Bergsagel, P. Leif

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

8043 Background: The mammalian target of rapamycin (mTOR) signal pathway controls cell proliferation and survival. The trial's goal was to determine the anti-tumor activity and safety of single-agent everolimus (TORC1 inhibitor) in patients with relapsed/refractory Waldenstrom macroglobulinemia (WM). Methods: Eligible patients had measurable disease (IgM monoclonal protein >1000 mg/dL with >10% marrow involvement or nodal masses >2 cm), a platelet count ≥75,000 x 106/L, a neutrophil count ≥1,000 x 106/L. Patients received everolimus 10 mg PO daily. Tumor response was assessed after cycles 2 and 6 and then every 3 cycles until progression. Results: 60 pts were treated. The median age was 64 years (range, 43-85). The median number of prior therapies was 3 (range, 1-11). All but two patients (97%) had received prior rituximab based therapy and 64% of patients had received prior alkylator based therapies. The overall response rate (complete response CR+ partial response PR+ minimal response MR) was 73% (95% CI: 60-84%), with a PR of 50% and 23% MR. The median time to progression (TTP), progression-free survival (PFS), and overall survival (OS) for the entire study population is 28 months (mos), (95% CI: 18-not reached (NR)), 22 mos (95% CI: 12 0-NR), and 55 mos (95% CI: 55-NR), respectively. The estimated PFS at 12 and 24 months is 62% (95%CI: 51-75%), and 48% (95%CI: 37-63%), respectively. The 30 patients who achieved a PR responded after a median of 2 months (range, 1-26) of treatment. The median duration of response (DR) for these patients has not yet been reached and 19 of these patients remain in response after a median follow up of 31 months (range, 3-54). All but two patients had a decrease in their serum IgM. Grade 3 or higher related toxicities were observed in 67% of patients. The most common were hematological toxicities with cytopenias. Pulmonary toxicity occurred in 5% of patients. Dose reductions due to toxicity occurred in 63% of patients. Conclusions: Everolimus has high single-agent activity with an overall response rate of 73% and manageable toxicity in patients with relapsed WM, and offers a potential new therapeutic strategy for this patient population.

8010 Background: Carfilzomib is a proteasome inhibitor that irreversibly binds its target with favorable toxicity profile that has shown significant activity in relapsed multiple myeloma (MM). Here we used carfilzomib as the center of a 4 drug induction regimen designed for MM patients pre stem cell transplant (SCT). Methods: We conducted a phase I safety run in 6 patients with no DLT observed before expanding to phase II. The phase II regimen is shown below. Treatment was for 4 cycles with expected SCT post induction. For the phase II portion of this trial, the primary endpoint is the proportion of patients who have ≥ very good partial response to treatment. All patients received herpes zoster prophylaxis and ASA daily. Results: Twenty seven patients were enrolled. Median age was 65 (range 27-74). ORR for evaluable patients (n=17) at phase II dosing is 100%: CR 35%, VGPR 48%, PR 18% after 4 cycles of CYCLONE. Grade 3 toxicity was reported in 52% of patients and 14% experienced a grade 4 toxicity. Grade 3/4 toxicities occurring in >5% of patients included fatigue, neutropenia, lymphopenia, thromboembolism, myopathy. Toxicities of any grade seen in >20% of patients included fatigue, constipation, lethargy, thrombocytopenia, somnolence, creatinine increased, malaise. Four patients (20%) developed grade 1 sensory neuropathy; no higher grade or painful neuropathy was evident. All patients are alive. All patients advancing to SCT successfully collected stem cells. One patient with t(4;14) disease who was not transplanted has progressed. 94% remain progression free. Conclusions: The 4 drug CYCLONE regimen has remarkable efficacy (83% ≥VGPR) and manageable toxicity in newly diagnosed patients with multiple myeloma. Especially notable was the low incidence of neuropathy and depth of response (CR 35%) after only 4 cycles. Given the relative lack of toxicity an extension of this regimen at higher doses of carfilzomib (20/45mg/m2) has been initiated. [Table: see text]

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

Abstract The most common genetic abnormality in multiple myeloma is the deletion of chromosome 13, seen in almost half of newly diagnosed patients. Unlike chronic lymphocytic leukemia, where a recurrent minimally deleted region including MIR15A/MIR16-1 has been mapped, the deletions in multiple myeloma predominantly involve the entire chromosome and no specific driver gene has been identified. Additional candidate loci include RB1 and DIS3, but while biallelic deletion of RB1 is associated with disease progression, DIS3 is a common essential gene and complete inactivation is not observed. The Vk*MYC transgenic mouse model of multiple myeloma spontaneously acquires del(14), syntenic to human chromosome 13, and Rb1 complete inactivation, but not Dis3 mutations. Taking advantage of this model, we explored the role in multiple myeloma initiation and progression of two candidate loci on chromosome 13: RB1 and MIR15A/MIR16-1. Monoallelic deletion of Mir15a/Mir16-1, but not Rb1, was sufficient to accelerate the development of monoclonal gammopathy in wild-type mice and the progression of multiple myeloma in Vk*MYC mice, resulting in increased expression of Mir15a/Mir16-1 target genes and plasma cell proliferation, which was similarly observed in patients with multiple myeloma. Significance: In the absence of a defined, minimally deleted region the significance of del(13) in multiple myeloma has remained controversial. Here we show that haploinsufficiency of Mir15a/Mir16-1, but not Rb1, upregulates the cell cycle–regulatory network, inducing monoclonal gammopathy in mice and promoting multiple myeloma progression in both mice and men. See related commentary by Walker, p. 16. This article is highlighted in the In This Issue feature, p. 5

Introduction Despite continuous improvement of clinical outcome in multiple myeloma (MM), disease relapse remains a major challenge, leading to progressively shorter remissions and fewer treatment options. Strategies attempting to counteract this challenge include recent efforts resulting in an increase in the availability of novel promising anti-MM agents and targeting specific genetic profiles of the disease. In this context, we aim to develop predictive models of sensitivity and resistance to novel compounds by connecting an ex vivo high-throughput drug screen with genetic, transcriptomics, FISH, and clinical features. Methods Twenty compounds (afatinib, afuresertib, belinostat, buparlisib, cobimetinib, CPI-0610, crenolanib, dinaciclib, dovitinib, JQ1, LGH447, osimertinib, OTX015, panobinostat, romidepsin, selinexor, sunitinib, trametinib, venetoclax, and vorinostat) were selected based on overall promising anti-MM activity from an ex vivo high throughput drug screen with a panel of 79 single agents incubated for 24 hours. The area under the curve (AUC) was used to rank order the ex vivo responses for each compound and the lowest and highest quartile samples were identified for further analysis. Clinical data and FISH data, including t(11;14), t(4;14), t(14;16), del(17p), +1q, monosomy 13, and MYC rearrangement, were collected. Targeted DNA sequencing was performed using a 2.3 Mb custom capture panel covering 139 MM-relevant genes. mRNA-sequencing was performed and differential gene expression analysis in the highest and lowest quartile identified subsets of markers positively and negatively associated with the AUC response for a given compound. An additional unbiased selection of markers using lasso techniques was performed, resulting in predictive generalized linear models (GLM) for each agent. Responses from the remaining intermediate samples were estimated with the predictive models, with overall predictive ability assessed by correlating predicted AUCs with their actual counterparts. Results Our integrative analysis was performed on 50 primary patient samples (36% untreated and 64% relapsed MM). Venetoclax, dinaciclib, romidepsin, panobinostat, osimertinib, belinostat and selinexor were the most active compounds in the cohort. Interestingly, LGH447, dovitinib, selinexor, JQ1, OTX-015, cobimetinib, and trametinib showed increased activity in relapsed MM when compared to untreated samples (Wilcoxon Test; p&lt;0.05). We generated GLMs using an average of 92 markers (range 64-107) per compound, combining mRNA-sequencing expression with FISH and mutation data. The analysis proposed in the present study was validated through the unbiased selection of BCL2 among the subset of markers included in the GLM predicting sensitivity to venetoclax, a first-in-class orally bioavailable selective BCL2 inhibitor. Expression level of critical NF-kB and cell cycle genes, such as BIRC3, CKS1B, PAX5, NFKB2, and CCND2, were included in 60% of our predictive models. Mutations of DNA repair genes (ATM,TP53) were included in the GLMs of three epigenetic therapies, one histone deacetylase inhibitor and two BET inhibitors, associated to ex vivo resistance to the drugs. The presence of monosomy 13 was also a marker for ex vivo resistance for five epigenetic therapies, four HDAC inhibitors and one BET inhibitor. The three BET inhibitors, JQ1, CPI-0610, and OTX015, were among the compounds most accurately predicted by our integrative approach, with Spearman correlation values between 0.773-0.858. Overall, our models accurately predicted the ex vivo response for 16 (80%) of the compounds (r&gt;0.7). Five (25%) of these compounds displayed a remarkably accurate prediction model in both training (highest and lowest quartiles) and validation (intermediate quartiles) samples (r&gt;0.8). Conclusions The GLM data integration approach enabled the establishment of effective predictive models, identifying FISH, transcriptomics, and mutations of putative driver genes important in anti-MM agent responsiveness. In addition, the resulting dataset is promising for future research focusing on the discovery of novel mechanisms of action and establishing markers of sensitivity and resistance to novel compounds. We are currently increasing our dataset and seek to create an omnibus approach that predicts responses to multiple anti-MM agents simultaneously. Disclosures Bergsagel: Celgene: Consultancy; Ionis Pharmaceuticals: Consultancy; Janssen Pharmaceuticals: Consultancy. Stewart:Amgen: Consultancy, Research Funding; Bristol Myers-Squibb: Consultancy; Celgene: Consultancy, Research Funding; Ionis: Consultancy; Janssen: Consultancy, Research Funding; Oncopeptides: Consultancy; Ono: Consultancy; Roche: Consultancy; Seattle Genetics: Consultancy; Takeda: Consultancy.

Abstract MYC expression is frequently dysregulated in multiple myeloma (MM). In one comprehensive study, MYC structural variations (SV) were found in nearly half of MM cases (Affer et al. Leukemia 2014). The prevalence was higher in hyperdiploid (HRD) tumors (65%) compared to non-hyperdiploid (NHRD) tumors (36%). The large amount of tumor DNA required for all of the genomic studies performed may have biased the samples analyzed (e.g., to those with higher tumor burdens). To validate the findings of recurrent MYC SV in another dataset, we analyzed the CoMMpass data. We analyzed long-insert whole genome sequencing (WGS) data from diagnostic samples in 420 patients from the IA7 release (dbGAP phs000748) for SV. The results of clinical data, processed WES (SNV), RNASeq (gene expression) and WGS (copy number) data from IA8 (http://research.themmrf.org) were used to calculate survival, RAS and NFKB pathway mutation (WES), TC class (RNA), NFKB index (RNA) and hyperdiploid index (WGS). MYC SVs were identified in 38% of tumors. They were present in 53% HRD and 28% NHRD, and by TC in 55% D1, 43% D2, 36% MMSET, 26% MAF, 13% CCND. Juxtaposition of an Ig enhancer (IgH, IgK, IgL) close to MYC was the most common MYC SV, representing ~40% of the MYC SV. Other enhancers identified have mostly been reported previously, with the most frequent being NSMCE2 (12% of SV) and TXNDC5 (5% of SV). Intrachromosomal SV (deletions, inversions, duplications) not associated with any known enhancer were also frequent (18% of SV). As expected, MYC expression was higher in tumors with MYC SV compared to those without (~2.4 fold, p-value<0.0001). We used Gene Set Enrichment Analysis (GSEA) to identify activated pathways that might substitute for MYC in HRD patients without MYC SV and observed significant activation of the NFkB pathway. Interestingly, examining patients with RAS/MAPK pathway (NRAS, KRAS, BRAF, FGFR3 - abbreviated RAS) mutations (identified in 50% of all patients) the same pattern was observed: in the absence of RAS mutation, there was a significantly higher NFkB index. In general, the HRD tumors seem to have either activation of RAS and/or MYC, or activation of NFkB (Figure). There was no difference in overall survival in patients with versus those without MYC SV. We developed a clinically applicable sequencing platform to identify MYC SV, which cannot be reliably identified by FISH. We sought to validate this targeted capture approach, where in addition to the coding exons of 81 interesting genes described previously (M3P), we also pulled down the region surrounding MYC (2 Mb), IgH (0.5 Mb), IgK (50 kb) and IgL (100 kb) allowing us to additionally identify SV in MYC and Ig loci. Using this approach we identified IgH translocations in 29/30 samples with translocations previously identified by FISH (97%). Moreover, we identified MYC SV in 19/22 patients with SV previously identified by mate-pair WGS (86%). Importantly, sequencing identified the precise translocation breakpoint, and identity of the enhancer dysregulating MYC, which may be important variables. In one informative patient two different MYC SV were present at diagnosis, only one of which was still present following a partial response to four cycles of lenalidomide and dexamethasone. This suggests that the two MYC SV are in different subclones, one of which was much more sensitive to the treatment. Interestingly, the enhancer dysregulating MYC in the sensitive subclone harbors 5 strong Ikaros binding sites identified by ChIPseq, suggesting one intriguing mechanism for sensitivity to lenalidomide. To summarize, we verified in a large dataset that MYC expression is frequently dysregulated by SV in MM (38%), and the RAS/MAPK (50%) and NFKB (23%) pathways are frequently activated by mutations. Surprisingly, given their generally good prognosis, nearly half of HRD tumors seem to be MYC driven, while this is true for only a quarter of NHRD tumors. HRD tumors not driven by MYC or RAS appear to be driven by NFKB. Remarkably, the pathways most commonly activated by mutation in MM: CCND, MYC, RAS, NFKB are common to many cancers and have been studied extensively individually. To understand their clinical impact in MM we have developed a comprehensive custom capture sequencing panel that identified 97% of IgH translocations, 86% of MYC SV, and as well as SNV and CNV of 81 recurrently mutated genes. It will be important to include such a comprehensive genetic analysis to complement clinical trials in the future. Figure. Figure. Disclosures Stewart: Bristol Myers Squibb: Consultancy; Celgene: Consultancy; Takeda Oncology: Consultancy; Janssen Pharmaceuticals: Consultancy.

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

Abstract Introduction. Growing evidence suggests that immune cells that reside within the tumor microenvironment are dysregulated and functionally impaired, leading to defective anti-tumor immunity of the host. One of the major immunosuppressive mechanisms during tumor progression is expansion of regulatory immune cells. Here, we analyzed the immune cells within the bone marrow (BM) and the peripheral blood (PB) of 2 immunocompetent multiple myeloma (MM) mouse models. We next studied the role of regulatory T cells (Tregs) in MM pathogenesis. Materials and methods. To study the immune cell populations of the BM and PB, we used two immuncompetent mouse models and transplanted VK*MYC cells or 5TGM1 cells into C57BL/6 and C57BL/Kalwrij mice respectively. The immune cell populations and checkpoint receptor expressions were analyzed by CyTOF mass cytometer or flow-cytometry. Treg induction assay was performed in vitro to study the mechanism of Treg increase in the BM of myeloma injected mice. CD4+ CD25- cells were obtained from C57BL/Kalwrij mice and were co-cultured with 5TGM1 cells or B cells from C57BL/Kalwrij mice in vitro. Treg induction was compared by flow-cytometry. Transplantable VK*MYC cells were injected into "depletion of regulatory T cell" (DEREG) mice, which expresses a simian diphtheria toxin (DT) receptor-enhanced GFP fusion protein under the control of the FOXP3 gene locus, or their wild type littermates. DT injection into these mice leads to depletion of Tregs as previously described (J Exp Med. 2007; 204: 57-63). DT was given once every week for a total 3 times i.p to the DEREG mice or the littermate controls to specifically deplete Tregs and to study the role of Tregs during MM progression. Tregs (CD4+ FOXP3-GFP+ cells) were sorted from VK*MYC injected mice or non-injected DEREG mice BM using FACSAria cell sorter. Cells isolated were subjected to RNA sequencing. Gene Set Enrichment Analysis (GSEA) was performed to define differences in molecular signatures between MM-associated and normal Tregs. Results. The Treg proportion was significantly increased within the CD4+ T cells in the BM of myeloma cell injected mice from the early stage of disease compared to control mice, while in the PB, the increase was observed only at the late stages of disease progression. The effector T cell (Teff)/Treg ratio was significantly decreased in the BM at the end-stage myeloma bearing mice (P<0.01). Checkpoint related molecules (PD-1, LAG-3 and Tim-3) on Tregs and Teffs were up-regulated at the protein level in the BM of myeloma injected mice compared to control (P<0.01). These data indicate the activation of Tregs and decrease of Teff activity, leading to suppression of anti-myeloma T cell activity in the MM BM. Under in vitro co-culture conditions, 5TGM1 cells induced a significant increase in the number of Tregs from non-Treg CD4+ T cells compared to controls (P<0.01). 5TGM1 cell-induced Tregs presented with enhanced ki-67 expression, thus suggesting the ability of MM cells to induce Treg proliferation. Additionally, the trans-well co-culture experiment showed that the major mechanism for Treg induction by 5TGM1 was by direct contact with T cells rather than secreting factors. Significant increase in survival was observed in the VK*MYC injected DEREG mice under Treg depletion compared to the DEREG mice without Treg depletion and wild type littermates under DT treatment (P<0.001). The Treg depleted DEREG mice were accompanied with an increase of Teffs (P<0.01), indicating recovery of anti-myeloma T cell activity. RNA sequencing of BM Tregs from VK*MYC injected mice showed increased expression of immune checkpoint related molecules and increased Treg effector molecules (IL-10, Granzyme B) compared to BM Tregs from control mice, indicating a more functionally active phenotype of VK*MYC associated Tregs. GSEA showed an enrichment of genes involved in type-1 interferon signaling in VK*MYC associated Tregs. Conclusions. We used 2 immunocompetent MM mouse models to study the characterization and significance of Tregs in MM progression. CyTOF analysis and RNA sequencing data indicated Treg activation in the MM BM microenvironment. The Treg in vivo depletion experiment showed that Tregs have a significant role in MM progression. These data indicate that immunotherapy targeting Tregs may represent a novel therapeutic strategy for MM. Studies are ongoing to understand the roles of Tregs in human MM patients. Disclosures No relevant conflicts of interest to declare.

Introduction We have shown that in myeloma (MM) the immunomodulatory drugs (IMiDs) lenalidomide and pomalidomide, in a CRBN dependent fashion, inhibit thioredoxin reductase and thus increase intracellular oxidative stress as a consequence of peroxide accumulation (Sebastian et al. 2017). Accordingly, we have also shown that CRBN expression alone does not fully correlate with lenalidomide sensitivity, as the cells ability to decompose H2O2 is important - MM cells with lower H2O2 decomposition capacity are more sensitive to IMiDs. We hypothezised that the specific metabolic pathways used by cells for biomass production would influence IMiD sensitivity since they also influence this cellular oxidative capacity. Cellular proteins are key elements of this biomass, and required for the proliferation of MM cells and production of immunoglobulin proteins. Methods We cultured MM cells under various nutrients conditions to understand its effect on cell proliferation and drug responses. Cell viability was assessed by MTT assay, the Luminescent Assay, and direct cell counting. MM cells glycolytic rate was measured using the Seahorse XF analyzer. Western blots were performed to quantify various protein expression levels in MM cells cultured under different nutrients conditions. CRBN CRISPR/Cas9 KO plasmid was used to generate CRBN knockout cells and a lentivirus system was used to over-express CRBN in MM cells. Results MM cells resistant to lenalidomide, but still expressing functional CRBN, show a higher glycolytic pathway use than sensitive cells. We found that the lenalidomide sensitive cell line MM1.S is highly dependent on extracellular glutamine for cell proliferation. In contrast, JJN3, a lenalidomide resistant cells line with wild type CRBN, preferentially consumes glucose. We found that glutamine depletion from culture media completely abolished lenalidomide sensitivity in MM1.S cell line. Western blot analysis revealed that antibody production by MM1.S was primarily dependent on glutamine availability, and that JJN3 antibody production was dependent upon glucose availability. While glutamine depletion from culture medium completely abolished lenalidomide sensitivity in MM1.S cell line, IKZF1, and IKZF3 degradation was unchanged. We further studied the role of CRBN in glutamine dependent cellular biomass protein production using isogenic cell lines (+/- wtCRBN). We found that wtCRBN expressing cells proliferate more and show higher antibody production in the presence of glutamine, over CRBN negative isogenic cell lines. Lenalidomide treatment further increased glutamine dependent antibody production in wtCRBN expressing cells. One possibile explanation is that activation of glutamine catabolism can facilitate protein demethylation via the supplementation α-ketoglutarate (α-KG). Therefore, we tested whether lenalidomide treatment could induce protein demethylation in sensitive cell lines. Western blot probed with mono-methyl lysine antibody showed lenalidomide induced protein demethylation. We further confirmed that protein demethylation, and lenalidomide sensitivity is a consequence of elevated α-KG by treating cells with cell-permeable 5-octyl- α-ketoglutarate which act as a substrate of the lysine demethylases. 5-Octyl-α-ketoglutarate treatment inhibited cell proliferation preferentially in wtCRBN expressing cells, and also enhanced lenalidomide induced sensitivity. Protein demethylation is associated with protein ubiquitination and proteasomal degradation. We thus hypothesize that lenalidomide induced protein demethylation also likely increases proteasome inhibitors sensitivity in MM. Conclusion MM cells with preferential glutamine consumption are likely to be more sensitive to lenalidomide, and extracellular glutamine depletion can induce lenalidomide resistance. MM cells expressing CRBN, but not dependent on glutamine for protein biomass production are more likely to be resistant to lenalidomide. Our study postulates that CRBN protein requirement in lenalidomide sensitivity cells is restricted to high glutamine dependency, and that it is quite likely CRBN has a role in glutamine metabolism. Moreover, MM cells that consume more glutamine are under higher oxidative stress and exhibit less H2O2 decomposition capacity and therefore increasing sensitivity to IMiDs. References Sebastian , S., et al., Blood 2017 129:991-1007 Disclosures Stewart: Ono: Consultancy; Roche: Consultancy; Seattle Genetics: Consultancy; Takeda: Consultancy; Amgen: Consultancy, Research Funding; Bristol Myers-Squibb: Consultancy; Celgene: Consultancy, Research Funding; Ionis: Consultancy; Janssen: Consultancy, Research Funding; Oncopeptides: Consultancy. Bergsagel:Janssen Pharmaceuticals: Consultancy; Ionis Pharmaceuticals: Consultancy; Celgene: Consultancy. Fonseca:AbbVie, Amgen, Bayer, Celgene, Kite, Janssen, Juno, Merck, Pharmacylics, Sanofi, Takeda: Other: Consultant/Advisor; Prognosticatin of MM based on Genetic Categorization by FISH: Patents & Royalties; Adaptive Biotechnologies: Other: Scientific Advisory Board.