Abstract: Background: The advent of immunotherapy renewed the interest in immune monitoring to identify determinants of treatment response. Flow cytometry is widely adopted in immunotherapy-based clinical trials, but manual analysis of multiparameter files poses a challenge to capture full cellular diversity and to provide unbiased reporting in large datasets. Methods: Here, we developed a semi-automated pipeline named "FlowCT" which, starting from compensated data obtained with standardized protocols, allows simultaneous analyses of multiple files and automated cell clustering. FlowCT starts with quality control and data normalization followed by an analytical stage with clustering algorithms, dimensional reduction techniques and cluster identification based on antigen expression. Statistical tools are included for immediate analysis of results. Results: As proof-of-concept, we used FlowCT in three different datasets. First, we applied FlowCT to bone marrow (BM) samples from three multiple myeloma (MM) patients stained with 17-color flow cytometry, to determine the increment in the complexity of analyzing 8 and 17 markers, chosen to characterize T cells. Of note, a single combination of CD3, CD4, CD8, CD45RA, CD56, CCR7, PD1 and TIGIT, allowed the identification of 31 lymphocyte subsets using FlowCT, which increased to 39 different clusters with 17 markers and unveiled a novel population of CD3- CD56- CD8+ CD16+ lymphoid cells in the MM immune microenvironment. Secondly, we applied FlowCT to matched peripheral blood (PB) and BM samples from 10 patients with smoldering MM, to objectively assess if PB represents a good surrogate of T-cell distribution in the BM. Using an 8-color combination to characterize CD4 T cells, up to 26 different subsets were identified, including several CD4 T helper (Th) type subsets. Of note, their distribution within PB CD4 T cells was similar to that found in BM, except for CD4 T CXCR3+CCR4+ effector memory and Th17 central memory subsets that decreased in the BM tumor immune microenvironment. Thirdly, we analyzed 30 BM samples from 10 MM patients studied every year during maintenance therapy, monitored with CD4, CD8, CD25, CD45RA, CD127, CCR7, PD1, and TCRγδ to characterize T cells. FlowCT identified 29 different T-cell populations, including 9 CD4 subsets, 14 CD8 subsets, 4 Tγδ cell subsets and 2 distinct Treg subsets. Longitudinal, semi-automated and unbiased analysis unveiled a significant fluctuation of CD4 naïve and transitional memory cells during maintenance, as well as a significant decrease of CD8 CD127- effector memory and transitional effectors cells after 2 years of maintenance. Conclusions: Here, we presented FlowCT, a pipeline optimized for the analysis of large flow cytometry datasets that could be easily implemented by research laboratories to unveil full cellular diversity, singular patterns of antigen expression, and to provide unbiased reporting in large studies, like clinical trials. Disclosures Puig: Amgen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; The Binding Site: Honoraria; Takeda: Consultancy, Honoraria. Borrello:WindMIL Therapeutics: Equity Ownership, Patents & Royalties, Research Funding; Aduro: Patents & Royalties: intellectual property on allogeneic MM GVAX; BMS: Consultancy; Celgene: Honoraria, Research Funding, Speakers Bureau. Rosinol Dachs:Janssen, Celgene, Amgen and Takeda: Honoraria. Mateos:Janssen, Celgene, Takeda, Amgen, GSK, Abbvie, EDO, Pharmar: Membership on an entity's Board of Directors or advisory committees; Janssen, Celgene, Takeda, Amgen, Adaptive: Honoraria; Amgen Inc, Janssen Biotech Inc: Other: Data and Monitoring Committee; Amgen Inc, Celgene Corporation, Janssen Biotech Inc, Takeda Oncology.: Speakers Bureau; AbbVie Inc, Amgen Inc, Celgene Corporation, Genentech, GlaxoSmithKline, Janssen Biotech Inc, Mundipharma EDO, PharmaMar, Roche Laboratories Inc, Takeda Oncology: Other: Advisory Committee. Lahuerta:Takeda, Amgen, Celgene and Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Bladé:Jansen, Celgene, Takeda, Amgen and Oncopeptides: Honoraria. San-Miguel:Amgen, Bristol-Myers Squibb, Celgene, Janssen, MSD, Novartis, Roche, Sanofi, and Takeda: Consultancy, Honoraria. Paiva:Celgene, Janssen, Sanofi and Takeda: Consultancy; Amgen, Bristol-Myers Squibb, Celgene, Janssen, Merck, Novartis, Roche and Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees.

Abstract: Large-scale immune monitoring is becoming routinely used in clinical trials to identify determinants of treatment responsiveness, particularly to immunotherapies. Flow cytometry remains one of the most versatile and high throughput approaches for single-cell analysis; however, manual interpretation of multidimensional data poses a challenge when attempting to capture full cellular diversity and provide reproducible results. We present FlowCT, a semi-automated workspace empowered to analyze large data sets. It includes pre-processing, normalization, multiple dimensionality reduction techniques, automated clustering, and predictive modeling tools. As a proof of concept, we used FlowCT to compare the T-cell compartment in bone marrow (BM) with peripheral blood (PB) from patients with smoldering multiple myeloma (SMM), identify minimally invasive immune biomarkers of progression from smoldering to active MM, define prognostic T-cell subsets in the BM of patients with active MM after treatment intensification, and assess the longitudinal effect of maintenance therapy in BM T cells. A total of 354 samples were analyzed and immune signatures predictive of malignant transformation were identified in 150 patients with SMM (hazard ratio [HR], 1.7; P & lt; .001). We also determined progression-free survival (HR, 4.09; P & lt; .0001) and overall survival (HR, 3.12; P = .047) in 100 patients with active MM. New data also emerged about stem cell memory T cells, the concordance between immune profiles in BM and PB, and the immunomodulatory effect of maintenance therapy. FlowCT is a new open-source computational approach that can be readily implemented by research laboratories to perform quality control, analyze high-dimensional data, unveil cellular diversity, and objectively identify biomarkers in large immune monitoring studies. These trials were registered at www.clinicaltrials.gov as #NCT01916252 and #NCT02406144.

Abstract: Early intervention in smoldering multiple myeloma (SMM) requires optimal risk stratification to avoid under- and overtreatment. We hypothesized that replacing bone marrow (BM) plasma cells (PC) for circulating tumor cells (CTC), and adding immune biomarkers in peripheral blood (PB) for the identification of patients at risk of progression due to lost immune surveillance, could improve the International Myeloma Working Group 20/2/20 model. Experimental Design: We report the outcomes of 150 patients with SMM enrolled in the iMMunocell study, in which serial assessment of tumor and immune cells in PB was performed every 6 months for a period of 3 years since enrollment. Results: Patients with & gt;0.015% versus ≤0.015% CTCs at baseline had a median time-to-progression of 17 months versus not reached (HR, 4.9; P  & lt; 0.001). Presence of & gt;20% BM PCs had no prognostic value in a multivariate analysis that included serum free light-chain ratio & gt;20, & gt;2 g/dL M-protein, and & gt;0.015% CTCs. The 20/2/20 and 20/2/0.015 models yielded similar risk stratification (C-index of 0.76 and 0.78). The combination of the 20/2/0.015 model with an immune risk score based on the percentages of SLAN+ and SLAN− nonclassical monocytes, CD69+HLADR+ cytotoxic NK cells, and CD4+CXCR3+ stem central memory T cells, allowed patient’ stratification into low, intermediate-low, intermediate-high, and high-risk disease with 0%, 20%, 39%, and 73% rates of progression at 2 years. Conclusions: This study showed that CTCs outperform BM PCs for assessing tumor burden. Additional analysis in larger series are needed to define a consensus cutoff of CTCs for minimally invasive stratification of SMM.

Abstract: MYD88 L265P occurs in between a normal mutated lymphopoiesis and additional genetic alterations during lymphomagenesis.

Abstract: Introduction : In patients (pts) with multiple myeloma (MM), next generation flow cytometry (NGF) and next generation sequencing have shown an increased capacity to identify the presence of disease and to anticipate patient's prognosis as compared to serum protein immunofixation (IFE). However, both methods rely on bone marrow (BM) samples and it is important to explore alternative techniques applicable in more accessible samples such as peripheral blood. Patients and Methods: Newly diagnosed MM pts enrolled in the PETHEMA/GEM2012MENOS65 trial received six cycles of induction with bortezomib, lenalidomide and dexamethasone (VRD), intensification with high-dose therapy (melphalan or busulfan and melphalan) followed by autologous stem cell transplantation and consolidation with two more cycles of VRD. At the end of the treatment (post-consolidation), the M-protein (MP) was analyzed in serum by conventional IFE and by EXENT Quantitative Immunoprecipitation Mass Spectrometry using IgG/A/M, κ, λ, free κ and free λ isotypic beads; negative samples by EXENT were re-analyzed by liquid chromatography mass spectrometry (LC-MS). The presence of clonal plasma cells in BM samples was investigated by NGF following the Euroflow guidelines (sensitivity≥10 -5). Samples from the first 164 pts enrolled in the trial were analyzed in this study. Results : After consolidation, persistent disease was detected in 42 (26%) pts by IFE, in 56 (34%) by EXENT and in 72 (44%) by NGF. Surprisingly, the presence or absence of disease by IFE did not discriminate pts with different progression-free survival (PFS), but both EXENT and NGF segregated two cohorts with a significantly different PFS (p=0.0016 and p & lt;0.0001, respectively; fig1A and 1C). Importantly, we observed that among pts in complete response (IFE negative), EXENT and NGF also distinguished two groups with different PFS (p=0.002 and p=0.0001, respectively.) Analyzing the results obtained with EXENT and NGF, we found that 76% were concordant (44 EXENT +/NGF +, 80 EXENT -/NGF -) and 24% discordant (28 EXENT -/NGF + and 12 EXENT +/NGF -). When we compared pts´ PFS according the combined results of both methods (fig 1D), we learnt that the 3 comparisons reaching statistical significance were EXENT +/NGF + vs EXENT -/NGF - (p & lt;0.0001), EXENT +/NGF + vs EXENT +/NGF - (p=0.0394) and EXENT -/NGF - vs EXENT -/NGF + (p=0.0363). Considering NGF as a reference, the negative predictive value (NPV) of EXENT was 74% overall (96% in MRD levels ≥10 -4, p & lt;0.0001; 89% in & lt;10 -4 - ≥10 -5 p & lt;0.0001; and 84% in ≥10 -6 cases, p=0.0524). Samples deemed negative by EXENT were re-analyzed with LC-MS. In 63 of them (58%) the MP was identified using LC-MS and therefore a total of 119 samples (73%) were considered positive with EXENT & LC-MS. We first confirmed that EXENT & LC-MS segregated two cohorts with different PFS (fig 1B, p=0.0193) Then, as earlier, we analyzed the results obtained with EXENT & LC-MS and NGF, finding that 65% were concordant (67 EXENT & LC-MS +/NGF +, 40 EXENT & LC-MS -/NGF -) and 35% discordant (5 EXENT & LC-MS -/NGF + and 52 EXENT & LC +/NGF -). Again, we compared pts´ PFS according the combined results of both methods (fig 1E) learning now that only the comparisons EXENT & LC-MS +/NGF + vs EXENT & LC-MS -/NGF - (p=0.0006) and EXENT & LC-MS +/NGF + vsEXENT & LC-MS +/NGF - (p=0.0006) reached statistical significance. With these results, the NPV of EXENT & LC-MS was 89% overall (100% in MRD levels ≥10 -4 p & lt;0.0001; 100% in & lt;10 -4 - ≥10 -5 p & lt;0.0001; and 89% in ≥10 -6 cases p=0.0914). Finally, we observed that whereas among pts deemed EXENT +, NGF identified 2 cohorts with different PFS (a NGF -group of 12 pts displaying a longer PFS as compared with those NGF +; median PFS: 4 years vs not reached, p=0.039) among EXENT & LC-MS - cases (n=45) NGF was not able to show any added clinical value. Conclusions : The use of IFE post-consolidation in pts with MM, as opposed to EXENT and NGF, did not identify pts with different PFS. When referred to NGF, EXENT provided a similar clinical value and displayed a very high NPV, increased further with the addition of LC-MS; this could be utilised to avoid the performance of a BM aspiration after treatment in pts with undetectable disease. Regarding EXENT + and/or LC-MS + cases future quantitative and sequential studies could reveal whether are due to the long half-lives of the MP or represent quiescent low-level disease. Figure 1 Figure 1. Disclosures Puig: Amgen, Celgene, Janssen, Takeda and The Binding Site: Honoraria; Amgen, Celgene, Janssen, Takeda: Consultancy; Celgene: Speakers Bureau; Celgene, Janssen, Amgen, Takeda: Research Funding. Paiva: Bristol-Myers Squibb-Celgene, Janssen, and Sanofi: Consultancy; Adaptive, Amgen, Bristol-Myers Squibb-Celgene, Janssen, Kite Pharma, Sanofi and Takeda: Honoraria; Celgene, EngMab, Roche, Sanofi, Takeda: Research Funding. Cedena: Janssen, Celgene and Abbvie: Honoraria. Rosinol: Janssen, Celgene, Amgen and Takeda: Honoraria. Martínez-López: Roche, Novartis, Incyte, Astellas, BMS: Research Funding; Janssen, BMS, Novartis, Incyte, Roche, GSK, Pfizer: Consultancy. Oriol: Karyopharm: Consultancy, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS/Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Sureda: Bluebird: Membership on an entity's Board of Directors or advisory committees; Kite, a Gilead Company: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Support for attending meetings and/or travel, Research Funding, Speakers Bureau; GSK: Consultancy, Honoraria, Speakers Bureau; Roche: Other: Support for attending meetings and/or travel; BMS/Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Support for attending meetings and/or travel, Speakers Bureau; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Mundipharma: Consultancy; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; MSD: Consultancy, Honoraria, Speakers Bureau; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Moraleda: Jazz Pharmaceuticals: Consultancy, Honoraria, Other: Educational Grants, Research Funding; Gilead: Consultancy, Honoraria, Other: Educational Grants, Research Funding; Novartis: Consultancy, Honoraria, Other: Educational Grants, Research Funding; Sandoz: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Other: Educational Grants, Research Funding; ROCHE: Consultancy, Honoraria, Other: Educational Grants, Research Funding; MSD: Other: Educational Grants, Research Funding; Sanofi: Other: Educational Grants, Research Funding; Pfizer: Other: Educational Grants, Research Funding; NovoNordisk: Other: Educational Grants, Research Funding; Janssen: Other: Educational Grants, Research Funding; Celgene: Other: Educational Grants, Research Funding; Amgen: Other: Educational Grants, Research Funding. Bladé Creixenti: Janssen, Celgene, Takeda, Amgen and Oncopeptides: Honoraria. San-Miguel: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, GlaxoSmithKline, Janssen, Karyopharm, Merck Sharpe & Dohme, Novartis, Regeneron, Roche, Sanofi, SecuraBio, and Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees. Mateos: Regeneron: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria; Adaptive Biotechnologies: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sea-Gen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene - Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bluebird bio: Honoraria; GSK: Honoraria; Oncopeptides: Honoraria.

Abstract: 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.

Abstract: Continuous treatment with lenalidomide (R) and dexamethasone (d) is a standard of care for multiple myeloma (MM) patients (pts) not candidates for autologous stem cell transplantation (ASCT). As previously reported, the addition of Clarithromycin (C) to Rd has proven to be safe and effective, and case-control analyses suggested a significant additive value with the combination. C optimizes the therapeutic effect of glucocorticoids by increasing the area under the curve, has immunomodulatory effects and may have direct antineoplastic properties. However, there are not randomized phase III trials confirming these results. GEM-Claridex in an open, randomized, phase III trial for untreated newly diagnosed MM pts ineligible for ASCT. Enrolled pts were randomly assigned 1:1 to receive 28-day cycles of R (25mg po qd days 1-21), d (40mg po [20mg in pts & gt;75 years], days 1, 8, 15 and 22) plus or minus C (500mg po bid) until disease progression or unacceptable toxicity. The primary endpoint was progression-free survival (PFS). Secondary endpoints included overall response rate (ORR), overall survival (OS) and minimal residual disease (MRD) negativity rate and safety. MRD was evaluated in 99 pts using Euroflow NGF (limit of detection, 2x10-6). As expected, most pts in CR were tested for MRD whereas the majority of pts with missing MRD data achieved VGPR or less and were thus considered as MRD-positive for intent to treat analyses. Two hundred and eighty-eight pts were included (144 to C-Rd and 144 to Rd). Median age was 76 (range: 65-93), 36.8% of pts had ISS 3 and 15.6% presented with high-risk cytogenetic abnormalities. Key baseline characteristics were well balanced between the two arms. The addition of C to Rd resulted in deeper responses with a ≥ complete response (CR) rate of 20.1% in the C-Rd arm compared to 11.2% in the Rd arm (p = 0.037). Also, the ≥ very good partial response (VGPR) rate was 52.8% in the C-Rd arm as compared to the 37.1% in the Rd arm (p = 0.007). MRD analysis was performed at suspected CR and yearly afterwards. On intent-to-treat, 5/144 (3,5%) and 9/143 (6,2%) of pts achieved undetectable MRD with C-Rd and Rd, respectively (p = 0,7). With a median follow-up of 16 months (range, 1-47), no significant differences were observed in PFS: in the C-Rd arm the median was 23 months and has not been reached in the Rd arm (p = 0.09); furthermore, although disease progression and/or death rate was comparable in both arms (C-Rd: 57/144 [39.6%] vs Rd: 45/144 [31.2%] ), a trend towards shorter PFS was observed in the C-Rd group (Figure 1). This effect was less evident in younger ( & lt;75) pts (median PFS, C-Rd: 24 months vs Rd NR, p = 0,588) but, in older pts (≥ 75), the addition of C to Rd resulted into a significant deleterious effect on PFS (median PFS, C-Rd: 19 vs Rd 28 months, p = 0.03) (Figure 2a and 2b). Irrespectively of treatment arm, pts with MRD negative had significantly longer PFS (NR vs 26 months, p = 0,03). Concerning OS, no differences have been identified (p = 0.41), although median has not been reached yet in any arm. Out of the 33 and 28 deaths documented in the C-Rd and Rd arms respectively, the percentage of pts dying w/o documented PD was significantly higher in the C-Rd group (27/33 [82%] vs 13/27 [48%] , p = 0.004). Furthermore, in the C-Rd arm, the most frequent causes of death were severe infections (14/27 [52%] and cardiovascular events 6/27 [22%] ) the majority of them occurring in older (≥75) pts (20/27, 74%). The most common G3-4 adverse events (AE) in the C-Rd and Rd arms were hematologic (neutropenia: 10,4% vs 16,7% [p = ns] and anemia: 2,1% vs 6,9% [p = 0,04] , respectively). G3-4 infections occurred in 16% of cases in both arms and were the most frequent non-hematological AE. 7% of pts in both arms developed G3-4 GI toxicity and there were no differences between the two arms in G3-4 skin-related AEs (2,8% vs 3,5%). Only one case of invasive SPM (colon cancer) in the C-Rd arm was reported. In conclusion, the addition of C to Rd in transplant ineligible newly diagnosed MM pts significantly increases the rate and depth of responses but it is not associated with an improved PFS and OS due to a higher proportion of deaths in the C-Rd arm, mostly infectious, in pts & gt; 75 years and being early deaths. Overexposure to steroids due to the delayed clearance induced by C in this elderly population could explain our results. Figure Disclosures Puig: The Binding Site: Honoraria; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding. Rosinol Dachs:Janssen, Celgene, Amgen and Takeda: Honoraria. De Arriba:Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Takeda: Honoraria. Oriol:Celgene Corporation: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau; Janssen: Consultancy; Amgen: Consultancy, Speakers Bureau. De La Rubia:AbbVie: Consultancy; AMGEN: Consultancy; Celgene Corporation: Consultancy; Takeda: Consultancy; Janssen: Consultancy. Amor:Celgene: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees. Martín Sánchez:GILEAD SCIENCES: Research Funding. Rossi:BMS: Research Funding; Janssen, Celgene, Amgen: Consultancy. Coleman:Merck: Research Funding; Pharmacyclics: Speakers Bureau; Kite Pharmaceuticals: Equity Ownership; Gilead, Bayer, Celgene: Consultancy, Research Funding, Speakers Bureau. 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. San-Miguel:Amgen, Bristol-Myers Squibb, Celgene, Janssen, MSD, Novartis, Roche, Sanofi, and Takeda: Consultancy, Honoraria. Bladé:Jansen, Celgene, Takeda, Amgen and Oncopeptides: Honoraria. Niesvizky:Takeda, Amgen, BMS, Janssen, Celgene: Consultancy, Research Funding. Mateos:EDO: Membership on an entity's Board of Directors or advisory committees; Pharmamar: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; 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; GSK: Membership on an entity's Board of Directors or advisory committees; Adaptive: Honoraria.

Abstract: Background: Transplant-eligible MM patients are achieving unprecedented CR rates with frontline therapy. This urges the question about what other tests are informative upon a negative immunofixation (IFx-), as well as if patients with short duration CR continue having dismal survival with modern frontline plus salvage therapies and if so, how to predict risk of unsustained CR. Aim: To provide an optimal definition of unsustained CR and biomarkers to predict it in transplant-eligible MM patients treated with optimal therapy. Methods: A total of 262 patients enrolled in the PETHEMA/GEM2012MENOS65 trial and who were in CR after receiving six induction cycles of bortezomib, lenalidomide and dexamethasone (VRD), autologous transplant and two consolidation cycles of VRD, were included in this study. Afterwards, patients were enrolled in the PETHEMA/GEM2014MAIN trial. Median follow-up of the series was 38 months after consolidation (53 months since diagnosis). Serum free light-chains (sFLC) were measured in 252 cases. MRD was assessment with next-generation flow (NGF) in 257 patients (median limit of detection of 2.8x10-6). FISH was performed in CD138-enriched plasma cells (PCs) from 223 patients at diagnosis [high-risk was defined by the presence of t(4;14), t(14;16) and/or del(17p)]. To understand the relationship between duration of CR and outcome, patients were segmented into 6-monht increments (range, 0 - 48 months) in time since response assessment after consolidation and loss of CR. Results: We first investigated what other tests commonly performed upon the achievement of IFx- were informative, particularly those employed to define stringent CR. The median percentage of PCs by morphology, at the time of IFx-, was 1.7% (range 0-5). Only 4 patients out of 266 (1.5%) with a negative immunofixation had & gt;5% BM PCs and therefore, were not classified as in CR. Almost one-fourth of patients in CR display an abnormal sFLC ratio (56/248, 23%), but their PFS was identical to that of cases with normal sFLC ratio (3 years-PFS rates of 70% vs 72%; P=.6). BM biopsies were not performed in this study to evaluate PC clonality by immunohistochemistry but we noted that in CR patients with persistent MRD, the median percentage of clonal and normal PCs among total PCs identified by NGF was of 3% and 97%, respectively. Thus, the median percentage of normal PCs is 24-fold greater than clonal PCs within the PC compartment, and therefore simple κ/λ ratios measured in ≥100 PCs are unable to detect such low-levels of residual disease. Indeed, persistent MRD was detectable by NGF in 73/252 (29%) CR patients at a median level of 0.03% (range 0.0002% - 0.59%), and resulted in significantly inferior PFS (3-year rates of 49% vs 83% in cases with persistent vs undetectable MRD, P & lt; .00001) and OS (3 years-PFS rates of 84% vs 95%; P=.001). Afterwards, we sought to identify the optimal landmark to define unsustained CR and to identify which biomarkers could identify patients at risk. A duration of CR of & lt;24 months emerged as optimal criteria to identify a numerically relevant subset of patients (39/262, 15%) with dismal OS (median of 48 months vs not reached in patients with duration of CR ≥24 months, P & lt; .00001). We then performed a logistic regression to identify biomarkers with independent value to predict unsustained CR. Elevated LDH levels (HR: 2.9 [1.1 - 8.0], P =.038) and & gt;20% PCs (HR: 2.8 [1.2 - 6.7], P =.020) at diagnosis together with persistent MRD (HR: 4.3 [1.9 - 9.6] , P & lt;.001) had independent value to predict unsustained CR in a multivariable analysis. Thus, a scoring system with the three parameters yielded significant stratification of patients in CR into favorable (no risk factors), intermediate (any risk factor) and dismal (all risk factors) PFS (3-year rates of 92%, 67% and 0%, respectively; P & lt;.0001; Figure 1) and OS (3-year rates of 99%, 90% and 83%, respectively; P=.001). Conclusions: This is the first study evaluating which baseline and response assessments are useful to stratify transplant-eligible patients with unsustained CR in the context of modern therapy; a simple model based on LDH levels and PC counts at diagnosis plus MRD status was identified and can be used broadly. These findings are clinically meaningful because patients with unsustained CR remain a high-risk population despite optimal therapy, and those at risk should be offered alternative treatment strategies before insurmountable disease progression occurs. Figure 1 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. Oriol:Amgen: Consultancy, Speakers Bureau; Janssen: Consultancy; Celgene: Consultancy, Speakers Bureau. Sureda Balari:Roche: Honoraria; Celgene: Consultancy, Honoraria; BMS: Speakers Bureau; Incyte: Consultancy; Janssen: Consultancy, Honoraria; Gilead/Kite: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Sanofi: Consultancy, Honoraria; Merck Sharpe and Dohme: Consultancy, Honoraria, Speakers Bureau; Celgene/Bristol-Myers Squibb: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Speakers Bureau. de la Rubia:Janssen: Consultancy, Other: Expert Testimony; Amgen: Consultancy, Other: Expert Testimony; Celgene: Consultancy, Other: Expert Testimony; Ablynx/Sanofi: Consultancy, Other: Expert Testimony. Moraleda:Takeda: Consultancy, Other: Travel Expenses; Sandoz: Consultancy, Other: Travel Expenses; Novartis: Consultancy, Other: Travel Expenses; Gilead: Consultancy, Other: Travel Expenses; Jazz Pharmaceuticals: Consultancy, Research Funding. Mateos:Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Regeneron: Honoraria, Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Honoraria; Seattle Genetics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; 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; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees. San-Miguel:GlaxoSmithKline: Consultancy, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Consultancy, Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; MSD: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: 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; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company); Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sanofi: Consultancy, Membership on an entity's Board of Directors or advisory committees.