a ligand-independent fashion and is sufficient to promote multiple myeloma proliferation. Vice versa, mutants lacking the cytoplasmic domain, including the human-derived G674* truncation, act dominantly negative. Interactomic and RNA-sequencing studies suggest that ROBO1 may be involved in RNA processing, supporting further studies. Significance: ROBO1 is highly expressed in t(4;14) multiple myeloma and supports homing and dissemination to the BM niche. ROBO1 knockout causes reduced tumor growth in intramedullary and extramedullary myeloma animal models, while the ROBO1 C-terminus is cleaved in multiple fragments and it is necessary and sufficient to sustain myeloma proliferation.

Introduction Long noncoding RNAs (lncRNAs) are profoundly dysregulated in multiple myeloma (MM), yet their tumor-promoting features remain to be defined. Here, we have coupled extensive transcriptomic profiling of patient samples (n=360) with a genome-wide CRISPR interference (CRISPRi) viability screen (4 cell lines) to generate a map of lncRNA "dependencies" in MM; moreover, we describe the molecular and functional role – as well as its therapeutic potential – of the screen top hit RNA Regulator of Lipogenesis (RROL), a nuclear-retained lncRNA generated by alternative splicing of MIR17HG. Methods Loss-of-function (LOF) studies using antisense oligonucleotides (ASO) confirmed the RROL dependency in a large panel of MM cell lines and CD138+ patient cells, in vitro and in vivo in animal models. This effect was not antagonized in DROSHA KO MM cells or by ectopic expression of MIR17HG-derived miR-17-92, indicating a microRNA-independent role of RROL. Results Transcriptomic analysis after RROL depletion indicated a significant impact on the de novo lipogenesis (DNL) gene networks. RROL occupancy at DNL gene loci was detected by chromatin isolation by RNA precipitation followed by qRT-PCR (ChIRP-qPCR) and confirmed by DUAL RNA FISH analysis. At functional level, we demonstrated that RROL depletion reduces DNL in MM cells using an unbiased lipidomic profiling as well as by measuring the incorporation of C14-radiolabeled glucose into lipids. Importantly, we also proved that exogenous palmitate, the downstream product of DNL pathway, can significantly rescue the growth inhibitory effect of RROL depletion in MM cells; thus implicating a role for DNL in the growth promoting effect of this lncRNA. RNA-Protein Pull Down (RPPD) and in vivo RNA yeast three-hybrid (Y3H) assays led to identify c-MYC (MYC) as a relevant protein interactor of RROL; a finding validated by RIP-qPCR. Coupling RNA FISH with immunofluorescence, we co-detected RROL and MYC at the ACC1 promoter. Importantly, neither RROL or MYC could occupy ACC1 promoter and exert regulatory control in the absence of the other factor. Moreover, using in vitro (Co-IP/MS) and in vivo (BioID) assays, we identified WDR82 as an RROL-dependent MYC partner implicated in the transcriptional control of ACC1 expression. Finally, to therapeutically antagonize RROL, we have screened >100 ASOs and provided the basis to develop a first-in-class RROL inhibitor. This inhibitor has shown a very strong anti-MM activity in vitro (IC50 Conclusion In conclusion, we here report a unique regulatory function of a novel lncRNA supporting MM cell growth via its control of the lipogenic metabolic axis. The ongoing development of RROL inhibitors may allow clinical application of this unique targeted therapy in MM.

Background Multiple Myeloma (MM) is a disease driven by numerous genetic and epigenetic alterations, however true drivers of the disease have yet to be identified. Methods To identify new dependencies and actionable therapeutic targets in MM we integrated gene expression and genetic dependency (CRISPR KO). Results We found that many of the specific and potent dependencies in MM are transcription factors, especially those establishing plasma cell identity. Among others, the POU2AF1 gene, which encodes the OCA-B/BOB-1, a B cell transcriptional coactivator protein, represented the most striking dependency in MM. Although BOB-1 is expressed throughout B-cell development, we found it to be highly expressed in CD138+ plasma cells from patients with precursor conditions (MGUS and SMM) as well and established MM compared to normal plasma cells (NPC). Loss-of-function studies using shRNA, siRNAs as well as antisense GapMers specific for BOB-1 confirmed significant impact on MM cell viability. Transcriptomic analysis by RNA-sequencing revealed a small set of genes commonly modulated in MM cell lines upon BOB-1 depletion, including the XBP1- BHLHA15 axis involved in lipid synthesis and unfolded protein response (UPR). Interestingly, among the genes most significantly upregulated by BOB-1 depletion was heme oxygenase 1 (HMOX1), that was affected via the NRF2/Keap1 pathway. We observed that HMOX1 expression is significantly lower in MM cells from patients compared to normal plasma cells and correlates with poor clinical outcome, suggesting important role in MM. Moreover, we found that siRNA depletion of HMOX1 reverted the inhibition of MM cell growth caused by BOB-1 KD, confirming significant role for HMOX1 in the BOB-1 addiction observed in MM cells. Next, we performed gene set enrichment analysis (GSEA) and observed ribosome biogenesis pathways and mRNA translation and elongation processes, along with WNT and senescence pathways, to be significantly enriched among genes modulated by BOB-1 depletion in MM cells. Since high protein load is a feature of MM, we evaluated the role of BOB-1 in the translational efficiency of MM cells. In MM cell lines, BOB-1 knockdown decreased de novo protein synthesis, while its overexpression significantly enhances protein synthesis compared to control cells. As MM is characterized by excess production of monoclonal immunoglobulins, we evaluated impact of BOB-1 perturbation on intracellular kappa and lambda light chains production. We observed changes in the intracellular abundance of the light chains with BOB-1 modulation in all MM cell lines tested. As a result, BOB-1 depletion was associated with induction of resistance to proteasome inhibition. Conclusion In conclusion, we report BOB1 as a specific dependency in MM cells with potential role on modulating the protein load/capacity balance in MM cells and therefore the sensitivity to proteasome inhibition.

BCMA targeting chimeric antigen receptor (CAR) T cell therapy has shown deep and durable responses in multiple myeloma. However, relapse following therapy is frequently observed, and mechanisms of resistance remain ill-defined. Here, we perform single cell genomic characterization of longitudinal samples from a patient who relapsed after initial CAR T cell treatment with lack of response to retreatment. We report selection, following initial CAR T cell infusion, of a clone with biallelic loss of BCMA acquired by deletion of one allele and a mutation that creates an early stop codon on the second allele. This loss leads to lack of CAR T cell proliferation following the second infusion and is reflected by lack of soluble BCMA in patient serum. Our analysis suggests the need for careful detection of BCMA gene alterations in multiple myeloma cells from relapse following CAR T cell therapy., Relapse following BCMA targeted CAR T-cell therapy is frequently observed in patients with multiple myeloma (MM). Here, by single cell transcriptome profiling on serially collected bone marrow samples, the authors report biallelic loss of BCMA as the mechanism of resistance underlying both relapse and lack of response to a second CAR T infusion in a patient with MM.

PURPOSE Multiple 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. METHODS We 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. RESULTS We 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. CONCLUSION This 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.

Introduction An increase in the incidence of OSAS (obstructive sleep apnoea syndrome) has been seen due to the reported association between OSAS and obesity. Subjects are predisposed to cardiovascular disease due to systemic inflammation caused by the interactions between obesity and OSA. Inflammatory markers could be used to predict the degree of systemic inflammation, which could be a prognostic factor for future adverse events such as metabolic risks. One marker that has recently started being used as an indicator of systemic inflammation is neutrophil-to-lymphocyte ratio (NLR). Materials and Methods The aim is to evaluate NLR, which is a easily measured parameter of systemic inflammation in OSAS subjects with and without obesity. 155 subjects were assigned to four different groups according to their body mass indices. Comparisons of white blood cell, neutrophil, lymphocyte, NLR values and anthropometric measurements were done for each group. Result The NLR and neutrophil counts of group 4 were statistically significant and higher than those of groups 1, 2 and 3. The lymphocyte counts of group 4 were the lowest amongst all groups, these values were lower than the lymphocyte counts of groups 1, 2 and 3 with statistically significant differences (p< 001). A positive correlation was found between the body mass index and lymphocyte count values of obese OSAS subjects (r= 0.027, p= 353). Conclusions The NLR ratio was found to be increasing by obesity grade and reveals that the associated inflammatory response also increases. The NLR ratio might be used as an inflammatory marker in obese OSAS subjects.

Multiple Myeloma (MM) is a malignancy driven by numerous genetic and epigenetic alterations. Recurrent IgH translocations, somatic mutations and copy number abnormalities all contribute to myelomagenesis, however true drivers of the disease have not been well defined. To identify new targetable dependencies in MM, we generated high-quality active enhancer landscape using large cohort of primary patient myeloma cells (n=70), MM cell lines, and normal plasma cells. We integrated this data with an in-house curated atlas of 600+ active enhancer profile across a wide range of tumor types and normal tissues. Combining these data with gene expression and genetic dependency (CRISPR KO) enabled a multidimensional integration of how transcriptional regulation intersects with tumor specific dependencies. We identified that many of the specific and potent dependencies in MM are transcription factors, especially those establishing plasma cell identity. Among these, the POU2AF1 gene, which encodes the OCA-B/BOB-1, a B cell transcriptional coactivator protein, represented the most striking dependency in MM. Although BOB-1 is expressed throughout B-cell development, we found it to be highly expressed in CD138+ plasma cells from patients with precursor conditions (MGUS and SMM) as well as symptomatic MM compared to normal plasma cells. To functionally validate the role of BOB-1 in MM, we performed loss-of-function studies using shRNA, siRNAs and antisense GapMers specific for BOB-1 and observed a significant impact on MM cell viability and cell cycle arrest. Transcriptomic analysis upon BOB-1 depletion by RNA-sequencing revealed a small set of genes commonly modulated in all 3 MM cell lines tested including the plasma cell differentiation related transcription factor XBP1 and heme oxygenase (HMOX1). Importantly, we observed ribosome biogenesis, RNA polymerase 1A transcription and mRNA translation and elongation processes to be significantly enriched among genes modulated by BOB-1 depletion in MM cells. Bob1 KD resulted in a rapid and robust decrease in the level of transcription of rDNA by RNA polymerase I as determined by qRT-PCR quantification of pre-rRNA (47S). In addition, ChiP assay revealed decreased binding of RNA polymerase 1A to the 18S ribosomal DNA promoter region in BOB-1 depleted cells compared to control. These data indicate that BOB1 downregulation results in the suppression of RNA-polymerase I activity in MM cells. RNA Pol I-dependent transcription governs abundance of rRNA and directly regulates cellular translational and proliferative capacity. Since high protein load is a feature of MM, we evaluated the role of BOB-1 in the translational efficiency of MM cells. We observed that in MM cells compared to control cells, BOB-1 KD decreased, while its overexpression significantly enhanced de novo protein synthesis. As MM is characterized by excess production of monoclonal immunoglobulins, we evaluated impact of BOB-1 perturbation on intracellular light chains (kappa or lambda) production. We observed changes in the intracellular abundance of the light chains with BOB-1 modulation in all MM cell lines tested. As a result of decreased protein production, BOB-1 depletion was associated with induction of resistance to proteasome inhibition suggesting that high expression of BOB-1 may be one the factors driving the exquisite sensitivity of MM cells to proteasome inhibitor. Interestingly, mass spectrometry analysis revealed BOB1 in a protein complex with mTOR, Raptor and mLST8 proteins which are members of mTORC1 complex which is also involved in ribosomal function and may suggest the mechanism of action of Bob-1 at molecular level. In conclusion, here we report BOB1 as a specific proximal dependency in MM cells with potential role in modulating the protein load/capacity balance and ribosomal biogenesis essential for MM cell protein production function and therefore their sensitivity to proteasome inhibition. Disclosures Shirasaki: FIMECS: Consultancy. Mitsiades: BMS: Research Funding; Nurix: Research Funding; H3 Biomedicine: Research Funding; Novartis: Research Funding; Abbvie: Research Funding; Arch Oncology: Research Funding; Janssen/Johnson & Johnson: Research Funding; Fate Therapeutics: Consultancy, Honoraria; Karyopharm: Research Funding; Sanofi: Research Funding; TEVA: Research Funding; EMD Serono: Research Funding; Adicet Bio: Membership on an entity's Board of Directors or advisory committees; FIMECS: Consultancy, Honoraria; Ionis Pharmaceuticals: Consultancy, Honoraria. Hajek: BMS: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharma MAR: Consultancy, Honoraria. Munshi: Abbvie: Consultancy; Oncopep: Consultancy, Current equity holder in publicly-traded company, Other: scientific founder, Patents & Royalties; Pfizer: Consultancy; Legend: Consultancy; Bristol-Myers Squibb: Consultancy; Janssen: Consultancy; Karyopharm: Consultancy; Celgene: Consultancy; Adaptive Biotechnology: Consultancy; Takeda: Consultancy; Amgen: Consultancy; Novartis: Consultancy.

Multiple myeloma (MM) is marked by several genetic abnormalities, including chromosome translocation t(11;14). Overexpression of anti-apoptotic BCL-2 in t(11;14) MM promotes disease progression, prompting clinical use of the BH3 mimetic and BCL-2 inhibitor venetoclax in combination with proteasome inhibitor therapy. Despite high initial response rates and prolonged progression-free survival, patients commonly relapse. To delineate mechanisms contributing to acquired drug resistance we modeled responses to venetoclax in two highly sensitive MM cell lines (KMS27 and KMS-12PE). Colonies generated from a surviving cell were cultured in high-dose venetoclax to generate monoclonal drug-tolerant expanded persister (DTEP) clones. To determine whether venetoclax resistance in DTEP clones is mediated by transcriptional adaptation via genomic or epigenomic regulation and transcriptional reprogramming, we conducted whole-genome sequencing (WGS) and RNA-seq of the clones. WGS analysis did not show significant differences between parental and resistant clones, but transcriptomic analysis showed shared and unique transcriptome signatures in DTEP clones. Gene set enrichment analysis of the common significantly modulated genes in resistant clones revealed that PKA-ERK-CREB and K-Ras pathway genes were significantly upregulated, whereas apoptotic genes were downregulated in resistant clones compared to parental cells. Importantly, ectopically expressed ERK in venetoclax-sensitive cells conferred a resistant phenotype that was rescued using two specific ERK inhibitors in DTEP clones. These data confirm a key role for ERK activation in acquired venetoclax resistance. Resistant clones were further characterized by reduced mitochondrial priming assessed by dynamic BH3 profiling, with altered expression of anti-apoptotic regulators including MCL-1, BCL-xL, and BCL-W and the replaced BCL-2: BIM complex by both MCL-1 and BCL-xL. Because these data suggested a functional substitution between anti-apoptotic BCL-2 family members in cells with acquired resistance to venetoclax, we next evaluated if MCL-1 or BCL-xL are codependent in MM cells that are insensitive or resistant to venetoclax. Simultaneous inhibition of MCL-1 (via S63845) or BCL-xL (via A155463) and BCL-2 (via venetoclax) increased BIM release and enhanced cell death in resistant clones (vs single agents), with combination index values < 0.3 in all doses. Upregulation of BCL-xL or MCL-1 in MM cells also mediated primary venetoclax resistance independent of genetic hallmarks (e.g. t [11;14]-translocated cells). Thus, simultaneous inhibition of MCL-1 or BCL-xL and BCL-2 triggered synergistic cytotoxicity in MM cell lines intrinsically resistant to venetoclax. These data suggest that combined inhibition of BCL-2 and BCL-xL may overcome venetoclax resistance. However, the dependence of BCL-xL in mature platelets had triggered thrombocytopenia for patients under therapy using BCL-xL inhibitor. To further explore the potential clinical application of targeting BCL-xL, we employed novel BCl-2/BCL-xL dual inhibitor, BH3 mimetic pelcitoclax (APG-1252). Using pro-drug strategy for design, pelcitoclax has limited cell permeability during circulation, and was converted to a more potent metabolite APG-1252-M1 in tumors/tissues. APG-1252-M1 was thus used for in vitro cell based assays. We discovered that APG-1252-M1 induced cytotoxicity in MM cell lines intrinsically resistant to venetoclax (regardless of genetic background or BCL-2:BCL-xL ratio) and also significantly reduced MM cell viability in clones with acquired venetoclax resistance, overcoming ERK activation and decreasing BIM sequestration by BCL-xL. In vivo study using pelcitoclax is ongoing and will be presented at the meeting. In conclusion, we report that venetoclax resistance in MM evolves from outgrowth of persister clones displaying activation of the ERK pathway and a shift in mitochondrial dependency towards BCL-xL, which can potentially be effectively targeted via the novel BCL-2/BCL-xL inhibitor pelcitoclax (APG-1252), which is currently in clinical investigation for solid tumors (NCT03080311). Disclosures Deng: Ascentage Pharma Group: Current Employment. Zhai: Ascentage Pharma Group Inc.: Current Employment, Current equity holder in publicly-traded company, Other: Leadership and other ownership interests, Patents & Royalties, Research Funding; Ascentage Pharma (Suzhou) Co., Ltd.: Current Employment, Current equity holder in publicly-traded company, Other: Leadership and other ownership interests, Patents & Royalties, Research Funding. Anderson: Sanofi-Aventis: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Millenium-Takeda: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Scientific Founder of Oncopep and C4 Therapeutics: Current equity holder in publicly-traded company, Current holder of individual stocks in a privately-held company; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Mana Therapeutics: Membership on an entity's Board of Directors or advisory committees. Munshi: Novartis: Consultancy; Janssen: Consultancy; Adaptive Biotechnology: Consultancy; Takeda: Consultancy; Celgene: Consultancy; Bristol-Myers Squibb: Consultancy; Karyopharm: Consultancy; Oncopep: Consultancy, Current equity holder in publicly-traded company, Other: scientific founder, Patents & Royalties; Amgen: Consultancy; Abbvie: Consultancy; Legend: Consultancy; Pfizer: Consultancy.

Background Focal amplifications and rearrangements drive tumor growth and evolution in cancer. Focally amplified regions often involve the juxtaposition of rearranged segments of DNA from distinct chromosomal loci into a single amplified region and nearly half of these regions can be explained by circular, extrachromosomal DNA (ecDNA) formation. Cancer-associated ecDNA shows a unique circular placing ecDNA at the interface of cancer genomics and epigenetics. As formation of ecDNA represents a manifestation of genomic instability, we have investigated presence and prognostic impact of ecDNA in multiple myeloma (MM). Methods Whole genome (WGS) and transcriptome (RNAseq) sequencing data from CD138 purified MM cells from 191 uniformly-treated newly diagnosed MM patients were used for this analysis. Copy number variants (CNV), single nucleotide variants (SNV) and structural variants (SV) were identified on all WGS samples using Facets, Mutect2 and Manta. Seed data from these CNV results was passed to the AmpliconArchitect tool to determine presence of focally amplified and rearranged segments of DNA. Seed CNV thresholds were set for a minimum CNV size of 100kb and a copy number of equal or greater to 5. Extrachromosomal calls were then annotated using the Amplicon Classifier to determine the presence of ecDNA. Multivariate survival analysis was performed after segregating samples into the conventional myeloma risk classifications including translocations, copy number alterations, ISS, age and mutations associated with risk. Differential expression analysis was performed on transcriptomic data using DEseq2. Results We identified 6.8% of the newly diagnosed patients with ecDNA, 12.5% with complex non-cyclic DNA amplifications and 10.1% with linear amplifications. ecDNA and complex events were targeting MM dependent genes, including MYC/PVT1, IRF4 as well as known driver genes such as CDYL and TRAF2. We further evaluated association between ecDNA, complex rearrangements, linear amplification and patients with none of these amplification types and found that patients with ecDNA had significantly poor PFS (median PFS 22 months vs. 41 months) and OS (median OS 41 months vs. 105 months). Patients having ecDNA in their MM cells did not show any significant enrichment for known translocations, double hit or TP53 mutations. In a multivariate model including ecDNA and all other known MM risk features, ecDNA was found to be an independent predictor of progression free survival.(HR 2.6, CI: 1.26 -5.6, p=0.0082) and overall survival (HR 7.94 CI:3.5-17.9 p < 0.0001). Patients with ecDNA have higher mutational load probability(8798 vs 6982, effect size = 0.64 , probability is 91.1). However, this was not reflected in heterogeneity by using MATH score. We found that patients with ecDNA are likely to have BRAF mutations (OR= 25.07 [2.57 - 330 95% CI], p value = 0.002), however overall RAS/RAF pathway mutations were similar to other patients. Patients with ecDNA showed fragile DNA with more breaks (median segments 197 vs. 125.5, p value = 0.001). Although ecDNA is defined as copy number gain with fragments having 5 or more copies, overall genomic gain between ecDNA and other patients were similar. However, overall genomic loss in patients with ecDNA were higher than others (7% vs. 4.2%, p = 0.06). By differential gene expression analysis we noted 98 differentially expressed genes in MM cells with ecDNA. The downregulated geneset involved pathways responsible for cell death as well as the RAS pathway. Interestingly, CD38 was upregulated in the ecDNA dataset suggesting greater potential for CD38 targeting therapies in these patients. Conclusions ecDNA, as an unique marker of perturbed genomic integrity, is observed in a subset of patients and is an independent prognostic marker in newly diagnosed MM patients. As patients with ecDNA are not fully captured by other risk features its incorporation in an expanded definition of a high risk group of multiple myeloma should be investigated. Future studies will endeavor to explore the biological mechanism through which ecDNA are formed and influences outcomes in myeloma. Figure 1 Figure 1. Disclosures Richardson: Sanofi: Consultancy; GlaxoSmithKline: Consultancy; Karyopharm: Consultancy, Research Funding; AstraZeneca: Consultancy; AbbVie: Consultancy; Oncopeptides: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Janssen: Consultancy; Protocol Intelligence: Consultancy; Celgene/BMS: Consultancy, Research Funding; Secura Bio: Consultancy; Regeneron: Consultancy; Jazz Pharmaceuticals: Consultancy, Research Funding. Perrot: Abbvie: Honoraria; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene/BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Moreau: Abbvie: Honoraria; Amgen: Honoraria; Janssen: Honoraria; Sanofi: Honoraria; Celgene BMS: Honoraria; Oncopeptides: Honoraria. Thakurta: Oxford University: Other: Visiting Professor; BMS: Current Employment, Current equity holder in publicly-traded company. Anderson: Gilead: Membership on an entity's Board of Directors or advisory committees; Millenium-Takeda: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Sanofi-Aventis: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Scientific Founder of Oncopep and C4 Therapeutics: Current equity holder in publicly-traded company, Current holder of individual stocks in a privately-held company; Mana Therapeutics: Membership on an entity's Board of Directors or advisory committees. Munshi: Legend: Consultancy; Karyopharm: Consultancy; Takeda: Consultancy; Janssen: Consultancy; Novartis: Consultancy; Bristol-Myers Squibb: Consultancy; Amgen: Consultancy; Abbvie: Consultancy; Adaptive Biotechnology: Consultancy; Oncopep: Consultancy, Current equity holder in publicly-traded company, Other: scientific founder, Patents & Royalties; Celgene: Consultancy; Pfizer: Consultancy.

To identify therapeutically actionable genetic dependencies we have pursued various approaches to derive a deeper understanding of the oncogenic hallmarks of myelomagenesis. We have studied the long noncoding RNA (lncRNA) landscape in multiple myeloma (MM) and identified a large number of differentially expressed lncRNAs in MM versus normal plasma cells. These lncRNAs presumably drive the tumorigenesis and MM cell growth, and in turn be susceptible to therapeutic intervention. To this end, we have developed and utilized a CRISPR interference (CRISPRi)-based platform for decoding and targeting the lncRNA dependencies (LongDEPs) in MM. In this study, we have used RNA-seq of patient-derived CD138+ MM cells (n=360) and MM cell lines (n=70) to generate a priority list of 913 expressed intergenic lncRNAs. Then, to systematically interrogate the role of these lncRNAs in MM cell growth, we have performed a CRISPRi viability screen transducing 3 MM cell lines engineered to express a dCAS9-KRAB fusion protein, with a pooled library consisting of 7 sgRNAs against each of the 913 transcription start sites (TSS) and 576 negative control sgRNAs. Relative representation of sgRNAs was assessed by deep sequencing after 3 weeks and analyzed using the MAGeCK robust rank aggregation (RRA) algorithm. The most enriched or depleted sgRNAs were further tested in a secondary CRISPRi viability screen. Focusing on depleted sgRNAs, we have identified >30 unique LongDEPs; which were further validated via an antisense oligonucleotide (ASO)-based loss-of-function study in a panel of MM cell lines (n=11). A comparative transcritpomic analysis comparing data from 360 newly-diagnosed and clinically-annotated MM patients and 16 healthy donors showed significant upregulation of these LongDEPs in MM patient cells. Of note, specific longDEPs were found selectively upregulated in genetically-defined patient subsets, including high-risk MM carrying t(4;14), 1q gain or del17p. Moreover, at least 18 LongDEPs were identified as independent risk-predictors of clinical outcome in newly-diagnosed MM patients. The lncRNA RROL was identified as a leading LongDEP, with a dependency score on a par with positive controls such as IRF4 or MYC. This lncRNA is specifically overexpressed in MM patients after disease relapse, and its higher expression in newly diagnosed MM patients could predict a worse clinical outcome. We have validated the essential role of RROL in support of the proliferation and survival of MM cells both in vitro and in vivo in NOD SCID mice, using ASO-based loss-of-function studies. To explain this effect, we have characterized its role in the control of the pro-survival de novo lipogenesis (DNL) pathway via an unbiased lipid profiling and by measuring the incorporation of C 14-radiolabeled glucose into the lipid pool. Mechanistically, we have shown that RROL promotes the DNL pathway via transcriptional regulation of rate-limiting enzymes including ACC1. Using in vitro (RNA protein pull down) and in cellulo (RNA yeast-3-hibrid) assays, we have identified the transcription factor c-MYC as a relevant protein interactor of RROL. This interaction occurs at the chromatin level and is required for i) MYC occupancy at DNL gene loci (e.g. ACC1), as shown by both ChIP-qPCR and single molecule dual RNA FISH coupled with immunofluorescence; ii) MYC interaction with a number of transcriptional co-activators, including WDR82, as assessed in vitro in 3 MM cell lines using co-immunoprecipitation followed by Mass spectrometry (Co-IP/MS) and in cellulo using the proximity-dependent biotin identification assay (BioID) in Flp-In T-REx cells expressing a FLAG-BirA*-MYC fusion protein. Overall, our data indicate that RROL provides the chromatin scaffold to assemble a transcriptionally activated ribonucleoprotein complex - minimally composed by RROL, MYC and WDR82 - at gene regulatory loci of DNL rate-limiting enzymes. To develop therapeutic inhibitors of LongDEPs, starting with RROL, we have tested >70 ASOs following a multi-step screening approach. The anti-MM activity of 2 leading compounds was demonstrated in vitro and in vivo in 2 clinically relevant animal models, including a BLI-based orthotopic model. In conclusion, our work establish LongDEPs as an additional source of genetic dependencies in MM paving the way for their biologic, clinical and therapeutic characterization in this disease context. Disclosures Young: Dewpoint: Consultancy, Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees; Syros Pharmaceuticals: Consultancy, Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees; Camp4 Therapeutics: Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees; Fate Therapeutics: Membership on an entity's Board of Directors or advisory committees; Omega Therapeutics: Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees. Gryaznov: MAIA Therapeutics: Current Employment. Anderson: Scientific Founder of Oncopep and C4 Therapeutics: Current equity holder in publicly-traded company, Current holder of individual stocks in a privately-held company; Gilead: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Sanofi-Aventis: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Millenium-Takeda: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Mana Therapeutics: Membership on an entity's Board of Directors or advisory committees. Munshi: Novartis: Consultancy; Amgen: Consultancy; Janssen: Consultancy; Oncopep: Consultancy, Current equity holder in publicly-traded company, Other: scientific founder, Patents & Royalties; Celgene: Consultancy; Adaptive Biotechnology: Consultancy; Takeda: Consultancy; Karyopharm: Consultancy; Legend: Consultancy; Abbvie: Consultancy; Pfizer: Consultancy; Bristol-Myers Squibb: Consultancy.

The histone modifications and associated changes in chromatin structure and function have emerged as important epigenetic mechanisms impacting gene expression and have significant translational relevance in cancers, including multiple myeloma (MM). Epigenetic intervention with histone deacetylases (HDACs) inhibitors is emerging as a promising therapeutic strategy in combination with current anti-myeloma agents. Although pan-HDAC inhibitors have been shown to be effective both in preclinical and clinical setting, they seem to be associated with toxicity. It is, therefore, extremely important to understand the biological and molecular roles of individual HDACs to then selectively target them to limit toxicities observed with pan-HDAC inhibitors. Based on our observation that elevated HDAC8 expression correlates with poor overall survival in MM patients in three different datasets including one publicly available dataset (GSE39754), we evaluated its functional role in MM. HDAC8, a member of class I HDAC isoenzymes, is responsible for the deacetylation of lysine residues on the N-terminal part of the core histones as well as non-histone proteins. We performed genetic modulation of HDAC8 by loss-of-function studies, using shRNA as well as siRNAs targeting HDAC8. Downregulation of HDAC8 in 3 different MM cell lines caused MM cell growth inhibition in a time-dependent manner which was associated with induction of cell apoptosis. Consistently, treatment with a selective and potent HDAC8 inhibitor (OJI-1) caused a significant inhibition of MM cell growth in a panel of 20 MM cell lines (IC50 = 80 nM) in a time- and dose-dependent manner, while having a minimal impact on six PBMC samples from healthy donors both in resting and activated state (IC50 = 150 nM). The mechanism of cell death was apoptosis as demonstrated by annexin-labeling. Importantly, both the HDAC8 knockdown and OJI-1 treatment inhibited DNA breaks as evidenced from γH2AX expression or a single cell gel electrophoresis method to visualize and quantitate DNA breaks. HDAC8 inhibition also caused inhibition of RAD51 foci and HR activity, as measured by strand-exchange assay. Interestingly, non-homologous end joining in MM cells was not impacted by these treatments. Consistent with these data, the overexpression of HDAC8 in MM as well as in normal cells increased DNA breaks and HR activity. Furthermore, the inhibition of HDAC8 (by knockdown and OJI-1) inhibited, whereas its overexpression increased genomic instability, as assessed by micronucleus assay, in surviving MM cells. We also demonstrate that HDAC8 interacts with RAD51 and impacts its acetylation. The treatment of MM cells with HDAC8 inhibitor (OJI-1) increased RAD51 acetylation. Next, we examined the in vivo efficacy of the HDAC8 conditional knockdown in a human xenograft mouse model, using H929 cells injected subcutaneously in SCID mice. HDAC8 knockdown not only caused a significant reduction in tumor growth but also increased survival (p=0.0016) compared to mice injected with control cells. Evaluation of tumors from these mice confirmed in vivo inhibition of DNA breaks and HR activity, and induction of apoptosis following HDAC8-knockdown. HDAC8 inhibitor OJI-1 also synergistically increased the cytotoxicity of existing MM drugs including dexamethasone, bortezomib and lenalidomide. In conclusion, our results demonstrate that elevated HDAC8 in MM cells is involved in inhibition of apoptosis but also contributes to increased DNA breaks and dysregulation of homologous recombination and genome stability. Therefore, HDAC8 is a novel target for therapeutic application in MM. Selective and potent HDAC8 inhibitor OJI-1 has shown a favorable therapeutic index with synergistic effect in combination with existing MM drugs. Disclosures Hajek: Pharma MAR: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Research Funding; BMS: Consultancy, Honoraria, Research Funding. Munshi: Janssen: Consultancy; Bristol-Myers Squibb: Consultancy; Amgen: Consultancy; Takeda: Consultancy; Celgene: Consultancy; Karyopharm: Consultancy; Abbvie: Consultancy; Adaptive Biotechnology: Consultancy; Oncopep: Consultancy, Current equity holder in publicly-traded company, Other: scientific founder, Patents & Royalties; Novartis: Consultancy; Pfizer: Consultancy; Legend: Consultancy.

On an average, 1% of monoclonal gammopathy of undermined significance (MGUS) and 10% of smoldering Multiple Myeloma (SMM) progress to symptomatic MM every year within the first five years of diagnosis. The probability of progression significantly decreases for SMM patients after first 5 years. However, a distinct subset of SMM patients progress within 2 years and are re-classified as high-risk patients based on risk markers such as 20/2/20 or certain genomic features. Although recent studies have evaluated the high-risk genomic features for SMM but genomic background of SMM patients who do not progress to MM after long-term follow-up (>= 5 years) has not been described. Here, we evaluated transcriptomic and genomic changes enriched in non-progressor (NP) (no progression after 5 years of follow-up) precursor conditions (N=31) with those progressed within short period of time (N=71) and compared them with changes observed in newly diagnosed MM (N=192). Additionally, using transcriptome, epigenome and whole genome profiling we also studied additional unique samples from 18 patients at their precursor stage as well as when progressed to MM. Overall, we have observed significantly lower mutational load for NP SMM from progressor SMM (median SNV 4900 vs. 7881 p < 3e-04) with high sensitivity (0.83) and specificity (0.65) to separate NP from progressors. We have further developed a deep learning model by using more than 4500 genome wide features using ten-fold cross validation. This model indicated that not only the load but also the patterns of mutations (type, location, frequency) are different between two conditions. We also found that NP samples have significantly lower heterogeneity (p < 0.05). However, progressed samples showed similar mutational load and heterogeneity at precursor stage and MM. Among CNA differences, absence of gain or deletion of chr8 (not involving MYC region) were strong predictor of NP (OR=7.2 95% CI 2.2-24). Focal genomic loss was also significantly lower for NP (p=0.004) which was also reflected by low genome scar score (GSS) (p=0.07). Structural variant and copy number signature analysis also showed that NPs were showing significantly low exposure to non-clustered variable size genomic deletions. We observed similar frequency of primary translocations [t(11;14), t(4;14), and t(14;16)] in both progressor and NP samples as well as newly diagnosed MM. MYC translocation with any partner was not observed in NP samples, whereas 37% of progressor samples had a MYC translocations (OR=12.8). Adding all these differences including chr8 CNAs, MYC translocations, mutation burden, GSS, focal deletions, all driver mutations as well as primary translocations into recursive partitioning model to predict non-progressor SMM, we have identified a simple genomic model only involving chr8 CN changes and overall mutational burden to achieve a high sensitivity (0.82) and specificity (74%). Our transcriptomic analysis measured the distance between progressor and NP SMM as well as MM and found that NP SMM has greater difference with MM which is closer to progressor SMM. We quantified transcriptomic heterogeneity by using molecular degree of perturbation. This analysis showed that consistent with DNA changes, DNA repair pathway and MYC target genes are expressed similarly in NP SMM as in normal plasma cells compared to progressor SMM. Epigenomic analysis yielded 75 SEs regions differentially utilized between precursor and symptomatic MM stage using paired samples. The targeted genes included BMP6, PRDM1, STAT1, SERTAD2 and RAB21 and possibly regulating genes related to oncogenic KRAS activities. In conclusion, we define genomic characterization of non-progressor SMM and our results now provide the basis to develop molecular definition of SMM as well as risk driving features. Disclosures Munshi: Janssen: Consultancy; Pfizer: Consultancy; Legend: Consultancy; Novartis: Consultancy; Adaptive Biotechnology: Consultancy; Oncopep: Consultancy, Current equity holder in publicly-traded company, Other: scientific founder, Patents & Royalties; Takeda: Consultancy; Abbvie: Consultancy; Karyopharm: Consultancy; Amgen: Consultancy; Celgene: Consultancy; Bristol-Myers Squibb: Consultancy.

Background Lenalidomide, bortezomib, and dexamethasone (RVD) is a standard front-line regimen for both transplant eligible and ineligible multiple myeloma (MM) patients. Based on original APEX study data, obtaining a complete blood count (CBC) before every administration of bortezomib has been recommended. Waiting for labs could add several hours to each visit. This can be inconvenient and costly for patients, payers, and institutions. There is a clear need to decease the frequency of labs drawn to promote increased cost-savings, improved patient safety, and decreased clinic wait times. Methods The primary objective of this study was to implement and evaluate a process change to decrease the frequency of labs for eligible patients on RVD for MM. First, an institutional review board-approved descriptive, retrospective study that included patients aged ≥ 18 years with MM receiving treatment with RVD was performed to assess trends in lab values. The objective of the retrospective review was to identify patients who can safely receive RVD without repeat labs prior to each bortezomib injection. Results from this retrospective review was presented to Dana-Farber Cancer institute (DFCI) and Massachusetts General Hospital myeloma clinicians, as well as the DFCI Pharmacy and Therapeutics committee. After approval was granted to implement institutional changes, we evaluated the impact of the process change. Results Retrospective study results Eighty-nine patients were included in the study. All patients had a platelet (PLT) count ≥ 75,000 cells/µL on day 1 of cycle 2 and beyond. Grade ≥ 3 thrombocytopenia developed in less than 3% of patients. Greater than 93% patients had an absolute neutrophil count (ANC) ≥ 1,000 cells/µL on day 1 of cycle 2 and beyond. Grade 3 and 4 neutropenia developed in 6.7% and 1.1% of patients, respectively. This study demonstrated that beyond the first cycle, patients with PLTs ≥ 75,000 cells/µL and an ANC ≥ 1,000 cells/µL on the first day of a cycle do not need labs prior to each administration of bortezomib in the cycle. These results provided the rationale for implementation of a new routine workflow. Workflow Implementation Implementation of a new workflow started on July 1, 2021 and included 71 adult patients receiving RVD for MM. First, a communication order was added to all RVD treatment plan templates in the electronic medical record specifying, "if on Day 1: ANC is ≥ 1,000 and PLTs are ≥ 75,000, no labs are required for remainder of that cycle." Following that, a flowchart was developed by nursing that instructed infusion nurses to request a cancelation of future labs within the current treatment cycle (if the patient met criteria). Workflow Evaluation The Centers for Medicare & Medicaid Services reimbursement rates for a comprehensive metabolic panel and CBC with differential is $18.33. Following the implementation of this workflow, we saved over $3,904 in unnecessary healthcare related costs per month (figure 2). The average time it takes for our patients on RVD to check into their lab appointment and have labs resulted is 55 minutes. It takes an average of 47 minutes for patients to have bortezomib administered after labs are reviewed and orders are released for preparation (figure 1). Ultimately, patients spend more than 50% of their time in clinic waiting for labs compared to the time it takes to have bortezomib prepared, delivered, and administered. The implementation of this new workflow resulted in saving 195 hours of clinic chair time per month (figure 2). This time saved results in improved quality of life for patients who already have multiple visits at various healthcare facilities. Spending less time in clinic and reducing the frequency of venipunctures could potentially reduce the risk of bleeding, bruising, and discomfort amongst a patient population that is typically older and more at risk for complications. Conclusion This study demonstrates that it is economical, resourceful, and safe to implement a workflow process aimed at decreasing the frequency of lab draws in patients receiving RVD for multiple myeloma. It allowed our institution to maximize chair time that could be used for other patients and generate additional value-added revenue. This is particularly very important with the Covid-19 pandemic, where reducing several hours of wait time will keep our patients and staff safer. Figure 1 Figure 1. Disclosures Munshi: Legend: Consultancy; Janssen: Consultancy; Abbvie: Consultancy; Adaptive Biotechnology: Consultancy; Karyopharm: Consultancy; Oncopep: Consultancy, Current equity holder in publicly-traded company, Other: scientific founder, Patents & Royalties; Takeda: Consultancy; Amgen: Consultancy; Novartis: Consultancy; Celgene: Consultancy; Pfizer: Consultancy; Bristol-Myers Squibb: Consultancy.

New generation immunotherapies in Multiple Myeloma (MM) targeting BCMA, have shown remarkable clinical benefits. However relapse still occurs due to tumor intrinsic and extrisic resistance mechanisms including antigen loss related to mutation, deletion and splicing pattern changes. Two recent case reports including ours highlighted biallelic loss of BCMA as a cause for resistance to anti-BCMA targeting therapy. In both studies BCMA locus at 16p was deleted bringing in focus importance of del16p. Here, we have evaluated 2883 MM patients at diagnosis and relapse to understand frequency characteristics of somatic events targeting BCMA. We first evaluated the frequency of deletion involving the BCMA locus (16p13.13) in MM patients from multiple studies using WGS sequencing data as well as using Affymetrix Cytoscan HD and SNP 6.0 arrays. We observed del16p in 8.58 % (7.6% to 14.6% in individual studies) of newly-diagnosed patients (n=2458). Similar frequency was observed in relapsed MM patients not previously exposed to BCMA targeting therapy. Next, we evaluated genome wide copy number alterations (CNAs) in all patients with loss of BCMA locus and observed similar frequency of loss in both hyperdiploid MM (HMM) and non-HMM suggesting its independence from cytogentic subtypes of MM. Overall copy number loss was significantly higher in patients with BCMA loss compared to rest of the MM patients. Patients with loss of BCMA locus have increased mutational load (8202 with 95% HDI 6921 and 9535) compared to those without BCMA locus loss (6975 with 95% HDI 6626 - 7343); probability of difference greater than 0 was 96.8% and difference of the means were 1222 [95% CI -112 - 2589] We next evaluated co-occurrence of BCMA loss with other high risk events and observed del1p and del17p as being significantly associated with loss of BCMA locus [Odds ratio 19.37 (13.13-25.80), FDR = 1.57e-65; and 8.8 (6.39-12.15), FDR = 5.57E-39, respectively)]. Furthermore, we observed that when both BCMA and TP53 loss are present, they have same log ratio (sequencing) or smoothed copy numbers (SNP array). Similarly, we used CDKN2C as a proxy to chromosome 1p loss and observed that when both BCMA and CKDN2C loss are present in the same patient they tend to show similar copy number values. These data suggested a possibility of co-occurrence of these events in the same cell. To further investigate this observation, we used single cell DNA sequencing data from patients with sub clonal and clonal BCMA locus loss. scDNA sequencing showed that almost all cells with BCMA deletion also had TP53 deletion (95%). Interestingly, almost all cells with BCMA loss also had p53 loss, while not all cells with p53 loss had BCMA loss suggesting that the chronology of this copy number alternation may suggest first p53 loss followed by BCMA loss. We further investigated whether a bi-allelic BCMA loss was observed after anti-BCMA targeted CAR-T cell therapy by imputing the copy number alterations using single cell RNA sequencing data. Our data from this case also indicated that BCMA loss tend to co-occur with TP53 deletions (OR=5.67 [95% CI 4.12-7.84], p value < 0.0001). Moreover, TP53 mutations were also more frequent in patients with del16p and del17p, compared to patients who only had del16p or del17p. In summary, our data from large scale copy number profiles at the diagnosis and relapse showed that monoallelic BCMA deletions are frequent events, patients with these events show increased aneuploidy, mostly deletions, potentially making these cells vulnerable for biallelic loss of genes, especially under the pressure of targeted therapy. Our results also highlight that BCMA expressions in bulk sample may not detect the presence or absence of cells with target loss and therefore combining strategies at bulk and single cell level are necessary to understand the disease status. These results suggest the need to study del16p in patients being targeted for BCMA-directed therapy and its association with other risk factors in MM. Disclosures Thakurta: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Anderson: Celgene: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Sanofi-Aventis: Membership on an entity's Board of Directors or advisory committees; Millenium-Takeda: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Scientific Founder of Oncopep and C4 Therapeutics: Current equity holder in publicly-traded company, Current holder of individual stocks in a privately-held company; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Mana Therapeutics: Membership on an entity's Board of Directors or advisory committees. Munshi: Takeda: Consultancy; Adaptive Biotechnology: Consultancy; Amgen: Consultancy; Karyopharm: Consultancy; Celgene: Consultancy; Abbvie: Consultancy; Oncopep: Consultancy, Current equity holder in publicly-traded company, Other: scientific founder, Patents & Royalties; Novartis: Consultancy; Legend: Consultancy; Pfizer: Consultancy; Janssen: Consultancy; Bristol-Myers Squibb: Consultancy.

Background On average 10% of SMM patients progress to symptomatic MM per year with in first 5 years of diagnosis. However, a subset of SMM patients re-classified as high risk patients on the basis of risk markers which identify risk of progression within 2 years. Although recent studies have evaluated the high-risk SMM, genomic background of SMM patients who do not progress to MM after long-term follow-up (>=5 years) has not been described. Methods Here, we evaluated transcriptomic and genomic changes enriched in non-progressor (NP) (no progression after 5 years of follow-up) precursor conditions (N=31) with those progressed within short period time (N=71) and compared them with changes observed in newly diagnosed MM (N=192). Additionally, using transcriptome, epigenome and whole genome profiling we also studied additional unique samples from 18 patients at their precursor stage as well as when progressed to MM. Results Overall, we have observed significantly lower mutational load for NP SMM (median SNV 5460 vs. 7018, p 90% accuracy and >0.80 area under the curve on ROC using ten-fold cross validation. This indicated that not only the load but also the patterns of mutations (type, location, frequency) are different between two conditions. We also found that NP samples have significantly lower heterogeneity (p 80%) with AUC score 0.80. Our transcriptomic analysis measured the distance between progressor and NP SMM as well as MM and found that NP SMM are less similar to MM which is closer to progressor SMM. Epigenomic analysis yield that 75 SEs regions were differentially utilized between precursor and symptomatic MM stage. The targeted genes included BMP6, PRDM1, STAT1 and RAB21 and possibly regulating genes related to oncogenic KRAS activities. Conclusions In conclusion, our results now provide the basis to develop genomic definition of SMM as well as risk driving features.

Background Immunotherapies in MM targeting BCMA, have shown remarkable clinical benefits. However, two recent reports highlighted that biallelic loss of BCMA cause resistance to anti-BCMA therapy. In both studies BCMA locus was deleted bringing in focus importance of del16p. We have evaluated 2883 MM patients at diagnosis and relapse to understand frequency of BCMA targeting events and characteristics of MM patients with BCMA deletion. Methods We observed del16p in 8.58% (7.6% to14.6% in individual studies) of newly-diagnosed patients (n=2458).Frequency of 16p loss in both HMM and NHMM were similar, suggesting its independence from MM subtypes. Overall CN loss was significantly higher in patients with BCMA loss compared to rest of the MM patients. High risk deletion events such as del1p and del17p were more likely to be observed in patients with loss of BCMA locus (OR [95% CI] 19.3(13.1-25.8), FDR = 1.5e-65; and 8.8(6.3-12.1), FDR = 5.5E-39, respectively)]. MM patients with loss of BCMA locus have increased mutational load (8202 with 95% HDI 6921 and 9535) compared to those without BCMA locus loss (6975 with 95% HDI 6626 – 7343); probability of difference greater than 0 was 96.8% and difference of the means were 1222 [95% CI 112-2589]. To understand the risk profile of patients with loss of BCMA locus, we next focused on the observation that BCMA loss frequently co-occurs with other deletions. Results We observed that when BCMA and TP53 or BCMA and del1p loss are present in the same patient, they are likely to have same clonality. These data suggested a possibility of co-occurrence of these events in same cell. To further investigate this observation, we used single cell DNA sequencing data from patients with sub clonal and clonal BCMA locus loss. Interestingly, almost all cells with BCMA loss also had p53 loss, while not all p53 loss cells had BCMA loss suggesting that the chronology of this copy number alternation may suggest first p53 loss followed by BCMA loss. Our data from a patient with BCMA targeting therapy also indicated that BCMA loss tend to co-occur with TP53 deletions (OR=5.67 [95% CI 4.12-7.84], p value Conclusions Our data from large scale copy number profiles showed that even without treatment pressure, monoallelic BCMA deletions are frequent events. Moreover, patients with these events show increased genomic loss. Such behavior potentially make these cells vulnerable for biallelic loss of other genes. Our results highlight that by looking at mRNA or protein expressions at bulk sample would not directly indicate the presence or absence of cells with target loss and therefore evaluating single cell level data are necessary. These results suggest the need to study del16p in patients being targeted for BCMA-directed therapy and its association with del17p raises question about the role of BCMA targeted therapy in high-risk myeloma.

Introduction To the best of our knowledge, no previous study regarding the serum telomerase levels in Maras powder users (MPUs) has been founded. The aim of the current study was to investigate serum telomerase levels in smokers and MPUs. Materials and Methods The study was carried out with 98 patients (36 MPUs, 32 smokers and 30 non-smokers). Blood samples were collected, and after having measured the serum telomerase and malondialdehyde (MDA) levels of the patients, comparison were made between the groups. Result It has been observed that the serum telomerase and MDA levels of smokers (p< 0.001) and MPUs (p< 0.001) were significantly higher compared to those of the non-smoker control subjects. In addition, the levels of serum telomerase and MDA were observed to be higher in the MPU group compared to those of the smoker group (p< 0.001). Conclusions The levels of serum telomerase and MDA were observed to be higher among MPUs and smokers. In this context, it may be useful to further measure and assess telomerase activity in such patients in order to better determine the harmful effects associated with these habits.

We recently shown that high-dose melphalan (HDM) followed by autologous stem cell transplant (ASCT) as first line therapy in young ( A significant change in frequency of driver mutations including RAS/RAF, FAM46C, TP53, and DIS3 was not observed at the time of relapse. Clonality level was increased only for KRAS (p=0.054), while all other specific driver genes had similar clonality level at diagnosis and relapse. Interestingly, a significant increase in mutations involving MYO16 and SLC7A8 genes was observed at relapse in both arms, implicating components of the induction regimen (RVD). Investigating the mutational signature utilization in only newly acquired mutations identified 4 signatures: APOBEC, HR Double Strand Repair, clock-like signature, and unknown. k-means clustering analysis of samples based on signature utilization showed four distinct clusters. All patients clustering with high DNA repair signature utilization were in the HDM arm (65% HDM patients), the majority of whom achieved CR or sCR (74%); these patients acquired 8308 (range 3302-19107) new mutations between diagnosis and relapse. None of the RVD only treated patients were in this cluster. The remaining 35% HDM group patients were clustered with RVD samples and showed unknown signature utilization. Furthermore, motif enrichment analysis identified CYWR and ATGAGATV (p < 1e-130) as enriched motifs around the new mutations in HDM compared to RVD cohort. Importantly and as expected, DNA damage repair pathway genes were frequently targeted in the HDM group: 72% HDM samples accumulated DDR gene mutations vs. only 17% in the RVD alone arm (p < 0.001). At the time of relapse, 100% HDM arm patients had at least one DDR gene mutation and 80% had two or more, while only 37% RVD only group had one or more such mutation. Finally, we have reconstructed phylogenetic and evolutionary trajectories based on mutation and copy-number data from samples at diagnosis and relapse. The clonal composition in both arms was similar at diagnosis; however, HDM caused a significant shift to more subclonal mutations at relapse. chromothripsis and chromoplexy events were detected in 30% patients at diagnosis, which remained constant at relapse regardless of treatment. In summary, we describe significant accumulation of mutations following high dose melphalan. This fundamental molecular change in the disease at relapse, suggests the need for reappraisal of the optimal use and sequencing of high dose melphalan in the era of novel agents. Disclosures Fulciniti: NIH: Research Funding. Richardson:Celgene/BMS, Oncopeptides, Takeda, Karyopharm: Research Funding. Thakurta:Oxford University: Other: visiting professor; Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Perrot:Amgen, BMS/Celgene, Janssen, Sanofi, Takeda: Consultancy, Honoraria, Research Funding. Moreau:Sanofi: Consultancy, Honoraria; Celgene/Bristol-Myers Squibb: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Takeda: Honoraria; Novartis: Honoraria; Abbvie: Consultancy, Honoraria; Amgen: Consultancy, Honoraria. Anderson:Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Oncopep and C4 Therapeutics.: Other: Scientific Founder of Oncopep and C4 Therapeutics.; Sanofi-Aventis: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Millenium-Takeda: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees. Parmigiani:Phaeno Biotehnologies: Current equity holder in publicly-traded company; CRA Health: Current equity holder in publicly-traded company; Foundation Medicine Institute: Consultancy; Delphi Diagnostics: Consultancy; BayesMendel Laboratory: Other: Co-lead. Munshi:Amgen: Consultancy; AbbVie: Consultancy; Karyopharm: Consultancy; Takeda: Consultancy; Adaptive: Consultancy; Janssen: Consultancy; C4: Current equity holder in private company; OncoPep: Consultancy, Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties; BMS: Consultancy; Legend: Consultancy.

Long noncoding RNA (lncRNAs) are key epigenetic factors that drive the origin and progression of human cancers via mechanisms that are largely unknown. We have previuosly reported the clinical significance of a lncRNA signature in multiple myeloma (MM) as independent risk predictor for clinical outcome; and recently identified a lncRNA RROL (RNA Regulator of Lipogenesis) with impact on MM cell proliferation. Here we describe a unique regulatory function for RROL in the control of gene networks involved in the de novo lipogenesis (DNL) pathway, ultimately impacting MM cell growth and survival. Based on growth and survival impact of RROL depletion, we performed integrated transcriptomic analysis of RNA-seq data after RROL depletion in MM cell lines and CD138+ patient MM cells, and identified a set of significantly modulated metabolic genes including the acetyl Co-A Carboxylase 1 (ACC1) gene, encoding a rate-limiting enzyme of the DNL pathway. This metabolic pathway converts nutrients into fatty acids serving for energy storage or biosynthesis of membranes and signaling molecules. Consistent with the transcriptional control of ACC1, we have observed that RROL inhibition in cell lines and primary MM cells significantly decreased the incorporation of C14-radiolabeled glucose into de novo synthesized lipids. Importantly, supplementation with exogenous palmitate, the main downstream product of DNL pathway, rescued the growth inhibitory effect of RROL depletion on MM cells, further confirming the importance of the DNL pathway in the oncogenic activity of RROL in MM. To understand the molecular mechanism through which RROL regulates ACC1 expression and its metabolic axis, we evaluated the RROL interactome in MM cells. RNA-Protein Pull Down (RPPD) and in vivo RNA yeast three-hybrid (Y3H) assays led to the identification of MYC as relevant direct partner of RROL. These results were further validated by qRT-PCR analysis of MYC-bound RNA obtained through RNA immunoprecipitation (RIP) assay. Using experimental model of conditional MYC KD (P493-6), we found that RROL exerts regulatory activity on ACC1 only in the presence of MYC. Mapping of MYC genomic occupancy by ChIP-seq and gene expression after MYC KD in MM cells revealed that ACC1 is a direct transcriptional target of MYC in cells expressing RROL. These data indicate that RROLand MYC cooperate in the transcriptional control of ACC1. Moreover, we found that RROL itself is transcriptionally regulated by MYC, suggesting the existence of a feed-forward regulatory loop in which MYC enhances the expression of RROL that, in turn, drives MYC transcriptional activity to ACC1. We hypothesized that RROL may shape the protein interacting network of MYC to confer specificity for ACC1 promoter. To this end, we performed mass spectrometry analysis of MYC interactome in three MM cell lines in the presence or in the absence of RROL and identified the transcriptional modulator WDR82 as RROL-dependent MYC partner. Interestingly, WDR82 directly interacts with RROL as assessed in the RPPD and RNA Y3H assays, and transcriptionally regulates ACC1 in RROL-dependent manner. These data indicate that RROL catalyzes the interaction of MYC with the transcriptional modulator WDR82 to form a transcriptional ternary complex regulating ACC1 expression. To therapeutically antagonize the RROL lipogenic signaling we have pre-clinically tested small molecule inhibitors of ACC1 (ACC1i). We have observed significant anti-MM activity of ACC1i in vitro in a large panel of MM cell lines and primary MM cells from patients; and in vivo in mouse models of human MM including the localized subcutaneous model and the disseminated model that establish a more aggressive systemic disease. Importantly, we have now developed clinically applicable ASOs and small molecule-like compounds to directly target RROL in MM cells. These studies are ongoing and will be presented. In conclusion, we here report a unique regulatory function of a novel lncRNA supporting MM cell growth via its control of the lipogenic metabolic axis. The availability of oral inhibitors of ACC1 as well as the ongoing development of RROL inhibitors may allow clinical application of this unique targeted therapy in MM. Disclosures Fulciniti: NIH: Research Funding. Chauhan:Oncopeptide AB: Consultancy; consultant to Stemline Therapeutics, Inc., and Equity owner in C4 Therapeutics.: Consultancy, Other: Equity owner in C4 Therapeutics.. Anderson:Celgene: Membership on an entity's Board of Directors or advisory committees; Millenium-Takeda: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Sanofi-Aventis: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Oncopep and C4 Therapeutics.: Other: Scientific Founder of Oncopep and C4 Therapeutics.. Munshi:Takeda: Consultancy; Karyopharm: Consultancy; AbbVie: Consultancy; Amgen: Consultancy; Legend: Consultancy; Adaptive: Consultancy; Janssen: Consultancy; C4: Current equity holder in private company; OncoPep: Consultancy, Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties; BMS: Consultancy.

Multiple myeloma (MM) is a proliferation of terminally differentiated plasma cells (PC) producing monoclonal immunoglobulins (Ig), most commonly IgG and IgA (50% and 25% respectively), and less frequently, light-chain only disease, non-secretory, and IgD. IgM-MM is a rare entity ( We performed deep whole-genome sequencing on five IgM samples as well as 211 MM and 34 WM samples, and transcriptome sequencing on the IgM samples as well as 30 MM, 35 WM, and 3 PC. All IgM-MM samples harbored t(11;14) which combines super enhancers in Ig genes with CCND1. All translocations involved VHDHJH regions (Figure 1A) at the immunoglobulin heavy chain (IGH) locus, compared to IgG/IgA MM samples that had predominantly switch-region translocations (Figure 1B/C). Switch-region translocations are generated through class-switch recombination (CSR) in mature B-cells in germinal centers (GC), and VHDHJH translocations occur during recombination at the early pro-B-cell stage in the bone marrow (BM). While IgG/IgA-MM displayed evidence of CSR with deletions between IGHM switch-region and IGHG/IGHA switch regions, IgM-MM had no such events. IgM-MM therefore appears to undergo malignant transformation prior to late-stage B-cell maturation, after which CSR is unlikely, which is supported by a lack of progression of IgM-monoclonal gammopathy of undetermined significance (MGUS) to non-IgM-MM. IgM-MM also displayed similar copy number variation (CNV) patterns and driver mutations compared to non-IgM-MM suggesting similar progression events. Unsupervised hierarchical clustering using differentially expressed genes between non-IgM-MM and WM separated the IgM-MM samples within non-IgM-MM. This indicates a closer molecular homology to MM compared to WM with a unique signature for this group not accounted for by the t(11;14) translocation. Running the same analysis using only B-cell specific transcription factors (TFs) yielded similar results, with separation of WM and MM and preferential clustering of IgM-MM within the latter while also exhibiting a unique signature (Figure 1D). Some noteworthy examples were the upregulation of PBX3, PAX5, BCL11A, and ATF2, and the downregulation of PRDM1 and BCL3 compared to non-IgM-MM. The loss of PAX5 and upregulation of PRDM1 in B-cells has been implicated in promoting commitment to PC differentiation, while BCL11A was found essential for early B-cell progenitor development through the GC but extinguished in terminally differentiated PC. It appears that IgM-MM has therefore a more immature phenotype compared with non-IgM-MM, which further supports the previously discussed findings of its pre-GC origin and lack of terminal development. Three clinically relevant targets were noted to be upregulated in IgM-MM, Bruton's tyrosine kinase (BTK), CD20 and BCL-2. BTK was significantly higher in IgM-MM compared to non-IgM-MM (log2fold=1.3; FDR0.2). This could elucidate a more prominent role for BTK-inhibition in the IgM-MM subgroup. Furthermore, as documented in t(11;14)-MM, IgM-MM had elevated transcript levels of CD20 with possible targeting using anti-CD20 antibodies. Finally, elevated levels of BCL-2 in both IgM and non-IgM-t(11;14)-MM were observed, an established target for both single-agent and combination therapy. Interestingly, although not significant, IgM-MM had lower transcript levels of BCL-XL and MCL-1 compared to non-IgM-t(11;14)-MM, believed to be a predictor of higher sensitivity to venetoclax, and therefore an important guide for treatment choice. Clinical data however is lacking, and further investigations are needed to fully understand the potential role of these drugs in treating IgM-MM. In summary we describe a unique genomic and transcriptomic profile of IgM-MM, compared to both non-IgM-MM and WM, that describes its cellular origin and provides the rationale for potential therapeutic intervention. Disclosures Fulciniti: NIH: Research Funding. Anderson:Gilead: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Sanofi-Aventis: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Millenium-Takeda: Membership on an entity's Board of Directors or advisory committees; Oncopep and C4 Therapeutics.: Other: Scientific Founder of Oncopep and C4 Therapeutics.. Parmigiani:Phaeno Biotehnologies: Current equity holder in publicly-traded company; CRA Health: Current equity holder in publicly-traded company; Foundation Medicine Institute: Consultancy; Delphi Diagnostics: Consultancy; BayesMendel Laboratory: Other: Co-lead. Treon:Bristol-Meyer-Squibb: Honoraria, Research Funding; Pharmacyclics: Honoraria, Research Funding. Mohty:Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau; GSK: Consultancy, Honoraria, Research Funding, Speakers Bureau; BMS: Consultancy, Honoraria, Research Funding, Speakers Bureau; Stemline: Consultancy, Honoraria, Research Funding, Speakers Bureau; Jazz Pharmaceuticals: Consultancy, Honoraria, Research Funding, Speakers Bureau; Sanofi: Consultancy, Honoraria, Research Funding, Speakers Bureau; Takeda: Consultancy, Honoraria, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau. Munshi:Takeda: Consultancy; BMS: Consultancy; OncoPep: Consultancy, Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties; C4: Current equity holder in private company; Janssen: Consultancy; Adaptive: Consultancy; Legend: Consultancy; Amgen: Consultancy; Karyopharm: Consultancy; AbbVie: Consultancy.

Introduction Lenalidomide, bortezomib, and dexamethasone (RVD) is a standard first-line regimen for patients with newly diagnosed multiple myeloma and is associated with high response rates and improvement in progression-free survival and overall survival compared to traditional chemotherapy regimens. Traditional (RVD Classic, RVD Lite) and non-traditional (RVD Premium Lite, RVD Ultra Lite) variations of the RVD regimen are utilized at Dana-Farber Cancer Institute (DFCI) and have not been fully evaluated in terms of safety and tolerability. RVD Premium Lite is administered in a 28-day cycle with weekly bortezomib; whereas, RVD Ultra Lite administers three weekly doses of bortezomib instead of four (Table 1). These two regimens have not been fully evaluated in terms of safety, tolerability, and efficacy. Selection is based on provider preference in addition to flexibility of dosing schedule. The regimens also allow for convenience of weekly dosing while keeping dose intensity. This retrospective, descriptive analysis is the first study to explore the safety, tolerability, and efficacy of four different RVD regimens used at DFCI. Methods This single-center, retrospective, descriptive analysis identified 90 newly diagnosed patients with multiple myeloma treated at DFCI main campus for >2 cycles of an RVD-based regimen in the front-line setting. We reviewed patients started on treatment from January 2017 to December 2019. Patients were excluded if treated primarily at an outside institution or satellite campus. Results A total of 90 patients were included between January 2017 to December 2019, and median age was 69.5 years (range 44-87). Most patients had either standard-risk or unknown cytogenetics. Of the 44 patients with available International Staging System (ISS) information, the majority were R-ISS/ISS I or II. The most common M-protein type at diagnosis was IgG (56.7%), followed by light chain restricted disease (25.6%). In terms of traditional and non-traditional RVD regimens, most patients received RVD Classic (33.3%) or RVD Ultra Lite (32.2%), followed by RVD Lite (23.3%) and RVD Premium Lite (11.1%). Patients in RVD Lite and RVD Ultra Lite groups were of older age when compared to the RVD Classic group (P Lenalidomide dosing delays and reductions trended higher in the RVD Classic regimen at 14.3%, followed by RVD Ultra Lite at 12.3%. Bortezomib dosing delays and reductions were similar between the RVD Lite and RVD Classic regimens at 11.8% and 11.2%, respectively. Overall, combined lenalidomide and bortezomib dosing delays/reductions trended higher in the RVD Classic (14.3%/11.2%) and RVD Lite (11.0%/11.8%) compared to RVD Ultra Lite (12.3%/9%) and RVD Premium Lite (10.8%/9.6%). The most common toxicities noted with all variations of the RVD regimen were peripheral neuropathy, cutaneous toxicity, infection, diarrhea, and constipation. The highest rates of adverse events among all RVD regimens were infection and peripheral neuropathy. Peripheral neuropathy was slightly higher in the RVD Premium Lite and RVD Classic regimen at 8.43% and 8.70%, respectively, compared to RVD Lite and RVD Ultra Lite at 7.1% and 7.7%, respectively. No significant difference in toxicities were seen when regimens were compared (p=0.1369). Intolerance leading to therapy change trended higher in the RVD Lite group at 23.8%, followed by RVD Classic and RVD Ultra Lite at 16.7% and 10.3%, respectively. Nineteen percent of patients in the RVD Lite group had minimal response or progression leading to therapy change, which was highest among all RVD regimens. Rate of transplant was highest in the RVD Classic group at 36.7%, followed by RVD Premium Lite at 20%. There was no significant difference in intolerance, minimal response or progression, maintenance, continued induction or planned change, transplant, and death between regimens (p=0.089). In terms of progression-free survival, no differences were seen between the groups (p=0.36). Conclusion In conclusion, the current investigation allowed us to assess the safety, tolerability, and efficacy of traditional and non-traditional variations of the RVD regimen in multiple myeloma used at our institution. There are minimal differences between each regimen when toxicities are managed appropriately. Disclosures Richardson: Celgene/BMS, Oncopeptides, Takeda, Karyopharm: Research Funding. Mo:Celgene/BMS: Membership on an entity's Board of Directors or advisory committees.

Multiple myeloma (MM) is a hematological malignancy characterized by various genetic abnormalities including translocations involving the IgH gene at 14q32. Amongst these, t(11;14) is one of the most common translocations. Recent clinical data suggests a significant impact of Venetoclax, a small molecule inhibitor of BCL2, in this subgroup of MM patients, representing the first example of personalized medicine in MM and opening a wide range of research aiming at elucidating its mechanism of action. However, despite the initial positive response to the drug, a significant proportion of patients eventually develop resistance and relapse. To delineate the mechanisms that contribute to the development of an acquired drug-tolerant/resistance phenotype, we modeled the response to Venetoclax in 2 MM cell lines (KMS27 and KMS-12PE with IC50 of 35.47nM and 3.64nM, respectively). Whereas the vast majority of cells plated into 96-well plates were killed within a few days of exposure to a high dose of drug concentration, we detected a small fraction of viable, largely quiescent cells, which were expanded by culturing them in high doses of Venetoclax. We successfully generated 4 independent clones from each cell line, that were single cell-cloned with continued growth in the presence of high doses of Venetoclax. These clones labelled as drug-tolerant expanded persisters (DTEP) were investigated for the mechanisms driving drug tolerance and resistance against Venetoclax. First, we observed that altered expression of apoptotic regulators were associated with Venetoclax resistance in DTEP cells. We indeed observe a significant increase in the anti-apoptotic proteins MCL1 and BCL-XL in DTEP clones, which translated in our observation of improved sensitivity to MCL1 and BCL-xL inhibitors (S63845 and A-1155463 respectively). We performed both whole genome sequencing (WGS) and RNA-seq to evaluate if DTEP cells undergo transcriptional adaptation via genomic or epigenomic regulation and transcriptional reprograming during development of acquired drug resistance. While, WGS analysis didn't show any significant differences between parental and resistant clones, transcriptomic analysis showed both shared and unique transcriptome signatures in the DTEP clones. Gene set enrichment analysis (GSEA) of the common significantly modulated genes in the resistant clones revealed that the genes belonging to the PKA-ERK-CREB pathway were significantly upregulated in resistant clones, while apoptotic genes were downregulated compared to parental cells. Western blot analysis confirmed activation of ERK and the downstream target cAMP response element-binding (CREB) gene in resistant clones; and importantly treatment with the ERK inhibitor U0126 rescued the resistance to Venetoclax, providing a synergistic activity in resistant clones but not in parental cells, with decreased cell viability and increased apoptotic cell death. To evaluate if the ERK pathway was also associated with intrinsic resistance to Venetoclax, we assessed a panel of 24 MM cell lines and then calculated Pearson correlation coefficients between the measured drug activity and individual gene expression levels (by RNA-seq) across all cell lines and subjected the resulting rank-ordered gene list to GSEA. This analysis showed that mechanisms driving the DTEP phenotype are different from those associated with the intrinsic resistance to Venetoclax. RNA processing and splicing pathways were strongly enriched, with high expression of these genes correlating with increased sensitivity. Moreover, among the genes correlated with a resistant phenotype, we observed that the gene G0S2 was significantly downregulated in the resistant cell lines. G0S2 is a tumor suppressor gene that binds and inhibits BCL2. Interestingly, we observed that while G0S2 is downregulated in MM compared to normal plasma cells, t(11:14) patients have a higher expression. We are now in the process of validating G0S2 in MM and its contribution to Venetoclax sensitivity in MM. In conclusion, we here provide evidences of molecular mechanisms of acquired resistance to Venetoclax with activation of the ERK pathway as one of the prime targets. Combining Venetoclax with ERK inhibitor may therefore prevent or overcome the acquired resistance to Venetoclax observed in MM patients. Disclosures Fulciniti: NIH: Research Funding. Munshi:C4: Current equity holder in private company; OncoPep: Consultancy, Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties; BMS: Consultancy; Adaptive: Consultancy; Legend: Consultancy; Amgen: Consultancy; AbbVie: Consultancy; Karyopharm: Consultancy; Takeda: Consultancy; Janssen: Consultancy. Anderson:Oncopep and C4 Therapeutics.: Other: Scientific Founder of Oncopep and C4 Therapeutics.; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Sanofi-Aventis: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Millenium-Takeda: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees.

Multiple myeloma (MM) and its precursor condition MGUS are characterized by chromosomal aberrations. Here, we comprehensively characterize the order of occurrence of these complex genomic events underlying MM development using 500 MGUS, and MM samples. We identify hyperdiploid MM (HMM) and non-HMM as genomically distinct entities with different evolution of the copy number alterations. In HMM, gains of 9,15 or 19 are the first and clonal events observed as clonal even at MGUS stage. These events are thus early and may underlie initial transformation of normal plasma cells to MGUS cells. However, CNAs may not be adequate for progression to MM except in 15% of the patients in whom the complex subclonal deletion events are observed in MM but not MGUS. In NHMM, besides the driver translocations, clonal deletion of 13 and 1q gain are early events also observed in MGUS. We combined this information to propose a timeline for copy number alteration.

Obstructive sleep apnea syndrome (OSAS) is a common disorder and in subjects with OSAS the prevalence of hypothyroidism is approximately 1.2–11 %. The episodes of hypoxia/reoxygenation associated with the respiratory disturbances observed in subjects with OSAS increases the risk of cardiovascular diseases. Hypothyroidism; primary or subclinical, has several effects on cardiovascular system. In our study, we investigated carotid artery intima-media thickness (IMT) which is an early sign of atherosclerosis, in OSAS subjects with hypothyroidism. Subjects who admitted to Kahramanmaras Necip Fazil City State Hospital Chest Diseases out-patient clinic between May 2014 and January 2016 for snoring and had polysomnographic evaluation at the sleep laboratory were included in this study. Each subject was evaluated for serum thyroid function tests and carotid artery IMT was measured by a Doppler ultrasound. Mean carotid artery IMT values in the isolated OSAS, OSAS plus hypothyroidism, and control groups were 0.67 ± 0.12, 0.8 ± 0.12, and 0.54 ± 0.08 mm, respectively; difference between groups was statistically significant (p

Background Lenalidomide, bortezomib, and dexamethasone (RVD) is a standard front-line regimen for both transplant eligible and ineligible multiple myeloma (MM) patients. Based on original APEX study data, which reported development of thrombocytopenia, anemia, and neutropenia in 35%, 26%, and 19%, respectively, complete blood counts before every administration of bortezomib has been recommended. Although an injection of bortezomib takes only 3-5 seconds, waiting for the results of a complete blood count (CBC), with or without a comprehensive metabolic panel (CMP), can add approximately an hour to the visit. This can be cumbersome for patients, who are usually older adults, and it can also present a financial burden for patients, payers, and institutions. Methods The primary objective of this study was to identify patients who can receive RVD safely without repeat labs prior to each bortezomib injection. Secondary objectives included evaluation of costs and appointment visit times. Eighty-nine patients were identified in an institutional review board- approved descriptive, retrospective, medical chart review of patients with MM aged ≥ 18 years who received ≥3 cycles of RVD treatment from January 1, 2016 to January 31, 2020. Sixty-eight patients (76%) received bortezomib on a weekly schedule and twenty-one patients (24%) received bortezomib on a twice weekly schedule. Seventy-four patients (83%) were newly diagnosed and fifteen patients were relapsed/refractory when they began treatment with RVD. Results Thrombocytopenia On day 1 of each cycle (starting cycle 2), 100% of patients had a platelet (PLT) count ≥75,000 cells/µL (Table 1 and 2). Less than 10% of patients developed grade ≥ 2 thrombocytopenia, including 2% and 0% with grade 3 and 4 events, respectively. No patients had treatment delays or interventions for any grade of thrombocytopenia. Only one patient (1.6%) had platelets less than 50,000 cells/µL on day 15 of cycle 2. In cycles 3 and 4, 100% of patients had platelets greater than 50,000 cells/µL on each treatment day. Neutropenia The majority of patients had an absolute neutrophil count (ANC) ≥ 1,000 cells/µL at the beginning of each cycle: 94%, 100%, and 100% in cycles 2-4, respectively. Of the patients with absolute neutrophils ≥ 1,000 cells/µL on the first day of cycles 2-4, more than 93% of the patients had absolute neutrophils ≥ 1,000 cells/µL on subsequent days of cycles 2-4 (Table 3 and 4). Grade 3 and 4 neutropenia was observed in 6.7% and 1.1% of patients, respectively. Only two patients (2.9%) had treatment delays. Filgrastim was administered for 3 incidences of grade 3 neutropenia and 1 incidence of grade 4 neutropenia. One patient (1.4%) had a dose reduction in lenalidomide due to grade 3 neutropenia. We did not observe any significant impact of either once a week or twice a week regimens on changes in platelet or absolute neutrophil counts. Serum Creatinine and Total Bilirubin No significant trends occurred in serum creatinine or total bilirubin. The average serum creatinine and total bilirubin for both cohorts was ≤ 1.2 mg/dL throughout the study for cycles 1-4. Wait Time and Costs Implications We evaluated the time saved and expense reduction by checking labs only on day 1 of each cycle and identified an average time saving of 3 to 4.5 hours and financial savings of $1,542 per cycle for each patient. Conclusion This study demonstrates that beyond the first cycle, patients with platelets ≥ 75,000 cells/µL and absolute neutrophils ≥ 1,000 cells/µL on the first day of a cycle do not need labs prior to each administration of bortezomib (while on RVD regimen). Furthermore, a CMP does not need to be obtained prior to each dose of bortezomib, unless otherwise indicated, since no significant trends occurred in serum creatinine or total bilirubin in our study. Decreased monitoring of CBCs and reducing the number of labs needed during each cycle will improve resource utilization, save money, and save time for patients and health care providers. These cytopenias were typically cyclic and transient. Prescribing information for bortezomib and lenalidomide recommend monitoring compete blood counts and platelets at several intervals and neither medication package inserts give guidance on how frequent serum creatinine and total bilirubin should be monitored. With so many recommendations for monitoring, the frequency of obtaining labs is often left at the discretion of the provider. Disclosures Munshi: BMS: Consultancy; OncoPep: Consultancy, Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties; C4: Current equity holder in private company; Janssen: Consultancy; Adaptive: Consultancy; Legend: Consultancy; Amgen: Consultancy; AbbVie: Consultancy; Karyopharm: Consultancy; Takeda: Consultancy.

Multiple myeloma (MM) is a genomically heterogenous malignancy characterized by a number of copy number alterations (CNA). Moreover, there is a clear evolution of genomic changes that may affect prognosis. To identify the drivers of this inherent genomic instability, we applied an integrated genomics approach utilizing genomic data for copy number changes and transcriptomic profile. We first identified genes whose expression correlated with total copy number events in a patient dataset (gse26863, n=246). We then applied those genes to identify the genes whose elevated expression correlated with both overall and event free survival in two different datasets (IFM70, n=170; gse2408, n=559). Elevated expression of this 30 gene signature also correlated with poor overall as well as event free survival in a third myeloma dataset (MMRF; P In summary, we demonstrate that elevated ATAD2 contributes to dysregulation of DNA repair and genome stability and is required for MM cell survival, indicating that it is a promising target to inhibit growth and reduce genomic evolution in myeloma. Disclosures Munshi: BMS: Consultancy; OncoPep: Consultancy, Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties; C4: Current equity holder in private company; Janssen: Consultancy; Adaptive: Consultancy; Legend: Consultancy; Amgen: Consultancy; AbbVie: Consultancy; Karyopharm: Consultancy; Takeda: Consultancy.

Multiple Myeloma (MM) is a complex disease driven by numerous genetic and epigenetic alterations. Recurrent IgH translocations, copy number abnormalities and somatic mutations all contribute to myelomagenesis, yet true drivers of the disease have yet to be identified. In order to investigate the enhancer landscape and identify new dependencies and actionable therapeutic targets in MM, we have generated high-quality active enhancer landscape in MM cell lines as well as in large cohort of primary patient myeloma cells (n=70) and normal plasma cell. We integrated this data with an in-house curated atlas of 600+ active enhancer profile across a wide range of tumor types and normal tissues. Combining this data with gene expression and genetic dependency (CRISPR KO) enables a multidimensional integration of how transcriptional regulation intersects with tumor specific dependencies. We identified genes that are super-enhancer associated, expressed, and required specifically in MM versus other tumor types or normal tissues. Many of the specific and potent dependencies in MM are transcription factors, and especially those establishing plasma cell identity. Among others, the POU2AF1 gene, which encodes the OCA-B/BOB-1, a B cell transcriptional coactivator protein, represented the most striking dependency in MM. BOB-1 is a gene regulatory factor that regulates B-cell development, maturation and GC formation. Although BOB-1 is expressed throughout B-cell development, we found it to be highly expressed in CD138+ plasma cells from patients with precursor conditions (MGUS and SMM) as well and established MM compared to normal plasma cells, giving us the rationale to study the transcriptional program associated with BOB-1 in MM cells. To confirm CRISPR data described above, we have performed loss-of-function (LOF) studies using shRNA, siRNAs as well as antisense GapMers specific for BOB-1. Downregulation of BOB-1 in a panel of MM cell lines caused MM cell growth inhibition in a time-dependent manner which was associated with G2/M cell cycle arrest and induction of MM cell apoptosis. Transcriptomic analysis by RNA-sequencing revealed a set of 72 genes (adj p-value=0.2) commonly modulated in AMO-1 and NCI-929 MM cell lines upon BOB-1 depletion, as compared with scrambled cells. Among the top 5 downregulated genes in BOB-1 knockdown samples, we found AMPD1, KCNN3, BHLHA15, HID1 and XBP1. The modulation of BOB1 target genes was confirmed at the protein level by Western blot analysis in BOB-1 LOF and gain-of-function (GOF) cell systems. Analysis of patient expression datasets revealed that these genes are positively correlated with BOB-1 expression in primary MM cells and overexpressed in MM cells compared to normal plasma cells. One of these 5 genes positively controlled by BOB-1, BHLHA15, is the gene coding for the transcription factor Mist1, which functions as a coregulator of the unfolded protein response (UPR) master transcription factor XBP1. Target genes of the XBP1- BHLHA15 axis are involved in lipid synthesis, protein folding and secretion, and ER-associated protein degradation. As a result, BOB-1 knockdown increased de novo protein synthesis in MM cells compared to control cells. Interestingly, Mist1 gene expression is induced during ER stress by XBP1, but as ER stress subsides, Mist1 serves as a feedback inhibitor. Moreover, we identified that LOF studies in two MM cell lines confirmed increased expression of BOB-1 and XBP1 upon KD of Mist1. However, XBP1 and/or Mist1 are dispensable for MM cell survival, as gene depletion did not affect MM cell viability. Among the genes most significantly upregulated by BOB-1 depletion was heme oxygenase 1 HMOX1 gene, whose expression is significantly lower in-patient MM cells compared to normal plasma cells. Moreover, its lower expression significantly correlated with poor clinical outcome; and siRNA depletion of HMOX1 increased MM cell growth in MM cell lines, suggesting important role in MM. Mechanistic studies aimed at investigating the functions of HMOX1 in MM and its relation with BOB-1 are ongoing and will be presented. In conclusion, we here report BOB1 as an important transcriptional regulator in MM and its two down-stream novel target genes (BHLHA15 and HMOX1) with potential significant biological role in MM. Disclosures Hajek: BMS: Consultancy, Honoraria, Research Funding; Oncopeptides: Consultancy; PharmaMar: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Fulciniti:NIH: Research Funding. Munshi:Janssen: Consultancy; C4: Current equity holder in private company; Karyopharm: Consultancy; Amgen: Consultancy; OncoPep: Consultancy, Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties; BMS: Consultancy; Legend: Consultancy; Adaptive: Consultancy; AbbVie: Consultancy; Takeda: Consultancy.

Chimeric antigen receptor (CAR) T-cell therapy targeting B cell maturation antigen (BCMA) has provided deep (73% - 100%) responses in relapsed/refractory multiple myeloma (MM). However, median PFS has been less than 12 months, and amongst the small number of patients retreated at the time of progression with the same CAR T product, responses have been infrequent. This highlights development of resistance that may preclude effectiveness of the 2ndinfusion, and may also underly relapse following response to the initial CAR-T cell therapy. Here, we have investigated one of the resistance mechanisms using longitudinal single cell transcriptomic and bulk genomic analysis. This patient had relapsed/refractory IgG lambda MM with hypodiploidy and a complex karyotype with t(8;12) (q24;q14), clonal t(11;14) (q13;q32), and clonal deletion 13. Patient received 150x106CAR+ T cells (ide-cel) and achieved partial response, with duration of response of 8 months. The patient was retreated with 450 x106CAR+ T cells at relapse, but with no response. To delineate the resistance mechanism, we evaluated the bone marrow (BM) niche using 37658 cells from eight time points from before 1st CAR T cell infusion to 2 months after 2nd CAR T cell infusion, and identified 13 clusters consisting of hematopoietic cells and MM/plasma cells. Using RT-PCR based detection, we observed engineered CAR T cells only at 2 weeks after first infusion, when maximal CAR T cell expansion was observed. We did not observe infused CAR T cells with single cell RNAseq after 2ndinfusion, but a limited expansion was confirmed using RT-PCR.Re-clustering of the T cell cluster showed an increased proportion of CD4+ helper and T regulatory cells (Treg) 2 weeks after 1st infusion. In contrast, TREG proportion remained constant at the 2nd infusion, suggesting other causes for lack of expansion of CAR-T cells. We also did not identify any significant increase in the proportion of cells expressing immune check point inhibitory markers or in accessory cell types with immune inhibitory function in MM BM. Since we did not delinate a role of the BM milieu mediating suppression of CAR-T cell expansion and function following 2ndinfusion, we next explored tumor intrinsic factors. Soluble BCMA level (produced predominantly by MM cells) was high before the first CAR T cell infusion and dropped significantly to a very low level coinciding with the clinical response; however, it remained low even at the time of relapse with increase burden of MM, indicating a lack of BCMA production by MM cells. We therefore investigated genomic changes in MM cells at the time of relapse. Our single cell analysis of BM samples identified 3 samples (at the time of relapse and post 2ndCAR T cell infusion) with significant numbers of MM cells, evidenced by expression of CD138 and XBP1 (marker of plasma cells), CCND1 (upregulated in this patient with t(11;14)) and lack of RB1 (downregulated in this patient with del13). Imputation of copy number alterations scRNAseq showed that the majority of MM cells had a deletion of 16p, including the BCMA locus located on 16p13.13. We further validated these findings using deep whole exome sequencing (WES) of purified CD138+ cells collected after the second CAR T infusion. Before first CAR T cell infusion, 4% MM cells showed deletion 17p, while after second infusion both WES and scRNAseq prediction showed that del17p and del16p were clonal, and longitudinal scRNAseq analysis indicated that del17p and del16p co-occurred in the same clone. Moreover, WES identified a subclonal nonsense mutation (p.Q38*) in BCMA that creates an early stop codon in the BCMA gene. This biallelic BCMA deletion, acquired with one copy loss and a 2ndloss-of-function mutation, provides the molecular basis for lack of BCMA expression in MM cells at the time of relapse. Our data showed that both TP53 and BCMA had deletion in one allele and mutation in the second allele. These results identify biallelic loss of BCMA locus as a potential resistance mechanism to BCMA targeting therapy. Our results highlight the need to investigate sBCMA as a potential indicator of BCMA loss at relapse, and to carry out detailed transcriptomic or genomic analysis to confirm mutations. Moreover, these data also demonstrate the ability of MM cells to survive without BCMA expression. With the growing number of BCMA targeting therapeutic modalities under development, we would expect to see such occurrences more commonly in the future. Disclosures Fulciniti: NIH: Research Funding. Campbell:BMS: Current Employment, Current equity holder in publicly-traded company. Petrocca:bluebird, bio: Current Employment, Current equity holder in publicly-traded company. Hege:Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company), Patents & Royalties: numerous, Research Funding; Celgene (acquired by Bristol Myers Squibb): Ended employment in the past 24 months; Mersana Therapeutics: Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees; Arcus Biosciences (Former Board of Directors): Divested equity in a private or publicly-traded company in the past 24 months. Kaiser:BMS: Current Employment, Current equity holder in publicly-traded company. Anderson:Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Sanofi-Aventis: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Millenium-Takeda: Membership on an entity's Board of Directors or advisory committees; Oncopep and C4 Therapeutics.: Other: Scientific Founder of Oncopep and C4 Therapeutics.. Munshi:C4: Current equity holder in private company; Legend: Consultancy; OncoPep: Consultancy, Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties; BMS: Consultancy; Janssen: Consultancy; Adaptive: Consultancy; Amgen: Consultancy; AbbVie: Consultancy; Karyopharm: Consultancy; Takeda: Consultancy.

Multiple Myeloma is preceded by precursor states of monoclonal gammopathy of undermined significance (MGUS) and smoldering multiple myeloma (SMM). Studies have shown that progression to symptomatic MM five years after diagnosis is 1% for MGUS and 10% for SMM. However, based on the genomic background, this rate is highly variable, especially for SMM patients. Recent studies have evaluated the high-risk genomic features for SMM, but the genomic background of SMM patients who do not progress to MM after long-term follow-up (>= 5 years) has not been described. Here, we evaluated genomic changes enriched in non-progressor (NP) (no progression after 5 years of follow-up) precursor conditions (N=31) with those progressed within a short time (N=71) as well as newly diagnosed Myeloma (N=192). We also studied additional unique samples from 18 patients at their precursor stage as well as when progressed to Myeloma. We report a similar large-scale CN alteration in non-progressor SMM compared to progressor SMMs or MM at diagnosis. However, whole-genome sequencing data showed that the overall mutational load for non-progressor SMM samples was lower than Progressor MGUS/SMM (median SNV 5460 vs. 7018). This difference significantly increased for mutations affecting the coding regions. NP samples at diagnosis had 26% and 53% less coding mutations (missense, nonsense, and frameshift mutations) compared to progressor MGUS/SMM (p=0.008) and newly diagnosed MM (p < 0.001) respectively. We observed very low NRAS (3%, OR=8.86) and BRAF (3%, OR=2.17), mutation frequency in non-progressor SMM samples compared to newly diagnosed MM. We did not observe driver mutations in FAM46C, TTN, CYLD, TP53, KMT2C, IRF4, HIST1H1E that are otherwise frequently mutated in high-risk SMM or symptomatic MM. None of the non-progressor SMM samples had MYC alteration. We observed t(11;14), t(4;14), and t(14;16) translocations at similar frequency compared to newly diagnosed MM samples. We also observed a significant difference in non-recurrent focal deletions. Based on our recent data in newly-diagnosed MM, we quantified genomic scar score, and observed that non-progressor SMM have lower GSS (median=3,IQR=[1-9]) compared to progressor MGUS/SMM (median=11,IQR=[5-15] / median=9,IQR=[9-15], respectively) as well as MM samples at diagnosis (median=9, IQR= [5-16],p=0.002). We further validated this observation in an independent cohort with 69 SMM samples in whom progressor SMM patients had high GSS (median =4, IQR=[2-7.75]), compared to delayed progressor (> four years) or non-progressor SMM (median =1.5, IQR= [0-3.5]; p=0.029). Moreover, non-progressor SMM had significantly low utilization of APOBEC and DNA repair mutational processes. Next, we compared non- progressor SMM with progressor SMM using RNAseq data. We identified 1653 differentially expressed genes (DEG) (762 up-regulated and 891 down-regulated). Genes that were upregulated in non-progressor SMM samples were enriched in IL6/JAK/STAT3 and IL2/STAT5 signaling and the regulation of cytokine secretion. Whereas genes up-regulated in progressor SMM were enriched in MYC targets, DNA repair, and mTOR pathways. Moreover, genes that control the translational initiation, translational elongation, mitochondrial translation, and ATP control were among the top highly expressed genes in progressor SMM. We used our MGUS/SMM to MM paired samples and showed that the E2F target, MYC target, and G2/M checkpoint pathways are more active at MM. We measured the distance between progressor and non-progressor SMM as well as MM and found that non-progressor SMM is less similar to MM compared to progressor SMM. In conclusion, the global CNA and translocations are similar between progressor and non-progressor SMM and symptomatic MM and confirm their role in the development of precursor condition but not adequate for progression to MM, which requires additional hits. On the other hand, lower GSS score reflecting genomic stability along with lower SNVs, low DNA damage and APOBEC mutational processes, down-regulated MYC target genes, and low DNA repair activation define low-risk SMM. These results now provide the basis to develop a genomic definition of SMM. Disclosures Fulciniti: NIH: Research Funding. Parmigiani:Phaeno Biotehnologies: Current equity holder in publicly-traded company; CRA Health: Current equity holder in publicly-traded company; Foundation Medicine Institute: Consultancy; Delphi Diagnostics: Consultancy; BayesMendel Laboratory: Other: Co-lead. Munshi:Janssen: Consultancy; Adaptive: Consultancy; Legend: Consultancy; Amgen: Consultancy; AbbVie: Consultancy; Karyopharm: Consultancy; Takeda: Consultancy; C4: Current equity holder in private company; BMS: Consultancy; OncoPep: Consultancy, Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties.

Multiple Myeloma (MM) is characterized by genomic heterogeneity with copy number alterations (CNA) as one of the most prominent genomic perturbation. Hyperdiploidy involving chromosomes 3,5,7,9,11,15,19, and 21 is observed in nearly half of the patients, however the chronological sequence of their occurrence during MM development remains unknown. Here, we have acquired one of the largest genomic datasets from 647 patients that combines data from monoclonal gammopathy of undermined significance (MGUS) to newly diagnosed MM (336 newly diagnosed MM, 147 smoldering MM (SMM) and 164 MGUS) to characterize when and in what sequence CNA occurs in MM development. We deduce the order of CNA events by identifying their pattern of clonality basically inferring that clonal genomic change suggest its origin at an earlier stage of the disease. In hyperdiploid MM (HMM), gains in chromosome 19 (95%), 15 (90%) and 9 (90%) are the most frequent events, followed by gains in 5,11,3,7 and 21. Based on the clonality assessment the gain of chromosome 15 is the first and most frequent clonal/near clonal event, observed in 95% of HMM patients followed by Chromosome 9. Surprisingly, although chromosome 19 gain is the most frequent event overall, its clonal occurrence was lower than clonal chromosome 15 gain. More than 96% of HMM samples had concurrent gains in at least 2 of the 3 most frequent chromosomes (9,15 and 19). Moreover, less frequent events such as chromosome 21 gain, 18p gain, and 1q gain showed higher frequency of clonal/near clonal occurrence compared to other events indicating that when these events occur they are early events. Majority of the deletions occur as late subclonal events with few or none observed as clonal events. In the nonhyperdiploid MM (NHMM), del13, gain of 1q and gain of 11 had the highest frequency of clonal occurrence. Most were clonal events signifying its importance in the early stages of the disease. As all MM originates from its precursor conditions, MGUS and SMM, clonal and likely early CNAs in MM, must also exist in MGUS and SMM. So, we next investigated genomic data from SMM and MGUS for the occurrence of clonal events observed in MM. We confirmed same patterns for top MM-related CNA events in SMM and MGUS and observed no significant difference (p=0.1) between the number of events in hyperdiploid groups in MM (median=10, IQR= [8-12]) and SMM (median=9, IQR= [7-11]).To further confirm the analysis, we calculated an average clonality score for each chromosomal alteration using a 1 to 5 clonality index (1 being clonal 5 being low subclonal) in MM, SMM and MGUS and observed that similar clonal trisomies median=5, IQR=[4-6] are observed in both HMM and hyperdiploid MGUS; and that not all trisomies are required or occur at the same time. With occurrence in over 96% of cases trisomy involving chromosome 15 is central to the development of MGUS and later on MM. This is closely followed by trisomy of 9, and 19. Gain of chromosome 21 is also an early event. Major events like deletion 13 and 1q gain occur relatively later than first hyperdiploid events. NHMM on the other hand is well known to have clonal IgH-associated translocation as an initiating feature which is also observed in SMM and MGUS. However, different from HMM, it shows only few CNAs at an early stage and does not accumulate frequent additional alterations. The only exception to this rule is a deletion group observed in HMM, NHMM and SMM but not MGUS. In this deletion in over 10 whole chromosome or its p or q arm are involved as subclonal events. Its absence in MGUS suggests them to be a later event in MM development. On the other hand, number of deletions are observed at the same locations in both hyperdiploid and non-hyperdiploid groups with similar frequency. Moreover, similarity of events in this deletion groups strongly suggest that in sub group of both HMM and NHMM a similar process may be operative to induce such deletions. Our results also highlight that for both HMM and NHMM groups the major copy number events are not adequate for eventual malignant transformation since only a small fraction of MGUS patients progress to MM. Here, we describe the time line of initial copy number alterations observed in MM and confirm their early occurrence using data from a unique early stage plasma cell cases. Similarities between stages show that large scale DNA alterations happen early however some copy number hotspots are enriched over the time which could be important for disease progression. Disclosures Moreau: Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Anderson:Bristol Myers Squibb: Consultancy; C4 Therapeutics: Equity Ownership, Other: Scientific founder; Gilead: Membership on an entity's Board of Directors or advisory committees; OncoPep: Equity Ownership, Other: Scientific founder; Millennium Takeda: Consultancy; Celgene: Consultancy. Munshi:OncoPep: Other: Board of director.

International audience; Although long intergenic non-coding RNAs (lincRNA) role in various cancers is described, their significance in Multiple Myeloma (MM) remains poorly defined. Here we have studied the lincRNA profile and their clinical impact in MM. We performed RNA-seq on MM cells from 308 newly diagnosed and uniformly treated patients, 16 normal plasma cells and utilized RNA-seq data from 532 newly diagnosed patients from CoMMpass study to analyze for lincRNAs. We observed 869 differentially expressed lincRNAs in MM compared to normal plasma cells. We identified 14 lincRNAs associated with PFS and calculated a risk score to stratify patients. The median PFS between high vs low-risk groups was 17 months vs not-reached (NR); and OS 30 months vs NR, respectively (p < 0.0001 for both). In the independent validation dataset between high and low-risk groups, PFS was 27 vs 42 months (HR 2.06 [1.44−2.96]; p < 0.0005); and 4-year OS 62% vs 86% (HR 2.76 [1.51–5.05]; p < 0.0005) confirming significant clinical relevance of lincRNA in MM. Importantly, lincRNA signature was able to further identify patients with significant differential outcomes within each low and high-risk categories identified using standard risk categorization including cytogenetic/FISH, ISS, and MRD negative or positive. Our results suggest that lincRNAs have an independent effect on MM outcome and provide a rationale to evaluate its molecular and biological impact.

Background/aim The optimal empiric antibiotic regimen for patients with community-acquired pneumonia (CAP) remains unclear. This study aimed to evaluate the clinical cure rate, mortality, and length of stay among patients hospitalized with community- acquired pneumonia in nonintensive care unit (ICU) wards and treated with a β-lactam, β-lactam and macrolide combination, or a fluoroquinolone. Materials and methods This prospective cohort study was performed using standardized web-based database sheets from January 2009 to September 2013 in nine tertiary care hospitals in Turkey. Results Six hundred and twenty-one consecutive patients were enrolled. A pathogen was identified in 78 (12.6%) patients. The most frequently isolated bacteria were S. pneumoniae (21.8%) and P. aeruginosa (19.2%). The clinical cure rate and length of stay were not different among patients treated with β-lactam, β-lactam and macrolide combination, and fluoroquinolone. Forty-seven patients (9.2%) died during the hospitalization period. There was no difference in survival among the three treatment groups. Conclusion In patients admitted to non-ICU hospital wards for CAP, there was no difference in clinical outcomes between β-lactam, β-lactam and macrolide combination, and fluoroquinolone regimens.