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SARS-CoV-2 infection can impact survival of patients with acute myeloid leukemia (AML). International experts recommend considering delaying or stopping AML treatment, test patients who need intensive induction and s prioritizing outpatient treatment. However there is little published evidence in AML. Objective To analyze the clinical futures and outcome of SARS-CoV-2 infection in AML patients. Methods and patients Observational multicenter study between March and May 2020; 117 patients reported from 47 Spanish centers, but 13 had no PCR or antibody test documented, finally including 104 patients from 45 hospitals. Results The median age was 68 years, men (56.7% vs 43.3%), and the median time from AML diagnosis to SARS-CoV-2 was 4 months. The mean of comorbidities was 1.2, high blood pressure (40.4%), heart disease (17.3%), diabetes (13.5%), smoking (8.8%), chronic obstructive pulmonary disease or emphysema (7.7%), renal failure (6.7%) and liver dysfunction (1.9%). Cytogenetic risk was low in 16.9%, intermediate in 57.1% and high in 26.0%; 55.7% had active disease, 39.2% complete remission and 5.1% partial response. 29.4% were off-therapy and 70.6% under antileukemic treatment at the time of SARS-CoV-2: induction chemotherapy (25.3%), hypomethylating (19.3%), clinical trial (17.0%), consolidation chemotherapy (14.8%), venetoclax (3.4%), FLT3 inhibitors (3.4%) and/or maintenance (1.1%). Overall 3.7% were newly diagnosed (no prior therapy), 77.8% had received one line of treatment, 14.8% two and 3.7% four. 15.4% had prior allogeneic transplantation. Only 4.0% of the patients were asymptomatic, while the main signs and symptoms were fever (77.8%), pneumonia (75.0%), cough (65.3%), dyspnea (52.0%), diarrhea (20.4%), nausea and/or vomiting (12.2%), rhinorrhea (10.2%) and headache (7.4%). Analytical parameters were: neutrophils 3112 cells/µL (1900-7300), lymphocytes 1090 cells/µL (1000-3000), interleukin 6 118 pg/mL (0-100), ferritin 4505 ng/mL (15-150) and D-dimer 2823 ng/mL (20-500), with liver enzymes altered in 23.9% of cases. 84.2% received specific treatment for coronavirus infection: chloroquine or hydroxychloroquine (82.2%), lopinavir/ritonavir (54.0%), corticosteroids (39.6%), azithromycin (33.0%), tocilizumab (15.8%), plasma convalescent (3.0%), clinical trial medication (3.0%), remdesivir (2.0%) and/or anakinra (1.0%). The course was mild in 14.7% (no hospitalization), moderate in 32.0% and severe in 53.3%. The implementation of intensive measures was assessed in 48.2%(14.9% admitted to the ICU and the remaining 33.3% rejected). The mean time to negativization was 20.5 days, duration of symptoms 17.6 days and the hospital stay 11.1 days. In 48.1% of the cases treatment for AML was maintained, in 26.6% delayed and in 25.3% modified due to coronavirus disease.47.5% died, establishing an association between mortality and age over 60 years (58.3% vs 36.4%, p=0.043), ≥2 lines of treatment (72.7% vs 44.3%, p=0.020), active disease (62.5% vs 29.4%, p=0.002) and pneumonia (61.2% versus 22.7%, p=0.002). Overall 47.5% overcame the infection, and in 5.0% SARS-CoV-2 genetic material was still detected at the time of analysis. A non-significant lower mortality rate was observed among: previous transplantation (45.7% vs 64.3%, p=0.19), neutrophil >1900 cells/µL (41.1% vs 60.0%, p=0.09), lymphocyte >1000 cells/µL (42.9% vs 63.6%, p = 0.09) and hydroxychloroquine/chloroquine plus azithromycin (35.3% vs 60.0%, p=0.10). Conclusions SARS-CoV-2 infection produces high mortality among AML patients. Mortality was correlated with age, active disease and pneumonia. Disclosures Martinez-Lopez: Janssen-cilag: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Research Funding; Novartis: Consultancy; Janssen: Consultancy, Honoraria; Incyte: Consultancy, Research Funding.

BACKGROUND The revised genetic risk classification established by the European Leukemia Net (ELN) in 2017 stratifies patients diagnosed with acute myeloid leukemia (AML) into 3 prognostic categories (favourable, intermediate, and adverse) based on cytogenetic and molecular characteristics.The ELN classification is widely accepted in AML patients despite the fact that validation studies were performed in participants who received exclusively first-line treatment with intensive chemotherapy. For this reason, it is not well established whether the ELN risk groups are applicable to patients on non-intensive first-line treatment. OBJECTIVES - To describe and compare baseline characteristics at diagnosis between patients with AML treated with intensive and non-intensive therapy. - To assess whether the ELN prognostic classification is applicable in these subgroups of patients. METHODS We retrospectively analysed patients with newly diagnosed AML admitted to our center between 2007 and 2020. Patients with acute promyelocytic leukemia (M3), patients younger than 18 years old and/or patients who received exclusively supportive treatment were excluded. Demographic and clinical data, disease characteristics at diagnosis and first-line treatment were collected. Cytogenetic and molecular characteristics were used to classify patients in ELN risk groups. RESULTS Of the total of patients (n=218), one hundred and fifty-six (71.6%) received intensive chemotherapy treatment, while 62 (28.4%) were treated with non-intensive strategies. Idarubicin and cytarabine based schemes regimens (IA) were administered in most patients (98.6%) who received intensive treatment while the rest received fludarabine based regimens. One patient (0.6%) was treated with danurubicin and cytarabine liposome (CPX-351). Fifty-four (87%) patients treated with non-intensive regimens received hypomethylating agents, mostly azacitidine. Five patients (8%) were treated with venetoclax in combination with a hypomethylating agent. Table 1 shows the characteristics at diagnosis in both groups of patients. Patients who received intensive chemotherapy were younger and had higher leukocyte count, LDH values and a higher percentage of blasts in peripheral blood and bone marrow with a median of 40% and 62% blasts respectively. On the other hand, patients under non-intensive treatment more frequently presented a past history of hemopathy and a higher percentage of bone marrow dysplasia. Regarding ELN stratification significant differences were found between both groups. Patients who received aggressive chemotherapy vs patients who did not, were classified in low (28% vs. 7%), intermediate (36% vs. 58%) and high risk (36% vs. 35%) respectively (Figure 1). At the end of the follow-up, 41% of the patients who had received intensive therapy were alive while only 6.5% of the patients who had received non-intensive treatment were alive. Significant differences in survival were observed between both groups (p In the intensive chemotherapy group, significant differences in survival were observed according to ELN risk stratification (p However, in patients receiving non-intensive therapies, there were no significant differences in survival among different prognostic categories (p=0.06). In this group, 1-year OS was 25%, 57.6% and 40.7% and median OS was 2.1, 14.8 and 10.1 months for low, intermediate and high-risk groups respectively. See Figure 2. CONCLUSIONS: As validated in previous trials, ELN classification constitutes an adequate prognostic marker for patients with newly diagnosed AML treated with intensive chemotherapy. In our series, this classification does not appear to be a good predictor of survival for patients diagnosed with AML who initiated non-intensive treatments. Further validation in prospective studies are needed to better classify this growing subgroup of patients in clinical practice. Figure 1 Figure 1. Disclosures Martín-Rojas: Celgene-BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees. Font Lopez: Pfizer: Membership on an entity's Board of Directors or advisory committees; 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. Kwon: Novartis, Celgene, Gilead, Pfizer: Consultancy, Honoraria.

INTRODUCTION Several studies have shown that morphological remission at day 14 is a predictor of post-induction response in patients with acute myeloid leukemia (AML) undergoing an intensive treatment. However, the role of measurable residual disease (MRD) by multiparameter flow cytometry (MFC) at day 14 remains unknown. The aim of our study is to explore the role of MRD at day 14 and its association with outcomes of patients with AML undergoing an intensive treatment. METHODS We conducted a retrospective study in adult patients with newly a diagnosed AML in our center between 2007 and 2020. Adult patients who received intensive chemotherapy, excluding those with an acute promyelocytic leukemia, were included. Bone marrow aspiration was performed at day 14 after induction to assess morphological response and MRD by MFC. Early blast clearance (EBC) was defined as RESULTS A total of 131 patients were analyzed. Median age was 55.6 years (IQR 42.3-64.2). The most frequent AML subtype was AML with myelodysplasia-related changes (34.4%), followed by NPM1-mutated AML (32.1%). The most commonly used induction regimen was "7+3" (96.2%) (Table 1). On day 14 bone marrow aspiration, median cellularity was 0.5/5 (IQR 0.5-1). 107 patients (81.7%) showed a blast reduction >50% compared to diagnosis and 87 patients (66.4%) had less than 5% of blasts. In this latter group, 28.6% of patients had a positive MRD and 71.4% had a negative MRD. NPM1-mutated AML showed the highest EBC rates while AML with myelodysplasia-related changes had the lowest rates (83.3% versus 55.5%; p=0.04). Furthermore, there were statistically significant differences in EBC rates based on the 2017 European Leukemia Net risk stratification, with 80% of EBC in low risk, 66.6% in intermediate risk and 53.4% in high risk AML (p=0.038). No differences were observed in MRD at day 14 based on AML subtypes or risk stratification. We subsequently analyzed the negative (NPV) and positive predictive values (PPV) of day 14 bone marrow aspiration results by morphology and MFC to predict post-induction results. As a predictor of post-induction CR, day 14 EBC had a NPV of 82% and a PPV of 69%, while day 14 MRD had a NPV of 86% and a PPV of 49%. However, for predicting post-induction MRD, day 14 EBC had a NPV of 49% and a PPV of 15%, while day 14 MRD had a NPV of 71% and PPV of 74%. The correlation between day 14 and post-induction bone marrow aspiration is shown in Table 2. Bivariate analysis showed that achieving CR with negative MRD in post-induction bone marrow aspiration was associated with EBC (p CONCLUSION Patients showing EBC with negative MRD on day 14 bone marrow aspiration are more likely to achieve post-induction CR with negative MRD, with day 14 MRD by MFC being the only independent factor able to predict post-induction CR with negative MRD in our cohort. However, further prospective studies are needed to confirm our findings. Figure 1 Figure 1. Disclosures Martín-Rojas: Celgene-BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees. Kwon: Novartis, Celgene, Gilead, Pfizer: Consultancy, Honoraria.

Introduction Donor cell leukemia (DCL) is a rare complication of allogeneic stem cell transplantation (allo-SCT). The leukemic transformation of otherwise healthy donor stem cells provides a useful in vivo model to study the mechanisms involved in leukemogenesis. The objective of the present study is to study the dynamics of emergence of mutations that precede the development of DCL. Material and methods We report the case of a female patient diagnosed of acute lymphoblastic leukemia with t(1;19), who developed normal karyotype acute myeloid leukemia (AML) of donor origin 16 months after unrelated cord blood transplantation (UCBT). Whole exome sequencing(SureSelect-XT Human exon capture 50Mb Agilent Technologies) was performed by next generation sequencing (Hiseq 2000 Illumina) on bone marrow samples post allo-SCT, obtained in the days +98, +189, +350, +486 (DCL diagnosis) and + 569 (DCL relapse) as well as on the UCB unit used in SCT. The exome of bone marrow samples post allo-SCT were aligned to the human reference genome (NCBI build 37/hg19), non-synonymous variants in the coding regions of genes related to leukemia were selected and matched to the UCB exome to identify the acquired variants. Variants meeting such criteria were evaluated with three softwares (SIFT, Polyphen and Mutation Taster) to predict their functional effects. The UCB exome was aligned to the human reference genome (NCBI build 37/hg19). Results In silico variants analysis revealed progressive emergence of multiple mutations related to the development of leukemia in bone marrow samples post allo-SCT (Figure 1). Interestingly three of the mutated genes (PTPN11, NRAS, MAP2K1) are part of the same cellular pathway (RAS-MAPK). In addition, mutations in leukemic subclones that disappear after chemotherapy were indentified, as well as the acquisition of new mutations in resistant subclones (Figure 2). Finally a mutation in SH2B3 gene, a gene that encodes for a regulatory protein of the JAK-STAT pathway, which links strongly to JAK2 inhibiting the activation of the pathway, was detected in the CBU. Conclusions The present study reveals the acquisition of additional somatic mutations in donor cells during leukemogenesis, including mutations not previously described in AML initiation (POU2F2, CA9, POU4F1, FMN2, TLR9, ELF5). Although the cause of DCL onset seems to be multifactorial, the infusion of a CBU with pre-leukemic potential due to mutation in SH2B3 in a context of residual toxicity in recipient as a result of pre-transplant chemotherapy, a post-transplant environment characterized by a decreased immune surveillance may well have played role in the case here reported. The study of a greater number of DCL cases by next generation sequencing could help to understand the process of leukemogenesis. Figure 1 Mutations related to the onset of donor cell leukemia after hematopoietic transplantation. Figure 1. Mutations related to the onset of donor cell leukemia after hematopoietic transplantation. Figure 2 Dynamic of mutation acquisitions in leukemic clones.(DCL: Donor cell leukemia, CBU: Cord blood unit, CBT: Cord blood transplantation, Quim: Quimerism, CQ: Complete quimerism) Figure 2. Dynamic of mutation acquisitions in leukemic clones.(DCL: Donor cell leukemia, CBU: Cord blood unit, CBT: Cord blood transplantation, Quim: Quimerism, CQ: Complete quimerism) Disclosures No relevant conflicts of interest to declare.

Background: We have overcome the limitations of 40 years of ex vivo testing. The aim of this study is to determine the ability of Vivia's novel test to predict the complete remission (CR) rates after induction chemotherapy with cytarabine (Ara-C) and idarubicin (Ida) in 1st line AML. Material and Methods: Bone marrow samples from adult patients diagnosed with de novo AML in Spanish centers from the PETHEMA group were included. Whole marrow samples maintaining their Native Environment were incubated for 48h in well plates containing Ara-C, Ida, or their combination. Pharmacological responses are calculated using population models. Induction response was assessed according to the Cheson criteria (2003). Patients attaining a CR/CRi were classified as responders and the remaining as resistant. Results: 390 patient samples were used to calculate the dose response (DR) curves for Ara-C alone, Ida alone, and their synergism. For clinical correlation we used 142 patients with median 56 years. The strongest clinical predictor was the Area Under the Curve (AUC) of the DR of Ara-C, and the AUC of IDA. The GAM models revealed a significant relationship between the AUC of the concentration-effect curves of both, idarubicin and, particularly, Ara-C, with greater values associated to higher probabilities of post-induction resistance. The fitted Generalized Additive Method predictions of expected values for each patient were in turn related to overall survival when a discrimination value to define positive and negative test results that prioritized specificity over sensitivity was chosen based on equaling positive and negative predictive values (Fig 1A). Prioritizing specificity over sensitivity reflects the higher cost of false positive over false negative decisions: only in very rare instances, an effective treatment would be erroneously negated to a sensitive patient at the expense of overlooking a number of resistant patients. However, the later patients could take their chances on re-induction therapy. While for diagnostics sensitivity and specificity should both be optimized, for Personalized Medicine the positive and negative predictive values should be optimized preferentially because they define the patient response correlation. Fig 1B shows a table illustrating the correlation between clinical outcome (columns) and the test predictions (lines). From a diagnostic criteria (columns), clinically resistant patients (1st column) are not well predicted with a Sensitivity of 51%, while clinically sensitive patients (2nd column) are very well predicted with a Specificity of 94%. From a Precision Medicine criteria (Lines), patients predicted resistant (1st line) and well predicted with 80% positive predictive value, similar to patients predicted sensitive (2nd line) well predicted with 79% Negative Predictive Value. The test does not properly identify 23/142 that are clinically resistant and the test predicts as sensitive (bottom left quadrant right panel). This mismatched subgroup mimics the problems from molecular markers where a resistant clone present in a minority of leukemic cells cannot be detected yet drives the patient response. However, this group mismatch does not prevent a good correlation with the test predicted outcomes. Flow cytometry identified 2 clones in 75% of these 23 samples, and we revised all samples analyzing each of 2 clones separately whenever they were present. Results did not change by this clonal analysis, suggesting flow cytometry may not identify resistant clones. Future improvements of the test adding 16 concentrations to the dose response curves may be able to detect the presence and parameters of these resistant clones driving patient response. Conclusions: This novel test is able to predict the clinical response to Ida + Ara-C induction with overall correlation and predictive values of 80%, higher than ever achieved. It is significantly higher than the current clinical response rate of 66.7%. Thus this novel test may be valuable information to guide 1st line patient therapy. Figure 1. ROC curve and clinical correlation Figure 1. ROC curve and clinical correlation Disclosures Ballesteros: Vivia Biotech: Employment. Cordoba:Celgene: Research Funding. Ramos:GlaxoSmithKline: Honoraria; Janssen-Cilag: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Honoraria; Celgene Corporation: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Honoraria. Gaspar:Vivia Biotech: Employment. Gorrochategui:Vivia Biotech: Employment. Rojas:Vivia Biotech: Employment. Gomez:Vivia Biotech: Employment. Hernández:Vivia Biotech: Employment. Robles:Vivia Biotech: Employment.

Abstract 4557 BACKGROUND: Natural killer (NK) cells are innate immune effectors that directly lyse virally infected or malignant cells. There are 2 different subsets of NK cells with distinct phenotypic and functional characteristics: the CD56dim subset, which composes 90% of peripheral blood NK cells and has a cytotoxic function, and the CD56bright subset, which cooperates with dendritic cells and T cells in lymph nodes to secrete interferon and promote adaptive immune responses. NK cells are the first donor-derived lymphocyte subset to reconstitute after hematopoietic stem cell transplantation, reaching normal levels after 1 month. Nearly all phenotyping studies of NK subsets after haploidentical hematopoietic stem cell transplantation (HHSCT) reveal a rapid reconstitution of NK cells towards the CD56bright subset. In addition, Y.-J. Chang et al found the highest 2-year survival in patients with a high number of CD56bright NK cells after unmanipulated HHSCT. We analyzed reconstitution of the NK compartment between days 90 and 180 after unmanipulated bone marrow HHSCT with reduced intensity conditioning (RIC). METHODS: Six adults received unmanipulated bone marrow HHSCT after RIC (fludarabine 30 mg/m2 [day –6 to –2], cyclophosphamide 14.5 mg/kg [day –6 and –5], and busulfan i.v. 3.2mg/kg [day –3]) at our institution between July 2007 and July 2010. Prophylaxis for acute graft-versus-host disease (GvHD) consisted of cyclophosphamide 50mg/kg (days +3 and +4) and cyclosporine A and mycophenolate mofetil from day +5 onwards. We monitored the reconstitution kinetics of circulating NK cells (CD56+, CD3–), and the CD56bright and CD56dim subsets by multiparametric flow cytometry (FC 500 Beckman® Coulter) at day +90 and day +180 after transplantation. Patient characteristics and clinical outcomes are shown in Table 1. 6 patients who underwent allogeneic HLA-identical sibling HSCT with RIC during the same period were used as controls. RESULTS: After HHSCT, NK cells reached normal levels in all patients but one at day +90, with a median number of NK cells of 111/mm3 (range, 25–195/mm3). At day +180 the median number of NK cells was 92/mm3 (range, 4–272/mm3). When we analyzed the absolute number of CD56bright and CD56dim subsets at day +90, we observed 2 patterns: Two patients showed skewed NK cell reconstitution towards CD56bright (Patient no. 3: 54 CD56bright/mm3; 11 CD56dim/mm3. Patient no. 4: 70 CD56bright/mm3; 17 CD56dim/mm3). Three patients reconstituted with a CD56dim/CD56bright ratio towards the CD56dim cell subset, similar to that of healthy adults (Patient no. 1: 17 CD56bright/mm3; 178 CD56dim/mm3. Patient no. 5: 9 CD56brigh/mm3; 135 CD56dim/mm3. Patient no. 6: 20 CD56bright/mm3; 116 CD56dim/mm3). One patient did not achieve adequate NK cell reconstitution (Patient no. 2: 15 CD56bright/mm3; 10 CD56dim/mm3). In contrast, in the control group, an increase in the CD56bright NK cell subset was not observed in any of the patients at any point. It is worth noting that 2 of the 3 patients with better clinical outcome (no GvHD, no relapse), namely patients no. 3 and no. 4 were the ones with skewed NK cell reconstitution towards the CD56bright NK cell subset. The other patient with a better clinical outcome (patient no. 6) had a normal CD56dim/CD56bright ratio at day +90. However, he showed an early CD56bright reconstitution (363 CD56bright/mm3; 34 CD56dim/mm3) in an additional determination on day +30. NK cell subsets reconstitution kinetics is shown in Figure 1. CONCLUSIONS: In our experience, NK cell reconstitution is adequate after RIC unmanipulated bone marrow HHSCT. Some patients recovered with a high proportion of CD56bright NK cells, as previously reported in other studies on HHSCT. Although limited by the sample size, our results are consistent with the previously observed survival advantage of patients with high early levels of CD56bright NK cells after unmanipulated haploidentical transplantation. Disclosures: No relevant conflicts of interest to declare.

Abstract 4825 Introduction: The majority of patients with classical Hodgkinxs Lymphoma (cHL) are cured with primary treatment. However, a significant proportion of patients will not achieve a complete response (CR) or relapse after completion of initial therapy and need to be rescued with high-dose chemotherapy and stem cell transplantation (SCT): autologous (aSCT) and/or alogeneic (Alo-SCT). The identification of clinical and biological characteristics of these patients at diagnosis is still a challenge and the most prognostic systems used to date fail to identify a proportion of patients with worse prognosis. The best understanding of the biology of cHL could help to identify these patients and different groups works in the use of biological marker as determinants of clinical outcome. Bcl2 over-expression has been described in cHL and seems to be an independent marker associated to bad prognosis in probably relation with alterations in apoptosis regulatory molecules. Objetive: To retrospectively analyze the frequency of Bcl2 protein over-expression in tissue biopsies of patients diagnosed with cHL, which required intensive treatment in our centre. Patients and Methods: We revised clinical data and samples at diagnosis of patients with cHL who received SCT (aSCT or/and Allo-SCT) due to partial remission, relapse or progression and we determined Bcl2 expression protein by immunohistochemistry. All patients received at least 2 lines of treatment previous to intensive treatment with SCT. We analyzed the expression of Bcl2 according to each patient histology: Nodular Sclerosis (NE), Mixed cellularity (MC), Lymphocyte-rich (LR), and Lymphocyte-depleted (LD). Results: Between September 1997 and May 2010, 39 patients with cHL required intensive treatment in our center: 32 aSCT and 7 Allo-SCT due to partial remission, refractory, relapse or progression after first line of treatment. Average age was 32 years (range: 18–64), males: 25/females 14. The characteristics of patients and remission status at transplant are described in table 1. We had available samples at diagnosis from 31 out of 39 patients (80%): 20 NE, 5 MC, 6 LR and we found over-expression of Bcl2 in 17/20 (85%) NE; 5/5(100%) MC and 2/6 LR (33%). Conclusions: Our results suggest that over-expression of Bcl2 is frequent in patients with cHL which needed intensive treatment after failure of the first line of therapy (particularly with NE and MC). Further studies are needed to confirm the worse prognosis of Bcl2 expression in cHL and if may be useful at diagnosis in association with other clinical parameters to identify patients with poor prognosis. Table 1 . CLASSICAL HODGKIN LYMPHOMA (c HL) NODULAR SCLEROSIS cHL MIXED CELLULARITY cHL LYMPHOCYTE-RICH cHL LYMPHOCYTE-DEPLETED cHL N (39) 23 8 7 1 Sex (F/M) 11/12 8/0 5/2 1/0 Age, Years: Md(R) 30(18-64) 37(31-62) 36(19-64) 54 Stage: I, II/III, IV 11/12 3/5 5/2 0/1 Bulky disease 14YES/9NO 1YES/7NO 2YES/5NO 1NO B Symptoms: (N) YES/NO (13) YES/(10) NO (3) YES/(5) NO (6) YES/(1) NO (1) YES Intensive treatment 5Alo-SCT/18aSCT 2AloSCT/6aSCT 7aSCT 1aSCT N:type of trasplant (status at transplant) 18: aSCT(11CR/5PR/2RF); 5:AloSCT(2PR with previous aSCT/1PR/1CR/1RF) 6: aSCT (4CR/2PR) 7:aSCT (6CR/1PR) 1:aSCT (in CR) 2: Alo-SCT(1CR/1PR with previus aSCT) Sample revised: N 20 (23 total NE) 5 (8 total MC) 6 (7 total LR) 0/1 Bcl2 expression: P/Nv (%) 17P/3Nv (85%) 5P/0Nv (100%) 2P/4Nv (33%) Not aplicable Alo-SCT: Alogeneic stem cell transplant; aSCT: autologous stem cell transplant; CR: Complete Remission; F: female; LD: Lymphocyte-deplete; LR: Lymphocyte rich; M: male; MC: mixed cellularity Md: median; n: number; NE: nodular sclerosis; Nv: negative; P: positive; PR: Parcial remision R: range; RF: refractory Disclosures: No relevant conflicts of interest to declare.

Abstract 1328 Introduction: CD4+CD25+ regulatory T-cells (Treg) play an important role in inducing and maintaining allogeneic tolerance and can inhibit graft-versus-host disease (GVHD) after allogeneic stem cell transplantation (SCT). However, the dynamics of donor and recipient Treg cell populations after Allo-SCT has not been studied yet. Objective: To analyze the dynamics of chimerism in Tregs and compare it to that of T lymphocytes (TL; CD3+) and whole blood leukocytes (WBL). Material and Methods: The study includes 53 patients subjected to Allo-SCT (myeloablative and non-myeloablative). PB samples were obtained weekly during the first month and every 14 days after day +30 until complete chimerism (CC) was achieved, and at fixed time-points (+30, +60, +90, +180, +365) thereafter. TL and Tregs were purified from PB until CC was achieved using inmunomagnetic technology (Miltenyi Biotec; CD3+ Microbeads and CD4+/CD25+ Treg Isolation Kit, respectively). Chimerism analysis was performed by microsatellite PCR (STR-PCR; AmpFlSTR SGM Plus; Applied Biosystems) on genomic DNA obtained from WBL as well as on cell lysates obtained from purified TL and Tregs. Complete chimerism was considered in samples with percentage of recipient cells Results: Median follow up for the whole cohort of patients was 338 days. CC was spontaneously achieved in WBL, TL and Tregs in 45/53 patients (85%) in a median time of 35.41, 38.8 and 42.5 days respectively. 5/3 patients (9%) suffered from graft failure/rejection showing mixed chimerism (MC) with increasing percentages of recipient cells both in WBL and leukocyte lineages. 3/53 patients (6%) maintained mixed chimerism (MC) in WBL and leukocyte lineages at day +180, with no signs of graft rejection or disease relapse. Analysis of the chimerism dynamics of those patients who spontaneously achieve CC revealed two different groups: Group 1 included 25/45 patients who achieved CC at the same time in WBL, TL and Tregs. Group 2 included 20/45 patients who achieved CC in WBL while maintaining MC in TL and Tregs. Interestingly enough, 9/20 patients from Group 2 maintained MC in Tregs 7–75 days after achieving CC in both WBL and TL (Figure 1). In a preliminary analysis, the small sample size precluded from obtaining statistically significant associations between the dynamics of chimerism in Tregs and the development of complications such as relapse or GVHD after SCT. Conclusions: To our knowledge, this is the first study dealing with Treg chimerism after SCT. We have shown it is feasible and can be performed on a routine basis together with standard lineage specific chimerism follow up. Although there is an association between chimerism dynamics in Tregs and TL, this is not absolute and a percentage of patients maintain residual Tregs of recipient origin after WTL and TL have become of complete donor origin. In this small cohort, Treg chimerism did not influence the development of post-SCT complications. Analysis of a larger and more homogeneous cohort would allow establishing the usefulness of Treg chimerism testing for the management of transplanted patients. Disclosures: No relevant conflicts of interest to declare.