ALBERT

Description: Background: Deep understanding of the complexity and diversity of the tumor immune microenvironment (TIME) and its influence on response to therapy is needed to improve the ability to predict, monitor and guide immunotherapeutic responsiveness. Among different cell types in the MM-TIME, granulocytic MDSCs (G-MDSCs) have a prominent role in promoting tumor growth and inducing immune suppression; however, their identification and monitoring is imprecise because the phenotypic profile of MDSCs in the MM-TIME is not well-established. Aim: To provide the detailed phenotypic profile of G-MDSCs based on the immune suppressive potential, gene regulatory network and clinical significance of distinct granulocytic subsets in the MM-TIME. Methods: First, we used multidimensional flow cytometry (MFC) to evaluate the preestablished phenotype of G-MDSCs in bone marrow (BM) samples from controls (n=4) and MM patients (n=5). We then used principal component analysis (PCA) to unbiasedly identify different granulocytic subsets in the MM-TIME, and FACS for in vitro experiments to determine their immune suppressive potential (n=9) and for RNAseq to analyze the molecular profile of G-MDSCs in MM (n=5) vs controls (n=5). Subsequently, the clinical significance of the different granulocytic subsets was investigated by comparing their numbers at diagnosis, in MM patients (n=124) achieving MRD-negativity vs MRD-positivity after treatment with VRD induction (x6) followed by autologous transplant and VRD consolidation (x2) (GEM2012MENOS65 clinical trial). Results: In humans, G-MDSCs have been defined as a unique cluster displaying a CD11b-, CD14-, CD15+, CD33+ and HLADR- phenotype, comprising 1% of total BM nucleated cells in healthy individuals and approximately 25% in MM patients. However, we found that the percentage of cells with a CD11b-CD14-CD15+CD33+HLADR- phenotype was similar in the BM of controls and MM patients (median of 8% in both, P〉.99). Since these cells were not expanded in MM and represented only 24% of total neutrophils, we next used MFC and PCA to unbiasedly identify other cell clusters within neutrophils. Accordingly, 3 major subsets were identified in neutrophils from controls and MM patients, based on homogeneous CD14-CD15+CD33+HLADR- expression but differential reactivity against CD11b, CD13 and CD16: CD11b-CD13lo/-CD16- (19% and 24%), CD11b+CD13lo/-CD16- (46% and 47%) and CD11b+CD13+CD16+ (35% and 29%). Afterwards, we used FACSorting to deplete or isolate individually, each of the 3 neutrophil subsets from the BM MM-TIME and determine its immune suppressive potential in 2 functional assays: 1) the proliferation rate of autologous T cells in presence of CD3/CD28 stimulatory beads and, 2) the cytotoxic potential of autologous T-cells against MM cells using a BCMAxCD3 bispecific antibody. Interestingly, we noted a significant decrease in T cell proliferation when these were stimulated in the presence of CD11b+CD13+CD16+ neutrophils (0.5-fold, p =.03) but not the CD11b-CD13lo/-CD16- and CD11b+CD13lo/-CD16- subsets. In addition, we noted that the cytotoxic potential of T cells engaged by the BCMAxCD3 bispecific antibody significantly increased with the depletion of CD11b+CD13lo/-CD16- and CD11b+CD13+CD16+ subsets (3-fold and 4-fold, respectively; p ≤.04) but not CD11b-CD13lo/-CD16- neutrophils. Furthermore, RNAseq of the 3 subsets in controls and MM patients revealed that genes related with the IL-4, IL-10 and IL-13 immunosuppressive pathways were specifically upregulated in the CD11b+CD13+CD16+ subset. Finally, based on the surrogacy between the achievement of MRD-negativity and prolonged survival, we compared the distribution of the 3 granulocytic subsets in the BM-TIME at diagnosis and observed that patients reaching MRD-negativity (n=56) displayed significantly lower percentages of total neutrophils (46% vs 52%, p =.002), particularly of the CD11b+CD13lo/-CD16- (11% vs 15%, p =.003) and CD11b+CD13+CD16+ (31% vs 35%, p =.07) subsets vs MRD-positive cases (n=68). Conclusions: We have determined the correlation between the phenotypic, molecular and immunosuppressive potential of unique granulocytic subsets. Thus, we have identified optimal markers for monitoring G-MDCSs in patients with MM (ie. CD11b, CD13, CD16) and unveiled that, in contrast to previous findings, the more mature granulocytes are the only stages with immunosuppressive potential. Disclosures Puig: Celgene: Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria. Martinez Lopez:Celgene: Research Funding, Speakers Bureau; Bristol Myers Squibb: Research Funding, Speakers Bureau; Novartis: Research Funding, Speakers Bureau; Janssen: Research Funding, Speakers Bureau. Oriol:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Rios:Amgen, Celgene, Janssen, and Takeda: Consultancy. Rosinol:Janssen, Celgene, Amgen, Takeda: Honoraria. Mateos:Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy, 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; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy, Membership on an entity's Board of Directors or advisory committees. Lahuerta: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; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees. Bladé:Celgene: Honoraria; Janssen: Honoraria; Amgen: Honoraria. San-Miguel:Janssen: Honoraria; Celgene: Honoraria; Amgen: Honoraria; BMS: Honoraria; Novartis: Honoraria; Sanofi: Honoraria; Roche: Honoraria.

Description: Granulocytic myeloid-derived suppressor cells (G-MDSCs) promote tumor growth and immunosuppression in multiple myeloma (MM). However, their phenotype is not well established for accurate monitoring or clinical translation. We aimed to provide the phenotypic profile of G-MDSCs based on their prognostic significance in MM, immunosuppressive potential, and molecular program. The preestablished phenotype of G-MDSCs was evaluated in bone marrow samples from controls and MM patients using multidimensional flow cytometry; surprisingly, we found that CD11b+CD14−CD15+CD33+HLADR− cells overlapped with common eosinophils and neutrophils, which were not expanded in MM patients. Therefore, we relied on automated clustering to unbiasedly identify all granulocytic subsets in the tumor microenvironment: basophils, eosinophils, and immature, intermediate, and mature neutrophils. In a series of 267 newly diagnosed MM patients (GEM2012MENOS65 trial), only the frequency of mature neutrophils at diagnosis was significantly associated with patient outcome, and a high mature neutrophil/T-cell ratio resulted in inferior progression-free survival (P 〈 .001). Upon fluorescence-activated cell sorting of each neutrophil subset, T-cell proliferation decreased in the presence of mature neutrophils (0.5-fold; P = .016), and the cytotoxic potential of T cells engaged by a BCMA×CD3-bispecific antibody increased notably with the depletion of mature neutrophils (fourfold; P = .0007). Most interestingly, RNA sequencing of the 3 subsets revealed that G-MDSC–related genes were specifically upregulated in mature neutrophils from MM patients vs controls because of differential chromatin accessibility. Taken together, our results establish a correlation between the clinical significance, immunosuppressive potential, and transcriptional network of well-defined neutrophil subsets, providing for the first time a set of optimal markers (CD11b/CD13/CD16) for accurate monitoring of G-MDSCs in MM.

Description: Background: The broad use of immunomodulatory drugs (IMiDs) and the breakthrough of novel immunotherapies in MM, urge the optimization of immune monitoring to help tailoring treatment based on better prediction of patients' response according to their immune status. For example, current T cells immune monitoring is of limited value because the phenotype of tumor-reactive T cells is uncertain. Aims: To characterize the MM immune microenvironment at the single-cell level and to identify clinically relevant subsets for effective immune monitoring. Methods: We used a semi-automated pipeline to unveil full cellular diversity based on unbiased clustering, in a large flow cytometry dataset of 86 newly-diagnosed MM patients enrolled in the PETHEMA/GEM2012MENOS65 clinical trial, including immune monitoring at diagnosis, after induction with bortezomib, lenalidomide, dexamethasone (VRD), autologous transplant and VRD consolidation. Immunophenotyping was performed using the first 8-color combination (CD19, CD27, CD38, CD45, CD56, CD81, CD117, CD138) of the next-generation flow (NGF) panel for MRD assessment. Results were then validated in additional 145 patients enrolled in the same trial. Deep characterization of T cells was performed using 17-color multidimensional flow cytometry (TIM3, CD160, TIGIT, CD57, CD8, PD1, CD45RA, CD56, BTLA, CD4, CD3, CD39, CD137, CTLA4, CCR7, CD16, CD27) and combined single-cell (sc) RNA/TCR sequencing (10xGenomics). Results: Simultaneous analysis of the entire dataset (n=333 files) unbiasedly identified 25 cell clusters (including 9 myeloid and 13 lymphocytes subsets) in the MM immune microenvironment. Afterwards, we correlated a total of 120 immune parameters derived from the cellular abundance of each cluster and specific cell ratios determined at all time points, with a total of 20 clinical parameters including the International Staging System (ISS) and FISH cytogenetics. Twelve variables had significant impact in progression-free survival (PFS) and the ratio between CD27- vs CD27+ T cells emerged as an independent prognostic factor (HR:0.09, p=0.04) together with the ISS in a Cox regression model. The 3-year PFS rates of patients with high vs low CD27-/CD27+ ratios were 94% vs 71% (p=0.02), respectively; these findings being confirmed in the validation dataset. Thus, we observed in the entire cohort (n=231) that a prognostic score including the CD27-/CD27+ T cell ratio (HR:0.21, p=0.013) and ISS (HR:1.41, p=0.015) outperformed each parameter alone (HR:0.06, p=0.007). To gain further insight into the biological significance of the CD27-/CD27+ T cell ratio, we performed scRNA/TCRseq in 44,969 lymphocytes from 9 MM patients. Downstream analysis unveiled that CD27- T cells were mostly CD8 and included senescent, effector and exhausted clusters. By contrast, CD27+ T cells were mainly CD4 and the remaining CD8 T cells had a predominant immune suppressive phenotype (ie. high GZMK, TIGIT, LAG3 and PD1 expression levels). Such T cell clustering was validated by 17-color multidimensional flow cytometry that confirmed the cellular distribution identified by scRNAseq, as well as higher reactivity for PD1, TIGIT, BTLA and TIM3 in CD27+ vs CD27- T cells. Simultaneous scTCRseq revealed a total of 90 different clonotypes (median of 12 per patient). Interestingly, most clonotypes where found in CD27- (74/90) as opposed to CD27+ T cells and, using the VDJB database, the CDR3 sequences of clonotypic effector/exhausted CD27- T cells were predicted to recognize MM-related epitopes such as MLANA, HM1.24 (CD319), TKT, or IMP2. In selected patients, we performed exome- and RNA-sequencing of tumor cells and analyzed their HLA profile. Using the T Cell Epitopes - MHC Binding Prediction tool from the IEDB Analysis Resource, we found expression of mutated genes (e.g. UBXN1, UPF2, GNB1L) predicted to bind MHC class I molecules on tumor cells and potentially recognized by autologous clonotypic CD27- T cells. Conclusion: We show for the first time that potential MM-reactive T cells are CD27-negative and that their abundance in the immune microenvironment of newly-diagnosed MM patients is prognostic, possibly due to their reactivation after treatment with IMiDs and autologous transplant. Because NGF is broadly used, these results are readily applicable for effective T cell immune monitoring. Disclosures Puig: Janssen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria; The Binding Site: Honoraria; Takeda: Consultancy, Honoraria. Rosinol Dachs:Janssen, Celgene, Amgen and Takeda: Honoraria. Oriol:Janssen: Consultancy; Takeda: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Celgene Corporation: Consultancy, Speakers Bureau. Rios: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. Sureda:Takeda: Consultancy, Honoraria, Speakers Bureau; Novartis: Honoraria; Gilead: Honoraria; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Honoraria; Roche: Honoraria; Sanofi: Honoraria; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel Support; Amgen: Membership on an entity's Board of Directors or advisory committees. De La Rubia:Takeda: Consultancy; Janssen: Consultancy; Celgene Corporation: Consultancy; AMGEN: Consultancy; AbbVie: Consultancy. Mateos:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive: Honoraria; EDO: Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pharmamar: Membership on an entity's Board of Directors or advisory committees; GSK: 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: Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Lahuerta:Takeda, Amgen, Celgene and Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Bladé:Irctures: Honoraria; Janssen, Celgene, Amgen, Takeda: Membership on an entity's Board of Directors or advisory committees. San-Miguel:Amgen, Bristol-Myers Squibb, Celgene, Janssen, MSD, Novartis, Roche, Sanofi, and Takeda: Consultancy, Honoraria. Paiva:Amgen, Bristol-Myers Squibb, Celgene, Janssen, Merck, Novartis, Roche, and Sanofi; unrestricted grants from Celgene, EngMab, Sanofi, and Takeda; and consultancy for Celgene, Janssen, and Sanofi: Consultancy, Honoraria, Research Funding, Speakers Bureau.

Description: The advent of immunotherapy in MM urges the need for in-depth knowledge about immune cells towards improved characterization of patients' immune profiles. Based on few studies, TAMs were suggested to be abundant in the MM tumor microenvironment where they promote cell growth and chemoresistance. However, further investigation about TAMs is warranted because i) their potential to induce chemoresistance was not determined tacking into account the effect of bone marrow (BM) stroma; ii) their chemoprotective role may be altered by the introduction of monoclonal antibodies (mAb) that target MM cells through ADCP; and iii) TAMs have been characterized with low-throughput flow cytometry, and recent studies in other clinical settings have suggested that novel markers may be more informative to characterize TAMs. Here, we started by producing human M2-like macrophages (ie. phenotypically similar to TAMs in MM) and investigated their contribution to chemoresistance, with or without MM patients' derived BM stroma (Panels A&B). In contrast to BM stroma, human derived M2-like macrophages were not capable to protect MM (RPMI-8226 and MM1S) cells against bortezomib or dexamethasone. Furthermore, whereas macrophages showed a trend (2.4 fold change, P=.06) to increase baseline MM cell growth (ie. Control in Panels A&B), it became irrelevant upon adding BM stroma to the culture (1.1 fold change, P=.52). No significant differences were observed in the presence of daratumumab or isatuximab, including ADCP that could have been potentially induced by the two anti-CD38 mAbs. Afterwards, based on novel 8-color multidimensional flow cytometry mAb combinations and automated maturation tools, we characterized with high-throughput resolution the BM monocytic/macrophage system by identifying up to 7 different maturation related cell subsets: monoblasts I, II and III, promonocytes, classic and intermediate monocytes, and three novel macrophages subsets identified according to SLAN expression, amongst others (Panels C&D). Accordingly, upon sensitive FACS-sorting we demonstrated that the 3 macrophage subsets had unique transcriptomes (Panel E) consistent with lower immune suppressive signatures from SLAN- into SLAN+ macrophages (eg. down-regulation of VCAN, ENTPD1 and STAB1). We then investigated whether the monocytic/macrophage BM system was truly altered in newly-diagnosed MM patients (n=30) by comparing it to that of healthy donors (HD; n=15). Our results show that total monocytic cells were increased in MM (although the distribution of different monocytic subsets was identical to HD); total intermediate monocytes were also increased in MM (Panel F). By contrast, the percentage of macrophages was identical between HD and MM patients but their subset distribution was significantly altered in MM, and was consistent with an accumulation of more immune suppressive SLAN- TAMs. Next, we investigated whether treatment altered TAMs composition by analyzing 10 patient longitudinal samples collected at diagnosis, after VRD induction, and after HDT/ASCT. Interestingly, we observed that while TAMs remained unaltered after VRD induction, there was a marked shift in their distribution after HDT/ASCT with an even greater accumulation of immune suppressive SLAN- TAMs (P=.08), at expenses of reduced numbers of SLAN+ TAMs (P=.01). Furthermore, chemoresistant MRD-positive patients (n=7/10) after HDT/ASCT showed a 2-fold increment in immune suppressive SLAN- TAMs vs MRD-negative cases. In conclusion, by taking into account the effect of MM patients' BM stroma we showed that TAMs do not induce significant tumor growth. TAMs do not protect MM cells from classic drugs, and MM cells with normal CD38 levels (ie. non lentiviral-transduced to express abnormally high levels of CD38) were not targeted by anti-CD38 mAbs via ADCP. We also showed that there is an expansion of classic and intermediate monocytes but not TAMs in MM; however, using multidimensional flow cytometry to identify novel TAM subsets we revealed that newly diagnosed patients are enriched with immune suppressive TAMs that become further expanded after therapy. Thus, improved monitoring of TAMs could help identifying patients less susceptible to benefit from immunotherapy due to an immune suppressive tumor microenvironment. Figure Figure. Disclosures Mateos: Takeda: Honoraria; Amgen: Honoraria; Celgene: Honoraria; Janssen: Honoraria. Paiva:Celgene: Honoraria, Research Funding; Janssen: Honoraria; Takeda: Honoraria, Research Funding; Sanofi: Consultancy, Research Funding; EngMab: Research Funding; Amgen: Honoraria; Binding Site: Research Funding.

Description: Monoclonal antibodies (mAbs) targeting CD38 are demonstrating remarkable efficacy, particularly when combined with anti-MM agents. Thus, in-depth understanding of the MoA of anti-CD38 mAbs is of utmost importance to design rational treatment combinations. Notably, while there is considerable data about the MoA of Daratumumab, there is virtually no data about the MoA of Isatuximab. Here, we started by analyzing in a selected panel of MM cell lines (RPMI8226, H929, MM1S and OPM2) the effect of Isatuximab on 1) proliferation, 2) direct cell death, 3) complement dependent cytotoxicity (CDC), 4) antibody dependent cell mediated cytotoxicity (ADCC), and 5) antibody dependent cellular phagocytosis (ADPC). Our results show that Isatuximab had no effect on proliferation, and did not directly killed any of the MM cell lines tested. Interestingly, while Isatuximab (similar to drugs such as Cetuximab) binds to C1q, CD38 receptor density in MM cell lines was insufficient to trigger CDC based on the absence of C3 deposition and impact on cell survival. Upon co-culture with human blood leukocytes, Isatuximab induced ADCC particularly on cells showing higher expression of CD38 (P=0.02). Upon co-culture with human-derived M2-like macrophages, we noted a trend (P=.1) towards decreased MM cell expansion; thus, in order to establish the exact contribution of ADCC and ADCP on the efficacy of Isatuximab, we co-cultured RPMI8226 MM cells with human leukocytes and prior to treatment (10µg/mL), used sensitive FACS sorting to remove key immune cell populations such as NK cells, macrophages and T cells from the culture. Our results show that the presence of NK cells was critical for the efficacy of Isatuximab, whereas macrophages and T cell depletion had no effect on MM cell viability in the presence of Isatuximab. We next tested Isatuximab (10µg/mL) in 10 primary patient samples. In the absence of C3 deposition in the majority of samples (ie. no CDC), we observed Isatuximab-induced cell death in all patients tested (P=0.002), along with increased proliferation and activation of NK cells upon Fc recognition. Due to broad expression of CD38 in hematopoietic cells, we also investigated presence of off-target effects of Isatuximab. Importantly, with the exception of CD38bright B cell precursors (P=.0006), there was no toxicity observed in other progenitor and mature hematopoietic cells. We also investigated the potential synergism of Isatuximab in combination with Bortezomib-Dexamethasone; interestingly, the addition of Isatuximab resulted in a (P=0.06) 2.7-fold increment in MM cell death. In order to further understand the direct effect of Isatuximab in both MM and (CD38bright) NK cells, we determined the molecular signature of both subsets in co-culture and upon treatment with Isatuximab. Interestingly (though consistent with the lack of impact in proliferation and direct apoptosis), MM cells showed no gene dysregulation upon treatment with Isatuximab and in the absence of NK cells. By contrast, in the presence of NK cells and respective ADCC, MM cells chemoresistant to Isatuximab showed 184 dysregulated genes, including significant down-regulation of CD38. Noteworthy, Isatuximab binding induced in NK cells up-regulation of genes related to antigen binding, chemokine receptor activity, G-protein coupled peptide receptor or hydrolase activity. One such gene was CD137, which up-regulation was subsequently confirmed at the protein (surface antigen) level. In summary, this critical analysis on Isatuximab's MoA using a comprehensive set of assays, MM cell lines and primary patient samples, suggests that ADCC is the major efficacy contributor for this particular mAb. Thus, drugs that can further stimulate NK cells might be optimal candidates for rational combinations with Isatuximab; in this regard, we showed that Isatuximab induces up-regulation of CD137 which warrants further investigations on the value of combined Isatuximab and anti-CD137 immune therapies. Figure Figure. Disclosures Paiva: Celgene: Honoraria, Research Funding; Janssen: Honoraria; Takeda: Honoraria, Research Funding; Sanofi: Consultancy, Research Funding; EngMab: Research Funding; Amgen: Honoraria; Binding Site: Research Funding.

Description: Novel agents have improved outcomes in MM, but prognosis after patients relapse remains poor and new drugs with novel MoA are needed. The breakthrough of immuno-oncology has rendered new therapeutic options, and most recently we reported on EM801, a novel BCMA-TCB that showed remarkably efficacy when used as single agent in primary bone marrow (BM) samples from MM patients (Seckinger, Blood 2015;126: abstr 117). Because of its novelty, further knowledge about the MoA of BCMA-TCB is of utmost importance to improve its efficacy by designing rational treatment combinations. In order to optimize the in vitro efficacy of the BCMA-TCB, we started by investigating in primary BM samples from 6 MM patients whether longer treatment periods with BCMA-TCB2 (a BCMA-TCB candidate sharing similar "2+1" structure of EM801 but displaying higher affinity to BCMA) would increase MM cell death. Upon treating samples with BCMA-TCB2 for 48h vs 96h, we noted a 2-fold increment in MM tumor cell lysis at 1nM and 10nM concentrations (Panel A). In parallel, the phenotypic profiles of CD4 and CD8 T cells showed that BCMA-TCB2 induced robust activation (ie. dose-dependent increment in CD69, CD25, HLADR after exposure to 100pM, 1nM and 10nM of BCMA-TCB2), but also led to the natural emergence of the checkpoint inhibitor PD-1 in the surface of activated CD4 and CD8 T cells (Panel B). We then investigated if there was a correlation between the percentage of PD-1 positive CD4 and CD8 T cells and the efficacy of BCMA-TCB2; interestingly, those patients with lower frequencies of PD-1 positive CD4 and CD8 T cells prior to treatment showed the highest rates of MM tumor cell lysis after 48h and 96h of BCMA-TCB2 at 10nM of (r=0.6, P=0.04; Panel C). By contrast, upon measuring the concentration of soluble BCMA and APRIL in the supernatants of primary BM samples from 16 MM patients treated with BCMA-TCB, we found no significant differences between responding (n=11) and non-responding (n=5) patients. Similar results were observed upon comparing the density of BCMA in the surface of MM tumor cells from responding vs non-responding patients (1256 vs 1522 SABC units; P=87). Since the efficacy of BCMA-TCB2 was found to be intrinsically related to the phenotype and activation status of T cells, we then investigated whether we could further harness immune cells by combining BCMA-TCB2 with three drugs representing different types of immunotherapy: lenalidomide (IMIDs), anti-PD1 (checkpoint inhibitors) and daratumumab (mAb). H929 MM cells were co-cultured with human leukocytes (n=5) and challenged to suboptimal concentrations of BCMA-TCB2 (10pM) alone, or in combination with standard doses of lenalidomide (1µM), anti-PD1 (10µg/ml) and daratumumab (10µg/ml) (Panel D). Interestingly, we observed that combining BCMA-TCB2 with lenalidomide or daratumumab significantly increased their anti-MM efficacy by 4-fold and 2.5-fold, respectively. Because lenalidomide and daratumumab share in common that they rely, at least in part, on activated NK cells to eradicate MM cells, we hypothesized whether such robust T cell activation induced by BCMA-TCB2 was leading to co-stimulation of NK cells. First, we demonstrated by analyzing the transcriptomes of T cells prior and after treatment exposure (n=3), that BCMA-TCB2 modulated the transcriptomes of CD4 and CD8 T cells (159 and 141 deregulated genes, respectively), consistent with enhanced activation and T-cell mediated inflammatory response (eg. TNFRS18, STAT1, CCL4). Furthermore, we observed a dose-dependent and significant increment of the CD69 (2-fold), CD25 (2.5-fold) and HLADR (4-fold) activation markers in the surface of NK cells from primary BM samples of 11 MM patients treated with BCMA-TCB2 (Panel E), suggesting a functional crosstalk between activated T cells and NK cells. In conclusion, we showed that the promising pre-clinical activity of the first-in-class IgG-based BCMA-TCB can be further enhanced by longer treatment periods followed by robust T cell activation. The observation that the efficacy of BCMA-TCB is intrinsically related to the activation status of T cells suggests its rational combination with IMIDs as demonstrated here. Most interestingly, potential crosstalk between activated T and NK cells could lead to enhanced function of the later immune subset, and provide a rational combination between BCMA-TCB and anti-CD38 antibodies to eradicate MM cells through highly activated T and NK cells. Figure Figure. Disclosures Strein: EngMab: Employment. Vu:EngMab: Employment. Paiva:Celgene: Honoraria, Research Funding; Janssen: Honoraria; Takeda: Honoraria, Research Funding; Sanofi: Consultancy, Research Funding; EngMab: Research Funding; Amgen: Honoraria; Binding Site: Research Funding.

Description: Background: The immune system reacts to viral infection with cellular and humoral responses. Thus, myelo- and lympho-suppression caused by cancer itself as well as cytotoxic treatment may pose a challenge to COVID-19 patients with solid and hematological tumors, but severe events from initial onset of COVID-19 appear to be more frequent in blood malignancies vs other cancer types. Preliminary data showed lower neutrophil and lymphocyte counts in COVID-19 patients bearing hematological cancer, but there are conflicting results supporting that both worsening of lymphopenia during COVID-19 and its depth prior to infection had a beneficial impact on survival. Thus, greater knowledge on the immune status of hematological patients may be useful to optimize prevention, risk stratification and treatment strategies. Aim: Analyze the immune status of COVID-19 patients with or without solid and hematological cancer. Methods: We use multidimensional flow cytometry (MFC) to analyze immune profiles in peripheral blood samples of 515 COVID-19 patients at presentation. Data was analyzed with a semi-automated pipeline that performs batch-analyses of MFC data to avoid variability intrinsic to manual analysis, and unveils full cellular diversity based on unbiased clustering. In 14 cases, deep immunophenotyping of B- and T-cells was performed and six myeloid- and dendritic-cell subsets were FACSorted for transcriptome analysis using RNAseq. Results: Of the 515 COVID-19 patients, 15 and 10 had solid and hematological tumors, respectively. Those with hematological cancer showed similar frequency of hospitalization than those with solid tumors (90% and 93%, respectively), which was modestly higher to that observed in persons without an active tumor (76%). By contrast, the frequency of hematological cases requiring intensive care (50%) and dying from COVID-19 (30%) was significantly higher to that observed in patients with no active tumor (5.5% and 4%, respectively), or with solid cancer (both 0%). Based on semi-automated analysis of MFC data, we systematically quantified a total of 19 cell types in PB that included 6 myeloid and 13 lymphoid subsets. Patients with hematological malignancies displayed altered immune profiles with significantly decreased absolute numbers of classical and intermediate monocytes, immunoregulatory and cytotoxic NK cells, double-negative, double-positive, CD4 and CD56- γδ T cells, as well as of mature B cells when compared to those with no tumor. Unsupervised hierarchical analysis of RNAseq data from basophils, myeloid and plasmacytoid dendritic cells, classical and non-classical monocytes and neutrophils showed considerable clustering of samples from hematological cases. Furthermore, a variable number of differentially expressed genes was found in all six cell types between COVID-19 patients with or without blood cancer. Genes related to NF-κB and STAT transcription factors as well as genes encoding toll-like receptors and proinflammatory interleukin receptors, all of which described to be implicated in the response and evasion of innate sensing by coronaviruses, were differentially expressed in many of these cell types. Deep phenotypic characterization of T- and B-cell compartments in PB of COVID-19 patients with (N = 4) or without (N = 10) hematological cancer showed that the relative distribution of antigen-dependent maturation stages within the T-cell compartment was generally similar between both groups. However, some hematological cases displayed profound alterations in virtually all of the 16 B-cell subsets analyzed, with a notorious reduction in memory B cells expressing IgG and IgA subclasses. We next compared immune responses from presentation to last follow-up in COVID-19 patients with hematological cancer and favorable (N = 3) vs fatal (N = 3) outcome. Interestingly, we found opposite kinetics in myeloid cell types such as eosinophils and neutrophils, decreasing numbers of various T cell subsets, as well as lower mature B cells and circulating PCs at presentation together with a decrease in B cell counts in deceased cases. Conclusions: Our study exposes for the first time that hematological patients show a constellation of immune alterations that could compromise the response to the infection caused by SARS-CoV-2, suggesting an association between impaired immune responses and poorer outcomes in COVID-19 patients with hematological malignancies. Disclosures Paiva: SkylineDx: Consultancy; Takeda: Consultancy, Honoraria, Research Funding; Roche: Research Funding; Adaptive: Honoraria; Amgen: Honoraria; Janssen: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Kite: Consultancy; Sanofi: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau.