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Monitoring of the monoclonal protein (M-protein) by electrophoresis and/or immunofixation (IFE) has long been used to assess treatment response in multiple myeloma (MM). However, with the use of highly effective therapies, the M-protein becomes frequently undetectable, and more sensitive methods had to be explored. We applied IFE and mass spectrometry (EXENT&FLC-MS) in serum samples from newly diagnosed MM patients enrolled in the PETHEMA/GEM2012MENOS65 obtained at baseline (n = 223), and after induction (n = 183), autologous stem cell transplantation (n = 173), and consolidation (n = 173). At baseline, the isotypes identified with both methods fully matched in 82.1% of samples; in the rest but 2 cases, EXENT&FLC-MS provided additional information to IFE with regards to the M-protein(s). Overall, the results of EXENT&FLC-MS and IFE were concordant in >80% of cases, being most discordances due to EXENT&FLC-MS+ but IFE− cases. After consolidation, IFE was not able to discriminate 2 cohorts with different median progression-free survival (PFS), but EXENT&FLC-MS did so; furthermore, among IFE− patients, EXENT&FLC-MS identified 2 groups with significantly different median PFS (P = .0008). In conclusion, compared with IFE, EXENT&FLC-MS is more sensitive to detect the M-protein of patients with MM, both at baseline and during treatment, and provides a more accurate prediction of patients’ outcome. This trial was registered at www.clinicaltrials.gov as #NCT01916252., This study was supported by grants from the Centro de Investigacion Biomédica en Red–Area de Oncología–del Instituto de Salud Carlos III CIBERONC, CB16/12/00369, CB16/12/00400, CB16/12/00233, and CB16/12/00284, Instituto de Salud Carlos III/Subdireccion General de Investigaci on Sanitaria FIS no. PI15/ 01956, PI15/02049, PI15/02062, PI18/01709, PI18/01673, and PI19/01451, the Cancer Research UK, FCAECC, and AIRC under the Accelerator Award Program (EDITOR).

Background: Evaluation of MRD is standard in patients with AML. However, the role of decentralized MRD assessment for risk stratification in AML remains largely unknown, and so it does which methodological aspects are critical to empower the evaluation of MRD with prognostic significance, particularly if using MFC. Aim: To evaluate the role of decentralized MRD assessment using MFC for risk stratification and putative treatment individualization of patients with AML. Methods: This study was performed on 1,076 AML patients in complete remission (CR) after 7+3 induction chemotherapy, in whom MRD was evaluated by MFC in local laboratories over a period of 20 years in the PETHEMA group. We conducted a survey of technical aspects of MFC based MRD testing in the laboratories of the 60 participating Hospitals, to determine the impact of methodological heterogeneity in the prognostic value of MFC. Results: We first investigated the most effective MRD cutoff to stratify patients' risk at first remission. Patients were segmented into progressively higher cutoffs, starting at 0.01% followed by 0.05%, 0.1%, 0.5% and 1%. Our results showed that 0.1% reached higher statistical significance to discriminate patients with different relapse-free survival (RFS, HR: 0.77; P = .001) and overall survival (OS, HR: 0.73; P = .001). In multivariate analyses together with patients' age, WBC, genetic risk and post-consolidation therapy, MRD status was selected as an independent prognostic factor for OS. To further define the utility of "real-world" MRD assessment using MFC in risk stratification of AML, recursive partitioning was performed using the prognostic and treatment related factors selected in the multivariate Cox model for OS. Of the four variables evaluated, hematopoietic stem cell transplantation (HSCT, regardless of autologous or allogeneic source) vs no transplant emerged as the best single discriminator for OS, followed by genetic risk, age and MRD status. There were two branching points defined by MRD status; the first in patients ≤60 years with intermediate genetic risk who were not transplanted and the second in patients with adverse genetics who were not transplanted, in whom Forty-nine of the 60 hospitals (82%) responded to the survey on questions regarding the measurement of MRD using MFC in the PETHEMA LMA 1999, 2007 and 2010 protocols, providing information corresponding to 966 of the 1,076 (90%) patients regarding the number of markers, preparation of samples, instruments, approach (ie, LAIP, DfN or LAIP+DfN), number of cells to define a cluster, etc. The survey revealed significant heterogeneity intra- and inter-protocols that reflected improvement in MFC assessment of MRD over time, in the absence of harmonization nor standardization at the national level. Accordingly, we investigated if the heterogeneity in methodological, interpretation and reporting aspects of MFC based MRD testing were hampering its ability to predict outcome independently of other patient and treatment related factors. Strikingly, our results showed that except for the denominator used to calculate MRD burden (ie, total nucleated cells vs leukocytes), lack of standardization in all other parameters had an impact on the ability of MFC to predict outcomes in AML (Figure). Namely, panels with ≤4 markers or ≤2 combinations failed to identify patients with significantly different RFS according to MRD status, and MFC-based MRD monitoring was prognostic only when >500,000 cells were measured. Only MRD assessment using patient-specific panels was predictive of outcome. Conclusions: We report here one of the largest studies investigating the role of MRD monitoring using MFC. Our results confirmed that detection of MRD identifies patients in CR/CRi with inferior survival, but uncovered that decentralized MRD testing lacks significance when compared to other baseline risk factors and in the context of risk-adapted post-consolidation strategies. Thus, while this study demonstrated that "real-world" decentralized assessment of MRD using MFC does provide prognostic information in AML patients at first remission, our results question its readiness for risk stratification towards clinical decisions outside trials, at least until adequate standardization of this technique is achieved. Figure Disclosures Paiva: SkylineDx: Consultancy; Takeda: Consultancy, Honoraria, Research Funding; Roche: Research Funding; Adaptive: Honoraria; Amgen: Honoraria; Janssen: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Kite: Consultancy; Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau; Sanofi: Consultancy, Honoraria, Research Funding. Alonso Dominguez:Celgene: Research Funding; Incyte: Research Funding; Pfizer: Research Funding. Martinez-Lopez:Janssen: Speakers Bureau; Altum: Membership on an entity's Board of Directors or advisory committees, Patents & Royalties; Hosea: Membership on an entity's Board of Directors or advisory committees, Patents & Royalties; Roche: Speakers Bureau; Amgen: Speakers Bureau; Takeda: Speakers Bureau; Vivia Biotech: Honoraria; Novartis: Research Funding; BMS: Research Funding, Speakers Bureau; Incyte: Research Funding, Speakers Bureau. Sossa:Astellas: Honoraria; Roche: Honoraria; Takeda: Honoraria; Novo: Honoraria. San-Miguel:Roche, AbbVie, GlaxoSmithKline, and Karyopharm: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb, Celgene, Novartis, Takeda, Amgen, MSD, Janssen, and Sanofi: Consultancy, Membership on an entity's Board of Directors or advisory committees.

The value of minimal residual disease (MRD) status by bone marrow and imaging analysis as independent prognostic factors has been well established in multiple myeloma (MM). Nevertheless data about their potential complementarity for a more accurate assessment are limited. With this aim, we retrospectively analyzed the prediction of outcome with the combination of PET-CT and MRD, assessed by multiparameter flow cytometry (MFC) in 103 patients with newly diagnosed MM. We confirmed the benefit in terms of progression-free survival (PFS), linked to the achievement of negativity by MFC (hazard ratio [HR] 0.53; 95% confidence interval [CI]: 0.28-0.98), and PET-CT (HR 0.18; 95% CI: 0.09-0.36) individually. By combining both techniques, patients who became MRD-/PET-, with a median of PFS 92 months, had significant prolonged median PFS (P < .001). This is compared with MRD+/PET- and PET+ patients (median PFS of 45 and 28 months, respectively). We observed a significant difference (P = .003) in overall survival (OS) outcomes between MRD-/PET- and MRD+/PET- patients (4-year OS 94.2% and 100%, respectively), vs PET+ patients (4-year OS 73.8%). All survival results were confirmed in a conditional landmark analysis. These findings support the potential complementarity between PET-CT and MFC, and highlight their better predictive capability when improving sensitivity.

The assessment of measurable residual disease (MRD) in bone marrow has proven of prognostic relevance in patients with multiple myeloma (MM). Nevertheless, and unlike other hematologic malignancies, the use of MRD results to make clinical decisions in MM has been underexplored to date. In this retrospective study, we present the results from a multinational and multicenter series of 400 patients with MRD monitoring during front-line therapy with the aim of exploring how clinical decisions made based on those MRD results affected outcomes. As expected, achievement of MRD negativity at any point was associated with improved PFS versus persistent MRD positivity (median PFS 104 vs. 45 months, p p = 0.005). In patients who achieved MRD negativity during maintenance (n = 186) on at least one occasion, stopping therapy in 24 patients vs. continuing in 162 did not alter PFS (mPFS 120 months vs. 82 months, p = 0.1). Most importantly, however, in patients with a positive MRD during maintenance (n = 214), a clinical decision (either intensification or change of therapy) (n = 43) resulted in better PFS compared to patients in whom no adjustment was made (n = 171) (mPFS NA vs. 39 months, p = 0.02). Interestingly, there were no significant differences when MRD was assessed by flow cytometry or by next-generation sequencing. Herein, we find that MRD is useful in guiding clinical decisions during initial therapy and has a positive impact on PFS in MM patients. This potentially opens a new dimension for the use of MRD in MM, but this role still remains to be confirmed in prospective, randomized clinical trials.

Simple Summary Multiple myeloma represents the cancer with the 21st highest global incidence. The rapid acquisition of drug resistance to proteasome inhibitors requires a deep knowledge on the mechanisms involved in proliferation in order to provide novel targets for the disease. The aim of our study was to characterize the mitochondrial activity in primary multiple myeloma (MM) cells along the course of the disease and to provide a therapeutic alternative to inhibit Myc function by blocking OXPHOS metabolism. We confirmed MM patients show enhanced mitochondrial activity linked to c-Myc expression. The use of tigecycline provides evidence for a novel strategy addressing c-Myc functionality by mitochondrial activity inhibition. Abstract Mitochondria are involved in the development and acquisition of a malignant phenotype in hematological cancers. Recently, their role in the pathogenesis of multiple myeloma (MM) has been suggested to be therapeutically explored. MYC is a master regulator of b-cell malignancies such as multiple myeloma, and its activation is known to deregulate mitochondrial function. We investigated the impact of mitochondrial activity on the distinct entities of the disease and tested the efficacy of the mitochondrial inhibitor, tigecycline, to overcome MM proliferation. COXII expression, COX activity, mitochondrial mass, and mitochondrial membrane potential demonstrated a progressive increase of mitochondrial features as the disease progresses. In vitro and in vivo therapeutic targeting using the mitochondrial inhibitor tigecycline showed promising efficacy and cytotoxicity in monotherapy and combination with the MM frontline treatment bortezomib. Overall, our findings demonstrate how mitochondrial activity emerges in MM transformation and disease progression and the efficacy of therapies targeting these novel vulnerabilities.

Although light-chain amyloidosis (AL) and multiple myeloma (MM) are characterized by tumor plasma cell (PC) expansion in bone marrow (BM), their clinical presentation differs. Previous attempts to identify unique pathogenic mechanisms behind such differences were unsuccessful, and no studies have investigated the differentiation stage of tumor PCs in patients with AL and MM. We sought to define a transcriptional atlas of normal PC development in secondary lymphoid organs (SLOs), peripheral blood (PB), and BM for comparison with the transcriptional programs (TPs) of tumor PCs in AL, MM, and monoclonal gammopathy of undetermined significance (MGUS). Based on bulk and single-cell RNA sequencing, we observed 13 TPs during transition of normal PCs throughout SLOs, PB, and BM. We further noted the following: CD39 outperforms CD19 to discriminate newborn from long-lived BM-PCs; tumor PCs expressed the most advantageous TPs of normal PC differentiation; AL shares greater similarity to SLO-PCs whereas MM is transcriptionally closer to PB-PCs and newborn BM-PCs; patients with AL and MM enriched in immature TPs had inferior survival; and protein N-linked glycosylation–related TPs are upregulated in AL. Collectively, we provide a novel resource to understand normal PC development and the transcriptional reorganization of AL and other monoclonal gammopathies.

INTRODUCTION: There is expectation of using biomarkers to personalize treatment in MM. Yet, a successful treatment selection cannot be confirmed before 5 or 10 years of progression-free survival (PFS). Treatment individualization based on the probability of an individual patient to achieve undetectable MRD with a singular regimen, could represent a new model towards personalized treatment with fast assessment of its success. This idea has not been investigated previously. AIM: Develop a machine learning model to predict undetectable MRD in newly-diagnosed transplant-eligible MM patients, treated with a standard of care. METHODS: This study included a total of 278 newly-diagnosed and transplant-eligible MM patients treated with proteasome inhibitors, immunomodulatory drugs and corticosteroids. The training (n=152) and internal validation cohort (n=60) consisted of 212 active MM patients enrolled in the GEM2012MENOS65 trial. The external validation cohort was defined by 66 high-risk smoldering MM patients enrolled in the GEM-CESAR trial, which treatment differed only by the substitution of bortezomib by carfilzomib during induction and consolidation. RESULTS: We started by investigating patients' MRD status after VRD induction, HDT/ASCT and VRD consolidation according to their ISS and R-ISS, LDH levels, and cytogenetic alterations. Surprisingly, neither the ISS nor the R-ISS predicted significantly different MRD outcomes. Indeed, high LDH levels and del(17p13) were the only parameters associated with lower rates of undetectable MRD. Because these two features are relatively infrequent at diagnosis, we next aimed to evaluate other disease features and develop integrative, weighted and more effective models based on machine learning algorithms. Of 37 clinical and biological parameters evaluated, 17 were associated with MRD outcomes. These were subsequently modeled using logistic regression for machine learning classification, where the sum of the weighted coefficients multiplied by its input variable, is transformed into a probability outcome that ranges from 0 to 1 using a logit sigmoid function. The most effective model resulted from integrating cytogenetic [t(4;14) and/or del(17p13)], tumor burden (plasma cell [PC] clonality in bone marrow and CTCs in blood) and immune related (myeloid precursors, mature B cells, intermediate neutrophils, eosinophils, CD27 negCD38 pos T cells and CD56 brightCD27 neg NK cells) biomarkers. Of note, immune biomarkers displayed the highest coefficient weights and were determinant to predict patients' MRD status in this model. Data obtained for an individual patient can be substituted into our formula, which results in a numerical probability of achieving undetectable (>0.5) vs persistent (0.685 or Patients predicted to achieve undetectable MRD using standard and high-confidence values showed longer PFS and overall survival (OS) than those with probability of persistent MRD. In fact, patients with >0.687 probability of achieving undetectable MRD showed 86% PFS and 94% OS at five years, whereas those in whom persistent MRD was predicted ( CONCLUSION: We demonstrated that it is possible to predict patients' MRD status with significant accuracy, using an integrative, weighted model based on machine learning algorithms. Although immune biomarkers are not commonly used, the raw data from which these can be developed is generally obtained in diagnostic laboratories using flow cytometry to screen for PC clonality. Furthermore, we made the model available to facilitate its use in clinical practice at www.MRDpredictor.com. Disclosures Puig: Celgene, Janssen, Amgen, Takeda: Research Funding; Celgene: Speakers Bureau; Amgen, Celgene, Janssen, Takeda: Consultancy; Amgen, Celgene, Janssen, Takeda and The Binding Site: Honoraria. Cedena: Janssen, Celgene and Abbvie: Honoraria. Oriol: Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; 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; 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. De Arriba: Amgen: Consultancy, Honoraria; Glaxo Smith Kline: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Speakers Bureau; BMS-Celgene: Consultancy, Honoraria, Speakers Bureau. Martínez-López: Janssen, BMS, Novartis, Incyte, Roche, GSK, Pfizer: Consultancy; Roche, Novartis, Incyte, Astellas, BMS: Research Funding. Lahuerta: Celgene: Other: Travel accomodations and expenses; Celgene, Takeda, Amgen, Janssen and Sanofi: Consultancy. Rosinol: Janssen, Celgene, Amgen and Takeda: Honoraria. Bladé Creixenti: Janssen, Celgene, Takeda, Amgen and Oncopeptides: Honoraria. Mateos: Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria; Bluebird bio: Honoraria; GSK: Honoraria; 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; Sea-Gen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies: 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; Oncopeptides: 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; Oncopeptides: Honoraria; Janssen: 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. San-Miguel: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, GlaxoSmithKline, Janssen, Karyopharm, Merck Sharpe & Dohme, Novartis, Regeneron, Roche, Sanofi, SecuraBio, and Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees. Paiva: Bristol-Myers Squibb-Celgene, Janssen, and Sanofi: Consultancy; Adaptive, Amgen, Bristol-Myers Squibb-Celgene, Janssen, Kite Pharma, Sanofi and Takeda: Honoraria; Celgene, EngMab, Roche, Sanofi, Takeda: Research Funding.

Introduction : 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 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 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 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.

Introduction. The boundaries between MDS and AML are still a matter of debate. In the 2001 WHO Classification, the myeloblast count distinguishing AML and MDS was lowered from 30% to 20% of the bone marrow (BM) cells or peripheral blood (PB) leukocytes. It was justified on the basis that treating patients with 20-29% BM blasts with intensive chemotherapy showed a similar outcome to those with > 30% BM blasts. However, the better knowledge of the biology of both diseases is showing that in several cases AML and high risk MDS share identical genetic profiles, as it is well known in AML with myelodysplasia- related changes (AML-MRC). Currently there are new therapeutic options, less toxic, and suitable for elderly people.The threshold of 20% BM blast is artificial, but it is still the main criterion used in clinical trials and also in real life to discriminate patients that probably belong to the spectrum of the same biological entity. Treatment of patients with MDS or AML is widely based in this relatively arbitrary condition. Objective: To study if the threshold of 20% bone marrow blasts, distinguishing MDS with excess of blasts type 2 (MDS EB 2) and AML, is reproducible among different observers. Methods. 120 bone marrow samples from patients previously diagnosed with MDS-EB-2, AML or therapy-related myeloid neoplasms (t-MN) according to 2016 WHO classification were included. The diagnosis of MDS required cytogenetics and/or FISH, and the cases with AML should have been classified following the 2017 ELN recommendations, regarding immunophenotyping, cytogenetics and molecular biology. The design of the study was established to include cases with Results. Finally 116/120 samples were considered suitable for the study. Regarding 2016 WHO categories, 55 cases showed MDS EB-2, 44 AML-MRC, 8 t-MN, 4 AML- NOS, 2 NPM1-mutated AML, 2 RUNX1-RUNX1T1 AML, 1 BCR-ABL1+ AML. Next generation sequencing was performed in 79 cases. Discordance was observed in 34/116 cases (29.3%). 14 cases with MDS-EB2 (1 NPM1+) were classified as AML-MRC by the second observer, 16 AML cases as MDS EB-2, 3 MDS EB-2 as MDS- EB1 and 1 AML as MDS- EB1. The genetic and /or molecular profile of the discordant cases was heterogeneous. Regarding the threshold of 20% BM blasts, discrepancies were 31/116 (26.7%, I Kappa test = 0.46, moderate agreement). The agreement between MDS-EB-2 and AML-MRC, with discordance in 28/98 cases (28.6%), was moderate-fair (Kappa test= 0.42). Conclusion. The threshold of 20% BM blasts did not accurately separate AML from MDS EB-2. Particularly less concordance was seen for AML-MRC. Incorporation of genetic and molecular characteristics to the morphologic diagnosis is needed to optimize the definition of both entities. Acknowledgment: Angel Cedillo, Secretaría Técnica AMHH. Disclosures Font Lopez: GILEAD: Membership on an entity's Board of Directors or advisory committees; CELGENE-BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees. Loscertales: Janssen, Abbvie, Astra-Zeneca, Beigene, Roche, Gilead: Consultancy; Janssen, Abbvie, Roche, Gilead: Speakers Bureau. Cedena: Janssen, Celgene and Abbvie: Honoraria.

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

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

Introduction: SMM is an asymptomatic plasma cell disorder with heterogeneous clinical behavior. Both the Spanish Myeloma and ECOG Groups have demonstrated that patients (pts) at high risk of progression to active MM have prolonged time-to progression upon receiving early treatment with R-based regimens. Our next step was to perform a phase 2, single arm trial, focusing on the same population, but aiming at abrogating the risk of progression through the achievement of sustained minimal residual disease negativity (MRD-ve) at 3 and 5 years after HDT-ASCT. Patients and methods: Ninety SMM pts at high-risk of progression (>50% at 2 yrs), younger than 70 years and transplant candidates were included. The high risk was defined by the presence of both ≥PC 10% and MC ≥3g/dL (Mayo criteria) or ifonly one criterion was present, pts should have >95%of aberrant PCs within the total PCsBM compartment by immunophenotyping plus immunoparesis (Spanish criteria). Induction therapy consisted of six 4-weeks cycles of KRd in which K was given at dose of 36 mg/m 2 twice per week plus R at dose of 25 mg on days 1-21 and dexamethasone at dose of 40 mg weekly. Melphalan at dose of 200 mg/m 2 followed by ASCT was given as intensification therapy followed by two KRd consolidation cycles and maintenance with R at dose of 10 mg plus dexamethasone at dose of 20 mg weekly for up to 2 yrs. The primary end-point was to evaluate the MRD-ve rate by next generation flow (NGF) after ASCT and MRD-ve rate maintained at 3 and 5 years after ASCT. Results: Between June 2015 and June 2017, 90 high-risk SMM pts were recruited and 70 pts (78%) have completed the treatment protocol. The reasons for early discontinuations were: IC withdrawal (4 pts), adverse events (8 pts) or biological progression (BP), either biochemical or because of MRD conversion from negative to positive (1 pt during induction and 7 pts during maintenance). Thirty-one pts (34%) shared at least one of the biomarkers considered as myeloma defining events that currently reclassify SMM into active MM. In the intent-to-treat (ITT) pts' population, after induction, the ≥CR rate was 41% and increased to 65% after HDT-ASCT and 72% after consolidation. During maintenance therapy, 7 pts experienced biological progression (2 pts conversion from MRD-ve into +ve and 5 pts biochemical progression) and the ≥CR rate at the end of treatment was 63.3%. In the ITT population, MRD-ve rates at 10 -5 were observed in 40% of pts after induction, 63% after HDT-ASCT, 68% after consolidation and 52% after maintenance therapy. Among MRD-ve patients after maintenance therapy that had MRD assessed one year after, 67% showed sustained MRD-ve. After a median f/u of 55 months (range: 6.2-71), only three patients progressed to symptomatic disease and the three had at baseline anyone of the biomarkers defining myeloma-defining events. At 5 years, 94% of pts remain alive and progression-free and 95% of pts alive (Figure 1). Overall, twenty-six pts (29%) have experienced biological progression (19 of them were conversion of MRD-ve into +ve), 8 of them during treatment phase (1 during induction and 7 during maintenance) and 16 pts during the follow-up period. The only factors predicting biological progression was failure to achieve MRD-ve at the end of treatment and unsustained MRD-ve at 1 year after finalizing maintenance. Concerning toxicity, during induction, G3-4 neutropenia and thrombocytopenia were reported in 5 (6%) and 10 pts (11%), respectively. G3-4 infections were reported in 16 pts (18%), followed by skin rash in 8 pts (9%). One patient reported G1 atrial fibrillation and another cardiac failure secondary to respiratory infection. Three pts reported hypertension (G2 in two and G3 in one). In all but two of the pts, PBSC collection was successful with a median of 4.10 x 10 6/Kg CD34 cells collected. All pts engrafted but one patient developed late graft failure. During consolidation, 2 pts developed G3-4 neutropenia, 3 pts G3-4 infections and 1 pt skin rash. Seven pts had to discontinue maintenance therapy due to: G3-4 hematological toxicity (4 pts), SPM (2pts) and cardiac arrest (1pt). One additional patient withdrew the IC. Conclusions: These results suggest that early treatment with intention to abrogate risk of progression in transplant candidate high risk SMM patients is associated with a 94% PFS at 55 months and a sustained MRD negative rate at 1 year post treatment of 67%. Figure 1 Figure 1. Disclosures Mateos: Sea-Gen: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria; Regeneron: 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; Roche: 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; Adaptive Biotechnologies: 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; Pfizer: 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; Bluebird bio: Honoraria; Celgene - Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Honoraria; Oncopeptides: Honoraria. Rodríguez-Otero: Celgene-BMS, Janssen, Amgen, Sanofi, GSK, Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees; Regeneron: Honoraria. Gonzalez-Calle: BMS, Janssen, Amgen: Honoraria. Oriol: Celgene: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau; Janssen: Consultancy; Amgen: Consultancy, Speakers Bureau. Rosinol: Janssen, Celgene, Amgen and Takeda: Honoraria. de la Rubia: Takeda: Consultancy; Amgen, Bristol Myers Squibb,: Honoraria, Speakers Bureau; GSK: Consultancy; Celgene, Takeda, Janssen, Sanofi: Honoraria; Ablynx/Sanofi: Consultancy; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel Accommodations; Celgene: Consultancy; AbbVie: Consultancy; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: TRAVEL, ACCOMMODATIONS, EXPENSES; Sanofi: Membership on an entity's Board of Directors or advisory committees. De Arriba: Amgen: Consultancy, Honoraria; Glaxo Smith Kline: Consultancy, Honoraria; BMS-Celgene: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau. Ocio: MSD: Honoraria; Sanofi: Consultancy, Honoraria; Karyopharm: Consultancy; Takeda: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Bristol-Myers Squibb/Celgene: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Oncopeptides: Consultancy, Honoraria; Pfizer: Consultancy; Secura-Bio: Consultancy. 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. Puig: Celgene, Janssen, Amgen, Takeda: Research Funding; Celgene: Speakers Bureau; Amgen, Celgene, Janssen, Takeda: Consultancy; Amgen, Celgene, Janssen, Takeda and The Binding Site: Honoraria. Cedena: Janssen, Celgene and Abbvie: Honoraria. Lahuerta: Celgene: Other: Travel accomodations and expenses; Celgene, Takeda, Amgen, Janssen and Sanofi: Consultancy. San-Miguel: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, GlaxoSmithKline, Janssen, Karyopharm, Merck Sharpe & Dohme, Novartis, Regeneron, Roche, Sanofi, SecuraBio, Takeda: Consultancy, Other: Advisory board.

Background There is expectation of using biomarkers to personalize treatment. Yet, a successful treatment selection cannot be confirmed before 5 or 10 years of progression-free survival (PFS). Treatment individualization based on the probability of an individual patient to achieve undetectable MRD with a singular regimen, could represent a new model towards personalized treatment with fast assessment of its success. This idea has not been investigated previously. Methods We sought to define a machine learning model to predict undetectable MRD in newly-diagnosed transplant-eligible MM patients (n=278). The training (n=152) and internal validation cohort (n=60) consisted of 212 active MM patients enrolled in the GEM2012MENOS65 clinical trial. The external validation cohort was defined by 66 high-risk smoldering MM patients enrolled in the GEM-CESAR clinical trial, which treatment differed only by the substitution of bortezomib by carfilzomib during induction and consolidation. Patients were included in the study based on data availability of 17 parameters (p≤.05) associated with MRD outcomes. Results We started by investigating patients’ MRD status after VRD induction, HDT/ASCT and VRD consolidation (GEM2012MENOS65) according to their ISS and Revised-ISS, LDH levels, and cytogenetic alterations. High LDH levels and del(17p13), two features relatively infrequent at diagnosis, were the only parameters associated with lower rates of undetectable MRD. The ISS and R-ISS were not predictive. Therefore, we aimed to evaluate other disease features associated with MRD outcomes and develop more effective models based on machine learning logistic regression. The most effective one resulted from integrating cytogenetic [t(4;14) and/or del(17p13)], tumor burden (plasma cell clonality in bone marrow and circulating tumor cells in peripheral blood) and immune related (myeloid precursors, mature B cells, intermediate neutrophils, eosinophils, CD27negCD38pos T cells and CD56brightCD27neg NK cells) biomarkers. Data obtained for an individual patient can be substituted into our formula, which results in a numerical probability of achieving undetectable (>0.5) vs persistent (0.685 or Conclusions We demonstrated that selecting a regimen based on probable MRD outcomes, and confirming soon after if that probability was accurate, is a possible new approach towards individualized treatment in MM. The model is available at www.MRDpredictor.com to facilitate its use in clinical practice.

Introduction: Myeloid malignancies are clonal disorders of hematopoietic stem cells and include acute myeloid leukemia (AML), myelodysplastic syndrome (MDS) and myeloproliferative neoplasm (MPN). Common biological markers have been described in the molecular pathogenesis, including gene mutations in splicing factors, epigenetic modifiers, transcription factors, signal pathways and tumor suppressors. These mechanisms have been associated with MDS and MPN progression to AML. Objectives: The main objective of this study is to identify differences in the mutational landscape of myeloid malignancies and describe mutation frequencies of genes and functional pathways in each neoplasm, as well as determine their clinical impact. Methods: This study involved a retrospective analysis of 430 patients with AML (209), MDS (106) and Philadelphia negative MPN (86) diagnosed in the Hospital Universitario 12 de Octubre (Spain). They were analyzed by a next generation sequencing (NGS)- panel for myeloid malignancies. The panel include 32 genes: CALR, ASXL1, EZH2, PHF6, DNMT3A 2, TET2, IDH1, IDH2, KDM6A, KMT2A, SF1, SF3A1, SF3B1, SRSF2, U2AF1, ZRSR2, PRPF40B, EPOR, FLT3, JAK2, KIT, SH2B3, MPL, CBL, HRAS, NRAS, KRAS, ETV6, RUNX1, VHL, TP53, PTEN. In addition, there were included 29 patients diagnosed with benign pathology that were referred to rule out MPN or congenital polyglobulia. Results: In the analyzed cohort we obtained a larger number of mutations in the more aggressive malignancies, AML and MDS. Mutations in epigenetic modifiers and signal pathways were the most frequent detected (31% and 24% respectively). The epigenetic modifiers were notably affected in AML (78%) and MDS (60.4%), whereas signal pathways were mutated more frequently in MPN (70.9%). Transcription factors, tumor suppressors and splicing factors mutations were more detected in AML and MDS (40%, 32%, 44% and 22%, 13%, 32% respectively). The mutation landscape obtained by genes was: Signal pathways: FLT3, NRAS, KIT, KRAS y SH2B3 were specially detected in AML (25%, 11%, 6%, 5% and 4% respectively). JAK2, CALR and MPL in MPN (38%, 15% and 6% respectively). Transcription factors: RUNX1, ETV6, PHF6, CEBPA and WT1 mutations were regularly observed in AML (21%, 6%, 6%, 6% and 5% respectively), and GATA1 in SMD (3.8%). Tumor suppressors: TP53 was particularly affected in AML (21%) and MDS (11%). Epigenetic modifiers: TET2 was notably mutated in MDS (32%), whereas ASXL1, DNMT3A, IDH2, IDH1 and EZH2 were in AML (21%, 21%, 17% 16% and 8% respectively). Splicing factors: SF3B1 was more frequently detected in MDS (18%) than AML (7%), whereas ZRSR2 presented a similar frequency in both pathologies (around 8%). U2AF1 was most commonly mutated in MPN (9%). SRSF2 was specially mutated in AML (23%). SF3A1 was altered in around 1%, similar in all three malignancies. With regard to survival studies, the presence of mutations in splicing factors (primarily in U2AF1) and its absence in signal pathways conferred an adverse outcome for overall survival (OS) in MPN. In MDS, gene mutations in tumor suppressors (especially TP53), U2AF1 splicing factor and EZH2 epigenetic modifier were associated with poor outcome. In our series of AML, gene mutations in tumor suppressors and TP53 were related to unfavorable prognosis in OS. Conclusion: The largest number of mutations and affected genes observed in AML suggest that leukemic transformation of MDS and MPN is conditioned by acquisition of new mutations. We observed different frequencies of mutations between AML, MDS and MPN that could guide the diagnostic and identify new targets of treatment. Further, some mutations have demonstrated differential prognostic impact. An extension of this study and the design of an algorithm with mutation data to elucidate a more accurate molecular prognosis will be presented at the meeting. This work has been financed thanks to the grant PI16/01225, PI 19/01518 and PI19/00730 from the Instituto de Salud Carlos III (Ministerio de Economia, Industria y Competititvidad) and cofinanced by the European Development Fund. Figure 1. Mutations detected (%) in AML, MDS and MPN classified by function. Table 1. Median overall survival of patients with MPN, MDS and AML according to gene state (mutated or not). Figure Disclosures No relevant conflicts of interest to declare.

Background: Previous studies showed that MRD- pts after transplant may have detectable monoclonal protein through IFx, creating confusion regarding their prognostication. That said, MRD assessment in these pts was not performed with next generation techniques nor or in later time points. Additional discordances have been identified between multiparameter flow cytometry (MFC) and NGS, which were confirmed in recent analyses comparing NGF vs NGS. Aim: To characterize discordances between flow cytometry vs NGS and IFx through the investigation of immature B cells sharing the same B-cell receptor immunoglobulin (BcR IG) with MM cells. Methods: Progression-free survival (PFS) according to negative vs positive IFx was analyzed in 219 MRD- pts by MFC after transplant, enrolled in the GEM2000 and GEM2005MENOS65 trials. The same comparison was performed in 205 MRD- pts by NGF after consolidation in the GEM2012MENOS65 trial. MRD detection by NGS was compared to MFC or NGF in 140 and 104 cases, respectively. We performed NGS of BcR IG gene rearrangements (mean: 69,975 sequences) and WES (mean depth: 145x) in a total of 68 B cell samples isolated from the bone marrow (BM) of 7 MM MRD- pts by NGF after treatment (GEM2012MENOS65). These were intentionally selected to avoid contamination from MM plasma cells (PCs) during sorting of CD34 progenitors, B cell precursors, mature B cells and normal PCs. We investigated these populations for the presence of clonotypic BcR IG and somatic mutations detected in MM PCs sorted at diagnosis, using T cells as germline control. In another 10 untreated MM pts, we performed scRNA/BcRseq of total BM B cells and PCs (n=52,735), to investigate if the clonotypic BcR IG of MM PCs was detectable in other B cell stages defined by their molecular phenotype. Results: Among 219 MRD- pts by 4 color MFC after transplant, 76 (35%) showed positive IFx and identical PFS to those with negative IFx (medians of 63 vs 66 months, p=0.96). Similarly, 23/205 (11%) MRD- pts by NGF after consolidation showed positive IFx and identical PFS to those with negative IFx (4y rates of 87% vs 78.5%, p=0.35). Thus, albeit the higher sensitivity of NGF and the later time point (consolidation), approximately 1/10 MRD- pts by NGF continued showing positive IFx, and their outcome was as favorable as that of MRD- cases in CR. We then investigated discordances between flow cytometry and NGS. Among 35 MRD- pts by 4 color MFC, 21 (60%) were MRD+ by NGS, whereas 8/44 (18%) MRD- cases by NGF were MRD+ by NGS; only one of the latter 8 pts relapsed so far. Noteworthy, 9/29 MRD- pts by MFC or NGF showed MRD levels ≥10-4 by NGS, suggesting that other factors beyond sensitivity were accounting for the discordances between MRD assessed by MFC/NGF (in the PC compartment) vs NGS (in whole BM samples). NGS of BcR IG gene rearrangements in sorted BM cells from MRD- pts by NGF, uncovered the presence of MM clonotypes in normal PCs (4/7 pts) and in B cells (5/7 pts) at low frequencies (mean of 0.31% in both, range: 0.003% - 9.4%). These findings were confirmed by scRNA/BCRseq, which unveiled in 10/10 pts that clonotypic cells were confined mostly but not entirely within PC clusters. We next performed WES to investigate if genetic abnormalities present in MM PCs at diagnosis were detectable in the same BM cells sorted after treatment in MRD- pts. Surprisingly, 41/201 (20%) somatic mutations present in diagnostic MM PCs were detectable in CD34 progenitors (n=6/7), B-cell precursors (n=4/7), mature B cells (n=5/7) and phenotypically normal PCs (n=4/7). All somatic mutations shared by MM PCs and sorted BM normal cells were non-recurrent, and genes recurrently mutated in MM (ATM, DIS3, KRAS, LTB, MAX,) as well as copy number alterations (CNA) found in MM PCs, were undetectable in normal cells. Conclusions: Albeit more-sensitive NGF, 11% of MRD- pts continue showing positive IFx. This should not be regarded as a false-negative result, since these pts have similar outcome to those in CR and MRD-. Our findings also suggest that, at least in some pts, discordances between NGF and NGS could be attributed to immature clonotypic cells. However, these lack most somatic mutations and CNA found in MM PCs, and therefore cannot drive disease relapse. This would explain the favorable outcome of MRD- pts by NGF despite positive NGS. From a pathogenic standpoint, our study proposes that a mutated and clonally expanded lymphopoiesis precedes secondary driver mutations or CNA leading to the expansion of MM PCs. Disclosures García-Sanz: Janssen: Honoraria, Other: Travel/accommodations/expenses; Novartis: Consultancy; Amgen: Honoraria; Gilead: Other: Research grants, Research Funding; IVS (Biomed 2-Euroclonality): Patents & Royalties: and other intellectual property; Takeda: Consultancy, Honoraria, Other: Travel/accommodations/expenses. Mateos: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; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: 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; Regeneron: 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; Adaptive: 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; AbbVie: 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; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Honoraria. Chatzidimitriou:Janssen: Research Funding. San-Miguel: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; Amgen: 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; Takeda: 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; Karyopharm: Consultancy, Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: 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; Roche: 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; MSD: Consultancy, Membership on an entity's Board of Directors or advisory committees. Paiva:Amgen: Honoraria; Janssen: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Kite: Consultancy; SkylineDx: Consultancy; Takeda: Consultancy, Honoraria, Research Funding; Roche: Research Funding; Adaptive: Honoraria; Sanofi: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau.

Altres ajuts: This work was supported by a grant from the Spanish Group of MDS (GESMD, 2017). LP, FF, PA and FS research is supported by a grant from (GRC) Generalitat de Catalunya, economical support from CERCA Programme/Generalitat de Catalunya, Fundacio Internacional Josep Carreras and from Celgene International. LP and JMHS are supported by a research grant from FEHH (Fundacion Española de Hematología y Hemoterapia, 2017). IV acknowledges support from Pethema. MC and LZ research is supported by a grant from Instituto de Salud Carlos III, Ministerio de Sanidad y Consumo, Spain. MFM and her research is supported by the Spanish Association against Cancer (AECC, AIO2014), and the Ministerio de Economía y Competitividad of Spanish Central Government. The landscape of medical sequencing has rapidly changed with the evolution of next generation sequencing (NGS). These technologies have contributed to the molecular characterization of the myelodysplastic syndromes (MDS) and chronic myelomonocytic leukaemia (CMML), through the identification of recurrent gene mutations, which are present in >80% of patients. These mutations contribute to a better classification and risk stratification of the patients. Currently, clinical laboratories include NGS genomic analyses in their routine clinical practice, in an effort to personalize the diagnosis, prognosis and treatment of MDS and CMML. NGS technologies have reduced the cost of large-scale sequencing, but there are additional challenges involving the clinical validation of these technologies, as continuous advances are constantly being made. In this context, it is of major importance to standardize the generation, analysis, clinical interpretation and reporting of NGS data. To that end, the Spanish MDS Group (GESMD) has expanded the present set of guidelines, aiming to establish common quality standards for the adequate implementation of NGS and clinical interpretation of the results, hoping that this effort will ultimately contribute to the benefit of patients with myeloid malignancies.

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.

Introduction: Smoldering Multiple Myeloma (SMM) is an asymptomatic plasma cell disorder that includes patients with different risk of progression to Multiple Myeloma (MM). The Spanish Myeloma Group demonstrated that early treatment with Rd versus observation in SMM at high risk (HR) of progression resulted into a significant benefit in terms of progression to MM and overall survival. Our next step was to design this phase 2 trial with the potential goal of cure, defined by a sustained minimal residual disease (MRD) negativity for at least 5 years (yr). Methods: In this phase 2 single-arm trial, 90 SMM patients (pts) at high-risk of progression (>50% at 2 yr), younger than 70 yr and transplant candidates were included. The HR was defined by the presence of both bone marrow plasma cells (PCs)≥ 10% and serum M-protein ≥3g/dL (Mayo) or ifonly one criterion was present, patients must have a proportionof aberrant PCs within the total PCs bone marrow compartment by immunophenotypingof 95% plus immunoparesis (Spanish). Asymptomatic MM patients with any of the three biomarkers that currently define active MM were allowed to be included, because the design of the trial was done before the publication (Lancet Oncol 2014). Induction therapy consisted on six 4-weeks cycles of KRd in which K was given at dose of 36 mg/m 2 twice per week plus R at dose of 25 mg on days 1-21 and dexamethasone (dex) at dose of 40 mg weekly. Melphalan at dose of 200 mg/m 2 followed by autologous stem-cell transplant (ASCT) was given as intensification therapy and three months later, patients received two KRd consolidation cycles followed by maintenance with R at dose of 10 mg on days 1-21 plus dex 20 mg weekly for up to 2 yr. MRD was evaluated by next-generation flow cytometry after induction, ASCT, consolidation and annually thereafter. Results: the 90 planned patients were recruited between June 2015 and June 2017. Although 126 patients signed the informed consent (IC), there were 36 screening failures, including 21 (17%) pts due to the detection of lytic lesions by PET-CT or MRI (the most frequent exclusion criteria). The median age of the whole series was 59 yr. All pts were at HR according to the Mayo and/or Spanish models, including 28 pts (31%) that shared at least one of the new MM biomarkers (MDE). Forty-three patients have completed the 6 induction cycles and are evaluable for response: the ORR was 98% including 46% of ≥CR (37% sCR and 9% CR) and 37% of VGPR. MRD by NGF was evaluated in 34 out of these 43 pts and was negative in 13 (38%). Twenty-nine patients have received ASCT and were evaluable at 3 months: the ORR was 100% including ≥CR in 69% of the patients (65% sCR and 3% CR) and VGPR rate in 21%. MRD was negative in 17 out of these 29 patients (58%). Nineteen patients have completed the two planned consolidation cycles and 85% of them are in ≥CR, including sCR in 74%, CR in 11% and VGPR in 16%. As far as toxicity during induction is concerned, , G3-4 neutropenia and thrombocytopenia were reported in 4 (4%) and 2 pts (2%), respectively. G3-4 infections were the most frequent non-hematological adverse events (AE), observed in 9 pts (10%), followed by skin rash in 7 pts (8%). With regard to cardiovascular events, 1patient reported atrial fibrillation and another cardiac failure, both of G1, and 2 patients reported G2 arterial hypertension. In all but one of the pts, peripheral blood stem cell collection was successful, with a median number of CD34 + cells collected of 6,79 x 10 6 /Kg. Engraftment occurred in all patients and the median number of CD34 + infused was 3.29 x 10 6 /Kg. During consolidation, 2 pts developed G3-4 neutropenia, 3 pts G3-4 infections and 1 pt skin rash. After a median f/u of 13 months (1-108), 98% of patients remain free of progression and alive. Three patients early discontinued: one withdrew the IC; and two treatment unrelated deaths, one during induction due to a massive ischemic stroke and the other one because of refractory disease after induction. No discontinuations due to related-AE have been reported. Conclusions: Although longer follow-up is required, this "curative strategy for high-risk SMM" seems to be encouraging. The depth of response improved along with the duration of treatment, achieving up to 85% of ≥CR in patients who completed induction, ASCT and consolidation, with an acceptable safety profile. Interestingly, novel imaging techniques at screening allowed us to identify up to 17% of MM that would have been considered SMM with the conventional criteria. Disclosures Mateos: Takeda: Consultancy, Honoraria, Membership on an entity9s Board of Directors or advisory committees; Amgen: Consultancy, Honoraria, Membership on an entity9s Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity9s Board of Directors or advisory committees; Janssen: Consultancy, Honoraria, Membership on an entity9s Board of Directors or advisory committees. Rodriguez-Otero: Janssen: Consultancy, Research Funding, Speakers Bureau; Celgene: Consultancy, Research Funding, Speakers Bureau; BMS: Consultancy, Research Funding, Speakers Bureau. Ocio: BMS: Honoraria; Mundipharma: Research Funding; Pharmamar: Honoraria; Array Pharmaceuticals: Research Funding; Novartis: Honoraria; Janssen: Honoraria; Takeda: Honoraria; AbbVie: Honoraria; Seattle Genetics: Honoraria; Amgen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding. Oriol: Amgen: Consultancy, Honoraria, Membership on an entity9s Board of Directors or advisory committees, Other: sponsored symposia, Speakers Bureau; Celgene: Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity9s Board of Directors or advisory committees, Other: sponsored symposia; Janssen: Consultancy, Honoraria, Membership on an entity9s Board of Directors or advisory committees, Other: sponsored symposia, Speakers Bureau. Paiva: Celgene: Consultancy, Honoraria, Membership on an entity9s Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Membership on an entity9s Board of Directors or advisory committees; Amgen: Honoraria; Merck: Honoraria; Novartis: Honoraria; Takeda: Consultancy, Honoraria, Membership on an entity9s Board of Directors or advisory committees, Research Funding; EngMab: Research Funding; Sanofi: Consultancy, Honoraria, Research Funding. Rosinol: Janssen: Honoraria; Celgene: Honoraria. de la Rubia: Amgen: Other: Honoraria; Celgene: Other: Honoraria; Janssen: Other: Honoraria. Blade: Amgen: Honoraria; Celgene: Honoraria; Janssen: Honoraria. San Miguel: MSD: Consultancy, Membership on an entity9s Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity9s Board of Directors or advisory committees; Takeda: Consultancy, Membership on an entity9s Board of Directors or advisory committees; Roche: Membership on an entity9s Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity9s Board of Directors or advisory committees; Bristol-Myers Squibb: Consultancy, Membership on an entity9s Board of Directors or advisory committees; Janssen: Consultancy, Membership on an entity9s Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity9s Board of Directors or advisory committees; Sanofi: Consultancy, Membership on an entity9s Board of Directors or advisory committees.

Introduction Congenital dyserythropoietic anemias (CDA) are characterized by hyporegenerative anemia with inadequate reticulocyte values, ineffective erythropoiesis, and hemolysis. Distinctive morphology of bone marrow erythroblasts and identification of causative genes allow classification into 4 types caused by variants in CDAN1, c15orf41, SEC23B, KIF23, and KLF1 genes. Objective Identify pathogenic variants in CDA patients. Methods Massive parallel sequencing with a targeted gene panel, Sanger sequencing, Comparative Genome Hybridization (CGH), and in silico predictive analysis of pathogenicity. Results Pathogenic variants were found in 21 of 53 patients studied from 44 unrelated families. Six variants were found in CDAN1: two reported, p.Arg714Trp and p.Arg725Trp and, four novel, p.Arg623Trp, p.Arg946Trp, p.Phe1125Ser and p.Ser1227Gly. Twelve variants were found in SEC23B: seven reported, p.Arg14Trp, p.Glu109Lys, p.Arg217Ter, c.835-2A>G, p.Arg535Ter, p.Arg550Ter and p.Arg718Ter and, five novel, p.Val164Leu, p.Arg190Gln, p.Gln521Ter, p.Arg546Trp, and p.Arg611Gln. The variant p.Glu325Lys in KLF1 was found in one patient and p.Tyr365Cys in ALAS2 in an other. Moreover, we identified genomic rearrangements by CGH in some SEC23B-monoallelic patients. Conclusions New technologies for genetic studies will help to find variants in other genes, in addition to those known, that contribute to or modulate the CDA phenotype or support the correct diagnosis.

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.

Although survival of elderly myeloma patients has significantly improved there is still a subset of patients who, despite being fit and achieving optimal responses, will die within 2 years of diagnosis due to myeloma progression. The objective of this study was to define a scoring prognostic index to identify this group of patients. We have evaluated the outcome of 490 newly diagnosed elderly myeloma patients included in two Spanish trials (GEM2005-GEM2010). Sixty-eight patients (13.8%) died within 2 years of diagnosis (early deaths) due to myeloma progression. Our study shows that the use of simple scoring model based on 4 widely available markers (elevated LDH, ISS 3, high risk CA or >75 years) can contribute to identify up-front these patients. Moreover, unsustained response (, This study was supported by the Cooperative Research Thematic Networkgrants RD12/0036/0058 and RD12/0036/0046 of the Redde Cancer (Cancer Network of Excellence); Instituto deSalud Carlos III, Spain, Instituto de Salud Carlos III/SubdirecciónGeneral de Investigación Sanitaria part-financedby the European Regional Development Fund (FIS: PI12/01761; PI12/02311; PI13/01469; PI14/01867, G03/136;Sara Borrell: CD13/00340); Asociación Española Contra el Cáncer (GCB120981SAN) and FEDER.

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 Disclosures Puig: Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Takeda, Amgen: Consultancy, Honoraria; The Binding Site: Honoraria; Janssen: Consultancy, Honoraria, Research Funding. Martinez-Lopez:BMS: Honoraria, Other: Advisory boards; Janssen: Honoraria, Other: Advisory boards and Non-Financial Support ; Amgen: Honoraria, Other: Non-Financial Support ; Celgene: Honoraria, Other: Advisory boards and Non-Financial Support ; Incyte: Honoraria, Other: Advisory boards; Novartis: Honoraria, Other: Advisory boards; VIVIA Biotech: Honoraria; F. Hoffmann-La Roche Ltd: Honoraria. Lahuerta:Takeda, Amgen, Celgene and Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Rosinol Dachs:Janssen, Celgene, Amgen and Takeda: Honoraria. Bladé:Jansen, Celgene, Takeda, Amgen and Oncopeptides: Honoraria. Mateos:EDO: Membership on an entity's Board of Directors or advisory committees; Abbvie: 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; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive: Honoraria; 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; Pharmamar: 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.

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.

Introduction: The GEM-CESAR trial is a potentially curative strategy for high-risk smoldering multiple myeloma (HRsMM) patients in which the primary endpoint is the assessment of bone marrow minimal residual disease negativity by next generation flow (NGF). However, alternative methods of tumor burden evaluation in serum, like Quantitative Immunoprecipitation Mass Spectrometry (QIP-MS), a polyclonal antibody-based technology to identify intact immunoglobulins, have been also evaluated. Patients and Methods: Ninety HRsMM patients included in the GEM-CESAR trial received six 4-weeks cycles of carfilzomib, lenalidomide and dexamethasone followed by high dose melphalan and ASCT and 2 further cycles of consolidation with the same regimen. All patients received maintenance with lenalidomide up to 2 years. SPEP and IFE were performed using standard procedures and MRD was analyzed by flow cytometry following EuroFlow recommendations. QIP-MS assessment has been previously described (1) and allowed us the characterization of the isotype of each Ig trough immunoprecipitation with paramagnetic beads as well as the measurement of the molecular mass of each Ig for each specific patient, with enough precision and accuracy to establish clonality. Standard response assignment was carried out as per the IMWG guidelines. Results: First, we confirmed the higher sensitivity of QIP-MS to identify the presence of a serum M-spike as compared to conventional protein immunofixation electrophoresis methods. Amongst patients in CR, QIP-MS identified the M-spike in 18/30 (60%) post-induction, 18/47(38%) post-ASCT and 25/58(43%) post-consolidation. Interestingly, similar results were obtained with MRD-NGF post-induction [17/30(57%)] and post-ASCT [15/47(32%)] although the positive rate post-consolidation [15/58(26%)] was higher with QIP-MS. Then, we analyzed the overall concordance between the results obtained with QIP-MS and MRD-NGF at the three timepoints of disease evaluation, finding an overall concordance of 81% post-induction (n=76), 70% post-transplant (n=76) and 68% post-consolidation (n=77). Thus, when compared to the results of MRD-NGF, QIP-MS demonstrated sensitivities of 100%, 79% and 77% post-induction, post-ASCT and post-consolidation, and negative predictive values (NPV) of 100%, 79% and 82% at each respective time-point. (P < 0,0001; P = 0,0004; P = =,0012) Evaluation of discrepant cases showed 14 out of 22 MRD-NGF-negative patients post-induction for whom QIP-MS identified a M-spike; in some cases (i.e. IgG MM isotype) this may be related to a longer immunoglobulin half-life. There were no cases with detectable disease by NGF but QIP-MS negative. By contrast, post-ASCT, QIP-MS was negative in seven MRD-positive patients, two of whom became MRD-NGF-negative after consolidation; at last follow-up, none of them have progressed. On the other hand, sixteen patients with negative MRD-NGF after ASCT had a detectable M-spike by mass spectrometry. Of note, the M-spike became undetectable after consolidation in six out of these 16 patients. Post-consolidation, there were 7 patients in which MRD-NGF was positive but QIP-MS negative: MRD evaluation during maintenance is pending but none of them have so far progressed. By contrast, there were 18 patients with the M-spike detectable by QIP-MS but MRD-NGF negative: follow-up of these patients will address their outcome but, the only patient that has progressed so far had MRD-NGF negative post-induction, becoming positive post-transplant and consolidation, but the M-spike was detectable by QIP-MS throughout. Conclusions: M-spike monitoring by QIP-MS shows a moderate concordance with the MRD assessment by NGF in this group of HRsMM homogeneously treated. Longer follow-up will allow us to unravel the outcome of discordant cases and to define the specificity of QIP-MS and its complementary value to NGF. North S, Barnidge D, Brusseau S, Patel R, Haselton M, Du Chateau B, et al. QIP-MS: A specific, sensitive, accurate, and quantitative alternative to electrophoresis that can identify endogenous m-proteins and distinguish them from therapeutic monoclonal antibodies in patients being treated for multiple myeloma. Clinica Chimica Acta 2019;493:S433. Disclosures Puig: Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding; The Binding Site: Honoraria; Takeda, Amgen: Consultancy, Honoraria. Mateos:Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive: Honoraria; GSK: 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; 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; EDO: Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. 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. Rodriguez Otero:Takeda: Consultancy; Kite Pharma: Consultancy; BMS: Honoraria; Celgene Corporation: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria. Oriol:Celgene, Amgen, Takeda, Jansse: 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. Alegre:Celgene, Amgen, Janssen, Takeda: Membership on an entity's Board of Directors or advisory committees. de la Rubia:AbbVie: Consultancy; Janssen: Consultancy; Amgen: Consultancy; Celgene: Consultancy; Takeda: Consultancy. De Arriba:Amgen: Consultancy, Honoraria; Takeda: Honoraria; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Ocio:Mundipharma: Research Funding; Pharmamar: Consultancy; Amgen: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; AbbVie: Consultancy; Takeda: Consultancy, Honoraria; Array Pharmaceuticals: Research Funding; Sanofi: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy; Novartis: Consultancy, Honoraria; BMS: Honoraria. Bladé:Janssen, Celgene, Amgen, Takeda: Membership on an entity's Board of Directors or advisory committees; Irctures: Honoraria. Lahuerta:Takeda, Amgen, Celgene and Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees.

Introduction Mitochondria controls crucial biological pathways such as proliferation, apoptosis and cell growth. However, the implication of mitochondrial activity in the pathogenesis of Multiple Myeloma (MM) still remains unknown and only a few studies connect the mitochondrial status and MM. We planned to decipher the role of the mitochondria in the MM mechanism of resistance and the potential exploitation of mitochondrial activity as a functional target in the MM therapy. Methods In order to understand the role of mitochondria in MM and its therapeutic exploitation, firstly we explored factors involved in the mitochondrial function (c-Myc, HNRNPK, TFAM, NRF1 and EF-Tu) from 770 MM patients RNAseq CoMMpass℠ data. Furthermore, we performed different studies in our MM 77 patients set: gene expression validation by RT-PCR (n=40), protein expression (COXII) by IHC (n=28); and mitochondrial activity (COX activity) by histoenzymatic-HE assay (n=11). Additionally, we analyzed the impact of bortezomib in the mitochondria regulator CD38 in 50 samples (n=30 RVD, n=20 RD regimens), at diagnosis and 6/9 months follow-up MM patients. We have tested the effect of tigecycline, a mitochondrial inhibitor, in three regimens: monotherapy, pre-treament of tigecycline (48h) with consecutive bortezomib treatment, and in combination with bortezomib in the MM cell lines JJN3, L363 and NCI-H929. To characterize the molecular mechanisms underlying the cytotoxic effect of tigecycline we analysed mitochondria load and activity (MitoTracker green and red) OXPHOS expression by WB and COX2 activity by HE assay. Finally, we followed an in vivo experiment in NSG mice (n=40) engrafted with the JJN3-GFP cell line (1x106) via tail vein and treated by 4 weeks. Analysis of the in vivo imaging and survival curve were obtained. Results The higher expression of factors involved in the mitochondrial function such as: c-Myc, HNRNPK, NRF1 and EF-Tu predict MM poor outcomes (Fig.1A). Furthermore, mitochondrial representative gene and protein expression and activity were found increased in MM relapse stage patients. We showed overexpression of C-Myc, TFAM and EF-Tu on the MM relapsed group (Fig. 1B). Moreover, IHC reveals overexpression of mitochondrial COXII protein in relapse MM patients (p-value ** < 0.001) (Fig. 1C). By functional assays we have demonstrated that gene/protein overexpression drives to an increase of activity (COX HE) in MM at relapse (p-value ***< 0.0001). (Fig. 1D). Moreover, we observed an increase of CD38 expression in patients with RVD regimen, but not without bortezomib (RD regimen) (Fig. 1E). Together these results suggest elevation of mitochondrial activity plays a role in the mechanism of resistance to treatment and/or progression of MM and the consequent relapse of the patients. In vitro studies with tigecyline and bortezomib showed cytotoxic effects in three MM cell lines (IC50 JJN3 11,91 µM; IC50 L363 10,21 µM and NCI-H929 26,37 µM, p-value *< 0.05). Moreover, bortezomib and tigecyline showed high levels of synergism (CI 0,19) (Fig. 1F). In fact, the "conditioning" treatment with tigecyline revert the resistance to bortezomib. The cells treated with tigecycline reflect diminishing in the mitochondria respiration by MitoTracker assays, decrease of COX activity and respiratory chain complexes, suggesting a reduction of mitochondrial activity (Fig. 1G). These molecular effects are exacerbated by the tigecycline and bortezomib combination. However, bortezomib monotherapy not decrease or inclusive, increase, all the molecular mechanisms of mitochondria studied. Finally, mice groups treated with tigecycline alone or in combination with bortezomib reported a better survival and lower JJN3-GFP infiltration (p-value *< 0.05) (Fig. 1H). Conclusion To sum up, these findings highlight new vulnerabilities in myeloma cells, suggesting a potential therapeutic target in the treatment of the disease. The metabolic activation of myeloma cells with the collaboration of CD38 and/or c-Myc overexpression or his regulators (e.g. HNRNPK) in response to bortezomib treatment lead an increase of mitochondria respiration. These data confirm the important role of mitochondria in the loss of efficacy in inhibitors of proteasome treatment. Thus, mitochondrial respiration emerges as a novel target in bortezomib relapsed MM patients, and, potentially, in multiple c-Myc, HNRNPK and CD38 overexpression neoplasms. Disclosures Munshi: Adaptive: Consultancy; Oncopep: Consultancy; Janssen: Consultancy; Takeda: Consultancy; Amgen: Consultancy; Celgene: Consultancy; Abbvie: Consultancy.

Myelodysplastic syndromes (MDS) are the commonest hematologic malignancies in the elderly. Since many patients with MDS actually die from age-related ailments, the very disease burden of MDS remains largely unknown. This registry-based study was aimed at investigating the excess mortality attributable to MDS. We analyzed 7,408 adult patients diagnosed with primary MDS from 1980 to 2014. Excess mortality was estimated by comparing the patients' survival with that expected in the matched general population. Median age of patients was 74 years, 58% were males, and 65% belonged to the lower risk categories of the Revised International Prognostic Scoring System (IPSS-R). Excess mortality accounted for three-fourths of the all-cause mortality and was mainly driven by factors unrelated to leukemic transformation. Excess mortality increased with the IPSS-R risk category [Incidence rate ratio (IRR): 2.1, 95% CI: 1.9-2.3; P .001]. Older age and male sex retained an independent association with higher excess mortality after discounting demographic effects. Excess mortality increased in the most recent periods just in the higher risk IPSS-R categories (IRR: 1.2; 95% CI: 1.1-1.3 when comparing periods 2007-14, 2000-06, and 1980-99). In conclusion, MDS carry a significant excess mortality, even in the lower risk categories, that is mainly driven by factors unrelated to leukemic transformation, and increases with older age, male sex, and poorer risk categories. Excess mortality has increased in recent years in the higher risk patients, which might be ascribed to a parallel increase in age-related comorbidities. Our results claim for more comprehensive treatment strategies for patients with MDS. Am. J. Hematol. 92:149-154, 2017. © 2016 Wiley Periodicals, Inc.

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 Since clearance of MRD notably lowered the risk of relapse and persistence of MRD significantly shortened the PFS in each cytogenetic group (p ≤.001), we investigated the unique features of MRD cells persisting after VRD-induction by comparing their transcriptome to that of patient-matched tumor cells at diagnosis (n=40). Accordingly, MRD cells showed 763 genes significantly deregulated (Padj Conclusions: This is one of the largest studies integrating patients' cytogenetics and MRD status. Our results, based on intensive treatment and MRD monitoring using NGF, unveil that achieving MRD-negativity may overcome the poor prognosis of HR cytogenetics. By contrast, persistent MRD significantly reduces PFS rates, particularly in patients with del(17p). Interestingly, MRD cells from SR and HR patients may have different transcriptional mechanisms leading to VRD resistance, and further understanding of these could provide knowledge on how to eradicate MRD in both patient subgroups. Disclosures Puig: Takeda: Consultancy, Honoraria; Celgene: Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding. Garcia-Sanz:Affimed: Research Funding. Martinez-Lopez:BMS: Research Funding; Pfizer: Research Funding; Vivia: Honoraria; Celgene: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Novartis: Research Funding. Oriol:Celgene: 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; Takeda: 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. Rios:Amgen, Celgene, Janssen, and Takeda: Consultancy. De La Rubia:Ablynx: Consultancy, Other: Member of Advisory Board. Mateos: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; GSK: Consultancy, 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; 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; 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. 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:Janssen: Honoraria. San-Miguel:Amgen: Honoraria; BMS: Honoraria; Novartis: Honoraria; Sanofi: Honoraria; Celgene: Honoraria; Roche: Honoraria; Janssen: Honoraria.

The current classification system for Myelodysplastic Syndromes lumps all therapy-related (tMDS) into one subgroup assuming all tMDS had the same poor prognosis. We have put together a database including 2032 patients with a diagnosis of tMDS from several different IWG centers and the MDS clinical research consortium. With the idea of developing an individual scoring system for tMDS, we decided to start by optimizing the cytogenetic part of the IPSSR. First, we did an extensive review of karyotypes. Finally, 1245 patients had complete data and correct ISCN formula to be used for score development. We could show regarding karyotypes there are very limited differences between primary and tMDS. Mainly the distribution of risk groups differs with complex occurring more (37%) and normal karyotypes occurring less frequent, although still accounting for 30%. There are few exceptions that are relatively special for tMDS, like translocations including 11q23. A few karyotypes are less frequent; therefore, we could not evaluate the value of IPSS-R cytogenetics for all karyotypes. However, if we apply IPSS-R cytogenetics to our patient cohort, we can separate 5 different risk groups as in pMDS. We tested the performance of the score by using the Dxy. As main endpoint we chose transformation-free survival giving better information about the severity of the disease compared to the single endpoints survival and AML transformation that where calculated for completeness as well. The Dxy for the IPSS-R cytogenetic part is 0.31 for transformation-free survival. This indicates an effective prognostic performance although not as good as in pMDS. Several attempts were done to develop a tMDS specific cytogenetic score. The best draft scoring component achieves a Dxy of 0.33. Counting the number of aberrations achieves a score of 0.30. If normal clone present or not is added, the performance of this very simple model is improved with a Dxy of 0.32. As we could show, all these different approaches lead to a comparable performance. One can argue that still regarding a few karyotypes the prognostic impact is slightly different between p and tMDS (e.g. +8). On the other hand, the most practical approach seems to be to adopt the original cytogenetic part of the IPSS-R for further score development since clinicians do not need to use different scoring systems for different MDS subtypes. While the final analyses for the development of a tMDS specific risk score are currently under way, extensive calculations regarding the performance of different scores like WHO- (Dxy 0.24), FAB-classification (Dxy 0.19), WPSS-R (Dxy 0.35), IPSS-R (Dxy 0.37), and IPSS-R+age (Dxy 0.36), show all these systems can separate different risk groups within our cohort. However, these results also show an inferior performance of the scoring systems in t compared to pMDS. There are multiple possible reasons for this. The most important seem to be tMDS patients are often not cured from the primary disease and its disease specific risk of death should ideally be considered. Unfortunately, we don't have that data. And second, we included treated as well as untreated patients. It seems not to be feasible otherwise since the selection bias for old unfit patients would be unacceptable. We could show already in pMDS that the score performances are considerably worse if we analyze treated patients and the score performance in our cohort is better if limited to untreated patients. To conclude, we can say existing classification and scoring systems work in tMDS and can separate groups with clearly different risk for death and transformation. Although we could not develop a tMDS specific cytogenetic score this could be seen positively since it underlines tMDS do not seem to be much different regarding disease specific risk. This should initiate a discussion of a revision of the WHO-classification and encourage clinicians to use the existing tools for risk assessment and treatment decisions. A simple solution could be to use the WHO classification for pMDS and precede each subgroup with a t, like tMDS-SLD, and so on. Such an approach would be of importance for patients falsely classified as tMDS. After all this classification is done according to anamnestic information only and sporadic cases cannot be excluded. Until now, in the first analyzes performed with the final tMDS-database, we did not find any indication that risk factors established in pMDS would lose or change their meaning in tMDS. Figure. Figure. Disclosures Komrokji: Celgene: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Novartis: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau. Sekeres:Celgene: Membership on an entity's Board of Directors or advisory committees; Opsona: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Opsona: Membership on an entity's Board of Directors or advisory committees. List:Celgene: Research Funding. Roboz:Orsenix: Consultancy; Eisai: Consultancy; Novartis: Consultancy; Celltrion: Consultancy; Astex Pharmaceuticals: Consultancy; Argenx: Consultancy; Janssen Pharmaceuticals: Consultancy; Jazz Pharmaceuticals: Consultancy; Argenx: Consultancy; Janssen Pharmaceuticals: Consultancy; Pfizer: Consultancy; Cellectis: Research Funding; Daiichi Sankyo: Consultancy; Sandoz: Consultancy; Otsuka: Consultancy; Daiichi Sankyo: Consultancy; Eisai: Consultancy; Pfizer: Consultancy; Roche/Genentech: Consultancy; Novartis: Consultancy; Celltrion: Consultancy; Celgene Corporation: Consultancy; Cellectis: Research Funding; Orsenix: Consultancy; Aphivena Therapeutics: Consultancy; Otsuka: Consultancy; Jazz Pharmaceuticals: Consultancy; Sandoz: Consultancy; Roche/Genentech: Consultancy; Aphivena Therapeutics: Consultancy; AbbVie: Consultancy; Bayer: Consultancy; Bayer: Consultancy; Astex Pharmaceuticals: Consultancy; Celgene Corporation: Consultancy; AbbVie: Consultancy. Döhner:Jazz: Consultancy, Honoraria; Astex Pharmaceuticals: Consultancy, Honoraria; Agios: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; AROG Pharmaceuticals: Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Astex Pharmaceuticals: Consultancy, Honoraria; AROG Pharmaceuticals: Research Funding; Pfizer: Research Funding; Sunesis: Consultancy, Honoraria, Research Funding; Celator: Consultancy, Honoraria; Agios: Consultancy, Honoraria; Celator: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; Bristol Myers Squibb: Research Funding; Astellas: Consultancy, Honoraria; Bristol Myers Squibb: Research Funding; Amgen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Pfizer: Research Funding; Novartis: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria; Sunesis: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Jazz: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria. Valent:Pfizer: Honoraria; Novartis: Honoraria; Incyte: Honoraria. Platzbecker:Celgene: Research Funding. Lübbert:TEVA: Other: Study drug; Celgene: Other: Travel Support; Cheplapharm: Other: Study drug; Janssen: Honoraria, Research Funding. Díez-Campelo:Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Stauder:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Teva: Research Funding. Germing:Janssen: Honoraria; Novartis: Honoraria, Research Funding; Celgene: Honoraria, Research Funding.

Introduction: To discriminate different outcomes among patients in CR, the International Myeloma Working Group (IMWG )introduced more stringent CR (sCR) criteria by adding to the pre-existing CR parameters the requirement of a normal free-light chain ratio (sFLCr) plus the absence of clonal plasma cells (PCs) in bone marrow (BM) by immunohistochemistry (IHC). In 2011,the low-sensitivity cytometrycriteria were included as alternative methodology to IHC to define sCR. Aim: To validate the preliminary data of our previous study (Blood 2015. 126:858-62) regarding the lack of influence of an abnormal sFLCr in the outcome of MM patients, through the analysis of a more extensiveseries of newly diagnosed multiple myeloma (NDMM) patients in CR or sCR. Patients and Methods: This study is based on 459 NDMM patients who were transplant candidates and enrolled in the GEM2012MENOS65phase 3trial;evaluable patients were enrolled in a subsequent maintenance trial (NCT02406144).CR and sCR was defined according to the IMWG criteria. Agreeing to the protocol, patients with 1.65 if the patient was κ). BM aspirates were assessed for morphological enumeration of PCs and monitoring of minimal residual disease (MRD) using next-generation flow (NGF) according toEuroFlow SOPs. The median limit of detection was of 3x10-6. We classified as sCR all patients in CR with normal sFLCr and absence of clonal PCs by NGF with a reduced threshold of sensitivity to 10-4.The median follow-up was 40 months. Results: After ASCT,392 patients were evaluable for response; 239 (61%) reached ≥CR. Data from sFLCr and MRD was available in 225 and 221 patients, respectively. In 153 out of a total of 203 (74%) patients in CR in which complete information about FLC and MRD was available were categorized as sCR. The remaining 55 patients were consider in CR because of failure to accomplish 1 of the 2 criteria: abnormal sFLCr (n=49) or MRD+veby low sensitivity flow (n=11); 5patientsshared both criteria.In a landmark from ASCT, with a follow up of 27 months, sCRdidn't show significantly differences inPFS (2 years-PFS 90% vs 83%; P=.2) neither in OS (2 years-OS 96% vs 98%; P=.6) as compared to CR patients.Interestingly, patients with abnormal (n=51) vs normal (n=174) sFLCr showed superimposable PFS (2 years-PFS 86% vs 88%; P=.6) and OS (2 years-OS 95% vs 100%; P=.2).By contrast, in the 11 patients (out of the 221, 5%) with persistent MRD (>10-4) the PFS was significantly poorer as compared with MRD-ve cases (2-yearsPFS 91% vs48%; P=.001)but the OS was similar (2 years-OS 98% vs 96%; P=.3).As validation, we reproduced the analysis in the consolidation-2 end-point (figure 1), where375patients were evaluable for response assessment,267 of them (71%) reached ≥CR. Once again, in the landmark analysis, sCR didn't show significantly differences in PFS with respect to CR patients (2 years-PFS 88% vs 84%; P=.2) neither in OS (2 years-PFS 96% vs 90%; P=.3); moreover, patients with abnormal (n=55) vs normal (n=195) sFLCr showed superimposable PFS (2 years-PFS 84% vs 87%; P=.4) and OS (2 years-OS 89% vs 96%; P=.2).In the MRD analysis, patients with persistent MRD, had significantly inferior PFS (2-years PFS 87% vs 72%; P=.04 for >10-4 MRDsensitivity). If we increase the sensitivity of the MRD to 10-6, the differences in PFS at 2 years are more evident (2 years-PFS 94% vs 67%; P10-6 sensitivity). Conclusion: These results confirm our previous findings based on GEM05menos65/ GEM10mas65 clinical trials, indicating that for MM patients stringent CR criteria does not predict a different outcome as compared to standard CR. Specifically, the sFLCr doesn't identify patients in CR at distinct risk. If this essential criterion in the definition of sCR lacks connotations for the prognosis, is it not justified to maintain a response category whose real significance depends on the combination of the traditional CR criteria with a negative MRD status based on very low (IHC) or low resolution ( Figure 1. Figure 1. Disclosures Martinez Lopez: Janssen: Research Funding, Speakers Bureau; Bristol Myers Squibb: Research Funding, Speakers Bureau; Novartis: Research Funding, Speakers Bureau; Celgene: Research Funding, Speakers Bureau. Rosinol:Janssen, Celgene, Amgen, Takeda: Honoraria. Puig:Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Honoraria, Research Funding. Oriol:Celgene: 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; Takeda: 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. Ocio:Pharmamar: Consultancy; AbbVie: Consultancy; Seattle Genetics: Consultancy; BMS: Consultancy; Janssen: Consultancy, Honoraria; 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. De La Rubia:Ablynx: Consultancy, Other: Member of Advisory Board. Rios:Amgen, Celgene, Janssen, and Takeda: Consultancy. Mateos: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; 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; 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; Amgen: Consultancy, 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. Bladé:Amgen: Honoraria; Celgene: Honoraria; Janssen: Honoraria. 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.

Background: Since survival in AL mainly depends on the extent of organ involvement of patients at presentation, early diagnosis and risk stratification are key to improve patients' outcome. Therefore, together with surrogates of organ involvement, biomarkers identifying patients with MGUS or MM at greater risk of developing AL would be highly valuable to prevent organ damage, to maximize therapeutic efficacy and to improve outcomes in AL. Aim: To investigate the value of multidimensional flow cytometry (MFC) for simultaneous fast diagnostic screening of plasma cell (PC) clonality and risk stratification, as well as to identify immunophenotypic markers useful for the selection of patients with monoclonal gammopathies candidates for monitoring of pre-symptomatic organ damage related to AL. Methods: We used MFC to characterize a large series of patients with newly-diagnosed (ND) AL (N=94) vs MGUS (N=20) and NDMM (N=52), as well as age-matched healthy adults (HA, N=30). For each patient with AL, automated risk stratification was performed using principal component analysis (PCA) based on the relative frequency of bone marrow (BM) PCs, plus the percentage of clonal and normal PCs within the whole BM PC compartment, vs a database containing information on the same three parameters from a total of 1,774 patients, including 497 MGUS and 1,227 NDMM. In parallel, immunophenotypic protein expression profiles (iPEP) of AL patients were clustered using t-SNE, and the comparison between the iPEP of clonal PCs from patients with AL vs MGUS and MM cases was performed using canonical-correlation analysis (CCA). To identify additional immunophenotypic hallmarks of AL, the BM cellular composition in HA, MGUS, AL and MM patients was compared using 2-dimensional minimum spanning tree (MST) force-directed classification to determine the distance among individual cases. Results: PC clonality was detected by MFC in 93/94 (99%) AL patients, whereas an M-component was detectable in 96% of cases by electrophoresis, immunofixation and sFLC. PCA as defined above, identified AL patients displaying an MM-like (n=6) and an MGUS-like (n=38) signature, as well as 49 cases with an intermediate signature between the MGUS and MM reference datasets. Multivariate analysis of baseline prognostic factors for survival, including patients' age, number of organs involved, Mayo staging, the percentage of BM PCs based on cytomorphology and eligibility for ASCT, showed that having an intermediate- or an MM-like profile had an independent adverse effect on patients' progression-free (PFS) and overall survival (OS) (HR:3.4; P≤.02). t-SNE based on the iPEP of clonal PCs revealed two major clusters of AL patients with significantly different PFS, defined by opposite patterns of expression for CD45, CD56 and CD138 (P≤.02). CCA of tumor iPEP showed partial overlap between AL vs MGUS and MM, with progressively higher percentages of cases with a CD38lo, CD45-ve, CD81-ve and CD138lo iPEP being observed from MGUS to AL and MM. In contrast, AL patients displayed significantly lower reactivity for CD56 (P≤ .03). Further characterization of the BM cellular composition allowed the systematic assessment of 16 cell populations and 18 phenotypic parameters that, by MST, mapped AL in between MGUS and MM. Of note, while AL patients displayed a predominantly-clonal PC compartment in the absence of an MM-like tumor PC expansion, the percentage of B-cell precursors was consistently lower in AL patients than in HA, MGUS and MM (P=.004). Thus, using optimal cut-off values to discriminate between AL vs MGUS and MM, we built a scoring model based on the presence of 80% clonal PCs within total BM PCs and Conclusions: We demonstrate the value of MFC for fast diagnostic screening of PC clonality in AL and simultaneous automated patient risk-stratification, based on the BM tumor burden and PC phenotype. In addition, our results also provide new immunophenotypic markers for the identification of patients with monoclonal gammopathies that are candidates for monitoring of pre-symptomatic organ damage related to AL. Disclosures Puig: Janssen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria; Celgene: Honoraria, Research Funding. Ocio:Array Pharmaceuticals: Research Funding; Sanofi: Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Pharmamar: Consultancy; BMS: Consultancy; AbbVie: Consultancy; Janssen: Consultancy, Honoraria; Seattle Genetics: Consultancy; Mundipharma: Research Funding; Takeda: Consultancy, Honoraria; Novartis: Consultancy, Honoraria. Oriol:Takeda: 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; Amgen: 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. De La Rubia:Ablynx: Consultancy, Other: Member of Advisory Board. Martinez Lopez:Janssen: Research Funding, Speakers Bureau; Celgene: Research Funding, Speakers Bureau; Novartis: Research Funding, Speakers Bureau; Bristol Myers Squibb: Research Funding, Speakers Bureau. Mateos:Amgen: 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; Abbvie: 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; Janssen: 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. Lahuerta:Janssen: Honoraria; Celgene: Honoraria; Amgen: Honoraria.

Background: The 2016 reviewed classification of the World Health Organisation (WHO) defines a group of myelodysplastic/myeloproliferative neoplasms (MDS/MPN) including the chronic myelomonocytic leukemia (CMML), the myelodyplastic syndrome with ring sideroblasts and thrombocytosis (MDS-RS-T) and the MDS/MPN unclassifiable (MDS/MPN-U). The presence of typical clinical characteristics of MDS and MPN hinders the diagnosis and the prognosis of MDS/MPN-U. Aim: The objective of this study was to compare the clinical characteristics and the prognosis of a series of patients with MDS/MPN such as CMML, MDS-RS-T and MDS/NPM-U from the Spanish registry of MDS. Method: We analized 107 patients diagnosed with MDS/MPN (MDS-RS-T, MDS/NPM-U and CMML) according to the 2016 WHO classification. A comparison of the clinical characteristics, overall survival (OS) and cumulative incidence of progression (CIP) was performed. Results: Median (range) age was 74 (23-93) years and 68/107 (64%) were males. The number of patients in each group was: MDS-RS-T (n=45), MDS/MPN-U (n=29) and CMML (n=33). The main clinical characteristics of the three groups are described in Table 1. There were significant statistical differences in hemoglobin and lactate dehydrogenase levels and leukocyte, monocyte and platelet counts between the three groups. With a median (range) of follow-up of 3.1 (0.3-19.3), 3.7(0.7-10.4) and 4 (1.8-8.5) years for MDS-RS-T, MDS/MPN-U, and CMML, respectively, the OS (95%CI) at 5 years was significantly better in patients with MDS-RS-T (61% [42%; 80%]) compared to MDS/MPN-U and CMML patients (21% [1%; 41%] and 19% [3%; 35%], p=0.002) (Figure 1). The CIP (95%CI) at 5 years between the three groups was significantly different: MDS/MPN-U and CMML (40% [18%; 61%] and 32% (14%-52%, respectively) vs. MDS/RS-T 8% [0.4%; 30%]) (p=0.005) (Figure 2). Conclusions: 1) In this series of patients with MDS/MPN (MDS-RS-T, MDS/MPN-U and CMML) according to the 2016 WHO classification clinical characteristics were similar except for hemoglobin and lactate dehydrogenase levels and leukocyte, monocyte and platelet counts. 2) Patients with MDS-RS-T had longer OS and less CIP than those with MDS/MPN-U and CMML; 3) The prognosis of MDS/MPN-U and CMML were similar. Supported by grants from: AGAUR 9015-470120/2015, 2017-SGR288 (GRC), CERCA Program from Generalitat de Catalunya, and "La Caixa" Foundation. Disclosures No relevant conflicts of interest to declare.

Introduction:SMM is an asymptomatic and heterogeneous plasma cell disorder. The Spanish Myeloma Group demonstrated that patients at high risk of progression benefit from early treatment with Rd. In addition, our preliminary results of the curative approach (GEM-CESAR) showed encouraging results (Mateos ASH 2017). Aim: The primary end-point was to evaluate the Minimal Residual Disease negative (MRD-ve) rate by next generation flow (NGF) after induction and ASCT and the sustained MRD-ve rate at 3 and 5 yrs after ASCT as secondary end-points. Our aim was to increase the MRD -ve rate from 34% (reported in NDMM patients after VTD and ASCT) to 50%. As all patients have completed induction and ASCT, we report the results of the primary end point, efficacy and safety after induction and ASCT. Methods: In this phase II single arm trial, 90 SMM patients at high-risk of progression (>50% at 2 yrs), younger than 70 yrs and transplant candidates were included. The high risk was defined by the presence of both ≥PC 10% and MC ≥3g/dL (Mayo criteria) or ifonly one criterion was present, patients must have a proportionof aberrant PCs within the total PCsBM compartment by immunophenotypingof 95% plus immunoparesis (Spanish criteria). Asymptomatic MM patients with any of the three biomarkers recently included into the definition of active MM were allowed to be included. Induction therapy consisted on six 4-weeks cycles of KRd in which K was given at dose of 36 mg/m2twice per week plus R at dose of 25 mg on days 1-21 and dexamethasone at dose of 40 mg weekly. Melphalan at dose of 200 mg/m2followed by ASCT was given as intensification therapy and three months later, patients received two KRd consolidation cycles followed by maintenance with R at dose of 10 mg on days 1-21 plus dex at dose of 20 mg weekly for up to 2 yrs Results: Between June 2015 and June 2017, the 90 SMM patients at high risk of progression were recruited. Twenty-eight pts (32%) shared at least one of the new biomarkers predicting imminent risk of progression to MM. The primary end point of the trial was met, since 55% of the patients who completed induction and ASCT achieved MRD -ve by NGF (sensitivity 3 x 10-6). Upon analyzing the results after induction, 88 patients completed the 6 induction cycles and were evaluable for response (two patients early discontinued): the ORR was 98% including 41% of ≥CR (32% sCR and 9% CR) and 41% of VGPR rate. Two patients were mobilization failures and one patient rejected ASCT. Two additional patients experienced biological progression before ASCT and went off the study. Eighty-three patients, therefore, proceeded to HDT-ASCT and were evaluable at day +100: the ORR was 100% including ≥CR in 63% of the patients (51% sCR and 12% CR) and VGPR rate in 23%. The MRD-ve rate increased from 31% after induction to 55% with the ASCT. No differences in outcome have been observed according neither to the definition of high risk (Mayo or Spanish model) nor ultra high risk SMM. Concerning toxicity, during induction, G3-4 neutropenia and thrombocytopenia were reported in 5 (6%) and 10 pts (11%), respectively. G3-4 infections were the most frequent non-hematological AE observed in 16 pts (18%), followed by skin rash in 8 pts (9%). One patient reported G1 atrial fibrillation and another cardiac failure secondary to respiratory infection. Three patients reported hypertension (G2 in two and G3 in one). Thirteen patients required lenalidomide dose reduction whilst carfilzomib was not reduced in any patient. In four patients, dexamethasone was reduced. In all but two of the pts, PBSC collection was successful with a median of 4.10 x 106/Kg CD34 cells collected. All patients engrafted. Consolidation and maintenance phases are ongoing. After a median follow-up of 17 months (5-36), 94% of patients remain alive and free of progression and 97% of them alive. Three patients experienced biological progression and discontinued the study: one of them was refractory to the rescue therapies and died and the other two are receiving rescue therapies. One additional patient died early during induction due to a massive ischemic stroke unrelated to the treatment. Conclusions: Although longer follow-up is required, this "curative strategy for high risk SMM" continues being encouraging with an acceptable toxicity profile. The study has met its primary endpoint. The depth of response improved over the treatment: 63% of patients who completed induction and ASCT achieved ≥CR with a MRD-ve rate of 55%. Disclosures Mateos: Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy, 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; GSK: Consultancy, 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; 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; GSK: Consultancy, Membership on an entity's Board of Directors or advisory committees. Rodriguez Otero:Takeda: Consultancy; Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Bristol Myers Squibb: Research Funding; Clínica Universidad de Navarra: Employment. Ocio:AbbVie: Consultancy; Pharmamar: Consultancy; Seattle Genetics: Consultancy; Janssen: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; BMS: Consultancy; Takeda: Consultancy, Honoraria; Sanofi: Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Mundipharma: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Array Pharmaceuticals: Research Funding. Oriol:Celgene: 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; Janssen: 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. Alegre:Takeda: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees. Puig:Janssen: Consultancy, Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Takeda: Consultancy, Honoraria. De La Rubia:Ablynx: Consultancy, Other: Member of Advisory Board. García Mateo:Binding Site: Research Funding; Amgen: Honoraria; Celgene: Honoraria. Bladé:Janssen: Honoraria. Lahuerta: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; 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. San-Miguel:Novartis: Honoraria; Janssen: Honoraria; BMS: Honoraria; Amgen: Honoraria; Celgene: Honoraria; Sanofi: Honoraria; Roche: Honoraria.

To develop a prognostic scoring system tailored for therapy-related myelodysplastic syndromes (tMDS), we put together a database containing 1933 patients (pts) with tMDS from Spanish, German, Swiss, Austrian, US, Italian, and Dutch centers diagnosed between 1975-2015. Complete data to calculate the IPSS and IPSS-R were available in 1603 pts. Examining different scoring systems, we found that IPSS and IPSS-R do not risk stratify tMDS as well as they do primary MDS (pMDS), thereby supporting the need for a tMDS-specific score (Kuendgen et al., ASH 2015). The current analysis focuses on cytogenetic information as a potential component of a refined tMDS score, based on this large, unique patient cohort. Of the 1933 pts, 477 had normal karyotype (KT), 197 had missing cytogenetics, while 467 had a karyotype not readily interpretable. Incomplete karyotype descriptions will be reedited for the final evaluation. Of the remaining 1269 pts the most frequent cytogenetic abnormalities (abn) were: -7, del(5q), +mar, +8, del(7q), -5, del(20q), -17, -18, -Y, del(12p), -20, and +1 with >30 cases each. Frequencies are shown in Table 1. Some abn were observed mostly or solely within complex KTs, such as monosomies, except -7. Others, like del(20q) or -Y, are mainly seen as single or double abn, while del(5q), -7, or del(7q) are seen in complex as well as non-complex KTs. The cytogenetic profile overlapped with that of pMDS (most frequent abn: del(5q), -7/del(7q), +8, -18/del(18q), del(20q), -5, -Y, -17/del(17p), +21, and inv(3)/t(3q) (Schanz et al, JCO 2011)), with notable differences including overrepresentation of complete monosomies, a higher frequency of -7 or t(11q23), and a more frequent occurrence of cytogenetic subtypes in complex KTs, which was especially evident in del(5q) occurring as a single abn in 16%, compared to 70% within a complex KT. IPSS-R cytogenetic groups were distributed as follows: Very Good (2%), Good (35%), Int (17%), Poor (15%), Very Poor (32%). Regarding the number of abn (including incomplete KT descriptions) roughly 30% had a normal KT, 20% 1, 10% 2, and 40% ≥3 abn, compared to pMDS: 55% normal KT, 29% 1, 10% 2, and 6% ≥3 abn. To be evaluable for prognostic information, abn should occur in a minimum of 10 pts. As a single aberration this was the case for -7, +8, del(5q), del(20q), del(7q), -Y, and t(11;varia) (q23;varia). Of particular interest, there was no apparent prognostic difference between -7 and del(7q); del(5q) as a single abn was associated with a relatively good survival, while the prognosis was poor with the first additional abn; t(11q23) occurred primarily as a single abn and was associated with an extremely poor prognosis, and prognosis of pts with ≥4 abn was dismal independent of composition (Table 1). To develop a more biologically meaningful scoring system containing homogeneous and prognostically stable groups, we will further combine subgroups with different abn leading to the same cytogenetic consequences. For example, deletions, unbalanced translocations, derivative chromosomes, dicentric chromosomes of 17p, and possibly -17 all lead to a loss of genetic material at the short arm of this respective chromosome affecting TP53. Further information might be derived from analyses of the minimal common deleted regions. For some abn, like del(11q), del(3p), and del(9q), this can be refined to one chromosome band only (table 1). Conclusion: Development of a robust scoring system for all subtypes of tMDS is challenging using existing variables. This focused analysis on the cytogenetic score component shows that favorable KTs are evident in a substantial proportion of pts, in contrast to historic data describing unfavorable cytogenetics in the majority of pts. Although complex and monosomal KTs are overrepresented, this suggests the existence of distinct tMDS-subtypes, although some of these cases might not be truly therapy-induced despite a history of cytotoxic treatment. The next steps will be to analyze the prognosis of the different groups, develop a tMDS cytogenetic score, and examine minimal deleted regions to identify candidate genes for development of tMDS, as well as to describe the possible influence of different primary diseases and treatments (radio- vs chemotherapy, different drugs) on induction of cytogenetic subtypes. Our detailed analysis of tMDS cytogenetics should reveal important prognostic information and is likely to help understand mechanisms of MDS development. Disclosures Komrokji: Novartis: Consultancy, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding. Sole:Celgene: Membership on an entity's Board of Directors or advisory committees. Sekeres:Celgene: Membership on an entity's Board of Directors or advisory committees; Millenium/Takeda: Membership on an entity's Board of Directors or advisory committees. Roboz:Cellectis: Research Funding; Agios, Amgen, Amphivena, Astex, AstraZeneca, Boehringer Ingelheim, Celator, Celgene, Genoptix, Janssen, Juno, MEI Pharma, MedImmune, Novartis, Onconova, Pfizer, Roche/Genentech, Sunesis, Teva: Consultancy. Steensma:Amgen: Consultancy; Genoptix: Consultancy; Janssen: Consultancy; Celgene: Consultancy; Millenium/Takeda: Consultancy; Ariad: Equity Ownership. Schlenk:Pfizer: Honoraria, Research Funding; Amgen: Research Funding. Valent:Amgen: Honoraria; Deciphera Pharmaceuticals: Research Funding; Celgene: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Ariad: Honoraria, Research Funding; Deciphera Pharmaceuticals: Research Funding. Giagounidis:Celgene Corporation: Consultancy. Giagounidis:Celgene Corporation: Consultancy. Platzbecker:Celgene Corporation: Honoraria, Research Funding; TEVA Pharmaceutical Industries: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Janssen-Cilag: Honoraria, Research Funding; Amgen: Honoraria, Research Funding. Lübbert:Janssen-Cilag: Other: Travel Funding, Research Funding; Celgene: Other: Travel Funding; Ratiopharm: Other: Study drug valproic acid.

INTRODUCTION MDS are a heterogeneous group, and it is necessary an adequate prognostic stratification in order to the best management. The new revised international prognostic scoring system (IPSS-R) has improved prognostic ability for survival and AML evolution comparing with the previous prognostic indexes. But, it is not clear the prognosis of patients included in the intermediate group, 20% of MDS, patients with a median OS of 3 years according to Greenberg et al, are they in the high or in the low risk category? The aims of the present study were to describe characteristics of patients included in this intermediate group of the IPSS-R in the Spanish MDS cohort and to identify which factors could have an impact on survival. A new score prognostic system (GESMDi score) in order to a better stratification should be proposed in this subset of patients that will be useful for determine the best therapeutic approach for them. METHODS: All patients were included in the GESMD, diagnosed of Primary MSD and Intermediate IPSS-R. The Statistical analyzes were performed using SPSS version 21, Cox models and Kaplan-Meier curves were used to demonstrate clinical outcomes. Regarding the new score proposed, GESMDi score, modeling of prognostic risk was based on multivariate analysis of survival time. Cox model for survival was built to derive the relative weights within the score. RESULTS: Data from 957 patients of 69 centers of GESMD were evaluated. Their median age was 73.9 years (p25/p75 66-80), 61.6% males (N=590), and median follow-up 21,4 months (p25-p75 de 11-41). Regarding WHO 2001 classification: 31% were RAEB-1, 21% CMML, 18% RCMD, 14% RAEB-2, 3% RCMD-RS, 3.1% RARS, 2.5% RA, 2% 5q-syndrome, 2% AML, 1% unclassified. Median hemoglobin at diagnosis was 9.8 g/dL (p25/p75:8.3-11.6), median bone marrow (BM) blasts 6% (p25/p75:3-8) and median platelet count 99x109/L (p25/p75:66-180). According to IPSS, 5% of patients were classified as low risk, 78% as intermediate-1, 16% as intermediate-2 and 1% as high risk. Cytogenetic were very good in 2% of patients, good in 76%, intermediate in 17%, poor in 5% and in 1% very poor. IPSS-R score classified patients in 3 different groups, with a punctuation of≤ 3.5 (35.6%), >3.5 and ≤ 4 (35.8%) and> 4 and ≤ 4.5 (28.5%). Median OS was 30.1 months, the estimated 1-year and 2-y OS were 79.2% and 57.8%, respectively. In the univariate analysis for OS older age (>74y, p500 ng/ml, p=0.002), and higher IPSS-R score (>3.5 and ≤ 4 and >4 and ≤ 4.5, p=0.023 and p=0.004, figure 1) had a deleterious impact on survival. In the multivariate analysis, only age, Hb level, PB blast, ferritine level and IPSS-R value retained statistical significant impact on OS (table 1a). In the multivariate analysis, Hazard ratio, a new score system (GESMDi score) was established for all patients. Patients with adverse features were added points in order to stratify the risk of death: age500 ng/ml and/or IPSS-R of >3.5 (1 point), table 1a. The GESMDi score was performed in 685 patients with all data available and 7 groups of patients were defined with different median OS (p30 months) and high risk patients ( CONCLUSIONS: GESMDi score, a proposed prognostic score system from patients with intermediate IPSS-R, allow us to establish a better prognosis stratification in this heterogeneous MDS population. Treatment and management should be better established for those patients nowadays according to this novel stratification. Table 1 a) Univariate and multivariate analysis for OS among patients with Intermediate IPSS-R b) OS according to the GESMDi score proposed Table 1. a) Univariate and multivariate analysis for OS among patients with Intermediate IPSS-R b) OS according to the GESMDi score proposed Figure 1 OS according to IPSS-R value in the intermediate group (≤3.5, ≤4 and ≤4.5) Figure 1. OS according to IPSS-R value in the intermediate group (≤3.5, ≤4 and ≤4.5) Figure 2 OS according the GESMDi score proposed in the intermediate IPSS-R group: low and high risk patients (n=685) Figure 2. OS according the GESMDi score proposed in the intermediate IPSS-R group: low and high risk patients (n=685) Disclosures Del Cañizo: Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Astex: Membership on an entity's Board of Directors or advisory committees; janssen: Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Díez Campelo:Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Astex: Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau.

Background: MM usually affects elderly patients and although novel agents-based combinations have substantially improved MM outcome, it is possible that this benefit would be particularly relevant for the "youngest-elderly" patients (65-80y). According to the frailty score published by IMWG, the chronological age ≥80 years identifies itself a frail patient population with poor outcome and we have here evaluated the efficacy, safety and outcome of patients included in the GEM2010 trial according to the age to identify the group of patients who benefit most of this total therapy approach. Patients and methods: 242 patients were randomized to receive a sequential scheme consisting on 9 cycles of VMP followed by 9 cycles of Rd or the same regimens in an alternating approach (one cycle of VMP alternating with one Rd, up to 18 cycles. VMP included the iv administration of weekly bortezomib (except in the first cycle that was given twice weekly) at 1.3 mg/m2 in combination with oral melphalan 9 mg/m2 and prednisone 60 mg/m2 once daily on days 1-4. Rd treatment consisted on lenalidomide 25 mg daily on days 1-21 plus dexamethasone 40 mg weekly. Results: 233 pts were evaluable for safety and efficacy (118 in the sequential and 115 in the alternating arm). One hundred and fifteen patients (49%) were between 65-75 years, 69 patients (30%) were aged between 75-80 years and 49 patients (21%) were older than 80 years. The allocation in both sequential and alternating arms was well balanced. There were not significant differences in the baseline characteristics of the three subgroups of patients. The ORR was similar in both patients aged 65-75 and 75-80 (80% and 83%), but significantly lower in patients older than 80 years (68%) (p=0.007). The CR rate was also almost identical in patients between 65-75 (45%) and 75-80 (49%), but significantly lower in those aged over 80 years (10%) (p The median PFS was 35 m and 32 m in the group of patients aged between 65-75 and 75-80, respectively (p=NS), but PFS was only 25 months in patients older than 80 (p=0.02). In terms of OS, 75% of the patients between 65-75 years remained alive at 4 years, 60% of patients between 75-80 years (p=0.05), as compared to only 30% of patients older than 80 years (p=0.003). There were no significant differences between the sequential and alternating arms. Hematological and non-hematological toxicity was not different in the different groups according to the age, but it is important to note that 63% of patients older than 80 years early discontinued the trial due to toxicity or informed consent withdrawal, while this occurred in only 30% of patients aged 65-75 and 75-80. Sixty-eight percent and 59% of the patients aged 65-75 and 75-80, respectively, completed the 18 planned cycles, as compared to only 36% of patients aged over 80 years. The median cumulative dose of bortezomib and lenalidomide was significantly higher in the group of patients aged 65-75 (44 mg/m2 for bz and 4410 mg for len) and 75-80 (41 mg/m2 for bz and 4078 mg for len) compared to patients over 80 years (33 mg/m2 for bz and 1783 mg for len). These differences were maintained in both sequential and alternating arms. Conclusions: The present therapeutic approach, based on VMP and Rd for newly diagnosed elderly MM patients probably represents the optimal therapeutic option for elderly patients between 65 and 80 years in a sequential or alternating approach. By contrast, further optimization for the patient population over 80 years is still required. Disclosures Mateos: Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: 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; BMS: Consultancy; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Onyx: Consultancy; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees. Ocio:Array BioPharma: Consultancy, Research Funding; Celgene: Consultancy, Honoraria; Amgen/Onyx: Consultancy, Honoraria, Research Funding; Bristol Myers Squibb: Consultancy; Mundipharma: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; MSD: Research Funding; Pharmamar: Consultancy, Research Funding; Janssen: Honoraria. Oriol:Celgene, Janssen, Amgen: Consultancy, Speakers Bureau. Gironella:Celgene Corporation: Consultancy, Honoraria. Paiva:Celgene: Consultancy; Binding Site: Consultancy; Millenium: Consultancy; Sanofi: Consultancy; Janssen: Consultancy; EngMab AG: Research Funding; BD Bioscience: Consultancy; Onyx: Consultancy. Puig:Janssen: Consultancy; The Binding Site: Consultancy. San Miguel:Celgene: Honoraria; Janssen-Cilag: Honoraria; Novartis: Honoraria; Sanofi-Aventis: Honoraria; Bristol-Myers Squibb: Honoraria; Millennium: Honoraria; Onyx: Honoraria.

INTRODUCTION Anemia is the most frequent cytopenia in lower-risk MDS. Erythropoietic-stimulating agents (ESAs) are commonly used in these patients. The use of ÒclassicalÓ parameters (EPO and ferritin levels) and the revised IPSS (IPSS-R) has been proposed1 (SantiniÕs score) to predict response to ESAs and overall survival (OS) among patients with lower risk MDS by IPSS and a favorable Nordic group score2. OBJECTIVES The main objective of the study was to evaluate overall response rate (ORR) to ESAs and OS according to the proposed SantiniÕs score in an independent and large cohort of anemic lower risk MDS patients receiving treatment with ESAs. METHODS Data from 530 anemic patients with low/int1 risk IPSS de novo MDS (according to FAB and WHO criteria) and sufficient follow-up data available were recorded in Spresas3 (SPanish Registry of Erythropoietic Stimulating Agents Study from GESMD). Two hundred and twenty six patients (42.6% of the patients) were selected according to specific criteria regarding the published SantiniÕs score1: Hb level 200mU/mL(=1), serum ferritin (SF) >350 ng/mL(=1) and IPSS-R very low=0, low=1, intermediate=2 and high=3) yielded a score ranging from 0 to 5. ESAs response rate and overall survival were analysed according to these score. Response to treatment was evaluated according to IWG 2006 response criteria and a multivariate logistic regression analysis was used to identify independent predictors of erythroid response (ER). OS were defined as the time between diagnosis and the corresponding event or last follow up (Feb 2015) and were analyzed using univariable and multivariable Cox proportional hazards regression methods. RESULTS Median age was 77 years (interquartile range [IQR] 25%-75%: 71-83 y), median Hb level at start of treatment was 10 g/dL (IQR25-75: 9-10), median EPO level was 90 (IQR25-75: 27,25-108) and median ferritin level was 338,5 (IQR25-75: 146,5-568,75). Among 139 patients with this data available, 85 patients (61,1%) were RBC transfusion dependent before ESAs treatment. Median time from diagnosis to ESAs treatment was 82 (IQR25-75: 27-353) days. According to the IPSS, 68.6% (N=155) and 31.4% (N=71) were in low and Int-1 risk groups, respectively. Regarding IPSS-R, 23% (N=52), 66.8% (N=151), 9.7% (N=22) and 0.4% (N=1) were in very low, low, intermediate and high risk, respectively. ORR to ESA treatment was 71.2% (N=161), with a median duration of response of 2.06 years. Prognosis factors of ER showed a trend toward to a higher ER among patients in the lower IPSS-R (P>0.05), low IPSS (p=0.039) and lower EPO levels (p According to SantiniÕs score, 11.5%(N=26), 42.9%(N=97), 25.8%(N=81), 8%(N=18) and 1.8%(N=4) of the patients were in the 0, 1, 2 3 and 4 score. Erythroid response was better for patients in the lower scores, with response rates of 73.1%, 82.5%, 65.4%, 50% and 0%, for patients in 0, 1, 2, 3 and 4 score, respectively (p CONCLUSIONS The present study confirms that SantiniÕs score is useful to identify patients with a higher probability of response to ESAs and better OS among lower risk MDS patients with an expected favorable response to ESA according to Nordic group score. Spresas study was partly supported by Janssen 1.-Santini et al, Blood 122(13), 2013. 2.-Hellstršm-Lindberg, Br J Haematol 120(6), 2003. 3.-D'ez Campelo, EHA 2015 meeting, P244. Disclosures Díez Campelo: Novartis: Research Funding, Speakers Bureau; Janssen: Research Funding; Celgene: Research Funding, Speakers Bureau. Off Label Use: Use of erythropoietic stimulating agents for anemia in patients with myelodysplastic syndromes. Ramos:JANSSEN: Honoraria, Membership on an entity's Board of Directors or advisory committees; AMGEN: Consultancy, Honoraria; NOVARTIS: Consultancy, Honoraria; CELGENE: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Falantes:Celgene: Honoraria. Garcia:Celgene: Research Funding. Sanz:JANSSEN CILAG: Honoraria, Research Funding, Speakers Bureau.

Background Therapy-related Myelodysplastic Syndromes (t-MDS) are those MDS occurring after cytotoxic and/or radiation therapy administered for a prior neoplastic or non-neoplastic disorder. Their prognosis is generally very poor. The commonly used risk prognostic models for MDS (IPSS and IPSS-R) are not validated in this entity as they were developed after the exclusion of therapy-related cases (Greenberg et al. Blood 1997; Greenberg et al. Blood 2012). Aims The main aims of this study are: a) to report clinical findings and overall survival on 233 patients with t-MDS, and to compare them with a large series of de novo cases; b) to test if IPSS-R is applicable to t-MDS patients. Patients and methods The study is based on the Spanish Registry for MDS, a retrospective database that includes more than 10000 cases. The investigators were asked to fill in a questionnaire regarding prior disease (PD) and prior therapy in those cases reported to be t-MDS. Herein are described the clinical features and overall survival of the first 233 cases with the required information, and compared with patients with de novo MDS from a single center series (n=725). Log Rank test was applied to asses IPSS-R in t-MDS group. Results The 233 reported patients were diagnosed between January 1993 and February 2014. The series includes 104 women (44,6%) and 129 men (55,4%). One hundred and two patients (43.9%) had a primary hematologic malignancy, 119 (51%) had a solid tumor, and 12 (5.1%) received cytotoxic therapy for autoimmune disorders. Ninety eight patients (42.6%) received only chemotherapy (CT), 45 (19.6%) received only radiotherapy (RT), 44 (19.1%) received combined modality treatment (CMT), and 43 (18.6%) received an autologous stem cell transplantation (ASCT). The median time of latency between PD and diagnosis in t-MDS group was 4.56 years (range: 0.03-29.63) in patients previously treated with CT or CMT, significantly lower than the observed after RT (8.54; range 0.83-23.02) or ASCT (8.64; range 2.87-28.32) groups (p=0.023 and p Conclusions In conclusion, our data supports the notion that t-MDS may contain entities with heterogeneous prognosis due to a diverse biological basis. The capacity of the IPSS-R for separating good prognostic from bad prognostic cases shown in this study could be very useful in the clinical setting in order to offer risk-adapted treatments to patients, although the development of a specific prognostic score for these entities would be needed. Disclosures No relevant conflicts of interest to declare.

Abstract 702 Despite that low and intermediate-1 (int-1) IPSS groups are commonly considered as low risk diseases with a median overall survival exceeding 60 months, some of these patients will evolve as higher risk myelodysplastic syndrome (MDS). Recently several new prognosis indexes (PI) have been proposed: The new IPSSr, WPSSr, MD Anderson for lower risk patients (MDA) Index, and the Spanish Group of MDS (GESMD) proposal that considers as high risk those patients with int-1 IPSS and at least one of the following: platelets A total of 2410 patients from the Spanish registry of MDS with low or int-1 IPSS were included. Median age was 74 years (42.6% female). The IPSS value was of: 0, 0.5 and 1 in 1314, 761 and 335 patients, respectively. The four poor risk variables defined by the GESMD confirmed its adverse predictive value for OS: granulocytes The distribution of patients across the four PI is detailed in the Table. These new PI identified between 16.9% and 46% of patients having a median OS of around 30 months within the int-1 patients (wide line in the table), but none of the PIs could identify such a poor prognosis patients in the low IPSS group. The PI that identified the highest number of patients with shorter OS was the new IPSSr, while MDA IP was the most discriminative in the Akaike analysis. In conclusion, IPSS is not discriminative enough in the int-1 group. In contrast, the application of the new PI can be employed to better identify poor prognosis patients within the int-1 group who could benefit from a high-risk approach. Table. Overall survival and AML evolution according to the different prognostic index. PROGNOSIS INDEX (AIC for the whole population/and for the Int-1) populations) PROGNOSIS GROUP IPSS LOW (N=1314) OS: 87.78 m (95% CI:74.5-101.0) AML EVOLUTION (3 years): 9.1% (95% CI: 6.9-11.3%) IPSS INT-1 (N= 1096) OS: 44.2 m (95% CI:39.1-49.3) AML EVOLUTION (3 years): 26.9% (95% CI: 23-30.8%) N (%) Overall Survival Median (95% CI) months AML evolution (3 years) % (95% CI) N (%) Overall Survival Median (95% CI) months AML evolution (3 years) % (95% CI) GESMD (12566.6/6425.9) LOW 1314 (100) 860 (78.5) 48.1 (40.9-55.3)* 25.1 (20.7-29.5)** HIGH 0 (0) 236 (21.5) 32.7 (39.1-49.3)* 34.3 (24.5-44.1)** MD. Anderson (12381.4/6357.2) LOW 508 (39.3) 130.3 (104.6-157.0)* 9% (5.4-12.6)! 109 (9.9) 115.2 (83.8-146.6)* 15.7 (6.5-24.9)* INT 781 (59.4) 69.7 (62.4-77.1)* 8.9% (6.9-11.9)! 653 (59.6) 51.3 (44.2-58.3)* 23.3 (18.3-28.3)* HIGH 25 (1.9) 58.4* (25.4-91.5)* ——–——–— 334 (30.5) 24.1 (19.3-28.9)* 39.9 (31.3-48.5)* IPSS-R (12409.9/6369.6) VERY LOW 690 (52.5) 118.8 (105.7-131.7)* 6.4% (4.2-8.6)*** 79 (7.2) 113.7 (39.9-187.4)* 17.8 (4.6-31)* LOW 602 (45.8) 65.9 (57.6-74.2)* 11.6% (7.8-15.4)*** 505 (46.1) 60.3 (53.3-67.2)* 18.2 (13.4-23)* INT 22 (1.7) 58.9 (25.2-92.7)* 26% (2-50)*** 416 (38) 30.5 (26.1-34.8)* 38.6 (30-47.2)* HIGH 0 (0) 95 (8.7) 21.2 (16.5-25.9)* 48.5 (32.5-64.5)* VERY HIGH 0 (0) 1 (0.1) WPSS-R (12477.4/6414.7) VERY LOW 517 (39.3) 115.2 (103.0-127.4)* 6.5 (3.7-9.3)$ 76 (6.9) 56.5 (38.2-74.9)* 22.8 (10.6-35)* LOW 524 (39.9) 78.5 (66.7-90.3)* 12.1 (7.7-15.5)$ 289 (26.4) 61.3 (48.3-74.2)* 19.2 (12.4-25.6)* INT 61 (4.6) 46.0 (30.8-61.1)* 13.7 (3.1-24.3)$ 386 (5.2) 42.5 (32.8-52.2)* 27.8 (20.8-34.8)* HIGH 3 (0.2) 185 (16.9) 24.11 (19.4-28.8)* 49.3 (35.7-62.9)* VERY HIGH 0 (0) 4 (0.4) NOT EVAL 209 (15.9) 87.8 (74.6-101.3)* 7.2 (3-11.4)$ 156 (14.2) 48 (30.8-65.2) 18.3 (9.1-27.5)* AIC: Akaike Information Criteria. Int: Intermediate, Not Eval: Not evaluable, CI: Confidence interval. * P Figure. Actuarial curves of overall survival according to the different PI. Figure. Actuarial curves of overall survival according to the different PI. Disclosures: No relevant conflicts of interest to declare.