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Prior studies suggest increased cytomegalovirus (CMV) infection after haploidentical donor transplantation with posttransplant cyclophosphamide (HaploCy). The role of allograft source and posttransplant cyclophosphamide (PTCy) in CMV infection is unclear. We analyzed the effect of graft source and PTCy on incidence of CMV infection, and effects of serostatus and CMV infection on transplant outcomes. We examined patients reported to the Center for International Blood and Marrow Transplantation Research between 2012 and 2017 who had received HaploCy (n = 757), matched related (Sib) with PTCy (SibCy, n = 403), or Sib with calcineurin inhibitor-based prophylaxis (SibCNI, n = 1605). Cumulative incidences of CMV infection by day 180 were 42%, 37%, and 23%, respectively (P < .001). CMV disease was statistically comparable. CMV infection risk was highest for CMV-seropositive recipients (R+), but significantly higher in PTCy recipients regardless of donor (HaploCy [n = 545]: hazard ratio [HR], 50.3; SibCy [n = 279]: HR, 47.7; SibCNI [n = 1065]: HR, 24.4; P < .001). D+/R− patients also had increased risk for CMV infection. Among R+ or those developing CMV infection, HaploCy had worse overall survival and nonrelapse mortality. Relapse was unaffected by CMV infection or serostatus. PTCy was associated with lower chronic graft-versus-host disease (GVHD) overall, but CMV infection in PTCy recipients was associated with higher chronic GVHD (P = .006). PTCy, regardless of donor, is associated with higher incidence of CMV infection, augmenting the risk of seropositivity. Additionally, CMV infection may negate the chronic GVHD protection of PTCy. This study supports aggressive prevention strategies in all receiving PTCy.

Background Limited data are available on the clinical activity of venetoclax (ven) in mantle cell lymphoma (MCL). In 2 small retrospective studies of patients (pts) with MCL previously treated with BTK inhibitors (BTKi), ven resulted in overall response rates (ORRs) of 50-53% and median overall survival (OS) of 9-14 months (Eyre et al, Haematologica 2019; Zhao et al, Am J Hematol 2020). We sought to report the clinical activity of ven and identify factors associated with outcomes in a larger cohort of pts. Methods We included pts with relapsed MCL from 12 US medical centers treated with ven alone or in combination with an antiCD20 monoclonal antibody (mAb) or a BTKi. Response was determined by the local investigator. We defined OS as time from start of ven to death. Pts not experiencing an event were censored at their last known follow up. OS was determined using the Kaplan-Meier method, and univariable (UVA) and multivariable (MVA) models were developed to identify predictors of response and OS. Results Eighty-one pts were included. Pt characteristics (Table) at diagnosis (dx) were: median age 64 years (yrs) (range 38-87), male 79%, stage III/IV 95%, Ki67 >30% in 61% (available n=62), blastoid/pleomorphic histology 29% (available n=75) and ≥3 cytogenetic abnormalities 34% (available n=62). BCL2 expression was present in 93% (available n=40). Frontline treatment (tx) included intensive chemotherapy [defined as including high-dose cytarabine and/or autologous transplant (ASCT) in first remission] in 52% with ASCT in first remission in 32%. Median number of therapies prior to ven was 3 (range 1-8) including antiCD20 mAb 99%, alkylator 93%, BTKi 91%, anthracycline 58%, cytarabine 56%, and lenalidomide 37%. 55% were refractory (defined as stable (SD) or progressive disease (PD)) to last tx prior to ven. ORR to BTKi prior to ven (n=70) was 66% (complete response (CR) 20%) with median duration of tx of 6.4 months (range 0.5-69). BTKi was stopped due to PD 82% and toxicity 18%. Median time from dx to start of ven was 3.9 yrs (range 0.2-17.8). Ven was given as monotherapy in 62% (n=50) and in combination with BTKi 20% (n=16), antiCD20 mAb 14% (n=11), or other 5% (n=4). Ten pts treated with ven in combination with BTKi received prior tx with BTKi with ORR to BTKi of 40% (all PR). Ven highest dose received was 20-100 mg in 12% (n=9), 200 mg 11% (n=8), 400 mg 61% (n=46), and 800 mg 17% (n=13). Median duration of tx with ven was 2.8 months (range 0.1-30). The best response to ven was CR 18%, partial response (PR) 24%, SD 11%, and PD 47% with ORR of 42%; 19 pts (23%) did not have available data for response. ORR was not significantly different with ven monotherapy 36% (13/36) vs ven + antiCD20 mAb 56% (5/9) vs ven + BTKi 43% (6/14) (p=.559), or with ven monotherapy 36% vs combination therapy 50% (13/26) (p=.274). Ven was stopped due to PD 69%, toxicity 9%, allogeneic transplant 3% or other reasons 19%. Laboratory tumor lysis syndrome (TLS) occurred in 10 pts (12%) including 3 (3.7%) with clinical TLS. 38 pts received post-ven tx with median time from stopping ven to next tx of 0.24 months (range 0-2.2); for the 33 pts with available data, the best response to post-ven tx was CR 24%, PR 27%, SD 9% and PD 39% with ORR of 51%. For the 75 pts with available data, median OS was 12.5 months (95% CI 6-17) with 3-year OS of 13.1% (95% CI 1.4-38.0%) (Figure A). Median OS was numerically longer with ven combination (28.7 months, 95% CI 4-not reached) vs monotherapy (8.6 months, 95% CI 4.7-14.4), p=.0825 (Figure B). Median OS did not significantly differ based on response (CR/PR vs SD/PD) to prior tx with BTKi (14.4 vs 9.5 months, p=.53, Figure C) or last tx prior to ven (16.7 vs 12.4 months, p=.14, Figure D). In MVA for response, achieving CR/PR with BTKi prior to ven (vs SD/PD) was associated with response to ven (odds ratio 3.48, 95% CI 1.01-12.05, p=.049). In MVA for OS, ven combination vs monotherapy (HR 0.13, 95% CI 0.03-0.53; p=.006), longer time from dx to start of ven (>4 vs ≤4 yrs) (HR 0.08, 95% CI 0.02-0.36; p=.001), and higher dose of ven (≥400 mg vs 6 vs ≤6 months) (HR 3.47, 95% CI 1.10-10.99; p=.038) was associated with inferior OS. Conclusions In these high-risk and heavily pretreated pts with MCL, ven resulted in low response rate and poor OS. Ven may have a better role in MCL in earlier lines of therapy and when combined with other agents such as BTKi and/or antiCD20 mAbs. Disclosures Kamdar: Roche: Research Funding. Greenwell:Lymphoma Research Foundation: Research Funding; Acrotech Biopharma LLC, Kyowa Kirin: Consultancy. Hess:ADC Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS, AstraZeneca: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Portell:Acerta/AstraZeneca: Research Funding; Kite: Consultancy, Research Funding; Amgen: Consultancy; Janssen: Consultancy; Pharmacyclics: Consultancy; Bayer: Consultancy; BeiGene: Consultancy, Research Funding; AbbVie: Research Funding; TG Therapeutics: Research Funding; Infinity: Research Funding; Roche/Genentech: Consultancy, Research Funding; Xencor: Research Funding. Goldsmith:Wugen Inc.: Consultancy. Grover:Genentech: Research Funding; Tessa: Consultancy. Riedell:Morphosys: Research Funding; Celgene/Bristol-Myers Squibb Company: Honoraria, Research Funding; Verastem Oncology: Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Kite Pharmaceuticals/Gilead: Honoraria, Research Funding; Bayer: Honoraria; Karyopharm Therapeutics: Honoraria. Karmali:BeiGene: Speakers Bureau; AstraZeneca: Speakers Bureau; Karyopharm: Honoraria; Takeda: Research Funding; Gilead/Kite: Honoraria, Other, Research Funding, Speakers Bureau; BMS/Celgene/Juno: Honoraria, Other, Research Funding, Speakers Bureau. Kumar:AbbVie: Research Funding; Kite Pharmaceuticals: Honoraria, Other: Honoraria for Advisory Board; Astra Zeneca: Honoraria, Other: Honoraria for Advisory Board; Celgene: Honoraria, Other: Honoraria for Advisory Board; Seattle Genetics: Research Funding; Pharmacyclics: Research Funding; Celgene: Research Funding; Adaptive Biotechnologies,: Research Funding. Hill:Abbvie: Consultancy, Honoraria, Research Funding; Pharmacyclics: Consultancy, Honoraria, Research Funding; Beigene: Consultancy, Honoraria, Research Funding; AstraZenica: Consultancy, Honoraria, Research Funding; Kite, a Gilead Company: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria; BMS: Consultancy, Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria, Research Funding; Takeda: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Genentech: Consultancy, Honoraria, Research Funding. Kahl:AstraZeneca Pharmaceuticals LP: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene Corporation: Consultancy; AbbVie: Consultancy; Genentech: Consultancy; Pharmacyclics LLC: Consultancy; Roche Laboratories Inc: Consultancy; BeiGene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Acerta: Consultancy, Research Funding; ADC Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Cohen:Genentech, BMS, Novartis, LAM, BioInvent, LRF, ASH, Astra Zeneca, Seattle Genetics: Research Funding; Janssen, Adicet, Astra Zeneca, Genentech, Aptitude Health, Cellectar, Kite/Gilead, Loxo: Consultancy. OffLabel Disclosure: Venetoclax is not licensed for use in mantle cell lymphoma

Multiple myeloma (MM) is a hematological cancer of the antibody-secreting plasma cells. Despite therapeutic advancements, MM remains incurable due to high incidence of drug-resistant relapse. In recent years, targeted immunotherapies, which take advantage of the immune system's cytotoxic defenses to specifically eliminate tumor cells expressing certain cell surface and intracellular proteins have shown promise in combating this and other B cell hematologic malignancies. A major limitation in the development of these therapies lies in the discovery of optimal candidate targets, which require both high expression in tumor cells as well as stringent tissue specificity. In an effort to identify potential myeloma-specific target antigens, we performed an unbiased search for genes with specific expression in plasma and/or B cells using single-cell RNA-sequencing (scRNAseq) of 53 bone marrow samples taken from 42 patients. By comparing >40K plasma cells to >97K immune cells across our cohort, we were able to identify a total of 181 plasma cell-associated genes, including 65 that encode cell-surface proteins and 116 encoding intracellular proteins. Of particular interest is that the plasma cells from each patient were shown to be transcriptionally distinct with unique sets of genes expressed defining each patient's malignant plasma cells. Using pathway enrichment analysis, we found significant overrepresentation of cellular processes related to B-Cell receptor (BCR) signaling, protein transport, and endoplasmic reticulum (ER) stress, involving genes such as DERL3, HERPUD1, PDIA4, PDIA6, RRBP1, SSR3, SSR4, TXNDC5, and UBE2J1. To note, our strategy successfully captured several of the most promising MM therapeutic targets currently under pre-clinical and clinical trials, including TNFRSF17(BCMA), SLAMF7, and SDC1 (CD138). Among these, TNFRSF17 showed very high plasma cell expression, with concomitant sharp exclusion of other immune cell types. To ascertain tissue specificity of candidate genes outside of the bone marrow, we analyzed gene and protein expression data from the Genotype-Tissue Expression (GTEx) portal and Human Protein Atlas (HPA). We found further support for several candidates (incl. TNFRSF17,SLAMF7, TNFRSF13B (TACI), and TNFRSF13C) as being both exclusively and highly expressed in lymphoid tissues. While several surface candidates were not found to be lymphocyte-restricted at the protein level, they remain relevant considerations as secondary targets for bi-specific immunotherapy approaches currently under development. To further investigate potential combinatorial targeting, we examine sample-level patterns of candidate co-expression and mutually-exclusive expression using correlation analysis. As the majority of our detected plasma cell-specific genes encode intracellular proteins, we investigated the potential utility of these epitopes as therapeutic targets via MHC presentation. Highly expressed candidates include MZB1, SEC11C, HLA-DOB, POU2AF1, and EAF2. We analyzed protein sequences using NetMHC and NETMHCII to predict high-affinity peptides for common class-I and class-II HLA alleles. To correlate MHC allelic preference with candidate expression in our cohort, we performed HLA-typing for 29 samples using Optitype. To support our scRNAseq-driven findings, we cross-referenced gene expression data with 907 bulk RNA-sequencing samples, including 15 from internal studies and 892 from the Multiple Myeloma Research Foundation (MMRF), as well as bulk global proteomics data from 4 MM cell lines (TIB.U266, RPMI8226, OPM2, MM1ST) and 4 patients. We see consistent trends across both cohorts, with high positive correlation (Pearson R ranging between 0.60 and 0.99) for a majority of genes when comparing scRNA and bulk RNA expression in the same samples. Our experimental design and analysis strategies enabled the efficient discovery of myeloma-associated therapeutic target candidates. In conclusion, this study identified a set of promising myeloma CAR-T targets, providing novel treatment options for myeloma patients. Disclosures Goldsmith: Wugen Inc.: Consultancy. DiPersio:Magenta Therapeutics: Membership on an entity's Board of Directors or advisory committees.

Historically, high-dose therapy in combination with autologous stem cell transplants (ASCT) for multiple myeloma (MM) was reserved for younger patients. In more recent years, the use of ASCT has expanded in the older population. However, there is still limited data on the utilization and efficacy of ASCT in older patients, particularly those over the age of 75. To further evaluate this issue, we retrospectively analyzed all patients with newly diagnosed MM between the ages of 75-78, the institutional cutoff for ASCT eligibility, that were referred to the stem cell transplant unit at our institution for consultation from the years 2012-2018. Baseline characteristics, anti-myeloma treatments, and patient outcomes were abstracted through chart review. Seventy-five patients were referred to our institution. 71% were male, 29% female. 39% patients were considered ineligible for ASCT by the consulting transplant physician. Most patients were considered transplant ineligible due to comorbidities or poor performance status. Of the 46 patients eligible for ASCT, 52% underwent the procedure during their first-line therapy. The majority of those patients received reduced intensity melphalan (140 mg/m2) while 2 patients received conventional dosing (200 mg/m2). The other 22 patients eligible for ASCT declined or elected to defer the procedure and to be treated with conventional therapy. The characteristics of these three groups were similar and are detailed in Table 1. After a median follow-up of 30 months, 25% of the patients had expired. Estimated median overall survival (OS) was 71.3 months (unable to quantitate 95% CI) for all patients. Compared to transplant eligible patients, regardless of transplant receipt, those who were transplant ineligible had a 186% increase risk for death (HR 2.86; 95% CI 1.12-7.35; p = 0.029). There was also a notable trend for longer OS in those who underwent ASCT compared to those who were eligible but declined the procedure, but it was not statistically significant (HR 0.36; 95% CI 0.10-1.28; p = 0.114). At a transplant center, two-thirds of patients referred for newly diagnosed MM between the ages 75-78 were considered eligible for ASCT and one-third underwent the procedure. Outcomes were better for patients eligible for ASCT, regardless of whether they underwent the procedure. There was also a trend for better OS in patients who underwent the procedure compared to those who declined. While small sample sizes and the retrospective nature of the study limit our ability to draw conclusions, it appears that ASCT has an OS benefit among patients age 75-78. Disclosures Fiala: Incyte: Research Funding. Stockerl-Goldstein:AbbVie: Equity Ownership; Abbott: Equity Ownership. Vij:Genentech: Honoraria; Janssen: Honoraria; Bristol-Myers Squibb: Honoraria, Research Funding; Sanofi: Honoraria; Karyopharm: Honoraria; Takeda: Honoraria, Research Funding; Celgene: Honoraria, Research Funding. Wildes:Janssen: Research Funding; Carevive: Consultancy.

Multiple myeloma (MM) is a disease defined by clonal proliferation of abnormal plasma cells from B-cells. Improved treatments for MM have led to improving overall lifespan, but still remains incurable due to acquired resistance to therapy and tumor heterogeneity. Single-cell RNA sequencing studies (scRNA-seq) of MM patients have highlighted the significant inter-individual heterogeneity and subclonal architecture of the malignant plasma cell populations, emphasizing the importance of developing personalized therapies specific to a patients molecular pathogenesis. In this study, we have integrated scRNA-seq with single-cell proteomics (sc-Prot) for 10 plasma cells and CD4+ T cells to validate and prioritize driver events in malignant cells and evaluate the tumor microenvironment. This effort will be expanded to another 10 cases to further integrate scRNA-seq, snATAC-seq, whole exome sequencing and bulk RNA-sequencing on a fraction of the cells isolated from bone marrow. The remaining cells will be sorted using FACS to select for specific malignant and immune cells including 40 plasma cells, 15 CD4+ T and 15 CD8+ T cells. These sorted cells will be profiled with a scProt technology (BASIL nanoPOTS) to illuminate their cell-to-cell heterogeneity. In our pilot study comparing bulk and single-cell proteomic data of a single patient's plasma cells (CD138+) for 400 representative proteins, while a majority of expression signatures are concurrent between the two methods, some signaling pathways including translation and apoptotic cleavage are discordant. Our findings stress the importance of interrogating subpopulations of immune and malignant cells at the single-cell level to further refine the transcriptomic and proteomic heterogeneity of MM in a cell type specific manner. With the aid of single-cell technology, we have assessed the heterogeneity of malignant and immune cell types to evaluate transcriptomic and proteomic changes contributing to altering the interplay between the immune environment and tumor cells. Disclosures Fiala: Incyte: Research Funding. Rettig:WashU: Patents & Royalties: Patent Application 16/401,950. O'Neal:Wugen: Patents & Royalties: Patent Pending; WashU: Patents & Royalties: Patent Pending. DiPersio:WUGEN: Equity Ownership, Patents & Royalties, Research Funding; Macrogenics: Research Funding, Speakers Bureau; Cellworks Group, Inc.: Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy; Magenta Therapeutics: Equity Ownership; RiverVest Venture Partners Arch Oncology: Consultancy, Membership on an entity's Board of Directors or advisory committees; NeoImmune Tech: Research Funding; Karyopharm Therapeutics: Consultancy; Incyte: Consultancy, Research Funding; Amphivena Therapeutics: Consultancy, Research Funding; Bioline Rx: Research Funding, Speakers Bureau. Vij:Bristol-Myers Squibb: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Genentech: Honoraria; Janssen: Honoraria; Karyopharm: Honoraria; Sanofi: Honoraria; Takeda: Honoraria, Research Funding.

Introduction: Inositol-requiring enzyme 1α (IRE1α) is one of three principal transmembrane sensors in the endoplasmic reticulum (ER) involved in regulating the unfolded protein response (UPR). It splices X-box protein 1 (XBP1) mRNA yielding a transcription factor intimately involved in the plasma cell differentiation and proliferation. The IRE1α-XBP1 axis exhibits positive feedback functions that promote the pro-survival UPR and allows plasma cells to survive the high biosynthetic burden of immunoglobulin production, although IRE1α also has functions that promote cell death depending on the chronicity and severity of ER stress. Functional IRE1α has been identified as critical for in vitro cytotoxicity of bortezomib by Leung-Hagesteijn et al. (Cancer Cell 2013), with loss of IRE1α leading to in vitro resistance to proteasome inhibition. However, Mimura et al (Blood 2012) identified in vitro synergy with IRE1α-inhibition and bortezomib, and Papandeou et al. (Blood 2011) identified in vitro and in vivo anti-myeloma activity of a different IRE1α endonuclease inhibitor. The clinical implications of IRE1α are still poorly understood. In this study, we sought to identify associations between IRE1α mRNA expression (the level at which it is principally regulated) with treatment resistance and patient outcomes. Methods: We performed a secondary analysis of data from the MMRF CoMMpass study (IA14). In the CoMMpass study, RNAseq on CD138-enriched bone marrow cells was performed using Illumina TruSeq RNA library kits. Cox Regression analysis was used to compare the association of IRE1α expression with progression-free and overall survival. To determine if IRE1α expression is modulated following disease progression, we also identified patients who had pre- and post-treatment RNAseq data. We analyzed expression of IRE1α from the pre- and post-treatment specimens using paired T-tests comparing patients who had relapsed disease (relapse following completion of therapy) and refractory disease (progression on or within 60 days of completing therapy). Results: We included 768 patients who had IRE1α expression data at myeloma diagnosis. The median age was 63 (range 27-93) and 50% were male. Thirty percent of patients (n = 231) were considered to have high IRE1a expression at myeloma diagnosis. High IRE1α expression was associated with worse clinical outcome. Those with high expression had a 37% (aHR 1.37; 95% CI 1.10-1.72; p = 0.006) increase hazard for progression and a 55% (aHR 1.55; 95% CI 1.13-2.15; p = 0.008) increase hazard for death. We then identified 46 patients who had pre- and post-treatment RNAseq data. Twenty-two had relapsed disease while off of treatment and 24 had developed refractory disease while on treatment. Patients who had refractory disease were noted to have a significant decrease in the expression of IRE1α (p = 0.008). This was similar when we performed subset analysis of patients who were refractory to PI-based treatments (n=8; p = 0.044) and IMID-based treatments (n = 13; p = 0.054). In contrast, there was not a significant difference between pre-treatment and post-treatment IRE1α in relapsed disease (p = 0.312). Expression of other UPR elements, specifically PERK and XBP1, was not significantly downregulated in relapsed or refractory disease. Conclusion: Our study demonstrates that high expression of IRE1α at diagnosis is associated with worse outcomes, but that resistance to therapy is associated with a significant decrease in IRE1α expression. While this seems counterintuitive, it highlights the complex nature of the UPR and the roles of IRE1α. More aggressive/proliferative disease relies heavily on an adapted pro-survival UPR, highlighted by increased expression of IRE1α de novo. However, IRE1α has previously been demonstrated to be required for anti-myeloma activity of novel therapies; potentially either by clonal selection, dynamic alterations in UPR signaling, or epigenetic modifications, treatment-refractory myeloma cells downregulate the expression of IRE1α, a phenomenon not seen in those who completed treatment but subsequently relapsed. IRE1α inhibition could initially potentiate the clinical effects of novel therapies in a higher-risk population, but may also promote later resistance to them. Importantly, IRE1α could serve as a prognostic biomarker for risk-stratification at diagnosis as well as one predictive of impending resistance to therapy. Disclosures Fiala: Incyte: Research Funding. Wildes:Janssen: Research Funding; Carevive: Consultancy. Vij:Takeda: Honoraria, Research Funding; Sanofi: Honoraria; Karyopharm: Honoraria; Bristol-Myers Squibb: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Genentech: Honoraria; Janssen: Honoraria. Stockerl-Goldstein:AbbVie: Equity Ownership; Abbott: Equity Ownership.

Introduction: Despite significant advances in multiple myeloma (MM) therapy, disease progression through multiple novel treatments is often inevitable. Quad-refractory MM (refractory to bortezomib, carfilzomib, lenalidomide, and pomalidomide), or penta-refractory MM (refractory to an anti-CD38 monoclonal antibody as well) portends a poor prognosis, with few subsequent lines of treatment currently available. We and others have used bendamustine combined with corticosteroids as a salvage regimen, but there is a paucity of outcomes data in this heavily pretreated population. Methods: We conducted a retrospective study to identify all patients who received bendamustine with corticosteroids for quad- or penta-refractory MM at our institution between 2013 and 2018. Disease response and refractoriness were defined by IMWG criteria. The primary endpoint was overall response rate (ORR) defined as PR or better. Secondary endpoints included overall survival (OS) and duration of response (DOR). Results: Twenty-seven patients were identified; 5 patients were quad-refractory, and 22 penta-refractory (Table 1). Twenty-two (81%) patients had at least one prior autologous stem cell transplant and 1 had a prior allogeneic. The median age at time of bendamustine was 61, 52% were female, and 85% were white. All patients received bendamustine at a dose of 90mg/m2 on days 1 and 2 of a 28 day cycle. Twelve patients (44%) received more than one cycle (range: 1-8). The overall response rate was 26%. While no patient achieved CR, 4 achieved VGPR and 3 a PR. Two of the 5 (40%) quad-refractory patients responded compared to 5 of the 22 (23%) penta-refractory. Sixteen (59%) were primary refractory to bendamustine and one patient went onto hospice prior to response evaluation. Overall the median PFS was 1.4 months (95% CI 1.1-1.6) and median OS was 8.7 months (95% CI 2.3-15.0). For responders (≥PR), median DOR was 6.6 months (95% CI 0.0-13.7) and median OS was 14.0 months (95% CI 0.6-27.4). Conclusion: The prognosis of quad- and penta-refractory MM remains poor. In this heavily pre-treated population, bendamustine demonstrates a 26% ORR (95% CI 11%-46%). The DOR and OS of the patients was poor but highly heterogeneous. Those who did respond to bendamustine had notably improved OS. Given the limited available options for quad- and penta-refractory MM, bendamustine remains a reasonable salvage therapy. Prospective trials are warranted perhaps including additional agents that are effective in penta-refractory patients. Disclosures Schroeder: Amgen Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees. Vij:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Jansson: 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; Jazz Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees; Karyopharma: 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, Research Funding.

Background:Poor graft function (PGF) is an uncommon but significant complication of hematopoietic cell transplantation (HCT). There is growing interest in treatment with positively selected CD34+grafts as "stem cell boosts" (SCB). No data are, to our knowledge, available concerning the use of SCBs in the HLA-haploidentical setting. Methods:We retrospectively identified all patients undergoing SCB after peripheral blood haplo-HCT with post-transplant cyclophosphamide at our institution between June 2009 and January 2016. CD34+ cell selection was carried out on the CliniMACS instrument (Miltenyi Biotec, Auburn, CA). PGF was defined as ≥95% donor chimerism, and at least two of the following three cytopenias for at least 2 consecutive weeks without alternative explanation: ANC < 1500 cells/mm3, platelets < 30,000/mm3 and Hgb < 8.5 g/dL. PGF was classified as primary if it occurred immediately following day +14. Otherwise, it was considered secondary. Patients with 5-95% donor chimerism and ANC > 500 cells/mm3 who otherwise met the criteria for PGF were classified as PGF with mixed chimerism. Hematologic improvement (HI) was defined as having no cytopenias. Hematological response (HR) was defined as ANC > 2500 cells/mm3, platelets >100,000/mm3, and Hgb >10 g/dL. Both HI and HR required transfusion independence for the previous 30 days. Acute and chronic graft-versus-host disease (GVHD) were graded based on established criteria. Overall survival (OS) was defined as time from SCB until death or last clinical contact. Results:Nineteen of 141 patients (13%) undergoing haplo-HCT received SCB. Clinical characteristics are summarized in Table 1. SCB was given at a median of 120 days (range: 21 - 455) after haplo-HCT. Median time from SCB to death or last clinical contact was 158 days (range: 3 - 564). Nine donors underwent remobilization; 10 patients used cryopreserved product. The median SCB contained 2.52 x 106 CD34+ cells/kg (range: 0.33 - 10.92). SCBs from remobilized donors contained significantly more CD34+ cells/kg (median: 4.06) than those from original mobilization (median: 1.50) (p At time of SCB, 63% (12/19) patients were cytopenic in at least two cell lines and 26% (5/19) were cytopenic in all three cell lines. Six patients had one cytopenia and one had no cytopenias, but was chronically transfusion dependent. The majority (74%) of patients had hypocellular bone marrows per pathology report. Patients with secondary PGF were less likely to have multiple cytopenias than the remaining cohort (36% versus 100%, p=0.01). No patients received conditioning prior to SCB. Eighteen patients were receiving immunosuppression, including steroids (79%), calcineurin inhibitors (63%) and mycophenolate mofetil (32%). At day +90 after SCB, 66% of surviving patients were in HI or HR.. ANC was significantly higher at day +90 (p=0.02). Hgb and platelets were significantly higher at all time points (p Conclusion:Our results suggest that SCB after haplo-HCT is safe and associated with acceptable rates of acute and chronic GVHD. It may also be effective in reducing transfusions and inducing HI and HR. The treatment of these patients continues to be a challenge. Further studies are needed to delineate the factors influencing outcomes in this population, including timing of therapy and optimal CD34+ cell dose. Table 1 Clinical and demographic characteristics Table 1. Clinical and demographic characteristics Figure 1 Overall survival by number of cytopenic cells lines at time of SCB. Figure 1. Overall survival by number of cytopenic cells lines at time of SCB. Disclosures DiPersio: Incyte Corporation: Research Funding. Vij:Celgene: Consultancy; Karyopharm: Honoraria; Novartis: Honoraria; Janssen: Honoraria; Takeda: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria. Fehniger:Celgene: Research Funding; Affimed: Consultancy; Fortress Biotech: Consultancy. Schroeder:Incyte Corporation: Honoraria, Research Funding.