scholarly journals Clonal Relapse Dynamics in Acute Myeloid Leukemia Following Allogeneic Hematopoietic Cell Transplantation

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 611-611
Author(s):  
Clara Wienecke ◽  
Bennet Heida ◽  
Katrin Teich ◽  
Konstantin Büttner ◽  
Alessandro Liebich ◽  
...  

Abstract Introduction The 2-year survival for AML patients relapsing after allogeneic hematopoietic cell transplantation (alloHCT) is <20%, independent of the choice of relapse-treatment. Relapse detection in its molecular state enables early interventions and possibly prevention of hematological recurrence of the disease. The role of measurable residual disease (MRD) monitoring for risk stratification has been described for pre and post-alloHCT MRD analyses. Yet, it remains unclear, if and by which lead-time NGS assessment can detect MRD before impending relapse. We hypothesize that the functional class of mutations determines the relapse kinetics in AML after alloHCT. Methods We identified mutations present at AML relapse after alloHCT by Illumina myeloid panel sequencing covering 48 AML associated genes. Peripheral whole blood samples were retrospectively collected before hematological relapse, with a minimum of one sample per patient at three months prior to relapse and if available, additional monthly samples. Amplicon-based NGS and bioinformatics error-correction were performed on those samples as described in Thol et al. 2018. Positive MRD was defined as MRD detectable above the limit of detection. In the last step, we performed polynomic curve interpolation to model relapse dynamics. Results MRD was assessed in 75 AML patients after alloHCT using 203 AML-related mutations present at the time of relapse, corresponding to a median of 2.7 trackable mutations per patient (range 1-7). In total, 305 MRD analyses were performed from peripheral blood (median 1.5 per mutation, range 1-5) prior to relapse. VAFs measured above the limit of detection (median LOD across all targets 0.0315) ranged from 0.0048-26% (median 1.3%). In 45 of 75 patients (60%), we detected MRD in at least one sample and one marker before relapse. Of those, 23 patients (51%) were MRD positive in all markers before relapse and 22 patients (49%) were MRD positive in some, but not all markers before relapse. The majority of MRD-positive patients (30 of 45) were first detected three or fewer months before relapse, whereas 15 (33%) of 45 patients were MRD positive more than 3 months before relapse. The median time to relapse from the first MRD-positive sample to relapse was 2.9 months (range 0.6-10.2). Among the 203 mutations found in relapse, 93 (46%) were detectable by MRD monitoring before relapse while the remaining 110 markers (54%) remained undetectable prior to relapse. Of note, 88 of those 110 markers (80%) were measured only once before relapse, indicating that frequent sampling increases the likelihood of MRD detection. Genes in which mutations were found mostly MRD-positive were TET2 (6 out of 6), ASXL2 (4 out of 5), SF3B1 (4 out of 5), and RUNX1 (7 out of 9). Mutations in WT1 (1 out of 13), NRAS (1 out of 8), FLT3-ITD (9 out of 29), and PTPN11 (1 out of 5) were among the most common MRD negative mutations before relapse. To assess clonal relapse dynamics, pre-relapse samples were assigned to the monthly interval that best matched the sampling time. If MRD was measured positive at one time point, all the following monthly intervals were considered MRD-positive, whether a sample was available for that interval or not. The fraction of positive samples from all samples per time point was plotted against time to relapse and the function was approximated by fifth-order polynomials. The percentage of patients being MRD positive increased markedly with shortened distance to relapse. Thus, 29% of patients were MRD positive at 3 months, 44% at 2 months and 66% 1 month prior to relapse. Summarized by functional gene classes, mutations in tumor suppressor genes and especially signaling genes showed a higher slope and thus a shorter lead-time to relapse than mutations in epigenetic modifier genes (Figure 2). Conclusion In summary, hematologic relapse can be detected in peripheral blood in 29, 44, and 66% of patients at 3, 2, and 1 months before relapse by NGS-MRD analysis, respectively. Mutations in epigenetic modifier genes show a higher fraction of MRD positivity before relapse than other mutations. In contrast, mutations in signaling genes show a shorter lead-time to relapse. Figure 1 Figure 1. Disclosures Ganser: Celgene: Honoraria; Novartis: Honoraria; Jazz Pharmaceuticals: Honoraria. Thol: Abbvie: Honoraria; Astellas: Honoraria; Novartis: Honoraria; Pfizer: Honoraria; Jazz: Honoraria; BMS/Celgene: Honoraria, Research Funding. Heuser: BergenBio: Research Funding; Bayer Pharma AG: Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS/Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding; Daiichi Sankyo: Membership on an entity's Board of Directors or advisory committees, Research Funding; Jazz: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Astellas: Research Funding; Tolremo: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Research Funding; Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 1091-1091
Author(s):  
Tarek H. Mouhieddine ◽  
Chidimma Nzerem ◽  
Robert A. Redd ◽  
Andrew Dunford ◽  
Matthew Joseph Leventhal ◽  
...  

Abstract Background: Recent studies have identified clinical and genomic factors contributing to worse clinical outcomes in patients with multiple myeloma (MM). Clonal hematopoiesis (CH) reflects the presence of somatic driver mutations in the blood or marrow of otherwise asymptomatic individuals. Using a variant allele frequency (VAF) cutoff of 2%, we recently reported CH in 21.6% of MM patients at the time of autologous stem cell transplant (ASCT) and found it was associated with shorter overall survival (OS) and progression-free survival (PFS) in those who did not receive maintenance therapy with an immunomodulatory drug (IMiD). However, this finding was based on a single tertiary center and only included MM patients who received ASCT. Methods: We studied a larger cohort of 986 newly diagnosed MM cases. Whole-exome sequencing (WES) data of peripheral blood and bone marrow samples of 986 MM patients (523 transplanted and 463 non-transplanted) from the Multiple Myeloma Research Foundation (MMRF) Clinical Outcomes in MM to Personal Assessment of Genetic Profile (CoMMpass, NCT0145429) study were analyzed. Both peripheral blood and tumor samples were analyzed to filter out myeloma mutations that could be contaminating the peripheral blood. Given the lower depth of coverage compared to prior targeted sequencing studies, small clones with a VAF below 2% were not detected. Altogether, the WES samples had a total depth of coverage of 117.68X. All data were analyzed using R version 3.5.0 (R Core Team). Results: Among the total cohort, 113 CH mutations were detected in 101/986 (10.24%) patients. CH was detected in 42/523 (8.03%) transplanted patients, compared to 59/463 (12.74%) non-transplanted patients. The most commonly mutated genes were DNMT3A, TET2, ASXL1, PPM1D, and TP53. The median age of the cohort was 63 years (range: 27 - 93), 60% were male, and median follow-up was 3.9 years (95% CI: 3.7 - 4.0). The presence of CH was associated with age (69 vs. 62 years, P < 0.001). As expected, the median age of transplanted patients was lower (60 vs. 67 years) than in the non-transplanted group, which likely explains the higher prevalence of CH detected in the non-transplanted group. CH was associated with recurrent bacterial infections (P = 0.01) and increased cardiovascular disease (P = 0.006), but not with cerebrovascular disease (P = 0.74) or coagulopathies (P = 0.65). There was a trend towards worse PFS in non-ASCT patients with CH who were not treated with IMiDs (1.8 years) compared to non-CH IMiD-treated patients (2.7 years) (P < 0.001). A CH effect on PFS was not detected in ASCT patients. OS was not different in those with or without CH in both ASCT and non-ASCT groups. 8 (0.8%) patients developed a second hematologic malignancy. CH at the time of MM diagnosis was not associated with an increased risk of developing a second hematologic malignancy (P = 0.58). To determine whether CH clones emerged or evolved during treatment, we examined serial samples from 52 patients (36 ASCT patients and 16 non-transplanted patients) with sequential samples. The median time between the first and second time point was 3.1 years (range: 1.0 - 5.4 years). At the first time point, only 3/52 (5.8%) patients had CH, but that number increased to 13/52 (25.0%) at the second time point. Five out of the 13 (38%) were non-transplanted patients. All but 1 patient were exposed to IMiDs. The most common emerging mutated gene was DNMT3A, found in 7 patient samples at the second time point, compared to 2 patients at the first time point. Conclusion: Using WES in a large cohort of newly diagnosed MM patients, we detected CH in 10.2% (VAF ≥ 2%) of patients. CH and non-IMiD treatment confers a shorter PFS in non-transplanted MM patients. However, throughout IMiD-based treatment, MM patients tend to acquire and/or expand previously undetected CH clones, particularly DNMT3A. The clinical significance of this clonal expansion during therapy is yet to be elucidated, and for now, this observation does not yet change clinical management. Figure 1 Figure 1. Disclosures Steensma: Novartis: Current Employment. Ebert: Deerfield: Research Funding; GRAIL: Consultancy; Exo Therapeutics: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Skyhawk Therapeutics: Membership on an entity's Board of Directors or advisory committees. Soiffer: NMPD - Be the Match, USA: Membership on an entity's Board of Directors or advisory committees; Gilead, USA: Other: Career Development Award Committee; Rheos Therapeutics, USA: Consultancy; Kiadis, Netherlands: Membership on an entity's Board of Directors or advisory committees; Juno Therapeutics, USA: Other: Data Safety Monitoring Board; Precision Biosciences, USA: Consultancy; Jazz Pharmaceuticals, USA: Consultancy; Jasper: Consultancy; Takeda: Consultancy. Sperling: Adaptive: Consultancy. Getz: Scorpion Therapeutics: Consultancy, Current holder of individual stocks in a privately-held company, Membership on an entity's Board of Directors or advisory committees; IBM, Pharmacyclics: Research Funding. Ghobrial: AbbVie, Adaptive, Aptitude Health, BMS, Cellectar, Curio Science, Genetch, Janssen, Janssen Central American and Caribbean, Karyopharm, Medscape, Oncopeptides, Sanofi, Takeda, The Binding Site, GNS, GSK: Consultancy.


Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 4761-4761
Author(s):  
Clara Chen ◽  
Philippe Armand ◽  
Basia Rogula ◽  
Karissa Johnston ◽  
Derek Peterson ◽  
...  

Introduction: Historically, patients with relapsed/refractory classical Hodgkin lymphoma (R/R cHL) who relapse after autologous hematopoietic cell transplantation (auto-HCT) have poor outcomes. In the phase 2 CheckMate 205 study (NCT02181738) of patients with R/R cHL and prior auto-HCT, patients in Cohort A were brentuximab vedotin (BV) naive, and those in Cohorts B and C had prior BV exposure. Nivolumab (nivo), an anti-PD-1 immune checkpoint inhibitor monoclonal antibody, was associated with a high response rate (71% Cohorts A+B+C; 65% Cohort A) and durable remissions (median duration of response 18 and 25 months, respectively). Notably, the 2-year overall survival (OS) rates were 87% in Cohorts A+B+C and 90% in Cohort A; the median OS was not reached (median follow-up 33 months; Armand et al. ASH 2018). These results appear better than those in prior studies in this patient population. In the phase 2 pivotal trial of BV (NCT00848926), patients with R/R cHL had a 2-year OS rate of approximately 65% (Chen et al. Blood 2016). Without direct head-to-head randomized trials, cross-trial comparisons have limitations primarily due to differences in patient populations and trial design, and the survival benefits of various treatments are difficult to distinguish. We used matching-adjusted indirect comparison (MAIC) to balance patient populations and then assess the efficacy and survival benefit of nivo relative to BV in patients with R/R cHL for whom auto-HCT had failed. Methods: Individual patient data (IPD) from patients receiving nivo in the CheckMate 205 study were matched to summary data from patients in the BV pivotal trial reported by Chen et al. IPD from Cohort A and combined Cohorts A+B+C of the CheckMate 205 study were re-weighted to match relevant baseline characteristics reported for BV. Pseudo-IPD were generated for BV from KM curves applying a published algorithm. Treatment outcomes (progression-free survival [PFS] and OS) were then compared across balanced trial populations and assessed using hazard ratios (HRs) generated via Cox regression and differences in the area under the curve (ΔAUC) from best-fitting parametric curves. For nivo, 2 well-fitting OS curves were selected for comparison, which conveyed optimistic and conservative assumptions. Restricted AUC at a specific time point is identical to mean survival time at that time point, thus ΔAUC was used as a summary metric to compare survival time between groups. Confidence intervals (CIs) for AUC estimates were generated via bootstrapping. Results: Patients receiving nivo from Cohort A (unmatched n = 63) and Cohorts A+B+C (unmatched n = 243) were matched to those receiving BV (n = 102) using age, sex, performance status score, B symptoms, prior radiotherapy, primary refractory disease, and best response to the most recent prior systemic regimen (matched size: Cohort A, n = 38, Cohorts A+B+C, n = 172). For Cohort A, MAIC analysis of nivo versus BV showed statistically significant reductions in the risk of death (HR, 0.11; 95% CI, 0.12-0.53; P < 0.001) and the risk of progression/death per investigator (HR, 0.54; 95% CI, 0.32-0.91; P = 0.02). Comparing mean survival time at 15 years using AUCs, the expected OS was estimated to range from 153 months (conservative) to 165 months (optimistic) for nivo versus 69 months for BV, with ΔAUC ranging from 85 (95% CI, 51-111) to 94 (72-113) months, respectively. The PFS per investigator at 5 years was estimated to be 32 months for nivo and 22 months for BV, with ΔAUC of 11 (95% CI, −1 to 22) months. MAIC analyses of Cohorts A+B+C produced similar findings (Figure), with the HR for nivo versus BV of 0.33 (95% CI, 0.21-0.53; P < 0.001) for OS, and 0.60 (0.43-0.83; P = 0.002) for PFS per investigator. Comparing AUC at 15 years, the expected OS ranged from 114 months (conservative) to 131 months (optimistic) for nivo versus 69 months for BV, with ΔAUC ranging from 46 (95% CI, 21-71) to 61 (36-83) months, respectively. The estimated PFS per investigator at 5 years was 29 months for nivo versus 22 months for BV, with ΔAUC of 8 (95% CI, 0.4-14) months. Conclusions: MAIC of Cohort A to BV suggests that nivo may provide a favorable OS compared with BV. Additionally, MAIC of Cohorts A+B+C with BV suggests that nivo alone or adding nivo after BV in patients with R/R cHL and prior auto-HCT may provide a meaningful OS benefit compared with BV alone. MAIC of Cohorts B+C with BV is ongoing. Study support: BMS. Writing support: Janice Zhou, Caudex, funded by BMS. Disclosures Chen: Bristol-Myers Squibb: Employment. Armand:Genentech: Research Funding; Sigma Tau: Research Funding; Infinity: Consultancy; Affimed: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Consultancy; Adaptive: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; ADC Therapeutics: Consultancy; Tensha: Research Funding; Roche: Research Funding; Otsuka: Research Funding. Rogula:Broadstreet HEOR: Employment; Bristol-Myers Squibb: Other: I am an employee of Broadstreet HEOR which was contracted by Bristol-Myers Squibb for the conduct of this work.. Johnston:Broadstreet HEOR: Employment; Bristol-Myers Squibb: Other: I am an employee of Broadstreet HEOR which was contracted by Bristol-Myers Squibb for the conduct of this work.. Peterson:Bristol-Myers Squibb: Employment, Equity Ownership. Connors:Bristol-Myers Squibb: Consultancy; Takeda Pharmaceuticals: Honoraria; Seattle Genetics: Honoraria, Research Funding. Lozano-Ortega:Broadstreet HEOR: Employment; Bristol-Myers Squibb: Other: I am an employee of Broadstreet HEOR which was contracted by Bristol-Myers Squibb for the conduct of this work..


Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 1346-1346
Author(s):  
Mat Makowski ◽  
Elshafa Ahmed ◽  
Sarah Schlotter ◽  
Rebecca Pearson ◽  
Rhonda Kitzler ◽  
...  

Abstract Background: Clinical outcomes for patients with HIV-related lymphomas who have undergone autologous hematopoietic cell transplantation (AHCT) are similar to HIV-negative patients (Alvarnas et al., Blood 2016). Here we report a detailed, longitudinal immunophenotypic and functional evaluation of immune recovery of patients enrolled on the BMT CTN 0803/AMC 071 multicenter phase II study (clinicaltrials.gov NCT01141712). Methods: Comprehensive analysis of cellular immunome was performed using 5 color flow cytometry. Acquisition and analysis was performed via FC500 cytometry analyzers with CXP software and prism plot. Comparisons were made between HIV+ and HIV- cohorts of peripheral blood mononuclear cell (PBMC) subsets at 56, 180, and 360 days post AHCT. The HIV- cohort was collected from 30 multiple myeloma patients enrolled in a longitudinal immune recovery study after AHCT (median age 52.5 years (18-71); 57% male, no post AHCT exposure to IMID or other treatment). Control samples were collected from 72 healthy volunteers (median age of 49 (21-68); 53%, M). A Wilcoxon rank sum test was utilized to compare the HIV+ and HIV- groups to controls and to each other at each time point for 18 immune cell subsets common to all three panels. An unsupervised analysis was performed utilizing a principal component analysis (PCA) to look for overall differences in the cohorts. Similar methodologies were used to compare HIV+ to controls that analyzed 100 PBMC subsets. Functional immune recovery was evaluated by IFNg Elispot assay where 2x105 PBMC collected at each time point were pulsed with control, EBV (BZLF1) or HIV (GAG) pepmix preparations. As a control for TCR responsiveness, anti CD3/CD28 antibody-beads were used to immobilize TCR in ELISPOT assay. T cell responses from PBMCs of each of the three time points of HIV+ patients on trial were compared to PBMCs from HIV- donors (n=6). Results: Wilcoxon Rank sum tests show significant differences between transplant patients and controls and between HIV+ and HIV- patients at all visits. There are fewer cell subsets significantly different at day 365 compared to day 56 or 120 in all comparisons. The PCA showed group differences between HIV+, HIV- and control subjects. CD3+/HLA-DR+ (late activation), CD8+/CD25- (cytotoxic T cells) and CD3+/CD314+ (T cells with activating NKG2D) were found to be more prevalent in HIV+ transplant patients. These findings may be consistent with expanded populations of chronically activated cytotoxic T lymphocytes in HIV+ transplant patients. Subsets of NK, Th1 and Th2 cells showed statistically significant differences between HIV+ (low), HIV- (higher) and controls (higher). When the principal components are plotted by visit there is a pattern of both HIV+ and HIV- transplant patients clustering closer to controls as patients recover from AHCT. The PCA was also utilized to compare the HIV+ cohort to controls which had the same panel of cell subsets tested and allowed for the use of 100 cell subsets in the analysis. This analysis showed a similar group separation and pattern of clustering closer to controls in later visits. These findings demonstrate complex interactions between T and NK cell subsets. Functional assessment of antigen-specific T cell responsiveness was evaluated in Elispot assays with EBV (BZLF1) and HIV (GAG) recall antigens and anti-CD3/CD28 controls. Of 30 evaluable patients, 28 HIV+ patients demonstrated measurable IFNg production in response to GAG (spots/2x105 PBMC, range: 8-615), 21 showed measurable response to BZLF1 pepmix (range 12-450); and all patients demonstrated responsiveness to anti CD3/CD28 stimulation. Magnitude of IFNg production from HIV+ samples was generally higher than that observed healthy, HIV- controls. Assessment of NK cell responsiveness is currently underway. Conclusions: While clinical outcomes following AHCT between HIV+ and HIV- patients is comparable, clear distinctions were observed with immune recovery of specific PBMC subsets during the first year following AHCT with differences diminishing as patients recover post transplant. Longitudinal immune responsiveness of PBMC from HIV+ patients to EBV and HIV recall antigens and TCR stimulation generally showed more robust IFNg production compared to PBMCs from HIV- volunteer controls. These data provide further justification supporting AHCT as an option for HIV+ patients provided they meet standard transplant criteria. Disclosures Little: This study was coordinated by the ECOG-ACRIN Cancer Research Group (Robert L. Comis, MD and Mitchell D. Schnall, MD, PhD, Group Co-Chairs) and supported by the National Cancer Institute of the National Institutes of Health under the following award number: Employment. Noy:Pharmacyclics, LLC, an AbbVie Company: Other: travel, accommodations, expenses, Research Funding. Krishnan:celgene: Consultancy, Speakers Bureau; takeda: Consultancy, Speakers Bureau; janssen: Consultancy, Speakers Bureau; onyx: Speakers Bureau. Hofmeister:Signal Genetics, Inc.: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Arno Therapeutics, Inc.: Research Funding; Incyte, Corp: Membership on an entity's Board of Directors or advisory committees; Janssen: Pharmaceutical Companies of Johnson & Johnson: Research Funding; Karyopharm Therapeutics: Research Funding; Takeda Pharmaceutical Company: Research Funding; Teva: Membership on an entity's Board of Directors or advisory committees. Forman:Mustang Therpapeutics: Other: Construct licensed by City of Hope. Lozanski:Boehringer Ingelheim: Research Funding; Beckman Coulter: Research Funding; Stemline Therapeutics Inc.: Research Funding; Genentech: Research Funding. Baiocchi:Essanex: Research Funding.


Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 4567-4567
Author(s):  
Sanghee Hong ◽  
Lisa Rybicki ◽  
Donna Corrigan ◽  
Betty K. Hamilton ◽  
Ronald Sobecks ◽  
...  

Introduction: Relapse is the most frequent cause of treatment failure after allogeneic hematopoietic cell transplantation (alloHCT). While transplant-related mortality has decreased substantially over the last few decades, little progress has been made in outcomes and no standard of care exists for patients (pts) with post-alloHCT relapse. In the recent era, several new therapies, including targeted agents, have been approved for ALL, AML, and MDS. We conducted a study to evaluate outcomes of pts with these diseases who relapse after alloHCT in the contemporary period with routine availability of these newer therapeutic agents. Methods: We performed a single-institution retrospective cohort study to review treatment strategies and outcomes of relapse post-alloHCT. We identified 420 adult pts who received their first alloHCT in 2010-2018 using any conditioning regimen or donor source. Overall, 115 (27%) pts experienced relapse (ALL=17/64 [27%], AML=67/242 [28%], MDS=31/114 [27%]) and were included in the analysis. Results: Myeloablative (54%) matched-unrelated donor grafts (50%) were the most common types of HCTs. Peripheral blood stem cell graft (49%) and bone marrow graft (48%) were used the most. Median time from alloHCT to relapse was 5 (range 1-65) months, and 83% of relapses occurred within the first year. Only 24% and 11% of pts experienced grade II-IV acute and any chronic GVHD prior to relapse, respectively. Seven of 17 pts had Philadelphia chromosome positive ALL. Mutation panel was tested in 56% of AML and MDS. Median follow-up period after relapse was 19 (range 6-80) months. The estimated survival after relapse for all diseases was 32% (95% CI 24-41%) at 6 months, 21% (14-28%) at 12 months, and 14% (8-21%) at 24 months (Fig 1). Excluding pts treated with supportive care only, the majority received a combination of different treatments; pts with ALL received median 3 (range 1-5), pts with AML received median 2 (1-4), and pts with MDS received median 1 (1-3) agent. Targeted therapies used for ALL pts included blinatumomab (n=5) and BCR-ABL targeting tyrosine kinase inhibitors with (n=2) or without (n=4) chemotherapy. Among AML pts, targeted agents were used in 15 pts (sorafenib [n=7], 2 each with enasidenib, gemtuzumab ozagamicin, and ivosidenib, and 1 each with venetoclax and SEL24 [a dual pan-PIM/FLT3 inhibitor]). One pt each was treated with enasidenib, gemtuzumab ozagamicin, and PTC299 (an inhibitor of VEGFA mRNA translation) followed by SEL24 for MDS. Second alloHCTs (n=5) were performed median 5 (range 1-16) months after first HCT and median 1 month (range 0-5 months) after relapse. Two pts received no bridging therapy, while 3 pts received chemotherapy (n=2) or donor lymphocyte infusions (DLI [n=1]) prior to the second transplant. DLI without second transplant was used in 25 pts at a median of 20 (range 3-18) months after ALL relapse, median 2 (range 0-13) months after AML relapse, and median 3 (range 1-5) months after MDS relapse. Following DLI, 53% pts developed GVHD. Targeted therapy was associated with a trend towards better survival compared to other therapies (Fig 2, HR 0.65, 95% CI 0.41-1.03, p=0.06). Based on multivariable analysis, matched unrelated (vs. matched sibling, HR 1.70, p=0.027) or haploidentical donor grafts (HR 2.69, p=0.003), presence of grade II-IV acute GVHD before relapse (HR 2.46, p<0.001), and less than 12 months from HCT to relapse (<6 vs. >12 months, HR 6.34, p<0.001; 6-12 vs. >12 months, HR 3.16, p=0.005) were adverse prognostic features with survival after relapse post-alloHCT (Table 1). Conclusion: Outcomes of pts with ALL, AML, and MDS who relapse following alloHCT remain poor in the contemporary era when several newer therapies, including targeted agents, are available for their treatment. Targeted agents were used only in a minority of post-alloHCT relapses likely due to the combination of pt status, absence of the target mutation, the agents' availability, and other factors. Pts who developed grade II-IV acute GVHD and had shorter "disease-free" duration from unrelated or haploidentical donor grafts had the significantly shorter survival following relapse. More innovative treatment strategies to prevent and treat relapse post-alloHCT are needed. Disclosures Hill: Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Celegene: Consultancy, Honoraria, Research Funding; Amgen: Research Funding; TG therapeutics: Research Funding; Genentech: Consultancy, Research Funding; Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Kite: Consultancy, Honoraria; Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AstraZeneca: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Takeda: Research Funding. Anwer:In-Cyte: Speakers Bureau; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees. Majhail:Atara Bio: Consultancy; Anthem, Inc.: Consultancy; Nkarta: Consultancy; Mallinckrodt: Honoraria; Incyte: Consultancy.


Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 266-266
Author(s):  
Sagar Patel ◽  
Saulius K. Girnius ◽  
Binod Dhakal ◽  
Lohith Gowda ◽  
Raphael Fraser ◽  
...  

Background Primary plasma cell leukemia (pPCL) is a rare plasma cell neoplasm with a high mortality rate. There have been improvements in multiple myeloma (MM) outcomes with novel induction agents and use of hematopoietic cell transplantation (HCT) with maintenance, but similar progress has not been reported for pPCL. We examined the outcomes of pPCL patients receiving novel agents with autologous (autoHCT) or allogeneic (alloHCT) approaches as reported to the Center for International Blood and Marrow Transplant Research (CIBMTR) in the modern era. Methods From 2008 to 2015, 348 pPCL pts underwent HCT (N = 277 - autoHCT and 71 - alloHCT) with 45% and 48% having research level data available, respectively. Cumulative incidences of non-relapse mortality (NRM) and relapse/progression (REL), and probability of progression-free survival (PFS) and overall survival (OS) were calculated. Cox multivariate regression was used to model survival after autoHCT only. Median follow-up in autoHCT and alloHCT was 48 and 60 months, respectively. Results AutoHCT Cohort Median age was 60 years and 93% received HCT within 12 months of diagnosis with 76% after a single line of induction (Table 1). 35% had high risk cytogenetics. 23% received bortezomib, doxorubicin, cisplatin, cyclophosphamide, and etoposide (VDPACE). Moreover, 40% received bortezomib (BTZ) and immunomodulatory drug (IMIID)-based triplets. Disease status at HCT was VGPR or better in 47%. 27% received maintenance therapy. At 4 years post-HCT, NRM was 7% (4-11%), REL 76% (69-82%), PFS 17% (13-23%), and OS 28% (22-35%) (Figures 1A, 2A, 2B). Disease status ≥VGPR at HCT and Karnofsky Performance Score &gt;90 significantly predicted superior OS in multivariate analysis. AlloHCT Cohort Median age was 53 years and 89% received HCT within 12 months of diagnosis (Table 1). 61% received a single alloHCT, while 39% used auto-alloHCT tandem approach. 42% had high-risk cytogenetics. 61% received total body irradiation with 44% receiving myeloablative conditioning. Use of VDPACE was higher at 41% in this cohort. VGPR status at HCT was similar (48%), while maintenance was used less often (12%). Grade II-IV acute GVHD occurred in 30% and chronic GVHD in 45%. At four years post-HCT, NRM was 12% (5-21%), REL 69% (56-81%), PFS 19% (10-31%), and OS 31% (19-44%) (Figures 1A, 1B, 2A, 2B). There were no differences in outcomes based on type of HCT. A comparison of post-HCT outcomes of CIBMTR pPCL patients from 1995 to 2006 showed that PFS and OS outcomes are inferior despite lower NRM in this modern cohort (Mahindra et al. Leukemia. 2012). In addition, analysis of SEER (1995-2009) and CIBMTR databases showed that use of HCT increased from 12% (7-21%) in 1995 to 46% (34-64%) in 2009. Conclusion More newly diagnosed pPCL patients are receiving modern induction regimens translating into a higher proportion receiving HCT, but without significant further benefit post-HCT. Post-HCT relapse remains the biggest challenge and further survival in pPCL will likely need a combination of targeted and cell therapy approaches. This study provides a benchmark for future HCT studies for pPCL. Disclosures Girnius: Takeda: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Genentech: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Dhakal:Takeda: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria. Shah:University of California, San Francisco: Employment; Indapta Therapeutics: Equity Ownership; Genentech, Seattle Genetics, Oncopeptides, Karoypharm, Surface Oncology, Precision biosciences GSK, Nektar, Amgen, Indapta Therapeutics, Sanofi: Membership on an entity's Board of Directors or advisory committees; Celgene, Janssen, Bluebird Bio, Sutro Biopharma: Research Funding; Poseida: Research Funding; Bristol-Myers Squibb: 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; Nkarta: Consultancy, Membership on an entity's Board of Directors or advisory committees; Kite: Consultancy, Membership on an entity's Board of Directors or advisory committees; Teneobio: Consultancy, Membership on an entity's Board of Directors or advisory committees. Qazilbash:Amgen: Consultancy, Other: Advisory Board; Bioclinical: Consultancy; Autolus: Consultancy; Genzyme: Other: Speaker. Kumar:Celgene: Consultancy, Research Funding; Takeda: Research Funding; Janssen: Consultancy, Research Funding. D'Souza:EDO-Mundapharma, Merck, Prothena, Sanofi, TeneoBio: Research Funding; Prothena: Consultancy; Pfizer, Imbrium, Akcea: Membership on an entity's Board of Directors or advisory committees. Hari:BMS: Consultancy, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Kite: Consultancy, Honoraria; Amgen: Research Funding; Spectrum: Consultancy, Research Funding; Sanofi: Honoraria, Research Funding; Cell Vault: Equity Ownership; AbbVie: Consultancy, Honoraria.


Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 32-33
Author(s):  
Aikaterini Poulaki ◽  
Theodora Katsila ◽  
Ioanna E Stergiou ◽  
Stavroula Giannouli ◽  
Jose Carlos Gόmez Tamayo ◽  
...  

Despite its major role in cellular biology, metabolism has only recently acquired a principal role in the research of the most profound cellular cycle disturbance, cancerous transformation. Myelodysplastic syndromes (MDS), a massively heterogeneous group of Hematopoietic Stem/ Progenitor Cell (HSC/HPC) disorders lie at the interface of normal differentiation and malignant transformation and have thus drew great attention due to their polymorphic presentation and elusive pathophysiology. Failure to establish a direct etiopathogenic relationship with specific genetic aberrations, along with the novel finding of a highly deregulated HIF1 activity by several unrelated research groups worldwide, including ours, urged us to investigate the metabolomic status of human bone marrow derived differentiating myeloid lineage in comparison with one another as well as with control samples. BM aspiration samples collected from 14 previously untreated MDS patients (10 patients with &lt;5% (1 SLD, 8MLD, 1del5q, group 1- G1) and 4 with &gt;5% BM blasts (2 EB1, 2 EB2group 2 - G2)) and 5 age matched controls. Myeloid lineage cells were isolated through ficoll bilayer protocol. All samples contained homogenous myeloid lineage subpopulations, assessedthrough optical microscopy. Two different metabolite extraction protocols were applied. The one with the best metabolites yield (50% MeOH, 30% ACN, 20% H2O) was chosen. LC-MS/MS analysis was performed using UPLC 1290 system (Agilent Technologies) coupled to a TripleTOF 5600+ mass spectrometer (SCIEX) equipped with SWATH acquisition, SelexION technology and an electrospray ionization source (ESI). A threshold of a minimum of three samples expressing a given metabolite was set against data sparsity. Data tables were scaled by data centering and setting unit variance. Log2 Foldcalculation and PLS analysis were performed for the two datasets (positive and negative ion-modes). R2 and Q2 for positive ion-mode and negative-ion mode analyses were determined. Both datasets were merged in a unique data table by taking into account maximum absolute log2 foldvalues, when a metabolite was found in both datasets. Warburg effect was evidently present in both the G1 and G2 vs control comparisons, yet the role of this stem like aerobic glycolysis seems markedly different in the two groups. While in the G2 group it serves to rescue glucose from complete burn in the mitochondrion and thus shuts it towards nucleotide synthesis (Pentose Phosphate Pathway found upregulated) with the added benefit of increased reduced Glutathione synthesis and improved redox state, in the G1 group proves detrimental. This greatly variable effect of the same phenomenon in the cellular fate lies upon the quality and functionality of the cellular mitochondrial content. G2 precursors presented functional mitochondrial (decreased NAD/NADH and FAD/FADH2) contrary to the G1 ones (Table). Failing TCA cycle, with increased NAD/NADH and FAD/FADH2 ratios and markedly increased ADP/ATP levels leads to FAs accumulation due to failure of effective adequate β oxidation. The uncontrolled increase in the NAD/NADH ratio stimulates upper glycolysis into a turbo mode further increasing the ADP/ATP, depleting cellular energy contents, engaging it to a never-ending deadly metabolism. The enormous abundance of upper glycolytic intermediates is relieved through phospholipid and ceramide synthesis, all found massively upregulated in both the MDS vs control yet also in the G1 vs G2 comparisons. FAs, mostly phospholipid and ceramide accumulation, interrupt the mitochondrial membrane lipidome further incapacitating metabolic integrity and inducing their autophagic degradation which further stimulates the Warburg effect. This type of metabolic reprogramming is eventually targeted to epigenetic modifier production, increased S-adenosyl-methionine, the major methyl group donor, 2-HydroxyGlutarate, a potent epigenetic modifier and notorious oncometabolite, Acetyl-Lysine, the major acetyl- group donor, even glutathione. We therefore present a model of an uncontrolled Warburg effect which in the G1 group confers premature death of the hematopoietic precursors, the ineffective hematopoiesis of MDS. Yet, under the pressure of the vastly upregulated epigenetic modifiers cellular fate changes, the G1 precursors adapt and transform to the G2 ones yet eventually to Acute Myeloid Leukemia blasts. Table Disclosures Vassilopoulos: Genesis pharma SA: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; Gilead: Research Funding; Abbvie: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees.


Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 2075-2075
Author(s):  
Sagar S. Patel ◽  
Betty K. Hamilton ◽  
Lisa Rybicki ◽  
Dawn Thomas ◽  
Arden Emrick ◽  
...  

Abstract Background MHC class I chain-related gene A (MICA) is a polymorphic ligand of the natural killer (NKG2D) receptor on immune effector cells. The activating NKG2D receptor controls immune responses by regulating NK cells, NKT cells and γδ-T cells. Dimorphisms at sequence position 129 of the MICA gene confers varying levels of binding affinity to NKG2D receptor. MICA previously has been associated with post-allogeneic hematopoietic cell transplantation (alloHCT) outcomes including graft-versus-host-disease (GvHD), infection, and relapse. However, it is unclear how MICA interacts with cytogenetic and somatic mutations in regards to these outcomes in acute myeloid leukemia (AML). Methods We conducted a single center, retrospective analysis of adult AML patients in first or second complete remission (CR1, CR2), who underwent T-cell replete matched related or unrelated donor alloHCT. Analysis was limited to those who had MICA data available for donors and recipients. In addition to cytogenetic risk group stratification by European LeukemiaNet criteria (Döhner H, et al, Blood 2016), a subset of patients had a 36-gene somatic mutation panel assessed prior to alloHCT by next-generation sequencing. Dimorphisms at the MICA-129 position have previously been categorized as weaker (valine/valine: V/V), heterozygous (methionine/valine: M/V), or stronger (methionine/methionine: M/M) receptor binding affinity. Fine and Gray or Cox regression was used to identify the association of MICA and outcomes with results as hazard ratios (HR) and 95% confidence intervals (CI). Results From 2000 - 2017, 131 AML patients were identified meeting inclusion criteria. Median age at transplant was 54 years (18-74), with 98% Caucasian. Disease status at transplant included 78% CR1 and 22% CR2. Cytogenetic risk stratification showed 13% of patients as favorable, 56% as intermediate, and 31% as adverse-risk. The five most common somatic mutations were FLT3 (15%), NPM1 (14%), DNMT3A (11%), TET2 (7%), and NRAS (6%). 60% of patients had a related donor. A myeloablative transplant was performed in 84% of patients and 53% had a bone marrow graft source. The most common conditioning regimen used was busulfan/cyclophosphamide (52%). 12% of patients were MICA mismatched with their donor. The distribution of donor MICA-129 polymorphisms were 41% V/V, 53% M/V, and 6% M/M. In univariable analysis, donor-recipient MICA mismatch tended to be associated with a lower risk of infection (HR 0.49, CI 0.23-1.02, P=0.06) and grade 2-4 acute GvHD (HR 0.25, CI 0.06-1.04, P=0.06) but was not associated with other post-transplant outcomes. In multivariable analysis, donor MICA-129 V/V was associated with a higher risk of non-relapse mortality (NRM) (HR 2.02, CI 1.01-4.05, P=0.047) (Figure 1) along with increasing patient age at transplant (HR 1.46, CI 1.10-1.93, p=0.008) and the presence of a TET2 mutation (HR 6.00, CI 1.77-20.3, P=0.004). There were no differences between the V/V and the M/V+M/M cohorts regarding somatic mutational status, cytogenetics and other pre-transplant characteristics and post-transplant outcomes. With a median follow-up of 65 months for both cohorts, 45% vs. 49% of patients remain alive, respectively. The most common causes of death between the V/V and the M/V+M/M cohorts was relapse (38% vs. 62%) and infection (31% vs. 8%), respectively. Conclusion While previous studies have demonstrated associations of somatic mutations and cytogenetics with survival outcomes after alloHCT for AML, we observed mutations in TET2 and the V/V donor MICA-129 polymorphism to be independently prognostic for NRM. Mechanistic studies may be considered to assess for possible interactions of TET2 mutations with NK cell alloreactivity. The weaker binding affinity to the NKG2D receptor by the V/V phenotype may diminish immune responses against pathogens that subsequently contribute to higher NRM. These observations may have implications for enhancing patient risk stratification prior to transplant and optimizing donor selection. Future investigation with larger cohorts interrogating pre-transplant AML somatic mutations with MICA polymorphisms on post-transplant outcomes may further elucidate which subsets of patients may benefit most from transplant. Disclosures Nazha: MEI: Consultancy. Mukherjee:Pfizer: Honoraria; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Projects in Knowledge: Honoraria; BioPharm Communications: Consultancy; Bristol Myers Squib: Honoraria, Speakers Bureau; Takeda Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; LEK Consulting: Consultancy, Honoraria; Aplastic Anemia & MDS International Foundation in Joint Partnership with Cleveland Clinic Taussig Cancer Institute: Honoraria. Advani:Amgen: Research Funding; Pfizer: Honoraria, Research Funding; Glycomimetics: Consultancy; Novartis: Consultancy. Carraway:Novartis: Speakers Bureau; Balaxa: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Jazz: Speakers Bureau; FibroGen: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Amgen: Membership on an entity's Board of Directors or advisory committees; Agios: Consultancy, Speakers Bureau. Gerds:Apexx Oncology: Consultancy; Celgene: Consultancy; Incyte: Consultancy; CTI Biopharma: Consultancy. 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. Maciejewski:Apellis Pharmaceuticals: Consultancy; Ra Pharmaceuticals, Inc: Consultancy; Alexion Pharmaceuticals, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Ra Pharmaceuticals, Inc: Consultancy; Alexion Pharmaceuticals, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Apellis Pharmaceuticals: Consultancy. Majhail:Incyte: Honoraria; Anthem, Inc.: Consultancy; Atara: Honoraria.


Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 42-43
Author(s):  
Prajish Iyer ◽  
Lu Yang ◽  
Zhi-Zhang Yang ◽  
Charla R. Secreto ◽  
Sutapa Sinha ◽  
...  

Despite recent developments in the therapy of chronic lymphocytic leukemia (CLL), Richter's transformation (RT), an aggressive lymphoma, remains a clinical challenge. Immune checkpoint inhibitor (ICI) therapy has shown promise in selective lymphoma types, however, only 30-40% RT patients respond to anti-PD1 pembrolizumab; while the underlying CLL failed to respond and 10% CLL patients progress rapidly within 2 months of treatment. Studies indicate pre-existing T cells in tumor biopsies are associated with a greater anti-PD1 response, hence we hypothesized that pre-existing T cell subset characteristics and regulation in anti-PD1 responders differed from those who progressed in CLL. We used mass cytometry (CyTOF) to analyze T cell subsets isolated from peripheral blood mononuclear cells (PBMCs) from 19 patients with who received pembrolizumab as a single agent. PBMCs were obtained baseline(pre-therapy) and within 3 months of therapy initiation. Among this cohort, 3 patients had complete or partial response (responders), 2 patients had rapid disease progression (progressors) (Fig. A), and 14 had stable disease (non-responders) within the first 3 months of therapy. CyTOF analysis revealed that Treg subsets in responders as compared with progressors or non-responders (MFI -55 vs.30, p=0.001) at both baseline and post-therapy were increased (Fig. B). This quantitative analysis indicated an existing difference in Tregs and distinct molecular dynamic changes in response to pembrolizumab between responders and progressors. To delineate the T cell characteristics in progressors and responders, we performed single-cell RNA-seq (SC-RNA-seq; 10X Genomics platform) using T (CD3+) cells enriched from PBMCs derived from three patients (1 responder: RS2; 2 progressors: CLL14, CLL17) before and after treatment. A total of ~10000 cells were captured and an average of 1215 genes was detected per cell. Using a clustering approach (Seurat V3.1.5), we identified 7 T cell clusters based on transcriptional signature (Fig.C). Responders had a larger fraction of Tregs (Cluster 5) as compared with progressors (p=0.03, Fig. D), and these Tregs showed an IFN-related gene signature (Fig. E). To determine any changes in the cellular circuitry in Tregs between responders and progressors, we used FOXP3, CD25, and CD127 as markers for Tregs in our SC-RNA-seq data. We saw a greater expression of FOXP3, CD25, CD127, in RS2 in comparison to CLL17 and CLL14. Gene set enrichment analysis (GSEA) revealed the upregulation of genes involved in lymphocyte activation and FOXP3-regulated Treg development-related pathways in the responder's Tregs (Fig.F). Together, the greater expression of genes involved in Treg activation may reduce the suppressive functions of Tregs, which led to the response to anti-PD1 treatment seen in RS2 consistent with Tregs in melanoma. To delineate any state changes in T cells between progressors and responder, we performed trajectory analysis using Monocle (R package tool) and identified enrichment of MYC/TNF/IFNG gene signature in state 1 and an effector T signature in state 3 For RS2 after treatment (p=0.003), indicating pembrolizumab induced proliferative and functional T cell signatures in the responder only. Further, our single-cell results were supported by the T cell receptor (TCR beta) repertoire analysis (Adaptive Biotechnology). As an inverse measure of TCR diversity, productive TCR clonality in CLL14 and CLL17 samples was 0.638 and 0.408 at baseline, respectively. Fifty percent of all peripheral blood T cells were represented by one large TCR clone in CLL14(progressor) suggesting tumor related T-cell clone expansion. In contrast, RS2(responder) contained a profile of diverse T cell clones with a clonality of 0.027 (Fig. H). Pembrolizumab therapy did not change the clonality of the three patients during the treatment course (data not shown). In summary, we identified enriched Treg signatures delineating responders from progressors on pembrolizumab treatment, paradoxical to the current understanding of T cell subsets in solid tumors. However, these data are consistent with the recent observation that the presence of Tregs suggests a better prognosis in Hodgkin lymphoma, Follicular lymphoma, and other hematological malignancies. Figure 1 Disclosures Kay: Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Rigel: Membership on an entity's Board of Directors or advisory committees; Juno Theraputics: Membership on an entity's Board of Directors or advisory committees; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Cytomx: Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma: Research Funding; Sunesis: Research Funding; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; MEI Pharma: Research Funding. Ansell:AI Therapeutics: Research Funding; Takeda: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Bristol Myers Squibb: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; ADC Therapeutics: Research Funding. Ding:Astra Zeneca: Research Funding; Abbvie: Research Funding; Octapharma: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Membership on an entity's Board of Directors or advisory committees; alexion: Membership on an entity's Board of Directors or advisory committees; Beigene: Membership on an entity's Board of Directors or advisory committees; DTRM: Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding. OffLabel Disclosure: pembrolizumab


Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 1962-1962
Author(s):  
Sandhya R. Panch ◽  
Brent R. Logan ◽  
Jennifer A. Sees ◽  
Bipin N. Savani ◽  
Nirali N. Shah ◽  
...  

Introduction: Approximately 7% of unrelated hematopoietic stem cell (HSC) donors are asked to donate a subsequent time to the same or different recipient. In a recent large CIBMTR study of second time donors, Stroncek et al. incidentally found that second peripheral blood stem cell (PBSC) collections had lower total CD34+ cells, CD34+ cells per liter of whole blood processed, and CD34+ cells per kg donor weight. Based on smaller studies, the time between the two independent PBSC donations (inter-donation interval) as well as donor sex, race and baseline lymphocyte counts appear to influence CD34+ cell yields at subsequent donations. Our objective was to retrospectively evaluate factors contributory to CD34+ cell yields at subsequent PBSC donation amongst NMDP donors. Methods. The study population consisted of filgrastim (G-CSF) mobilized PBSC donors through the NMDP/CIBMTR between 2006 and 2017, with a subsequent donation of the same product. evaluated the impact of inter-donation interval, donor demographics (age, BMI, race, sex, G-CSF dose, year of procedure, need for central line) and changes in complete blood counts (CBC), on the CD34+ cell yields/liter (x106/L) of blood processed at second donation and pre-apheresis (Day 5) peripheral blood CD34+ cell counts/liter (x106/L) at second donation. Linear regression was used to model log cell yields as a function of donor and collection related variables, time between donations, and changes in baseline values from first to second donation. Stepwise model building, along with interactions among significant variables were assessed. The Pearson chi-square test or the Kruskal-Wallis test compared discrete variables or continuous variables, respectively. For multivariate analysis, a significance level of 0.01 was used due to the large number of variables considered. Results: Among 513 PBSC donors who subsequently donated a second PBSC product, clinically relevant decreases in values at the second donation were observed in pre-apheresis CD34+ cells (73.9 vs. 68.6; p=0.03), CD34+cells/L blood processed (32.2 vs. 30.1; p=0.06), and total final CD34+ cell count (x106) (608 vs. 556; p=0.02). Median time interval between first and second PBSC donations was 11.7 months (range: 0.3-128.1). Using the median pre-apheresis peripheral blood CD34+ cell counts from donation 1 as the cut-off for high versus low mobilizers, we found that individuals who were likely to be high or low mobilizers at first donation were also likely to be high or low mobilizers at second donation, respectively (Table 1). This was independent of the inter-donation interval. In multivariate analyses, those with an inter-donation interval of >12 months, demonstrated higher CD34+cells/L blood processed compared to donors donating within a year (mean ratio 1.15, p<0.0001). Change in donor BMI was also a predictor for PBSC yields. If donor BMI decreased at second donation, so did the CD34+cells/L blood processed (0.74, p <0.0001). An average G-CSF dose above 960mcg was also associated with an increase in CD34+cells/L blood processed compared to donors who received less than 960mcg (1.04, p=0.005). (Table 2A). Pre-apheresis peripheral blood CD34+ cells on Day 5 of second donation were also affected by the inter-donation interval, with higher cell counts associated with a longer time interval (>12 months) between donations (1.23, p<0.0001). Further, independent of the inter-donation interval, GCSF doses greater than 960mcg per day associated with higher pre-apheresis CD34+ cells at second donation (1.26, p<0.0001); as was a higher baseline WBC count (>6.9) (1.3, p<0.0001) (Table 2B). Conclusions: In this large retrospective study of second time unrelated PBSC donors, a longer inter-donation interval was confirmed to be associated with better PBSC mobilization and collection. Given hematopoietic stem cell cycling times of 9-12 months in humans, where possible, repeat donors may be chosen based on these intervals to optimize PBSC yields. Changes in BMI are also to be considered while recruiting repeat donors. Some of these parameters may be improved marginally by increasing G-CSF dose within permissible limits. In most instances, however, sub-optimal mobilizers at first donation appear to donate suboptimal numbers of HSC at their subsequent donation. Disclosures Pulsipher: CSL Behring: Membership on an entity's Board of Directors or advisory committees; Miltenyi: Research Funding; Bellicum: Consultancy; Amgen: Other: Lecture; Jazz: Other: Education for employees; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Medac: Honoraria. Shaw:Therakos: Other: Speaker Engagement.


Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 5742-5742
Author(s):  
Han Bi Lee ◽  
Jae-Ho Yoon ◽  
Gi June Min ◽  
Sung-Soo Park ◽  
Silvia Park ◽  
...  

Allogeneic hematopoietic cell transplantation (allo-HCT) preconditioning intensity, donor choice, and graft-versus-host disease (GVHD) prophylaxis for advanced myelofibrosis (MF) have not been fully elucidated. Thirty-five patients with advanced MF were treated with reduced-intensity conditioning (RIC) allo-HCT. We searched for matched sibling (n=16) followed by matched (n=10) or mismatched (n=5) unrelated and familial mismatched donors (n=4). Preconditioning regimen consisted of fludarabine (total 150 mg/m2) and busulfan (total 6.4 mg/kg) with total body irradiation≤ 400cGy. All showed engraftments, but four (11.4%) showed either leukemic relapse (n=3) or delayed graft failure (n=1). Two-year overall survival (OS) and non-relapse mortality (NRM) was 60.0% and 29.9%, respectively. Acute GVHD was observed in 19 patients, and grade III-IV acute GVHD was higher with HLA-mismatch (70% vs. 20%, p=0.008). Significant hepatic GVHD was observed in nine patients (5 acute, 4 chronic), and six of them died. Multivariate analysis revealed inferior OS with HLA-mismatch (HR=6.40, 95%CI 1.6-25.7, p=0.009) and in patients with high ferritin level at post-HCT D+21 (HR=7.22, 95%CI 1.9-27.5, p=0.004), which were related to hepatic GVHD and high NRM. RIC allo-HCT can be a valid choice for advanced MF. However, HLA-mismatch and high post-HCT ferritin levels related to significant hepatic GVHD should be regarded as poor-risk parameters. Disclosures Kim: Handok: Honoraria; Amgen: Honoraria; Celgene: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; Hanmi: Consultancy, Honoraria; AGP: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; SL VaxiGen: Consultancy, Honoraria; Novartis: Consultancy; Janssen: Honoraria; Daiichi Sankyo: Honoraria, Membership on an entity's Board of Directors or advisory committees; Otsuka: Honoraria; BL & H: Research Funding; Chugai: Honoraria; Yuhan: Honoraria; Sanofi-Genzyme: Honoraria, Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees. Lee:Alexion: Consultancy, Honoraria, Research Funding; Achillion: Research Funding.


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