ALBERT

Description: In MM patients relapsing after MRD-negativity, the disease could reemerge from immature cells or from undetectable MRD. However, it remains unknown if immature cells have the same genetic background as MM plasma cells (PCs), as well as the amount of MRD that persists below the limit of detection (LOD) of next-generation techniques. To obtain further insight, we compared the biological landscape of MM PCs at diagnosis to that of CD34 progenitors, B cells and normal PCs isolated from patients with negative MRD by next-generation flow (NGF) after treatment. We performed whole-exome sequencing (WES, mean depth: 90x) with the 10XGenomics Exome Solution for low DNA-input as well as deep NGS of B-cell receptor immunoglobulin (BcR IG) gene rearrangements (mean, 69,975 sequences), in a total of 68 cell-samples isolated from the bone marrow (BM) of 7 MM patients with MRD-negativity by EuroFlow NGF after induction with VRD and auto-transplant (GEM2012MENOS65 trial). Patients with negative MRD were intentionally selected to avoid contamination with MM PCs during sorting of CD34 progenitors, B-cell precursors, mature B cells and normal PCs after induction and transplant. We investigated in these populations the presence of somatic mutations and clonotypic BcR Ig rearrangements detectable in MM PCs sorted at diagnosis, using peripheral blood T cells as germline control. We also performed WES in matched diagnostic MM PCs and MRD cells persisting after VRD induction in 14 cases as control. In another 6 patients with untreated MM, we performed single-cell RNA and BcR IG sequencing (scRNA/BcRIGseq) of total BM B cells and PCs (n=16,380) to investigate before treatment, if the clonotypic BcR IG sequence of MM PCs was detectable in other B cell stages defined by their molecular phenotype. We used multidimensional flow cytometry (MFC) to investigate the frequency of B cell clonality in BM samples from a larger series of 195 newly-diagnosed MM patients, prospectively enrolled in the GEM-CLARIDEX trial. Somatic mutations present in diagnostic MM PCs were detectable in the lymphopoiesis of 5/7 patients achieving MRD-negativity after treatment. In one case, out of 55 mutations present in diagnostic MM PCs, a single mutation in PCSK1N (VAF: 0.30) was detectable in normal PCs. In the other four patients, a total of 85 mutations were present in MM PCs and up to 10 (median VAF, 0.16) were found all the way from CD34 progenitors into B-cell precursors, mature B cells and normal PCs, but not in T cells. Of note, most mutations were reproducibly detected in each cell type after induction and after transplant. All somatic mutations shared by MM PCs and normal cells were non-recurrent, and genes recurrently mutated in MM (eg. ACTG1, ATM, DIS3, FAM46C, KRAS, LTB, MAX, TRAF3) were found in MM PCs but never in normal cells. Copy number alterations (CNA) were found only in MM PCs. By contrast, up to 513/827 (62%) mutations and 48/67 (72%) CNA were detectable in matched diagnostic MM PCs and persistent MRD cells, indicating that the few somatic variants present in normal cells were unlikely related to contaminating MRD below NGF's LOD. Accordingly, MM clonotypic BcR IG rearrangements were detectable in normal PCs (4/7patients) and in immature B cells (5/7 patients) but at much lower frequencies (mean of 0.02% in both). Of note, 9 additional clonotypes (mean 8.4%) were found in MM PCs of 5/7 patients (range, 1-3). scRNR/BcRIGseq unveiled that clonotypic cells were confined mostly but not entirely within PC clusters, and that in 1 patient another clonotype was detectable in mature B cells. Accordingly, using MFC we found in a larger series that 25/195 (13%) of newly-diagnosed MM patients display B-cell clonality (median of 0.7% BM clonal B cells, range 0.02%-6.3%). In conclusion, we show for the first time that MM patients bear somatic mutations in CD34 progenitors that specifically differentiate into the B cell lineage, likely before the disease onset. Because diagnostic, MRD (and relapse) MM PCs display great genetic similarity, these results suggest that undetectable MRD

Description: Patients with multiple myeloma (MM) carrying high-risk cytogenetic abnormalities (CA) have inferior outcome despite achieving similar complete response (CR) rates when compared to cases with standard-risk CA. This questions the legitimacy of CR as treatment endpoint for high-risk MM, and represents a biological conundrum regarding the nature of tumor reservoirs persisting after therapy in patients with standard- and high-risk CA. Here, we used next-generation flow (NGF) to evaluate measurable residual disease (MRD) in MM patients with standard- (N=300) vs high-risk CA (N=90) enrolled in the PETHEMA/GEM2012MENOS65 trial (NCT01916252), and to identify mechanisms determining MRD resistance in both patient subgroups (N=40). The 36-month progression-free and overall survival rates were higher than 90% in patients with undetectable MRD, with no significant differences (P≥0.202) between cases having standard- vs high-risk CA. Persistent MRD resulted in median progression-free survival of approximately three and two years in patients with standard- and high-risk CA, respectively (P

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: Background: MM and AL are the two most common malignant monoclonal gammopathies. Both diseases result from the accumulation of clonal PCs, but their clinical behavior is significantly different suggesting fundamental differences in disease biology. Previous attempts to identify genetic hallmarks that could explain such differences have been unsuccessful. Furthermore, it is unknown if MM and AL arise from the same or different normal PC counterparts. Aim: To define a transcriptional atlas of the normal PC development in peripheral blood (PB) and bone marrow (BM) for comparison with the transcriptional programs of clonal PCs in MM and AL. Methods: A total of 93 subjects were studied. In 7 healthy adults (HA), PB PCs were phenotypically sorted according to heavy-chain isotypes (IgG, IgA and IgM). In addition, 5 different BM PCs subsets were isolated based on the differential expression of CD19, CD39, CD81 and CD56, due to their ascribed role in dissecting unique BM PC differentiation states. Clonal PCs from patients with MM (n=38) and AL (n=41) were isolated by FACS according to patient-specific aberrant phenotypes. Due to small numbers of PCs sorted from each subset in HA and clonal PCs in AL patients, we used an RNAseq method optimized for limited cell numbers. Differential expression across all pairwise comparisons between groups was analyzed with Deseq2 R package followed by k-means clustering of genes in R. Single-cell RNAseq (scRNAseq, 10xGenomics) was performed in a total of 35,910 PCs from 3 HA, 2 MM and 2 AL. We used Seurat R package to remove batch effect followed by canonical correlation to perform an integrated analysis of all single PCs from HA, MM and AL subjects. Results: Principal component analysis of RNAseq data unveiled two major clusters of normal PCs: those in PB and those in BM (with some transcriptional diversity between CD19+ and CD19- PCs), whereas the CD19+CD39+CD81+CD56- BM subset co-localized with PB and CD39- BM PCs (Panel A). Clonal PCs from MM and AL patients clustered together, and both displayed some transcriptional variance related to the spatial location of normal PCs (i.e. PB or BM). In total, 2174 genes were found significantly deregulated after cross-comparing the 10 PC groups (adj.p-value1) and semi-supervised k-means clustering unveiled 8 transcriptional modules (Panel B). Namely, the transition from PB into BM PCs was characterized by genes related to proliferation (clusters 1 & 2), whereas CD39+ and CD39- BM PC subsets differed on the expression of genes associated with proliferation, homing, and metabolism (1, 2, 4 & 6). Thus, CD19+CD39+CD81+CD56- BM PCs emerged as a novel subset that bridges new-born PB with long-lived (CD39-) BM PCs. Interestingly, clonal PCs from MM and AL shared transcriptional programs related to quiescence (5 & 6) with long-lived BM PCs; however, skewing of polyclonal immunoglobulin gene expression (3) and active gene transcription (8) emerged as hallmarks of the neoplastic transformation from normal, long-lived PCs into clonal PCs. That notwithstanding, the later displayed expression levels of the proliferation and homing transcriptional modules (1 & 4) similar to new-born PB and CD39+ BM PCs. Of note, a small transcriptional cluster of genes related to ribosome biogenesis (7) was significantly more expressed in MM than AL. These findings led us to integrate scRNAseq profiles of normal and clonal BM PCs from MM and AL patients, to define PC clusters based on their transcriptional program rather than their normal vs malignant status (Panel C). This strategy unveiled 11 different PC clusters with unequal distribution between groups. Thus, more than half of clonal PCs in MM and AL were assigned to a cluster that is also predominant in normal PCs (1). By contrast, other clusters with a transcriptional program similar to that of new-born PCs (2 & 5) became rarer in MM and AL. Furthermore, a cluster of PCs with an immature-like phenotype (6) was detectable in MM but almost absent in AL. Conclusions: This is the first integrated analysis of the transcriptional programs of normal PC subsets and clonal PCs in MM and AL, both at the bulk and single-cell levels. Our results unveil shared and exclusive transcriptional states in normal and clonal PCs, together with unique differences between clonal PCs in MM and AL. Thus, we provide here a fundamental resource to understand normal PC development and the cellular origin of both malignant monoclonal gammopathies. Figure Figure. Disclosures Puig: Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Honoraria, Research Funding. Ocio:Pharmamar: Consultancy; AbbVie: Consultancy; Janssen: Consultancy, Honoraria; Seattle Genetics: Consultancy; BMS: Consultancy; Takeda: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Sanofi: Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Mundipharma: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Array Pharmaceuticals: Research Funding. Oriol: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; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Martinez Lopez:Bristol Myers Squibb: Research Funding, Speakers Bureau; Janssen: Research Funding, Speakers Bureau; Novartis: Research Funding, Speakers Bureau; Celgene: Research Funding, Speakers Bureau. Mateos:Janssen: 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; 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; GSK: Consultancy, Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees. Lahuerta:Takeda: 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; Celgene: 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. San-Miguel:Sanofi: Consultancy; Takeda: Consultancy; Novartis: Consultancy; MSD: Consultancy; Janssen: Consultancy; Celgene: Consultancy; Brystol-Myers Squibb: Consultancy; Amgen: Consultancy; Roche: Membership on an entity's Board of Directors or advisory committees.

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: Background: Genetic characterization is becoming relevant to predict risk of progression in smoldering MM and is fundamental to estimate survival in active MM. Thus, patients undergo multiple bone marrow (BM) aspirates for genetic screening that beyond painful, may not be fully representative due to patchy BM involvement, spatial genomic heterogeneity, or extramedullary disease. Accordingly, cell-free DNA has been investigated and showed high concordance with BM aspirates, but information is typically restricted to a few recurrent mutations since comprehensive genetic characterization (eg. whole-exome sequencing, WES) is applicable to

Description: Risk of developing myelodysplastic syndrome (MDS) is significantly increased in both multiple myeloma (MM) and monoclonal gammopathy of undetermined significance, suggesting that it is therapy independent. However, the incidence and sequelae of dysplastic hematopoiesis at diagnosis are unknown. Here, we used multidimensional flow cytometry (MFC) to prospectively screen for the presence of MDS-associated phenotypic alterations (MDS-PA) in the bone marrow of 285 patients with MM enrolled in the PETHEMA/GEM2012MENOS65 trial (#NCT01916252). We investigated the clinical significance of monocytic MDS-PA in a larger series of 1252 patients enrolled in 4 PETHEMA/GEM protocols. At diagnosis, 33 (11.6%) of 285 cases displayed MDS-PA. Bulk and single-cell–targeted sequencing of MDS recurrently mutated genes in CD34+ progenitors (and dysplastic lineages) from 67 patients revealed clonal hematopoiesis in 13 (50%) of 26 cases with MDS-PA vs 9 (22%) of 41 without MDS-PA; TET2 and NRAS were the most frequently mutated genes. Dynamics of MDS-PA at diagnosis and after autologous transplant were evaluated in 86 of 285 patients and showed that in most cases (69 of 86 [80%]), MDS-PA either persisted or remained absent in patients with or without MDS-PA at diagnosis, respectively. Noteworthy, MDS-associated mutations infrequently emerged after high-dose therapy. Based on MFC profiling, patients with MDS-PA have altered hematopoiesis and T regulatory cell distribution in the tumor microenvironment. Importantly, the presence of monocytic MDS-PA at diagnosis anticipated greater risk of hematologic toxicity and was independently associated with inferior progression-free survival (hazard ratio, 1.5; P = .02) and overall survival (hazard ratio, 1.7; P = .01). This study reveals the biological and clinical significance of dysplastic hematopoiesis in newly diagnosed MM, which can be screened with moderate sensitivity using cost-effective MFC.

Description: Background: Despite significant improvements in the treatment of MM, the outcome of patients with HR cytogenetics remains poor despite similar complete remission (CR) rates as compared to SR cases. Relapses among patients in CR are attributed to the persistence of MRD, but knowledge about the impact of MRD in patients with SR and HR cytogenetics, treated with modern therapies and monitored with next-generation techniques, is limited. Similarly, there is virtually no data about in vivo mechanisms of resistance in SR and HR MM; however, since MRD represents those very few cells that are resistant to treatment, it could be hypothesized that profiling MRD cells may shed light into the mechanisms of resistance in both SR and HR patients. Aim: To determine the clinical impact of MRD in MM patients with SR vs HR cytogenetics, and to identify transcriptional mechanisms determining MRD resistance by investigating the transcriptome of MRD cells in both patient subgroups. Methods: This study was conducted in a series of 390 patients enrolled in the PETHEMA/GEM2012 trial (6 induction cycles with VRD followed by ASCT and 2 courses of consolidation with VRD). FISH was analyzed on CD138 purified PCs at diagnosis. MRD was predefined to be prospectively assessed following induction, transplant and consolidation, using next-generation flow (NGF) according to EuroFlow. In 40 patients [28 with SR and 12 with HR cytogenetics: i.e., t(4;14), t(14;16) and/or del(17p)], diagnostic and MRD tumor cells persisting after VRD-induction were isolated by FACS according to patient-specific aberrant phenotypes. Due to the small number of sorted MRD cells (median of 25,600) we used a 3' end RNAseq method optimized for generating libraries from low-input starting material (MARSeq). Differential expression analyses were performed with DESeq2 R package. Results: At the latest time-point in which MRD was assessed, MRD-positive rates progressively increased (p =.006) from SR patients (148/300, 49%) to cases with t(4;14) (24/42, 57%) and del(17p) (29/38, 76%). Furthermore, MRD levels were significantly superior in patients with del(17p) compared to SR FISH (0.02% vs 0.006%, p =.009), while MRD levels in patients with t(4;14) (0.004%) were similar to those in SR MM. Only 10 patients had a t(14;16) and 4 were MRD-positive. Among patients achieving MRD-negativity (.05). Conversely, 3-year PFS rates for MRD-positive patients decreased from those having SR FISH to those with t(4;14) and del(17p) (59%, 46% and 24%, respectively), with statistically significant differences between the first and the latest subgroups (p