Search

Pivotal clinical trials of B-cell maturation antigen-targeted chimeric antigen receptor T (CART)-cell therapy in patients with relapsed/refractory multiple myeloma (MM) resulted in remarkable initial responses, which led to a recent US Food and Drug Administration approval. Despite the success of this therapy, durable remissions continue to be low, and the predominant mechanism of resistance is loss of CART cells and inhibition by the tumor microenvironment (TME). MM is characterized by an immunosuppressive TME with an abundance of cancer-associated fibroblasts (CAFs). Using MM models, we studied the impact of CAFs on CART-cell efficacy and developed strategies to overcome CART-cell inhibition. We showed that CAFs inhibit CART-cell antitumor activity and promote MM progression. CAFs express molecules such as fibroblast activation protein and signaling lymphocyte activation molecule family-7, which are attractive immunotherapy targets. To overcome CAF-induced CART-cell inhibition, CART cells were generated targeting both MM cells and CAFs. This dual-targeting CART-cell strategy significantly improved the effector functions of CART cells. We show for the first time that dual targeting of both malignant plasma cells and the CAFs within the TME is a novel strategy to overcome resistance to CART-cell therapy in MM.

Identifying factors secreted by multiple myeloma (MM) cells that may contribute to MM tumor biology and progression is of the utmost importance. In this study, hepatoma-derived growth factor (HDGF) was identified as a protein present in extracellular vesicles (EVs) released from human MM cell lines (HMCLs). Investigation of the role of HDGF in MM cell biology revealed lower proliferation of HMCLs following HDGF knockdown and AKT phosphorylation following the addition of exogenous HDGF. Metabolic analysis demonstrated that HDGF enhances the already high glycolytic levels of HMCLs and significantly lowers mitochondrial respiration, indicating that HDGF may play a role in myeloma cell survival and/or act in a paracrine manner on cells in the bone marrow (BM) tumor microenvironment (ME). Indeed, HDGF polarizes macrophages to an M1-like phenotype and phenotypically alters naïve CD14+ monocytes to resemble myeloid-derived suppressor cells which are functionally suppressive. In summary, HDGF is a novel factor in MM biology and may function to both maintain MM cell viability as well as modify the tumor ME.

Multiple myeloma (MM) measurable residual disease (MRD) persisting after treatment is an adverse prognostic factor for progression free survival (PFS) and overall survival.1Genomic mutations occurred in the remaining clonal aberrant plasma cells (A-PCs) are linked to the development of drug resistance and disease relapse.2 Thus, personalised treatment based on the genomic profile of MRD could be highly beneficial and ultimately increase patients’ survival. However, while large-scale sequencing studies have characterised the genome of many malignancies including MM,3–8 the genomic mutations present in MM MRD are at the beginning of investigation.9 Here, we set up an exome sequencing analysis to identify genomic mutations characteristic for MM MRD and explore if they could mediate drug response, resistance or disease progression.

Introduction Monoclonal immunoglobulin (Ig) is a valuable diagnostic marker in patients with multiple myeloma (MM). An inevitable consequence of extensive Ig synthesis is overload of misfolded proteins that saturate proteasome capacity making the myeloma cells highly sensitive to proteasome inhibitors (PI). Even though PI are regularly used in the clinic, resistance often emerges leaving clinicians with limited treatment options. Therefore, there is a need for a robust marker selecting MM patients for precise PI-based combination therapy. Methods We performed a multiple database search for genes associated with Ig production and MM patients' survival. Additionally, we compared gene expression profiles (RNAseq) of primary MM cells with low and high Ig levels. Next, we validated the identified hits by shRNA knockdown and overexpression studies using myeloma cell lines, primary MM samples, and mouse models. We also applied mass spectrometry-based proteomic analysis, advanced biochemical approaches, and genetic models to reveal the Ig production pathway components and function. Finally, we performed a limited rational drug screening to select suitable compounds for combination treatment. Results RNAseq and database mining revealed a strong association between the expression of plasma cell-specific deubiquitinase OTUD1, Ig production, and MM patient survival. Suppression of OTUD1 with shRNAs in RPMI8226 and MM1.S cell lines reduced Ig levels, increased proliferation, and induced bortezomib resistance. Conversely, inducible OTUD1 overexpression enhanced Ig production, slowed down proliferation, and increased bortezomib sensitivity. In the xenografts mouse models cells with high OTUD1 levels synthesized more Ig and developed smaller tumors. Intriguingly, the transcription of Ig genes was not influenced by OTUD1 expression suggesting that OTUD1 functions as a posttranslational regulator of Ig assembly. To gain mechanistic insight into the Ig pathway regulation by OTUD1, we utilized the biotin proximity labeling method (Turbo-ID) combined with mass spectrometry analysis. We found several novel OTUD1 interaction partners including the E3 ubiquitin ligase KEAP1 and endoplasmic reticulum (ER) redox protein PRDX4. We demonstrated that KEAP1 acts upstream of OTUD1 by regulating OTUD1 ubiquitination and stability. Consistently, survival analysis revealed that MM patients with high KEAP1 expression (low OTUD1) had a worse prognosis than patients with low levels of KEAP1 (high OTUD1). PRDX4 regulates disulfite bonds formation during protein folding and is uniquely expressed in fully differentiated plasma cells. Here, we revealed that OTUD1 specifically deubiquitinates and thus stabilizes PRDX4 inside the ER. Additionally, we performed rescue genetic experiments and found a direct link between the OTUD1-PRDX4 axis and Ig production. The increase in OTUD1 expression (high Ig) led to a dramatic increase in the total pool of ubiquitinated proteins formed mainly by misfolded Ig, while OTUD1 knockdown (low Ig) had an opposite effect. We showed that changes in the level of ubiquitinated proteins correlated with PI sensitivity. Of note, OTUD1 did not affect the expression of proteasome subunits, either their enzymatic activity. Our mechanistic findings prompted us to propose a novel therapeutic opportunity in PI resistant MM patients. We hypothesize that the resensitization of Ig low MM cells to PI could be achieved by enhancing ER stress leading to an increase in misfolded proteins that would ultimately saturate proteasomes. Indeed, from clinically relevant drugs tested so far, the HSP-90 inhibitor (17-AAG) reverted the PI resistance in OTUD1 low (Ig low) myeloma cells. An in vivo validation of the combination treatment and testing of Ig involvement in PI sensitivity and proliferation of MM cells is ongoing. Conclusion Here we present the discovery of a novel regulatory mechanism for Ig production in plasma cells. Based on our results and previously published studies, we conclude that Ig synthesis is a clinically significant factor related to PI response and MM patient survival. Our findings suggest that the intracellular Ig level is an important biomarker to identify patients benefiting the most from PI-based therapies. Finally, we provide a rational solution for selective, combination therapy to overcome PI resistance in MM patients with a decreased capacity to synthesize Ig. Figure Disclosures Hajek: Janssen: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Consultancy, Honoraria; PharmaMar: Consultancy, Honoraria; Oncopeptides: Consultancy.

Background: CTCs may be responsible for MM spreading and accordingly, their numbers in peripheral blood (PB) could be a potential surrogate marker for the rate of dissemination and overall tumor burden in bone marrow (BM). In such case, CTCs may be a powerful biomarker of malignant transformation and disease aggressiveness. Aim: To investigate the clinical significance of CTCs in patients with smoldering (SMM), newly diagnosed (NDMM) and relapsed/refractory MM (RRMM), and to compare the transcriptional profile of CTCs across the disease spectrum. Methods: Next-generation flow (NGF) cytometry was used to assess the percentage of CTCs in PB of 1,157 patients: 316 with SMM, 650 with NDMM and 191 with RRMM. In each disease setting, patients were sub-classified into three groups with undetectable, low and high percentage of CTCs. Cutoffs were defined using maximally selected rank statistics adjusted for time to progression (TTP) in SMM and progression free survival (PFS) in NDMM/RRMM. A subset of SMM patients (n=86) was enrolled in GEM-CESAR. Transplant eligible (n=374) and ineligible (n=276) NDMM, as well as RRMM patients, were homogenously treated according to the GEM2012MENOS65, GEM-CLARIDEX and GEM-KYCYDEX clinical trials, respectively. In 40 patients (2 SMM, 33 NDMM and 5 RRMM) paired CTCs and BM tumor cells were FACSorted and their transcriptional profile was analyzed using RNAseq. Differentially expressed genes were investigated using DESeq2. Results: CTCs were detected in 248/316 (78%), 597/650 (92%) and 170/192 (89%) of SMM, NDMM and RRMM patients. Median CTC frequencies were: 0.001% (0.05 CTCs/µL), 0.01% (0.64 CTCs/µL) and 0.005% (0.22 CTCs/µL), respectively. There were 79 genes differentially expressed between patient-matched CTCs and BM tumor cells (e.g., FLNA, EMP3, LGALS9, MUC1). These were functionally related with TNFα signaling and inflammatory response (enriched in CTCs), as well as to cell cycle and MYC targets (enriched in BM tumor cells). Interestingly, the enrichment of these signatures in CTCs and BM tumor cells was progressively more pronounced from SMM to NDMM and RRMM. Altogether, these data suggest that the CTC-based dissemination potential peaks at the stage of NDMM, which could be related to greater inflammation in BM and cell cycle arrest driving tumor cell egression into PB. There were significant associations between the percentage of CTCs and the 2/20/20 IMWG risk model in SMM, the ISS in NDMM, and high-risk cytogenetics in all three-disease settings. Untreated SMM patients (n=230) with high CTC levels (≥0.02%) showed ultra-high risk of transformation vs those with low and undetectable CTCs (median TTP of 11 months vs not reached [NR] in both; P < .0001). Notably, SMM patients with ≥0.02% CTCs enrolled in GEM-CESAR have not reached a median TTP; thus, early intervention abrogated the poor prognosis of high CTC levels. Transplant-eligible NDMM patients stratified by undetectable, low and high (≥0.2%) CTC levels showed median PFS of NR, 78 and 47 months, respectively (P < .0001). Significant risk stratification was further observed in transplant ineligible NDMM (median PFS: NR, 31 and 14 months, respectively, P = .002) and RRMM (median PFS: NR, 24 and 7 months, respectively, P = .004). In untreated SMM, multivariate analysis of TTP including CTCs, serum M-component (>2 g/dL), sFLC ratio (>20) and BM plasma cells (>20%) selected CTCs as an independent prognostic factor (hazard ratio [HR]: 1.61, P = .015) together with the M-component and sFLC ratio. In NDMM, multivariate analysis of PFS including CTCs, BM plasma cells counts by morphology and flow cytometry, ISS, LDH, cytogenetics and transplant eligibility showed that high CTC levels had independent prognostic value (HR: 1.43, P = .003). Only the achievement of undetectable measurable residual disease (MRD) abrogated the poor prognosis of high CTC levels. Conclusions: This is the largest study investigating the role of CTCs in smoldering and active MM. Our results show that tumor cells are continuously trafficking in PB, possibly through a dynamic mechanism of egression that peaks in NDMM. Evaluation of CTCs in PB outperformed quantification of BM tumor burden in SMM and NDMM, and showed prognostic value in all three-disease stages. Thus, CTC assessment should be part of the diagnostic workup of MM. Early intervention in high risk SMM and undetectable MRD in NDMM may abrogate dismal outcomes associated with high CTC levels. Disclosures Puig: Amgen, Celgene, Janssen, Takeda: Consultancy; Celgene: Speakers Bureau; Celgene, Janssen, Amgen, Takeda: Research Funding; Amgen, Celgene, Janssen, Takeda and The Binding Site: Honoraria. Cedena: Janssen, Celgene and Abbvie: Honoraria. Oriol: GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Consultancy, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS/Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Sureda: Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Kite, a Gilead Company: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; GSK: Consultancy, Honoraria, Speakers Bureau; Roche: Other: Support for attending meetings and/or travel; Bluebird: Membership on an entity's Board of Directors or advisory committees; Mundipharma: Consultancy; MSD: Consultancy, Honoraria, Speakers Bureau; BMS/Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Support for attending meetings and/or travel, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Support for attending meetings and/or travel, Research Funding, Speakers Bureau. De Arriba: Amgen: Consultancy, Honoraria; Glaxo Smith Kline: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Speakers Bureau; BMS-Celgene: Consultancy, Honoraria, Speakers Bureau. Moraleda: Pfizer: Other: Educational Grants, Research Funding; Sanofi: Other: Educational Grants, Research Funding; MSD: Other: Educational Grants, Research Funding; ROCHE: Consultancy, Honoraria, Other: Educational Grants, Research Funding; Takeda: Consultancy, Honoraria, Other: Educational Grants, Research Funding; Sandoz: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Other: Educational Grants, Research Funding; Gilead: Consultancy, Honoraria, Other: Educational Grants, Research Funding; Jazz Pharmaceuticals: Consultancy, Honoraria, Other: Educational Grants, Research Funding; NovoNordisk: Other: Educational Grants, Research Funding; Janssen: Other: Educational Grants, Research Funding; Celgene: Other: Educational Grants, Research Funding; Amgen: Other: Educational Grants, Research Funding. Terpos: GSK: Honoraria, Research Funding; Genesis: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Sanofi: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Novartis: Honoraria; Janssen-Cilag: Consultancy, Honoraria, Research Funding; BMS: Honoraria; Amgen: Consultancy, Honoraria, Research Funding. Goldschmidt: Incyte: Research Funding; Adaptive Biotechnology: Consultancy; BMS: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Celgene: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Chugai: Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; GSK: Honoraria; Novartis: Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Johns Hopkins University: Other: Grant; Molecular Partners: Research Funding; MSD: Research Funding; Mundipharma: Research Funding; Dietmar-Hopp-Foundation: Other: Grant; Sanofi: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Takeda: Consultancy, Research Funding; Amgen: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding. Avet-Loiseau: Adaptive Biotechnologies: 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; Janssen: 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; Sanofi: 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; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Roccaro: AstraZeneca,: Research Funding; Amgen, Celgene, Janssen, Takeda: Membership on an entity's Board of Directors or advisory committees; Associazione Italiana per la Ricerca sul Cancro (AIRC): Research Funding; European Hematology Association: Research Funding; Fondazione Regionale per la Ricerca Biomedica (FRRB), Transcan-2 ERA-NET: Research Funding. Martinez-Lopez: Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: 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; Incyte: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: 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; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Lahuerta: Celgene: Other: Travel accomodations and expenses; Celgene, Takeda, Amgen, Janssen and Sanofi: Consultancy. Ocio: Amgen: Consultancy, Honoraria; Bristol-Myers Squibb/Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Speakers Bureau; Takeda: Consultancy, Honoraria, Speakers Bureau; Sanofi: Consultancy, Honoraria; Karyopharm: Consultancy; MSD: Honoraria; Oncopeptides: Consultancy, Honoraria; Pfizer: Consultancy; Secura-Bio: Consultancy. Rosinol: Janssen, Celgene, Amgen and Takeda: Honoraria. Bladé Creixenti: Janssen, Celgene, Takeda, Amgen and Oncopeptides: Honoraria. Mateos: AbbVie: Honoraria; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Honoraria; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bluebird bio: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies: Honoraria, Membership on an entity's Board of Directors or advisory committees; Regeneron: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene - Bristol Myers Squibb: 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; Oncopeptides: Honoraria; Sea-Gen: Honoraria, Membership on an entity's Board of Directors or advisory committees. San-Miguel: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, GlaxoSmithKline, Janssen, Karyopharm, Merck Sharpe & Dohme, Novartis, Regeneron, Roche, Sanofi, SecuraBio, and Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees. Paiva: Adaptive, Amgen, Bristol-Myers Squibb-Celgene, Janssen, Kite Pharma, Sanofi and Takeda: Honoraria; Bristol-Myers Squibb-Celgene, Janssen, and Sanofi: Consultancy; Celgene, EngMab, Roche, Sanofi, Takeda: Research Funding.

Introduction: Daratumumab (Dara) is an anti-CD38 monoclonal antibody representing a novel treatment agent for multiple myeloma (MM). Nonetheless, several studies have reported a Dara-related impairment of CD34+ hematopoietic stem cell (HSC) mobilization and post-autologous stem cell transplantation (ASCT) complications, including low yields of mobilized HSCs and delayed neutrophil engraftment. Impact of Dara on the mobilization process and HSCs remains poorly understood even though sufficient yields of CD34+ cells are necessary for a successful ASCT and subsequent patient recovery. Aims: To compare the effect of the Dara-containing (Dara-Bortezomib-Dexamethasone [D-VCd]) and conventional (Bortezomib-Thalidomide-Dexamethasone [VTd]) therapy on CD34+ HSCs. Methods: Transplant eligible MM patients were treated with D-VCd or VTd induction regimen followed by a cyclophosphamide + G-CSF mobilization and a high-dose melphalan D -1 before ASCT. Flow cytometry (FCM) screening of CD34+ subsets was performed in the bone marrow (BM) or apheresis product (AP) at three consecutive time points: 1) diagnostic BM (DG), 2) mobilization AP (MOB), 3) a day prior ASCT BM (D-1). Furthermore, RNA sequencing (RNAseq) of sorted CD34+ cells was performed on total RNA with ribo-depletion protocol in AP after the induction. D-VCd samples had lower RNA yields thus the D-VCd or VTd groups were processed as independent batches. Results: Clinical data revealed no significant differences in mobilization (p >0.050) likely due to a small cohort sizes (D-VCd n=5 vs VTd n=9), though a trend towards worse performance in D-VCd was observed. Median CD34+ cell yield was 3.08 vs 10.56 x 10 6/kg. Platelet recovery of >20x10 9/L was D+14 vs D+12 (range: 11-18 vs 10-16). Neutrophil recovery of >0.5x10 9/L was D+12 in both groups (range: 11-17 vs 11-12). In FCM analysis, DG (n=14), MOB D-VCd (n=5) vs VTd (n=9), D-1 D-VCd (n=7) vs VTd (n=15) were compared. CD34+ frequency (Fig. 1A) difference in MOB D-VCd vs VTd was insignificant (median: 1.15% vs 1.89%), whereas CD34+ fraction dropped in D-1 D-VCd (median: 0.52% vs 0.72%, p=0.027), albeit there was no significant reduction in D-1 D-VCd vs initial DG (median: 0.52% vs 0.45%). Differences in the distribution of certain HSC subsets were detected in the CD34+ pool (Fig. 1B-E). Frequency of multipotent progenitors (MPPs) (Fig. 1B) was increased in MOB D-VCd (median: 82.1% vs 66.2%, p=0.004). Frequency of lympho-myeloid-primed progenitor + granulocyte-monocyte progenitor (LMPP+GMP) (Fig. 1C) subset was reduced in D-VCd in both MOB (median: 1.7% vs 16.9%, p=0.042) and D-1 (median: 5.3% vs 14.0%; p=0.026). Erythro-myeloid progenitors (EMPs) (Fig. 1D) were reduced in MOB D-VCd (median: 10.7% vs 19.5%, p=0.042), while the frequency of EMPs increased in D-1 D-VCd (median: 20.8% vs 12.4%, p=0.045). No considerable differences were found in the expression of adhesion molecules CD44/HCAM or CD184/CXCR4. CD38 was strongly diminished in the whole D-VCd CD34+ fraction of MOB and D-1. To understand whether the differences in the mobilization efficacy after D-VCd induction were reflected in the expression profile of mobilized CD34+ cells, differential expression analysis was performed. Overall 133 significantly deregulated genes (p(-)1) between cohorts (D-VCd n=5 vs VTd n=5) were revealed (Fig. 2). Pathway analysis showed cellular response and localization as the most deregulated categories. The list of deregulated genes contained 25% of non-coding RNAs, some of which were linked to a protein localization in the cell (RN7SL1/2). The expression of adhesion molecules was inspected independently. Out of 59 HSC hallmark genes, only 8 were significantly altered in D-VCd. Interestingly, the main homing molecule CXCR4 seemed to be downregulated in D-VCd, while integrins A3 and B4 were upregulated. Conclusions: Despite the limited cohort sizes, a prospective trend of delayed neutrophil and platelet recovery was observed after D-VCd therapy. FCM analysis revealed a significant reduction of CD34+ subsets responsible, among others, for a reconstitution of neutrophils and megakaryocytes. A strong signal in transcriptome data which would potentially explain differential mobilization in D-VCd cohort was not detected, nevertheless, several genes with adhesive/homing and stem cell differentiation function were indeed altered. The results warrant further investigation. Figure 1 Figure 1. Disclosures Hajek: BMS: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria; Novartis: Consultancy, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharma MAR: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding.

I ntroduction Extramedullary disease (EMD) is a less frequent manifestation of multiple myeloma (MM), where MM plasma cells become independent of the bone marrow (BM) microenvironment and infiltrate other tissues and organs. The incidence of EMD is increasing and is associated with worse prognosis and drug resistance. The specific and efficient treatment is lacking. Therefore, a better understanding of EMD pathogenesis is desperately needed. Aims To identify biological pathways leading to EMD development and to evaluate therapeutic targets in EMD plasma cells with further focus on EMD tumor microenvironment to reveal presence of effector immune cells that are crucial for immunotherapy. Methods To identify EMD specific genes, FACS/MACS sorted aberrant plasma cells were collected from: i) fresh 11 EMD relapse tumors for which we had ii) 7 corresponding cryopreserved paired BM samples from the time of MM diagnosis (NDMM), iii) 9 unpaired fresh NDMM without EMD confirmed by PET-CT and iv) 6 unpaired fresh relapsed MM (RRMM). For library preparation, we used total RNA with rRNA depletion protocol and Illumina sequencing. Residual rRNA was filtered out by SortMeRNA. Differential expression analysis was performed using Salmon for read mapping and quantification and Deseq2 package. For single-cell RNAseq we used 10x Genomics technology for sequencing and CellRanger and Seurat for data processing and analysis. Results To better understand the aggressive nature of EMD, we have analyzed bulk RNA samples (7 EMD samples plus 7 corresponding cryopreserved paired BM samples from the time of MM diagnosis). Our preliminary analysis revealed a unique EMD profile (Fig 1A) with 423 up-regulated and 421 down-regulated genes in EMD samples (adjusted p-value < 0.1; absolute fold change > 1.5), with G2M checkpoint proteins being the most enriched hallmark pathways pointing to higher proliferation of EMD cells. EMD down-regulated genes mainly belong to genes of the adaptive immune response which together with lower immunoglobulin production suggest loss of mature plasma cell function. Among the top genes uniquely overexpressed in EMD (versus RRMM or NDMM) were SCD and ELOVL6 that regulate crucial steps in unsaturated fatty acids synthesis. Also their transcription factor SREBF1 was significantly up-regulated. The importance of these genes in EMD pathogenesis can be supported by the involvement of SREBP1 in stem cell differentiation and mediation of bortezomib resistance by ELOVL6 (Yi et al. 2018, Lipchick et al. 2021). Our dataset also revealed several deregulated lncRNA in EMD compared to NDMM. MALAT1 was highly expressed, however, we did not confirm results by Handa et al. 2017 showing lncRNA MALAT1 as upregulated in EMD. Furthermore, we aimed to evaluate expression of known immunotherapy MM targets being currently in use or under investigation. We compared the information about expression level in EMD vs paired NDMM, with unpaired NDMM without EMD lesion confirmed by PET/CT, and with RRMM. The analysis revealed a decrease in the expression of several antigens commonly used in anti-MM immunotherapy (e.g. CD38, SLAMF7, BCMA or PDL1) on EMD PCs (Fig 1B). Intriguingly, our data show EMD specific elevated expression of EZH2 gene being promising target in preclinical MM investigation which can prove efficient especially for the aggressive MM stage - EMD. Effective immunotherapy depends on the presence of effector immune cells. Therefore, we have evaluated immune cell types and their proportion in EMD tumors. Using flow cytometry we identified T and NK cells as the only immune cell subsets present in EMD tumors (median 0.9% and 0.5%, respectively). Single-cell RNAseq analysis of two EMD samples supported these findings. Conclusions Here, we present up to our knowledge the worldwide largest cohort of 11 EMD samples (including 7 longitudinal pre-EMD/EMD samples) analysed using RNAseq with focus on biological pathways and dysregulation of particular genes leading to EMD development. Drop of expression of several known drug targets may suggest limited efficacy of the modern treatment in EMD as already presented by Jelinek et al., 2021. Importantly, we are also providing the initial insight into the microenvironment (including single-cell RNA analysis) of EMD tumors, where we detected presence of T cell and NK cells in very limited numbers. Figure 1 Figure 1. Disclosures Hajek: Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria; Novartis: Consultancy, Research Funding; Pharma MAR: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding.

Background: Tumor burden in multiple myeloma (MM) is routinely evaluated in the bone marrow, though its prognostic value is not proven. There is an increasing interest in liquid biopsies due to its minimally invasive nature and more comprehensive evaluation of tumor burden. Growing evidence supports the quantification of circulating plasma cells (cPCs) measured by multiparameter flow cytometry (MFC) as a powerful diagnostic biomarker suitable for risk stratification of newly diagnosed transplant eligible MM (Garces et al, EHA 2021). Nevertheless, there are virtually no data regarding prognostic impact of cPCs in MM patients ineligible for transplantation. Primary plasma cell leukemia (pPCL) is a rare and most aggressive monoclonal gammopathy with dismal outcomes defined by more than 20% of cPCs and/or absolute cPCs count of ≥2 x10 9/L. Recently, there have been many efforts to redefine these criteria as lower number of cPCs probably portends equally poor prognosis. Aims: To evaluate prognostic significance of cPCs in a large cohort of transplant ineligible (Tx-ineligible) newly diagnosed MM patients and to define cut-offs for risk stratification. Moreover, to establish cut-off identifying ultra high risk MM patients mimicking the prognosis of pPCL and propose new definition of pPCL. Methods: Circulating PCs were measured by 8 color flow cytometry in 402 Tx-ineligible MM patients (including n=7 pPCL) diagnosed between 2012 and 2019 at University Hospitals Brno and Ostrava, Czech Republic. Patients were treated in real-world setting and the clinical analysis was performed retrospectively based on data from the Czech Registry of Monoclonal Gammopathies. Median follow-up was 20.5 months. The intermediate cutoff was identified using ROC analysis considering overall survival (OS). Moreover, data from the large published cohort of pPCL patients treated in real-world setting were used to find a new cut-off identifying these ultra-high-risk pPCL-like patients (Jurczyszyn et al. BJH,2018). Results: Circulating PCs were detected in peripheral blood (PB) of 303/402 (75%) patients. In 303 patients with detectable cPCs the median percentage was 0.06% with range 0.0008% - 79%. The median limit of detection of MFC technique was 0.006 (sensitivity 10e-5). Patients stratification into 3 subgroups according to quantification of cPCs (low: ≤ 0.2%; intermediate: 0.2 - 2% and high: >2.0%) resulted in significantly different OS (36.5 vs. 28.1 and 13.6 months; p < 0.0001) and progression free survival (PFS) (17.9 vs. 14.7 and 3.4 months; p < 0.0001). Patients with no detected cPCs (0%) did not separate from subgroup >0% to 0.05) suggesting that next-generation flow cytometry (NGF) with sensitivity 10e-6 is needed for the identification of this favorable prognostic group. In order to demonstrate that patients with more than 2% of cPCs have similarly poor outcome as pPCL patients, we compared those with 2% - 20% (n=15) vs. those with >20% (n=7) of cPCs. The outcomes were practically identical with median PFS of 3.1 vs. 4.2 months (p = 0.23) and median OS of 13.6 vs. 14.6 months (p=0.23). Next, we analyzed patient´s characteristics in association with the level of cPCs (low, intermediate and high) and we demonstrated that there was significantly higher proportion of patients with ISS III stage (38%, 52% and 82%), elevated LDH level (8%, 19% and 55%) and high risk cytogenetics (12%, 21% and 36%) hand in hand with increasing number of cPCs. CPCs were identified as the most powerful prognostic marker in univariate (HR=2.7 for OS and HR=6.3 for PFS; p=0.001) and multivariate analysis (HR=4.2 for OS and HR=5.8 for PFS; p Conclusion: The quantification of cPCs in PB of newly diagnosed MM is the most powerful prognostic factor as we demonstrated on a large cohort of transplant ineligible patients. We defined 2% of cPCs as a new cut-off for ultra high risk myeloma resembling behavior of primary PCL. We propose this 2% cut-off for redefinition of pPCL criteria that warrants further investigation in prospective setting. To identify subgroup with especially favorable outcome with no detectable cPCs, NGF with high sensitivity of 10e-6 is needed. Quantification of cPCs by MFC is easy, fast, affordable and worldwide available procedure providing highly relevant prognostic information that might be implemented into routine clinical practice. Figure 1 Figure 1. Disclosures Jurczyszyn: Janssen-Cilag, Amgen: Honoraria, Speakers Bureau. Castillo: Abbvie: Consultancy, Research Funding; BeiGene: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; Janssen: Consultancy; Roche: Consultancy; TG Therapeutics: Research Funding. Hajek: Janssen: Consultancy, Honoraria, Research Funding; Pharma MAR: Consultancy, Honoraria; BMS: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding.

Background: The addition of ixazomib to the doublet lenalidomide and dexamethasone (RD) in relapsed and refractory multiple myeloma (RRMM) has shown significant benefit in progression free survival (PFS) in the TOURMALINE-MM1 study. Several real-world data including our previous analysis confirmed that the combination IRD is feasible and with fair outcomes even outside the clinical trial. Here we report an updated analysis which is aimed at overall survival (OS) and the PFS2 interval which is defined as the time from the date of treatment initiation to the date of first documentation of progressive disease after initiation of further anti-myeloma treatment or death from any cause. Methods: We analyzed a cohort of 344 patients with RRMM, 127 being treated by IRD and 217 by RD combination. The group characteristics and study design are described elsewhere. 1 The median follow-up of the whole cohort was 28.5 months. The primary endpoint was OS, OS in patients with relapse 1-3, progression free survival (PFS), and PFS2. Secondary endpoints were response rates and toxicity profile. For statistical analysis we used Fisher's exact test or Mann-Whitney U test. Survival measures were assessed using the Kaplan-Meier methodology, and statistical significance was assessed using the log-rank test at a significance level of α = 0.05 (all tests two-sided). Results: The outcomes of OS in the whole cohort were already published before, with significantly longer median OS in the IRD vs RD cohort (mOS 36.6 months vs 26.0 months, p = 0.008).1 In the follow-up analysis, the medians were slightly improved, maintaining a significant difference (mOS 40.9 vs 27.1 months, p = 0.001). In patients treated within relapse 1-3, the results outcomes were even more pronounced (mOS 51.7 vs 27.8 months, p ˂ 0.001). The median PFS was also better in the IRD cohort (mPFS 17.5 vs 12.5 months, p = 0.013) but the results did not substantially differ from our previous analysis. The median PFS2 in the IRD vs RD cohort was significantly longer in the IRD cohort (mPFS2 29.8 vs 21.6 months, p = 0.016). The subsequent therapy included mostly pomalidomide (27.5% vs 30.8%), bortezomib (28.8% vs 28.2%) or thalidomide (10.0% vs 16.2%). Monoclonal antibodies (daratumumab, isatuximab) were more frequently used after IRD combination (21.3% vs 4.3%). The response rates in the IRD vs RD cohort were similar as in our primary analysis: overall response rate (ORR) 73.0% vs 66.8%, with significant difference in very good partial response and better (VGPR+) 38.1% vs 26.3%. The toxicity profile did not reveal any additional safety concerns. Majority of grade 3+ toxicities included hematological toxicity (anemia, neutropenia, thrombocytopenia) and infections, with similar distribution in the cohorts. Conclusion: The treatment of RRMM using the full oral IRD regimen in routine clinical practice is easy, safe and with significantly improved outcomes in comparison to RD doublet. Our follow-up analysis confirmed the impact on OS in patients in the whole cohort including relapse 1-3. The median PFS2 was also longer in the IRD cohort, possibly affected by more frequent use of monoclonal antibodies in the next treatment. With support of AZV 17-29343A, NV18-03-00500, MH CZ - DRO (FNOl, 00098892), IGA-LF-2021-001. 1) Minarik J, Pika T, Radocha J. et al. Survival benefit of ixazomib, lenalidomide and dexamethasone (IRD) over lenalidomide and dexamethasone (Rd) in relapsed and refractory multiple myeloma patients in routine clinical practice. BMC Cancer 2021; 21: https://doi.org/10.1186/s12885-020-07732-1 Disclosures Minarik: Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria. Hajek: Novartis: Consultancy, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Pharma MAR: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; BMS: 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.

Background: Within the spectrum of monoclonal gammopathies, there are various subgroups with unique biological and clinical profiles. Namely, the presence of multiple myeloma (MM) and light-chain amyloidosis (AL) pts with MGUS-like phenotype has been hypothesized, but the criteria to identify this subgroup are poorly defined and lack clinical validation. Aim: Develop an algorithm based on a large flow cytometry dataset across the spectrum of monoclonal gammopathies, for automated identification of MM and AL pts with MGUS-like phenotype. Methods: This study included 5,114 pts with monoclonal gammopathies and available flow cytometry data on the frequency of bone marrow (BM) plasma cells (PC) and the percentages of normal and clonal PC within the BM PC compartment, at diagnosis. An algorithm to classify pts with MGUS-like phenotype was developed based on these three parameters, obtained from 548 MGUS, 393 smoldering MM (SMM) and 2,011 MM pts. Newly diagnosed MM pts were homogeneously treated according to the GEM2000 (n = 486), GEM2005MENOS65 (n = 330), GEM2005MAS65 (n = 239), GEM2010MAS65 (n = 230), GEM2012MENOS65 (n = 450) and CLARIDEX (n = 276) protocols. The prognostic value of the MGUS-like phenotype was validated in 96 SMM pts studied in Arkansas and 1,859 MM pts treated outside clinical trials in Czech Republic. The clinical significance of the algorithm was investigated in two independent series of Spanish (n = 102) and Italian (n = 105) AL pts. Results: The frequency of BM PC and of normal and clonal PC within the BM PC compartment were used to plot MGUS, SMM and MM pts in a principal component analysis (PCA). Lines defining 1.5 standard deviations of MGUS and MM pts were used as reference to classify each of the 5,114 cases. Once plotted against the dataset, individual pts were classified as MGUS-, intermediate- or MM-like, if their location in the PCA fell inside the MGUS, the overlapping or the MM reference lines, respectively. In the training SMM series, patient classification into MGUS-, intermediate- and MM-like phenotype resulted in significantly different rates of disease progression (0%, 54% and 66% at 5y, respectively; P < .001). These results were validated in the Arkansas series (8%, 27% and 71% at 5y, respectively; P < .001). Only 5% of SMM pts with high-risk disease according to Mayo or PETHEMA criteria had an MGUS-like phenotype, and these had virtually no risk of progression at 5y. In the training MM series, pts with MGUS-like phenotype showed significantly longer progression free (PFS) and overall survival (OS) vs the remaining pts. Median PFS was 10y vs 3y (hazard ratio [HR]: 0.46, P < .001) and median OS was not reached (NR) vs 6.5y (HR: 0.48, P < .001), respectively. These results were validated in the Czech Republic series with significant differences in PFS (HR: 0.45, P < .001) and OS (HR: 0.38, P < .001) between MGUS-like vs other MM pts. MGUS-like classification in the training MM series retained independent prognostic value in multivariate analyses of PFS (HR: 0.48, P < .001) and OS (HR: 0.54, P = .033), together with ISS, LDH, cytogenetics, induction regimen, transplant-eligibility and complete remission (CR). MGUS-like pts showed similar PFS (P = .932) and OS (P = .285) regardless of having standard vs high risk cytogenetics. Notably, MGUS-like transplant-eligible MM pts treated with proteasome inhibitors, immunomodulatory drugs and corticoids during induction showed PFS and OS rates at 5y of 86% and 96%, respectively. Differences in PFS among MGUS-like MM pts achieving ≥CR vs Classification of AL pts into the MGUS-, intermediate- and MM-like phenotype resulted in significantly different PFS in the Spanish (median of 28, 20 and 1 months, respectively; P = .001) and Italian (median 32, 11 and 3 months, respectively; P < .001) cohorts. Conclusions: We developed an algorithm that can be readily installed in clinical flow cytometry software, and requires three parameters that are routinely assessed at screening. Patient' automated classification using the algorithm was validated in large series across the spectrum of monoclonal gammopathies. Because pts with MGUS-like phenotype have a distinct clinical behavior, their identification could become part of the diagnostic workup in SMM, MM and AL. Disclosures Cedena: Janssen, Celgene and Abbvie: Honoraria. Milani: Celgene: Other: Travel support; Janssen-Cilag: Honoraria. Cordon: Cytognos SL: Research Funding. Oriol: Takeda: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Janssen: Consultancy. de la Rubia: Amgen, Bristol Myers Squibb,: Honoraria, Speakers Bureau; Celgene, Takeda, Janssen, Sanofi: Honoraria; Ablynx/Sanofi: Consultancy; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: TRAVEL, ACCOMMODATIONS, EXPENSES; AbbVie: Consultancy; Bristol Myers Squibb: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel Accommodations; GSK: Consultancy; Takeda: Consultancy; Sanofi: Membership on an entity's Board of Directors or advisory committees. De Arriba: Amgen: Consultancy, Honoraria; Glaxo Smith Kline: Consultancy, Honoraria; BMS-Celgene: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau. Cabañas: Janssen: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Sanofi: Honoraria. Gonzalez De La Calle: Celgene-BMS, Janssen, Amgen: Honoraria. Rodríguez-Otero: Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Regeneron: Membership on an entity's Board of Directors or advisory committees; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees; Kite: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Consultancy, 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; BMS/Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel and other expenses. Hajek: Pharma MAR: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Research Funding; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding. Jimenez-Zepeda: BMS, Amgen, Takeda, Janssen: Honoraria. Palladini: Janssen Global Services: Honoraria, Other: advisory board fees; Pfizer: Honoraria; Siemens: Honoraria. Rosinol: Janssen, Celgene, Amgen and Takeda: Honoraria. Bladé Creixenti: Janssen, Celgene, Takeda, Amgen and Oncopeptides: Honoraria. Martínez-López: Janssen, BMS, Novartis, Incyte, Roche, GSK, Pfizer: Consultancy; Roche, Novartis, Incyte, Astellas, BMS: Research Funding. Mateos: Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; Regeneron: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene - Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sea-Gen: 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; AbbVie: Honoraria; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bluebird bio: Honoraria; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Honoraria; Oncopeptides: Honoraria. San-Miguel: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, GlaxoSmithKline, Janssen, Karyopharm, Merck Sharpe & Dohme, Novartis, Regeneron, Roche, Sanofi, SecuraBio, Takeda: Consultancy, Other: Advisory board. Paiva: Bristol-Myers Squibb-Celgene, Janssen, and Sanofi: Consultancy; Adaptive, Amgen, Bristol-Myers Squibb-Celgene, Janssen, Kite Pharma, Sanofi and Takeda: Honoraria; Celgene, EngMab, Roche, Sanofi, Takeda: Research Funding.

Introduction: Although highly effective agents and novel therapeutic strategies are being developed, high-dose chemotherapy followed by autologous stem cell transplantation (HDT/ASCT) has not been overcome in the first-line treatment for fit patients (pts) with multiple myeloma. The objective of this work is to retrospectively analyze the use of this procedure in newly diagnosed Czech patients. Methods: Data were derived using the Czech Myeloma Group Registry of Monoclonal Gammopathies. By February 2 nd 2021, a total of 2154 newly diagnosed multiple myeloma patients who underwent HDT/ASCT were identified. Results: At the time of multiple myeloma diagnosis, the median age was 59 years; 24%/56%/14%/5%/1% pts were ECOG 0/1/2/3/4; 44%/32%/24% pts were ISS stage I/II/III; 14.5%/17.5%/68% and 84%/16% pts were Durie-Salmon stage I/II/III and subclassification A/B, respectively. The combinations of agents used in the induction regimen were proteasome inhibitor (PI), immunomodulatory drug (IMiD) and glucocorticoid (GC) in 28.5% (613/2154) pts; PI, GC and chemotherapy (CHT) in 24.8% (534/2154) pts; GC and CHT in 22,5% and IMiD, GC and CHT in 16.1% (346/2154). Other combination of drugs was used in 8.2% (177/2154) pts. It was registered that 3.7% (79/2154) induction regimens were switched to a different combination because of toxicity, patient's choice, poor peripheral venous access or other reasons. Single HDT/ASCT was performed in 77.3% (1665/2154) cases whereas tandem HDT/ASCT was given to 11.8% (254/2154) patients. In 10% (215/2154) cases, the transplantation technique was not specified. Nine percent (193/2154) patients were treated within a clinical study. The median progression free survival (mPFS) and the median overall survival (mOS) of the whole cohort was 28.9 and 92.1 months, respectively. Information about response to treatment before and after the high-dose therapy were available for 75.7% (1627/2154) and 92.2% (1987/2154) patients, respectively. Disease status at the time of HDT/ASCT was defined as stringent complete response (sCR) at 2.2% (36/1627), complete response (CR) at 11.9% (194/1627), very good partial response (VGPR) at 38.2% (621/1627), partial response (PR) at 40.9% (666/1627), minimal response (MR) at 3.6%, (58/1627), stable disease (SD) at 2.2% (36/1627), progressive disease (PD) at 1% (16/1627) patients. The overall response rate (ORR) on day 100 was 92.8% (sCR: 10.5% [209/1987], CR: 22.4% [446/1987], VGPR: 35% [696/1987], PR: 24.8% [493/1987], MR: 2.7% [54/1987], SD: 1.4% [27/1987], PD: 3.1% [62/1987]). We also performed a survival analysis of patients progressing up to 18 months after HDT/ASCT (n=1219) versus patients progressing in more than 18 months (n=935). The median OS was 41.5 versus 124.9 months, respectively. An analysis of the role of tandem HDT/ASCT in this real-world cohort will be presented at the conference. Conclusion: Globally as well as in the Czech Republic, HDT/ASCT is an important therapeutic approach in the first-line treatment of multiple myeloma. Our analysis of 2154 newly diagnosed transplant-eligible patients confirms high effectiveness - ORR of 92.8%, mPFS of 28.9 months, and long-term survival reaching mOS of 92.1 months. Disclosures Minarik: Amgen: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Takeda: Consultancy, Honoraria.

Background: Evaluation of minimal residual disease (MRD) in multiple myeloma (MM) has become a standard procedure and has been incorporated to International Myeloma Working Group updated response criteria in 2016. Its value as an important prognostic factor with impact on survival as well as a relevant end-point in clinical trials has been established by many studies. Assessment of MRD inside the bone marrow is performed basically by two standardized techniques: i) next generation flow cytometry (NGF) and ii) next generation sequencing (NGS). Positron emission tomography and computed tomography (PET/CT) is currently considered as a best tool to evaluate MRD outside of the bone marrow. The standard timepoint to assess the MRD by PET/CT in transplant eligible newly diagnosed multiple myeloma (TE NDMM) patients is considered Day +100 post-autologous stem cell transplantation (ASCT) according to largest CASSIOPET study (Moreau et al., Blood, 2019). Nevertheless, this kind of data from real-world outside the clinical trials setting remains limited. Aim: To evaluate the prognostic impact of PET/CT performed on Day +100 post-ASCT in consecutive cohort of real-world TE NDMM patients from a single center in the Czech Republic. Methods: 18 TE NDMM patients with median age of 59 years (range 42 - 71 years), ISS stage III 17% (3/18) diagnosed between September 2017 and June 2019 received proteasome inhibitor plus immunomodulatory drug containing induction. Patients who reached at least very good partial response (VGPR) after ASCT were indicated for MRD evaluation using NGF technique according to standardized EuroFlow protocol with sensitivity to 10e-6 and for PET/CT evaluation - both at Day +100 post-ASCT. For the evaluation of PET/CT scans complex evaluation by nuclear medicine specialist based on Italian Myeloma criteria for PET Use (IMPeTUs) criteria were used (IMPeTUs) criteria were used (Nanni et al., Eur. J. Nucl. Med. Mol. Imaging. 2018). Results: Of 18 evaluated TE NDMM patients (17 in complete remission (CR), 1 in VGPR), there were 78% (14/18) considered PET/CT negative and 22% (4/18) were considered PET/CT positive at Day +100 post-ASCT. Patients who were PET/CT positive had significantly shorter median PFS (mPFS 29 days) versus those who were PET/CT negative (mPFS not reached); p value < 0.001. Calculated median follow-up for the whole cohort was 245 days. Interestingly, one patient who was NGF MRD negative within the bone marrow was considered PET/CT positive and has early relapse after ASCT. Conclusion: We demonstrated on limited number of real-world TE NDMM patients that those who are PET/CT positive at Day +100 post-ASCT have significantly shorter mPFS compared to those who are PET/CT negative. The aim of myeloma community should lead to the implementation of simultaneous assessment of MRD inside the bone marrow in combination with imaging technique (PET/CT) outside the bone marrow, as this combined evaluation seems to be the most important prognostic factor. Moreover, great effort should be make to establish standardized evaluation protocols for nuclear medicine specialists as well as the most appropriate time-points to perform PET/CT, such as Day +100 post-ASCT in TE NDMM. Figure Disclosures No relevant conflicts of interest to declare.

An unresolved issue in chronic lymphocytic leukemia (CLL) is whether IGHV3-21 gene usage, in general, or the expression of stereotyped B-cell receptor immunoglobulin defining subset # 2 (IGHV3-21/IGLV3-21), in particular, determines outcome for IGHV3-21-utilizing cases. We reappraised this issue in 8593 CLL patients of whom 437 (5%) used the IGHV3-21 gene with 254/437 (58%) classified as subset # 2. Within subset # 2, immunoglobulin heavy variable (IGHV)-mutated cases predominated, whereas non-subset # 2/IGHV3-21 was enriched for IGHV-unmutated cases (P =.002). Subset # 2 exhibited significantly shorter time-to-first-treatment (TTFT) compared with non-subset # 2/IGHV3-21 (22 vs 60 months, P =.001). No such difference was observed between non-subset # 2/IGHV3-21 vs the remaining CLL with similar IGHV mutational status. In conclusion, IGHV3-21 CLL should not be axiomatically considered a homogeneous entity with adverse prognosis, given that only subset # 2 emerges as uniformly aggressive, contrasting non-subset # 2/IGVH3-21 patients whose prognosis depends on IGHV mutational status as the remaining CLL.

Peripheral T-cell lymphomas (PTCLs) are generally aggressive non-Hodgkin lymphomas with poor overall survival rates following standard therapy. One-third of PTCLs express interferon regulatory factor-4 (IRF4), a tightly regulated transcription factor involved in lymphocyte growth and differentiation. IRF4 drives tumor growth in several lymphoid malignancies and has been proposed as a candidate therapeutic target. Because direct IRF4 inhibitors are not clinically available, we sought to characterize the mechanism by which IRF4 expression is regulated in PTCLs. We demonstrated that IRF4 is constitutively expressed in PTCL cells and drives Myc expression and proliferation. Using an inhibitor screen, we identified nuclear factor κB (NF-κB) as a candidate regulator of IRF4 expression and cell proliferation. We then demonstrated that the NF-κB subunits p52 and RelB were transcriptional activators of IRF4. Further analysis showed that activation of CD30 promotes p52 and RelB activity and subsequent IRF4 expression. Finally, we showed that IRF4 transcriptionally regulates CD30 expression. Taken together, these data demonstrate a novel positive feedback loop involving CD30, NF-κB, and IRF4; further evidence for this mechanism was demonstrated in human PTCL tissue samples. Accordingly, NF-κB inhibitors may represent a clinical means to disrupt this feedback loop in IRF4-positive PTCLs.

Follicular lymphoma (FL), an indolent neoplasm caused by a t(14;18) chromosomal translocation that juxtaposes the BCL2 gene and immunoglobulin locus, has a variable clinical course and frequently undergoes transformation to an aggressive lymphoma. Although BCL2 mutations have been previously described, their relationship to FL progression remains unclear. In this study, we evaluated the frequency and nature of BCL2 mutations in 2 independent cohorts of grade 1 and 2 FLs, along with the correlation between BCL2 mutations, transformation risk, and survival. The prevalence of BCL2 coding sequence mutations was 12% in FL at diagnosis and 53% at transformation (P.0001). The presence of these BCL2 mutations at diagnosis correlated with an increased risk of transformation (hazard ratio 3.6; 95% CI, 2.0-6.2; P.0001) and increased risk of death due to lymphoma (median survival of 9.5 years with BCL2 mutations vs 20.4 years without; P = .012). In a multivariate analysis, BCL2 mutations and high FL international prognostic index were independent risk factors for transformation and death due to lymphoma. Some mutant Bcl-2 proteins exhibited enhanced antiapoptotic capacity in vitro. Accordingly, BCL2 mutations can affect antiapoptotic Bcl-2 function, are associated with increased activation-induced cytidine deaminase expression, and correlate with increased risk of transformation and death due to lymphoma.

Background : Outcomes reported in real-world practice versus controlled clinical trials show markedly shorter treatment durations, progression free survival (PFS) and overall survival (OS). Understanding effectiveness of therapeutic regimens in routine practice is critical for treating physicians as well as for regulatory and reimbursement authorities. We have performed a real-world comparison of two regimens, ixazomib, lenalidomide and dexamethasone (IRD) triplet and lenalidomide and dexamethasone (Rd) doublet in patients with relapsed and/or refractory multiple myeloma (RRMM) treated in seven Czech and one Slovak hematology-oncology centers. Patients and methods: Between 3/2015 and 5/2017, 344 patients with RRMM were treated with either IRD (N=127) or RD (N=217). Patients selected for both cohorts had the same inclusion and exclusion criteria. Patient baseline characteristics were well balanced. The data were collected through the Czech Registry of Monoclonal Gammopathies (RMG), which is an international database gathering data from patients with monoclonal gammopathies within Central Europe. Results: The median follow-up in the IRD vs RD arm was 20.8 vs 15.5 months, respectively. Median PFS in pts with 1-3 prior lines for the IRD cohort was 23.1 months (95% CI 11.8-34.5 months) and 11.6 months (95% CI 8.4-11.8 months) for the RD cohort favoring the all-oral triplet (p=0.001). The median PFS for all patients including 4+ line of therapy was 17.5 months (95% CI 10.3-24.7) in the IRD cohort versus 11.5 months (95% CI 8.6-14.3) in the RD group (p=0.005). Median OS for pts with 1-3 prior lines for IRD cohort was not reached, and was 27.1 months (95% CI 23.1-31.1 months) in the RD cohort (p=0.002). Median OS for all patients, including 4+ lines of treatment was 36.6 months in the IRD vs 26.0 months in the RD cohort (p=0.008). The PFS benefit of IRD over RD was observed in most of the assessed subgroups; in younger pts ≤65 years with hazard ratio (HR) 0.58, in pts 66-75 years HR 0.64. There was a trend towards better PFS in patients with lower ISS stage; ISS1 HR 0.53, ISS2 HR 0.58 and ISS3 the HR was 0.87. Patients in the 1st relapse (HR 0.53) benefited most from the IRD, followed by the 2nd relapse (HR 0.58), 3rd relapse (HR 0.90) and pts relapsing after 4+ therapies (HR 0.88). The PFS benefit of IRD regimen was observed in pts regardless of previous stem cell transplantation; transplant-eligible patients HR 0.51 and transplant-ineligible HR 0.71. Patients who did not benefit from the triplet regimen were those over 75 years of age and pts with the presence of extramedullary disease. The IRD treatment was well tolerated. The safety profile was concordant with previously reported data. Conclusions: This RMG comparative cohort analysis shows PFS benefit of all-oral IRD regimen over RD in the real world setting, and confirms growing evidence that long term outcomes with IRD triplet are comparable with phase 3 TOURMALINE-MM1 trial. Our analysis also shows an overall survival benefit of IRD over RD treatment. Patients older than 75 years, with 4+ lines of therapy and presence of extramedullary disease did not profit from addition of ixazomib to RD doublet.Additional data with larger patient populations confirming RWE effectiveness are warranted. With support of AZV 17-29343A, NV18-03-00500, FNOl 00098892, IGA-LF-2019-001, PROGRES Q40/08, MH CZ-DRO (UHHK, 00179906) Disclosures Minarik: Celgene: Consultancy, Honoraria, Research Funding; Amgen, BMS, Janssen-Cilag, Takeda: Consultancy, Honoraria. Straub:Amgen, Takeda, Celgene: Consultancy. Spicka:Celgene: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Sanofi: Consultancy; Takeda: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Janssen-Cilag: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen-Cilag: Consultancy, Honoraria; Sanofi: Consultancy. Skacel:Millennium Pharmaceuticals, Inc., subsidiary of Takeda Pharmaceutical Company Limited: Employment. Maisnar:Janssen, Amgen, Celgene, Takeda, BMS: Consultancy, Honoraria.

BACKGROUND: Chemoimmunotherapy with fludarabine, cyclophosphamide, and rituximab (FCR) has been the standard therapy for younger patients with CLL. FCR therapy is particularly effective in patients with immunoglobulin heavy chain variable region (IGHV) mutated CLL. Approximately half of IGHV mutated patients are progression free 8 years after FCR therapy. At the ASH 2018 meeting, we reported the initial results of the ECOG 1912 (E1912) trial, a phase 3 trial comparing the FCR regimen to the combination of ibrutinib and rituximab (IR) for previously untreated CLL patients age 70 or younger who required therapy. With median follow-up of approximately 34 months, the trial demonstrated both a progression-free survival (PFS) and an overall survival (OS) benefit relative to FCR. On sub-set analysis by IGHV mutation status, the difference in PFS was statistically significant for IGHV unmutated patients but, with current follow-up, not IGHV mutated patients. Here, we present updated results for PFS in the E1912 trial. METHODS: As previously reported, eligible patients were treatment-naive individuals with CLL age 70 or younger. Patients with deletion 17p- were excluded from participating in the E1912 trial given their known poor response to FCR therapy. Patients were randomly assigned in a two-to-one ratio to receive ibrutinib (420 mg/day until disease progression or unacceptable toxicity) and rituximab (50 mg/m2 on day 1 of cycle 2, 325 mg/m2 on day 2 of cycle 2, and then 500 mg/m2 on day 1 of cycles 3-7) or six courses of intravenous fludarabine (25 mg/m2 days 1-3), cyclophosphamide (250 mg/m2 days 1-3) and rituximab (50 mg/m2 on day 1 of cycle 1, 325 mg/m2 on day 2 of cycle 1, and then 500 mg/m2 on day 1 of cycles 2-6) every 28-days. Adverse events (AEs) were graded according to the NCI Common Toxicity Criteria (version 4). Dose adjustments for cytopenias were based on the IWCLL CLL Working Group grading scale. The primary endpoint of the trial was PFS with OS a secondary endpoint. Analysis was by intention to treat. RESULTS: With median follow-up of 45 months, 257 (73%) of 354 patients randomized to IR remain on ibrutinib. With extended follow-up, grade 3 and above treatment-related AEs were observed in 70% of IR and 80% of FCR treated patients (OR=0.56; 95% CI 0.34 - 0.90; p=0.013). Among IR-treated patients, the median time on treatment is currently 43 months (range=0.2-61). Among the 95 patients who have discontinued ibrutinib, the reason for discontinuation was progression or death in 23 (7% of patients who started IR; 24% of those who discontinued treatment), AE or complication in 48 (14% of patients who started IR; 51% of those who discontinued treatment), and withdrawal of consent or other reasons in 24 (7% of patients who started IR; 25% of those who discontinued treatment). On multivariable Cox regression adjusting for Timed Up and Go test score, Cumulative Illness Rating Scale (CIRS) score, age, gender, ECOG performance status, creatinine clearance, and baseline anemia/thrombocytopenia, only CIRS score (range 0 - 14) predicted discontinuation of ibrutinib for a reason other than progression or death (HR=1.13 per unit increase; 95% CI 1.03 - 1.23; p=0.009). Among the 72 patients who discontinued ibrutinib for a reason other than progression or death, the median time on ibrutinib was 15.1 months (range 0.2-58.2 months). The median time from ibrutinib discontinuation to disease progression or death was 23 months. With current follow-up, we observed 110 PFS events. The hazard ratio (HR) for PFS favored IR over FCR (HR=0.39; 95% CI 0.26-0.57; p CONCLUSIONS: Although less than 7% of ibrutinib treated patients progressed while on therapy, roughly 1 in 5 patients have discontinued ibrutinib for a reason other than progression or death. The only parameter significantly associated with discontinuation for a reason other than progression was increased baseline CIRS score. With extended follow-up, the combination of ibrutinib and rituximab continues to provide superior PFS compared to FCR for younger patients with previously untreated CLL. Disclosures Shanafelt: Pharmacyclics: Research Funding; Patent: Patents & Royalties: US14/292,075 on green tea extract epigallocatechin gallate in combination with chemotherapy for chronic lymphocytic leukemia; Polyphenon E International: Research Funding; Merck: Research Funding; Abbvie: Research Funding; Genentech: Research Funding; Celgene: Research Funding; Glaxo-SmithKline: Research Funding; Hospira: Research Funding; Cephalon: Research Funding. Kay:MorphoSys: Other: Data Safety Monitoring Board; Infinity Pharmaceuticals: Other: DSMB; Celgene: Other: Data Safety Monitoring Board; Agios: Other: DSMB. O'Brien:Janssen: Consultancy, Honoraria; Pharmacyclics LLC, an AbbVie Company: Consultancy, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria; Astellas: Consultancy; Aptose Biosciences, Inc: Consultancy; Amgen: Consultancy; Alexion: Consultancy; Acerta: Research Funding; Eisai: Consultancy; Gilead: Consultancy, Research Funding; GlaxoSmithKline: Consultancy; Verastem: Consultancy; Celgene: Consultancy; Sunesis: Consultancy, Research Funding; TG Therapeutics: Consultancy, Research Funding; Vaniam Group LLC: Consultancy; Regeneron: Research Funding; Kite: Research Funding. Barrientos:AbbVie: Consultancy, Research Funding; AstraZeneca: Consultancy; Genentech: Consultancy; Bayer: Consultancy; Gilead: Consultancy; Janssen: Honoraria; Pharmacyclics LLC, an AbbVie Company: Consultancy, Research Funding; Sandoz: Consultancy; Oncternal Therapeutics: Research Funding. Coutre:Astellas: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Research Funding; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses, Research Funding; Astra Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees; Acerta: Research Funding; Gilead: Research Funding; BeiGene: Other: Travel, Accommodations, Expenses & Data Safety Monitoring Committee; Genentech: Consultancy. Barr:Pharmacyclics LLC, an AbbVie company: Consultancy, Research Funding; Gilead: Consultancy; Verastem: Consultancy; Genentech: Consultancy; Seattle Genetics: Consultancy; Merck: Consultancy; Celgene: Consultancy; Janssen: Consultancy; AbbVie: Consultancy; Astra Zeneca: Consultancy, Research Funding; TG Therapeutics: Consultancy, Research Funding. Cashen:Celgene: Other: Speaker's Bureau; Seattle Genetics: Other: Speaker's Bureau; Novartis: Other: Speaker's Bureau. Mato:AstraZeneca: Consultancy, Research Funding; AbbVie: Consultancy, Research Funding; Sunesis: Consultancy, Research Funding; Celgene: Consultancy; Johnson & Johnson: Consultancy, Research Funding; TG Therapeutics: Consultancy, Other: DSMB member , Research Funding; LOXO: Consultancy, Research Funding; DTRM Biopharma: Research Funding; Genentech: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; Gilead: Research Funding; Acerta: Consultancy; Janssen: Consultancy. Erba:Amgen: Consultancy; MacroGenics: Consultancy, Other: Lecture fees, Research Funding; MacroGenics: Consultancy, Other: Lecture fees, Research Funding; Novartis: Consultancy, Research Funding, Speakers Bureau; Novartis: Consultancy, Research Funding, Speakers Bureau; Jazz Pharmaceuticals: Consultancy, Speakers Bureau; Agios: Consultancy, Speakers Bureau; Agios: Consultancy, Speakers Bureau; Incyte: Consultancy, Speakers Bureau; Jazz Pharmaceuticals: Consultancy, Speakers Bureau; Incyte: Consultancy, Speakers Bureau; ImmunoGen: Consultancy, Research Funding; Astellas Pharma: Consultancy; Astellas Pharma: Consultancy; Amgen: Consultancy; GlycoMimetics: Consultancy, Other: Chair, data and safety monitoring board, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Celgene: Consultancy, Other: chair, AML Registry Scientific Steering Committee, Speakers Bureau; ImmunoGen: Consultancy, Research Funding; AbbVie: Consultancy, Other: Chair, IRC for phase III studies, Research Funding; GlycoMimetics: Consultancy, Other: Chair, data and safety monitoring board, Research Funding; Covance: Other: Fees for serving as chair on an independent review board for AbbVie Phase III studies; Covance: Other: Fees for serving as chair on an independent review board for AbbVie Phase III studies; AbbVie: Consultancy, Other: Chair, IRC for phase III studies, Research Funding; Celgene: Consultancy, Other: chair, AML Registry Scientific Steering Committee, Speakers Bureau; Pfizer: Consultancy; Pfizer: Consultancy; Seattle Genetics: Consultancy; Seattle Genetics: Consultancy; Daiichi Sankyo: Consultancy, Research Funding. Stone:Arog Pharmaceuticals: Consultancy, Honoraria, Research Funding; Otsuka-Astex Pharmaceuticals: Consultancy; Fujifilm: Consultancy; AstraZeneca: Consultancy; Celator Pharmaceuticals: Consultancy; Abbvie: Consultancy, Research Funding; Ono Pharmaceutical-Theradex Oncology: Consultancy; Cornerstone Pharmaceuticals: Consultancy; Daiichi Sankyo: Consultancy; Takeda: Other: Fees for serving on a data and safety monitoring board ; Orsenix: Consultancy; MacroGenics: Consultancy; Jazz Pharmaceuticals: Consultancy; Agios: Consultancy, Research Funding; Stemline Therapeutics: Consultancy; Pfizer: Consultancy; Celgene: Consultancy, Other: Fees for serving on a steering committee, and fees for serving on a data and safety monitoring board; Novartis: Consultancy, Research Funding; Actinium Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Astellas Pharma: Membership on an entity's Board of Directors or advisory committees; Argenx: Other: Fees for serving on a data and safety monitoring board ; Roche: Consultancy. Tallman:Jazz Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Oncolyze: Consultancy, Membership on an entity's Board of Directors or advisory committees.

Antibody secreting plasma cells (PCs) play an important role in effective humoral immune responses. The low frequency of bone marrow PCs in humans makes it challenging to obtain sufficient numbers of PCs for biologic studies. Previous studies have employed in vitro model systems to generate cells that morphologically, phenotypically, and functionally resemble normal polyclonal PCs. Gene expression profiles of in vitro generated PCs (IVPCs) mirror their normal counterparts, however to date extensive immunoglobulin (Ig) repertoire analysis of IVPCs is lacking. Here, we used a modified 3-step protocol to generate IVPCs and used RNA-seq to explore the transcriptome with emphasis on the Ig repertoire of plasmablasts and PCs. Total B cells were isolated from 3 normal donors and cultured with various cytokines and the B cell activators CpG ODN and CD40L. RNA was obtained from freshly isolated B cells (Day 0; D0) as well as from Day 4 (D4) plasmablasts, and Day 10 (D10) IVPCs. Morphologically, D10 cells exhibited typical PC morphology, including an eccentric nucleus and perinuclear hof. RNA-seq was performed on total RNA from all 3 donors and time points using the Standard TRuSeq v2 library prep and with paired end sequencing on the Illumina HiSeq 4000 platform. Principle component analysis of gene expression data showed that D0, D4 and D10 cells could be clearly segregated across all 3 normal donors. Of importance, transcripts previously described as distinguishing B cells from PCs were found to be differentially expressed including overexpression of CXCR5, CD19, EBF, CD83, PAX5, IRF8 in D0 B cells and overexpression of IRF4, Blimp-1, XBP1, BCMA, SLAMF7, Syndecan-1, CD38 and CD27 in IVPCs, thus validating our in vitro model for generating PCs. Furthermore, expression of cell cycle related transcripts such as CKS1, CDK1, and CCDN2 followed the pattern of low expression in resting B cells, increased expression in plasmablasts, and decreased expression in IVPCs confirming the cells are actively cycling in a manner comparable to cells in vivo. D10 IVPCs also overexpressed transcripts known to be upregulated during the unfolded protein response. As expected from Ig secreting cells, D10 IVPCs had an over-representation of Ig transcripts. At D0, resting B cells had high levels of IgD and IgM heavy chain (HC) transcripts. At D10, IgM transcripts modestly increased with Log2 fold change (FC) = 3 and as expected, IgD levels decreased significantly (Log2 FC = -2.2). IgA and IgG isotype transcripts significantly increased at D10 (Log2 FC > 6.0) with the IgG4 subtype having the greatest Log2 FC at 8.4. Next we focused on the Ig repertoire of D0, D4, and D10 cells. By aligning to known germline Ig sequences in IMGT/V-Quest (www.imgt.org) and then assembling the paired ends of D0, D4 and D10 Ig transcripts, we were able to analyze the Ig repertoire. Since the Ig HC variable (V) region is encoded by V, diversity (D) and joining (J) segments, only fragments that could be confidently determined were considered. All but 3 IGHV transcripts (IGHV3-35, IGHV3-47 and IGHV7-8) and 2 IGHD transcripts (IGHD4-4 and IGHD5-5) were found and all IGHJ segments were represented across the differentiation spectrum. In D0 cells, the number of unique VDJ combinations ranged from 643 to 863 across all 3 normal samples and increased to a range of 2524 to 2867 in D10 IVPCs. When looking at the differential expression of each VDJ combination from D0 to D10, a pairwise t-test for relative frequency showed that there was no significant change greater than 1%, suggesting the repertoire diversity was not skewed, thus proving the conditions for stimulation were not targeting any one starting B cell. Our data also allowed us to track clonal expansions during differentiation as defined by the increasing frequency of sequences with identical nucleotide sequence in the V region and CDR3 (including D and J regions). Hence, a single sequence could be tracked from D0 to D10. Of interest, in a small sampling of the total available sequences, only those B cells with a mutated IGHV region, characteristic of a memory B cell, went on to expand in this system whereas B cells with an unmutated IGHV did not. Our analysis of the Ig repertoire of IVPCs suggests this system provides a functional model to study Ig repertoire along the B cell differentiation process and further delineate the conditions that may result in a clonal expansion, a hallmark of many hematologic malignancies including multiple myeloma. Disclosures No relevant conflicts of interest to declare.

Introduction Multiple myeloma (MM) being one of the most widely spread haematological malignancies remains an incurable disease. As malignant plasma cells produce abnormally large amounts of immunoglobulins they particularly rely on the ubiquitin-proteasome system (UPS) to avoid aberrant protein overload. This unique feature is targeted by proteasome inhibitors (PI) that induce MM cell death especially by increasing levels of reactive oxygen species (ROS). Despite the high efficacy of PI most of the MM patients eventually relapse and expansion of drug resistant clones makes the treatment ineffective. Therefore, uncovering new molecular mechanisms of drug resistance is a crucial task. UPS is a very complex system that involves hundreds of proteins. While the roles of the proteasome and E3 ligases in PI resistance are well established, the third UPS component, deubiquitinating enzymes (DUBs), is much less explored. In this work, we performed a comprehensive search for DUBs with impact on MM pathogenesis and PI resistance, and further investigated the underlying molecular mechanisms. Methods Gene expression and survival For analysis of DUB genes (n = 101) expression in blood cells, expression dataset Gds3997, DICE database and data from (Jourdan et al., J Immunol. 2011 Oct 15;187(8):3931-41., Jourdan et al., Blood. 2009 Dec 10;114(25):5173-81.) submitted to http://www.genomicscape.com were used. For survival analysis MM patients were divided into two groups by median of gene expression for each DUB (datasets GSE2658, GSE4581 and GSE9782). Cell line models RPMI8226 and HEK293 cells were used as model cell lines. Cells with OTUD1 knockdowns and overexpression were generated by lentiviral infection using vectors containing doxycycline-inducible shRNA's and different versions of OTUD1 gene, respectively. Proliferation and cell death MTT assay was used for the analysis of cell proliferation and viability. Cell death was also evaluated by flow cytometry by staining with Annexin V and 7-AAD. Cell migration Cells were labelled with calcein-AM and placed into the upper chamber of transwell insert with 8-µM pores. After 16 hours of migration towards SDF-1α gradient, cells were counted by fluorescence detection. ROS analysis ROS was detected by labelling cells with 2′,7′-dichlorodihydrofluorescein diacetate and measuring fluorescence intensity using flow cytometry. Immunoprecipitation HEK293 cells were co-transfected with HA-OTUD1 and FLAG-KEAP1, and reciprocal co-immunoprecipitation and western blot analyses were performed. Results We analysed the expression of all human DUBs in different blood cell types and identified OTUD1 as the most differentially expressed DUB between B-cell lineage and other haematopoietic cells. During B-cell maturation OTUD1 expression reaches the maximum in the bone marrow plasma cells. MM patients with low OTUD1 expression had significantly worse prognosis in OS based on three large datasets (p value= 0,035; 0,008; 2.4e−06. HR=0,55; 0,19; 0,41). Expression of shRNA targeting OTUD1 in MM cell line RPMI8226 did not affect cell proliferation and migration but dramatically increased survival under oxidative stress (high ROS) conditions induced by bortezomib. Treatment with bortezomib promoted expression of OTUD1 in the wild type MM cells in a ROS-dependent manner. Additionally, we identified oxidative stress regulator, the E3 ligase KEAP1 as a novel direct interaction partner of OTUD1 that regulates OTUD1 stability under high ROS conditions. Conclusion Based on the gene expression analysis, OTUD1 was identified as a novel, potentially important player in MM pathogenesis. Low levels of OTUD1 expression in MM patients correlate with significantly worse OS. Knocking down OTUD1 in MM cells causes resistance to bortezomib. Mechanistically, bortezomib-induced ROS promotes transcription of OTUD1 mRNA and further induces stabilization of OTUD1 on protein level via disruption of OTUD1-KEAP1 complex. Our collective data suggest on a crucial role of OTUD1 in bortezomib-mediated MM cytotoxity. Further mechanistic studies delineating the role of OTUD1 in MM pathogenesis and PI resistance are ongoing. Disclosures Hajek: Janssen: Honoraria, Other: Consultant or advisory relationship, Research Funding; Amgen: Honoraria, Other: Consultant or advisory relationship, Research Funding; Celgene: Honoraria, Other: Consultant or advisory relationship, Research Funding; AbbVie: Other: Consultant or advisory relationship; Bristol-Myers Squibb: Honoraria, Other: Consultant or advisory relationship, Research Funding; Novartis: Other: Consultant or advisory relationship, Research Funding; PharmaMar: Honoraria, Other: Consultant or advisory relationship; Takeda: Honoraria, Other: Consultant or advisory relationship, Research Funding.

Introduction: Medical care has recently been moving from wards to outpatient clinics due to a growing number of patients, convenient therapeutic approaches and rising emphasis on quality of life. There is an increased need for intensive monitoring of haemato-oncological patients undergoing long-lasting treatment especially when serious infectious complications are expected. Telemedicine is a great tool to keep an eye on patients spending most of their treatment at home, where reaction time plays an important role in reducing the impact of severe adverse events. Methods: We plan on enrolling 100 haemato-oncological patients undergoing treatment who are at high risk of febrile neutropenia and/or sepsis. In the comfort of their homes, selected patients will measure their body temperature, blood pressure and pulse regularly every morning, plus whenever they feel unwell. Contactless measuring is provided by a digital blood pressure monitor and an infrared thermometer. Both devices communicate via bluetooth with a mobile HUB (cell phone), which then encrypts the information and forwards it to the National Monitoring Center. Physicians have real-time access to the measured values through a web portal using any device with an internet connection. Importantly, values registered outside the individually set-up range are immediately sent by SMS to a designated physician, who can then promptly react. Results: In our pilot project, we enrolled 21 patients (33-80 y; median 60 y) including 9 treated for acute leukemia, 5 for multiple myeloma, 4 for chronic lymphocytic leukemia, 1 for myelodysplastic syndrome, 1 for malignant lymphoma and 1 for aplastic anemia. The median duration of monitoring was 6 months (1-16). One thousand, six hundred and twenty-three critical values of systolic (91 mmHg) blood pressure in 19 patients were registered. High blood pressure in patients with inadequate antihypertensive therapy was the most frequent warning. Forty-four critical values of body temperature (>37.9°C) in 6 patients were registered, two cases with concomitant low blood pressure. After a telephone conversation with a physician, ambulatory care was recommended 12 times. Two cases of febrile neutropenia were detected, with the patients instantly hospitalized without progression into sepsis. Four cases of infectious complications (genital herpes, upper respiratory tract infection) with the need for anti-infective therapy and 6 cases of viral infections with only symptomatic treatment indicated were also addressed. Conclusion: Even in a small cohort of patients we demonstrated that the remote monitoring of body temperature, blood pressure and pulse at home enables the early detection of infections and prompt provision of adequate treatment. An evaluation of the financial savings on medical expenses might also be a useful aspect to revise. Disclosures Hajek: Celgene: Honoraria, Other: Consultant or advisory relationship, Research Funding; AbbVie: Other: Consultant or advisory relationship; Bristol-Myers Squibb: Honoraria, Other: Consultant or advisory relationship, Research Funding; Novartis: Other: Consultant or advisory relationship, Research Funding; PharmaMar: Honoraria, Other: Consultant or advisory relationship; Takeda: Honoraria, Other: Consultant or advisory relationship, Research Funding; Janssen: Honoraria, Other: Consultant or advisory relationship, Research Funding; Amgen: Honoraria, Other: Consultant or advisory relationship, Research Funding.