Villasboas, José C.

SummaryWe sought to dissect the tumour microenvironment in a small cohort (N = 10) of patients with POEMS at diagnosis and after therapy using mass cytometry. We included 10 MGUS patients as controls. We identified 29 immune cell subsets in the CD45+ and CD3+ compartments. Double positive T cells and PD‐1 positive CD4 T cells were expanded and naïve CD4 T cells were decreased in the bone marrow of patients with newly diagnosed/progressing POEMS. These findings provide evidence for possible antigenic‐driven selection as a driver of disease pathogenesis in POEMS.

Introduction: With the expanding use of CAR-T cell therapy, which is associated with serious adverse effects (AEs), there is a need to characterize the patient's experience over time to guide patient/provider education, and help optimize symptom management. This study reports on longitudinal evaluation of patient-reported quality of life (QOL) and symptom burden of CAR-T cell therapy compared with established forms of cellular therapy i.e autologous stem cell transplant (autoSCT) and allogeneic SCT (alloSCT). Methods: Patients with hematologic malignancies were prospectively recruited in three cohorts: CAR-T, autoSCT and alloSCT. The primary endpoint was change in QOL from baseline, using the FACT-G questionnaire. Secondary endpoints were patient-reported AEs (PRO-AEs) using 7 items from the PRO-CTCAE and assessment of cognition/memory using the NeuroQOLv2 questionnaire. PRO-CTCAE data was graded using a composite score (combining frequency, severity, and interference) and rates, using a method adjusting for pre-existing baseline symptoms, were compared using Fisher's exact test. We also evaluated the time profile of PRO-AEs using the Toxicity over Time (ToxT) approach, a longitudinal approach to AE analysis (Thanarajasingam Lancet Onc 2016). Patients completed questionnaires at baseline, week 2 and monthly thereafter. Results: From 07/2018 to 06/2019, 93 patients were recruited (CAR-T: 20; autoSCT: 37; alloSCT: 36). At data cut-off, week 2 and months 1, 2 and 3 data were available in 74, 62, 46 and 35 patients, respectively. There was no difference in patient age across the 3 groups (median age 63, range 23-77; p=0.26). Baseline QOL by FACT-G total score (mean=83.4, SD=14.7; p=0.77), side effect bother by FACT-G GP5 (66/93 [71%] a little bit or less; p=0.72), activities and function (70/93 [75%] fairly normal activities or no limitations; p=0.68) and cognition by NeuroQOL t-score (mean=52.2, SD=8.13; p=0.39) were similar across 3 groups at baseline. The CAR-T group experienced significantly less worsening in QOL (FACT-G) than both autoSCT and alloSCT groups (Fig. 1a). Worsening in overall QOL nadired at week 2, after which QOL gradually returned to baseline in all groups. When comparing changes from baseline in overall QOL, statistically significant differences between groups were evident at week 2 (CAR-T vs autoSCT p<0.001; vs alloSCT p<0.001), month 1 (CAR-T vs autoSCT p=0.02; vs alloSCT p=0.003), month 2 (CAR-T vs autoSCT p=0.02; vs alloSCT p=0.001) and month 3 (CAR-T vs autoSCT p=NS; vs alloSCT p=0.03). Results for physical (Fig. 1b) and functional well-being (WB) were similar, with significantly less QOL worsening at week 2 in CAR-T vs autoSCT and alloSCT groups. The most common PRO-AEs (Table 1) in the CAR-T group were decreased appetite (59%), diarrhea (53%) and fatigue (44%). There was no statistically significant difference in the PRO-AEs between CAR-T and autoSCT groups. However, patients undergoing alloSCT had significantly higher proportion of PRO-AEs vs the CAR-T group, except for neuropathy and sad feelings. AutoSCT and alloSCT groups had significant worsening of FACT-G side effect bother (GP5) at week 2, which was significantly different from that of the CAR-T group, following which the side effect bother gradually returned to baseline. (Fig. 1c) This was the first application of ToxT to PRO-CTCAE data (graphs not shown). Bar charts of maximum grade frequency and stream plots of mean grade over time demonstrate that mouth sores, fatigue, diarrhea and decreased appetite peak at week 2 and improve by month 3, and are of lesser severity in the CAR-T vs autoSCT and alloSCT groups. The trajectory of maximum grade across all PRO-AEs was similar by group as overall side effect burden by FACT-G GP5. Heatmap visualization demonstrated significant intra-patient variability and allowed inspection of data completeness. No difference in cognition and memory was observed across the three groups over the first three months. (Fig. 1d) Conclusion: This study is the first to our knowledge to provide comprehensive PRO data comparing QOL, patient-reported AEs and cognition in CAR-T cell therapy vs. auto- and alloSCT, and the first application of ToxT to PRO-CTCAE data. Short-term QOL, including physical and functional WB domains was better in the CAR-T group vs. SCT groups. These data can serve as a guide for patient education and symptom management in CAR-T cell therapy. Co-senior authors: SKK & ACD Disclosures Paludo: Celgene: Research Funding; Celgene: Research Funding; Verily Life Sciences: Research Funding; Verily Life Sciences: Research Funding. Gertz:Johnson and Johnson: Speakers Bureau; Celgene: Consultancy; Appellis: Consultancy; Amyloidosis Foundation: Research Funding; DAVA oncology: Speakers Bureau; Physicians Education Resource: Consultancy; Amgen: Consultancy; Janssen: Consultancy; Abbvie: Other: personal fees for Data Safety Monitoring board; Medscape: Consultancy, Speakers Bureau; Prothena Biosciences Inc: Consultancy; Teva: Speakers Bureau; Research to Practice: Consultancy; Annexon: Consultancy; Alnylam: Consultancy; International Waldenstrom Foundation: Research Funding; Ionis/Akcea: Consultancy; Spectrum: Consultancy, Research Funding; i3Health: Other: Development of educational programs and materials; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Proclara: Membership on an entity's Board of Directors or advisory committees; Springer Publishing: Patents & Royalties. Dispenzieri:Akcea: Consultancy; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Alnylam: Research Funding. Ansell:Trillium: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding. Bennani:Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Adicet Bio: Other: Advisory board; Adicet Bio: Other: Advisory board; Purdue Pharma: Other: Advisory board; Purdue Pharma: Other: Advisory board; Seattle Genetics: Other: Advisory board; Seattle Genetics: Other: Advisory board; Seattle Genetics: Other: Advisory board; Kite Pharma: Other: Advisory board; Adicet Bio: Other: Advisory board; Kite Pharma: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Kite Pharma: Other: Advisory board; Purdue Pharma: Other: Advisory board. Kumar:Takeda: Research Funding; Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding.

Background: Follicular lymphoma (FL) is the most frequent indolent lymphoma. While immunochemotherapy (IC) treated FL patients who achieve event-free status at 24 months after diagnosis (EFS24) have the subsequent life expectancy of the general population, those who fail to achieve EFS24 have aggressive disease with poor outcomes. Similarly, in FL patients initially observed or treated with rituximab monotherapy, EFS at 12 months (EFS12) is a strong predictor of subsequent outcome. Thus, an unmet patient need is to predict at diagnosis those at greatest risk of early failure in order to identify better treatments. The lymphoma microenvironment may be a key determinant of early failure. Therefore, we aimed to improve risk stratification of newly diagnosed FL patients by using a discovery and validation study design to identify microenvironment determinants of early failure and then integrate them into the Follicular Lymphoma International Prognostic Index (FLIPI). Patients and Methods: We evaluated 496 patients with FL grade 1-3A who were prospectively enrolled into the Molecular Epidemiology Resource (MER) cohort from 2002-2012. In the discovery set of patients (N=166), we stained tissue microarrays for CD4, CD8, FOXP3, CD32b, CD14, CD68, CD70, SIRPa, TIM3, PD-1 and PDL1. Immunohistochemical staining was determined both within and between malignant follicles. Stains were scored to the nearest decile as the percentages of cells positive. Scores for each stain were dichotomized as 0% vs >0% except for CD32b (<20% vs ≥20%), CD70 (<10% vs ≥10%), and SIRPa (<30% vs ≥30%). EFS was defined as time from diagnosis to progression, relapse, retreatment, or death. Early failure was defined as failing to achieve EFS24 for patients treated with IC at diagnosis and failing to achieve EFS12 for patients who were observed or received other treatments. Risk of early failure was estimated using odds ratios (ORs) and 95% confidence intervals (CI) from logistic regression models. Markers at P≤0.15 were brought forward for validation in a separate set of patients from the MER cohort (N=330), with P<0.005 being declared statistically significant after a Bonferroni correction (0.05/10 tests). In the combined dataset, we also used Cox regression to assess associations with continuous EFS and overall survival (OS). Mass cytometry (CyTOF) was then performed on a subset of patients (N=51) to comprehensively characterize the phenotype of intratumoral immune cells associated with outcome. Results: In the discovery set, CD4, CD8, FOXP3, PD-1, and SIRPα were associated with risk of early failure at P≤0.15 and were subsequently evaluated in the validation set. Only CD4 expression inside the follicle validated. Specifically, lack of CD4 expression inside the follicle was associated with higher risk of early failure in the discovery (OR=1.77, P=0.15) and validation (OR=2.59, P=0.001) sets, with a pooled OR=2.29 (95% CI 1.47-3.58; P<0.001). CyTOF analysis characterized the favorable CD4+ T-cell population associated with achieving EFS12/24 as activated effector memory T cells lacking exhaustion markers (Figure 1A). Adjustment of CD4 expression for FLIPI in the combined dataset did not weaken this association (OR=2.38, 95% CI 1.51-3.79), and lack of CD4 expression was prognostic within each FLIPI group 0-1 (OR=2.65; p=0.036), 2 (OR=2.07; P=0.064) and 3-5 (OR=2.51; P=0.015). We next established a bio-clinical risk model (termed BioFLIPI) that combined CD4 intrafollicular expression and FLIPI into a 1-4 scale, where any expression of intrafollicular CD4 moved a patient up one FLIPI risk group, adding a fourth (high) risk group for FLIPI 3-5 and any CD4 inside expression. The BioFLIPI score was strongly associated with risk of early failure: compared to a BioFLIPI score of 1 (24% of patients), patients with a score of 2 (35% of patients; OR=2.17, 95% CI 1.08-4.69), 3 (31% of patients; OR=3.53, 95% CI 1.78-7.54), and 4 (10% of patients; OR=8.92, 95% CI 4.00-21.1) had increasing risk of early failure. The c-statistic for BioFLIPI was 0.665, which was higher than that for FLIPI alone (0.636). BioFLIPI was also strongly predictive of continuous EFS [Figure 1B], OS [Figure 1C], and for EFS and EFS24 when restricted to IC-treated patients [Figure 1D]. Conclusion: Integration of CD4 expression inside the follicle at diagnosis with FLIPI improves identification of FL patients at risk for early failure. Disclosures Novak: Celgene Coorperation: Research Funding. Nowakowski:Curis: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding; Genentech, Inc.: Research Funding; MorphoSys: Consultancy, Research Funding. Cerhan:NanoString: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding. Ansell:LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment.

AbstractHistological transformation in Waldenström macroglobulinemia (WM) is an uncommon complication, with limited data, particularly regarding the impact of MYD88 L265P mutation on transformation. We examined risk factors and outcomes associated with transformation in WM, highlighting the role of MYD88 L265P mutation. Patients with WM seen at Mayo Clinic, Rochester, USA and University Hospital of Reims, France, between 01/01/1996 and December 31, 2017 were included; 50 (4.3%) of 1147 patients transformed to a high‐grade lymphoma, with median time‐to‐transformation of 4.5 (range 0‐21) years in the transformed cohort. The MYD88 L265P mutation status was known in 435/1147 (38%) patients (406 with non‐transformed WM and 29 patients in transformed cohort). On multivariate analysis, MYD88 WT status alone was an independent predictor of transformation (odds ratio, 7[95%CI: 2.1‐23]; P = .003). Additionally, the MYD88 WT status was independently associated with shorter time‐to‐transformation (HR 7.9 [95%CI: 2.3‐27; P = .001]), with a 5‐year transformation rate of 16% for MYD88 WT vs 2.8% with MYD88 L265P mutated patients. Patients with transformation demonstrated a significant increase in risk of death compared to patients who did not transform (HR 5.075; 95%CI: 3.8‐6.8; P < .001). In conclusion, the MYD88 WT status is an independent predictor of transformation and associated with a shorter time‐to‐transformation. Additionally, transformation conferred an inferior overall survival in patients with WM.

Abstract High‐dimensional mass cytometry data potentially enable a comprehensive characterization of immune cells. In order to positively affect clinical trials and translational clinical research, this advanced technology needs to demonstrate a high reproducibility of results across multiple sites for both peripheral blood mononuclear cells (PBMC) and whole blood preparations. A dry 30‐marker broad immunophenotyping panel and customized automated analysis software were recently engineered and are commercially available as the Fluidigm® Maxpar® Direct™ Immune Profiling Assay™. In this study, seven sites received whole blood and six sites received PBMC samples from single donors over a 2‐week interval. Each site labeled replicate samples and acquired data on Helios™ instruments using an assay‐specific acquisition template. All acquired sample files were then automatically analyzed by Maxpar Pathsetter™ software. A cleanup step eliminated debris, dead cells, aggregates, and normalization beads. The second step automatically enumerated 37 immune cell populations and performed label intensity assessments on all 30 markers. The inter‐site reproducibility of the 37 quantified cell populations had consistent population frequencies, with an average %CV of 14.4% for whole blood and 17.7% for PBMC. The dry reagent coupled with automated data analysis is not only convenient but also provides a high degree of reproducibility within and among multiple test sites resulting in a comprehensive yet practical solution for deep immune phenotyping.

Background: The DIAL study is testing the efficacy of dual immunomodulation in patients with advanced aggressive B cell non-Hodgkin lymphoma (B-NHL). Sponsored by the Cancer Therapy Evaluation Program (CTEP), the trial combines the use of a programmed cell death protein 1 (PD-1) inhibitor (nivolumab) with an agonist of the CD27 receptor (varlilumab) in a randomized phase 2 design. CD27, a co-stimulatory receptor, regulates T cell activation in the context of T cell receptor (TCR) engagement through interaction with CD70. T cell exhaustion plays a major role in immune evasion in B-NHL. Varlilumab is an agonistic IgG1 monoclonal antibody that recognizes CD27 leading to prevention or reversal of exhaustion in pre-clinical models. Varlilumab also demonstrates direct anti-tumoral activity in xenograft models of human lymphoma cell lines via antibody-dependent cell-mediated cytotoxicity. Phase 1 data supports the safety and tolerability of single-agent varlilumab in advanced hematologic malignancies (NCT01460134). We hypothesize that CD27 activation synergizes with PD-1 inhibition resulting in a superior anti-lymphoma effect compared to PD-1 blockade alone. The study will also evaluate the effect of these agents on tumor and immune cells using immunohistochemistry (IHC), mass cytometry (CyTOF), multiplex ELISA, imaging mass cytometry (IMC), and whole exome sequencing. Methods: The trial is enrolling patients with advanced aggressive B-NHL. Standard inclusion criteria and prior treatment with at least 2 lines of standard therapy are required. Prior autologous stem cell transplant and/or chimeric antigen receptor (CAR) T cell therapy is allowed. Patients with active CNS disease are excluded. Eligible patients are randomized to treatment with single-agent nivolumab (group 1) or dual immunotherapy with nivolumab and varlilumab. Group 1 is allowed to cross-over at the time of progression. Nivolumab will be administered intravenously (IV) every 2 weeks (240 mg) for 4 months followed by monthly dosing thereafter (480 mg). Varlilumab will be given IV every 4 weeks (3 mg/kg). Response assessment will be done by PET-CT scan every 12 weeks. Primary outcome is overall response rate (ORR) according to the LYRIC criteria. The trial will enroll 48 patients per arm, allowing 80% power to detect at least 20% increase in ORR in the experimental arm (group 2) assuming a 25% ORR in the control arm (group 1). The trial is registered (NCT03038672) and open to participation to members of the Experimental Therapeutics Clinical Trials Network (ETCTN) and Early Drug Development Opportunity Program (EDDOP). Figure Disclosures Tun: BMS: Research Funding; Celgene: Research Funding; Curis: Research Funding; TG Therapeutics: Research Funding; Mundi-pharma: Research Funding; DTRM Biopharma: Research Funding. Bartlett:Pharmacyclics: Research Funding; Merck: Research Funding; Incyte: Research Funding; ADC Therapeutics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Research Funding; Millennium: Research Funding; Kite Pharma: Research Funding; Janssen: Research Funding; Immune Design: Research Funding; Affimed: Research Funding; Autolus: Research Funding; Bristol-Myers Squibb: Research Funding; Celgene: Research Funding; Forty Seven: Research Funding; Genentech, Inc.: Research Funding; Gilead: Research Funding. Kline:Merck: Honoraria; Merck: Research Funding. Awan:Janssen: Consultancy; Gilead: Consultancy; Sunesis: Consultancy; Genentech: Consultancy; Abbvie: Consultancy, Speakers Bureau; Pharmacyclics: Consultancy, Research Funding; AstraZeneca: Consultancy, Speakers Bureau. Lazaryan:Kadmon: Consultancy. Ansell:Affimed: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Trillium: Research Funding. Diefenbach:Bristol-Myers Squibb: Consultancy, Research Funding; Denovo: Research Funding; Genentech: Consultancy, Research Funding; Incyte: Research Funding; LAM Therapeutics: Research Funding; MEI: Research Funding; Merck: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Millenium/Takeda: Research Funding; Trillium: Research Funding.

BACKGROUND: Angioimmunoblastic T cell lymphoma (AITL) has a unique histological phenotype with a relatively small number of malignant T-cells and an extensive infiltrate of normal cells including T-cells, B-cells, NK cells and FDCs. The malignant cell has a T follicular helper (Tfh) cell phenotype with increased expression of immune checkpoint molecules including PD-1 and ICOS. With the routine use of antibodies targeting immune checkpoint molecules, clinical results in limited numbers of AITL patients have thus far been mixed with some responding patients but also some who rapidly progress. Because both malignant T-cells and normal T-cells in AITL may be PD-1 positive, we conducted a study to compare the phenotype of normal T-cells and malignant T-cells within the tumor microenvironment. We also evaluated whether soluble immune checkpoint molecules in the peripheral blood differed between AITLs, controls, and other PTCL subgroups. METHODS: We designed a novel CyTOF antibody (Ab) panel comprised of 37 markers to identify and characterize cells of T, B, NK, macrophage and FDC lineages within a cohort of biopsy specimens from 6 AITL patients compared to 6 normal controls (2 LN, 4 tonsil). Soluble immune receptors and ligands were then measured by multiplex ELISA on peripheral blood from 8 AITLs, 5 controls, and 32 additional samples from PTCL subtypes including PTCL-NOS, ALCL and CTCL. RESULTS: Malignant T-cells in AITL specimens could clearly be identified by viSNE mapping based on CyTOF expression of CD4, CD5, BCL6, CD10 (variable), CXCR5 (variable), PD-1 and ICOS. Aberrant loss of CD3 and CD7 on malignant T-cells was commonly seen. Expression of other immune checkpoint molecules was assessed. Malignant cells expressed high levels of TIGIT and moderate levels of CD27, but malignant T-cell populations were negative for expression of TIM3, LAG3, and CTLA-4. A substantial proportion of normal T-cells also expressed immune checkpoint molecules including PD-1 and CD27, and a subset of these cells also expressed TIGIT and ICOS. A small minority of normal T-cells expressed TIM3, LAG3, and CTLA-4. As others have described, the normal Tfh cell population had an immunophenotype that was otherwise relatively similar to the malignant population, but distinguishable via viSNE mapping with our CyTOF Ab panel. Expression of PD-L1 could be detected on NK-cells, macrophages, and a few select populations of normal T cells, but not on B-cells or FDCs. Malignant T-cells did not express PD-L1. Due to the potential importance of immune checkpoint molecules in this disease, we then measured soluble checkpoint receptors and ligands in the serum. Soluble PD-1 was significantly increased in the peripheral blood of AITL when compared to normal controls (average 2637 pg/mL (SE = 512.1) in AITL vs 57.87 (SE = 16.88) in controls). Similarly, soluble PD-L1 was significantly increased in AITL compared to normal controls (13.8 (SE = 10.5) in AITL vs 0.94 (SE = 0.25) in controls). CONCLUSIONS: Malignant T-cells in AITL have a unique phenotype which was able to be reliably identified through use of viSNE mapping with our CyTOF Ab panel. Furthermore, malignant T-cells were found to consistently express additional immune regulatory molecules beyond PD-1 and ICOS, including TIGIT and CD27. However, a substantial subset of normal T-cells have a very similar phenotype suggesting that activation of T-cells in this disease will likely stimulate both normal and malignant T-cells. This may explain the rapid disease progression seen in a subset of AITL patients treated with PD-1 blockade. Furthermore, soluble PD-1 is significantly increased in the serum of AITL patients and may explain the overall lack of clinical efficacy of anti-PD-1 antibodies in treating AITL. Disclosures Cerhan: NanoString: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding. Ansell:LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; LAM Therapeutics: Research Funding.

BACKGROUND: Axi-cel is an autologous anti-CD19 chimeric antigen receptor (CAR) T-cell therapy that is approved for treatment of relapsed/refractory (R/R) large B-cell lymphoma and is associated with high response rates and durable remissions. Recent data show that axi-cel is effective across various adverse prognostic features, namely cell of origin, disease bulkiness, and extranodal disease, among others. Hypoalbuminemia is a known adverse prognostic factor in lymphomas. It is unknown if axi-cel overcomes the adverse prognostic feature of hypoalbuminemia in R/R large B-cell or transformed follicular lymphoma. METHODS: We conducted a retrospective analysis of patients treated with axi-cel across three Mayo Clinic campuses (Rochester, Jacksonville, and Phoenix) from 06/01/2018 until 04/01/2019. The primary objective of this analysis was to assess the impact of hypoalbuminemia (defined at day 0, prior to infusion) on outcome after axi-cel therapy. RESULTS: A total of 50 (male=37, 74%) patients (pts), median age of 53 (26-67) years received axi-cel. The median number of prior lines of therapy was 3 (2-8) (Table 1). Two pts had no available serum albumin levels at time of axi-cel infusion. Seven (15%) of 48 pts had serum albumin levels lower than 3.5 g/dL (median= 3.3 g/dL (range 2.6-3.4)) and the median follow up of survivors was 7.6 (1.9-14.3) months. The best overall response rate (ORR) and complete remission (CR) rates in these pts were 57% and 57%, respectively. One (14%) patient had stable disease and 2 (29%) had disease progression. The median overall survival (OS) for pts with hypoalbuminemia was not reached. On the other hand, 41 (85%) pts had a normal serum albumin level (median=4.0 (range 3.5-5.1) g/dL) and the median follow up for survivors was 6.3 months. The best objective response rate (ORR) and complete remission (CR) rates in these pts were 82% and 44%, respectively. The median OS for pts with normal serum albumin was 14 (95%CI=6.3-29.6) months. There was no significant difference at 6-months and 1-year OS between pts with hypoalbuminemia vs. those with normal baseline serum albumin levels [6-month=100% vs. 79%(95%CI=64-93%); 1-year (100% vs. 54% (95%CI=26-82%), p=0.17] (Figure 1). All grades cytokine release syndrome (CRS) was diagnosed in all 7 pts with hypoalbuminemia (100%) and in 38 of 41 (92%) pts without hypoalbuminemia. There was no difference in the median duration of CRS between pts with or without hypoalbuminemia [6 (range 1-11) days vs 5 (range 1-19) days, p=0.89]. Neurotoxicity (all grades) was observed in 5 (71%) pts with hypoalbuminemia compared 26 (63%) with normal albumin levels. There was no statistically significant difference in median duration of neurotoxicity between pts with hypoalbuminemia and those with normal baseline albumin levels [9 (range 1-10) days vs. 3 (range 0-25) days, p= 0.72]. CONCLUSIONS: Hypoalbuminemia does not have a significant impact on the outcomes of axi-cel therapy, including the incidence of CRS or neurotoxicity. These results need to be validated in a large collaborative multicenter study. Further investigation is needed to assess the prognostic impact of severe hypoalbuminemia (<3g/dL) on axi-cel therapy. Disclosures Ansell: Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Mayo Clinic Rochester: Employment; Affimed: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Affimed: Research Funding. Bennani:Seattle Genetics: Other: Advisory board; Kite Pharma: Other: Advisory board; Seattle Genetics: Other: Advisory board; Adicet Bio: Other: Advisory board; Seattle Genetics: Other: Advisory board; Purdue Pharma: Other: Advisory board; Adicet Bio: Other: Advisory board; Purdue Pharma: Other: Advisory board; Purdue Pharma: Other: Advisory board; Adicet Bio: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Kite Pharma: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Kite Pharma: Other: Advisory board. Paludo:Verily Life Sciences: Research Funding; Celgene: Research Funding; Verily Life Sciences: Research Funding; Celgene: Research Funding. Tun:DTRM Biopharma: Research Funding; Mundi-pharma: Research Funding; BMS: Research Funding; Celgene: Research Funding; Curis: Research Funding; TG Therapeutics: Research Funding. Foran:Agios: Honoraria, Research Funding. Kharfan-Dabaja:Daiichi Sankyo: Consultancy; Pharmacyclics: Consultancy.

Background: Central nervous system (CNS) involvement by peripheral T cell lymphoma (PTCL) is a rare condition. Among primary CNS lymphomas, only 2% are secondary to PTCL, while the risk of CNS relapse in all cases of PTCL is estimated at 2% to 6%. Little is known about the presentation and outcomes of PTCL patients with CNS involvement given the rarity of this entity. In this study, we describe patient characteristics, histology, and clinical course of patients with CNS involvement by PTCL. Methods: The Mayo Clinic Lymphoma Database was used to identify PTCL patients with primary or secondary CNS involvement seen at our institution between 2000 and 2018. A total of 12 patients were identified and their medical records were reviewed for patient and disease characteristics, CNS-directed treatment modality, and outcomes. The Kaplan-Meier method was used for time-to-event analysis. Results: The median age at CNS diagnosis was 63 years (range 41 to 76) and 11 (93%) patients were male. The histological diagnoses were PTCL, NOS in 9 (75%) patients, enteropathy-associated T-cell lymphoma in 2 (17%) patients, and angioimmunoblastic T-cell lymphoma in 1 (8%) patient. Five patients presented with primary T-cell CNS lymphoma (all with a PTCL, NOS histology), while the remaining 7 (58%) patients also had systemic involvement. All patients presented with neurologic symptoms at the time of CNS involvement diagnosis including: focal motor deficits in 6 patients (unilateral upper extremity weakness, gait impairments, and hemiparesis), cognitive decline in 5 patients (memory impairments, reduced attention, and confusion), headache in 4 patients, and seizure in 3 patients. The CNS disease location included the brain parenchyma in 9 (75%) patients, leptomeninges in 1 (8%) patient, and lumbar plexus in 1 (8%) patient. One patient (8%) had positive CSF finding only without radiologic evidence of involvement. CSF analysis was performed in 11 patients. Elevated protein levels were noted in 3 (27%) patients, malignant cells in 2 (18%), and no clear abnormalities in the remaining 6 (55%) patients. Concomitant bone marrow involvement was seen in only 1 patient. Elevated LDH was seen in 2 patients. The a median LDH was 195 U/L (range 139 to 4,360) The most common CNS-directed therapies were: high-dose methotrexate (MTX)-based regimens in 8 (67%) patients, including high-dose MTX in combination with temozolomide (n=2), or cytarabine and thiotepa (n=2). Intrathecal MTX, temozolomide and dexamethasone, lenalidomide, high-dose steroids, and surgical resection were the treatment modality used for one patient each. At a median follow up of 18 months, eight (75%) out of 12 patients were not alive at the time of last follow up. The median overall survival (OS) from diagnosis was 16 months (95% CI: 2.8-173). The median progression free survival (PFS) from initiation of CNS-directed therapy was 9 months (95% CI: 1.6-33) (figure). Four patients had a PFS longer than 12 months. These 4 patients were treated with: temozolomide/dexamethasone, high-dose MTX, lenalidomide, and high-dose MTX followed by cytarabine/thiothepa. Conclusion: CNS involvement by T-cell lymphoma is a rare complication that carries a poor prognosis. Early onset of neurologic symptoms should trigger prompt investigation of CNS involvement. Despite the short OS and PFS, some patients may achieve a relatively longer disease free interval. Disclosures Bennani: Adicet Bio: Other: Advisory board; Seattle Genetics: Other: Advisory board; Purdue Pharma: Other: Advisory board; Seattle Genetics: Other: Advisory board; Seattle Genetics: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Kite Pharma: Other: Advisory board; Kite Pharma: Other: Advisory board; Bristol-Myers Squibb: Research Funding; Adicet Bio: Other: Advisory board; Purdue Pharma: Other: Advisory board; Purdue Pharma: Other: Advisory board; Adicet Bio: Other: Advisory board; Kite Pharma: Other: Advisory board. Cerhan:Celgene: Research Funding; NanoString: Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees. Nowakowski:Celgene: Consultancy, Research Funding; Bayer: Consultancy, Research Funding; Curis: Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Genentech, Inc.: Research Funding; MorphoSys: Consultancy, Research Funding; NanoString: Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees. Ansell:Mayo Clinic Rochester: Employment; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Regeneron: Research Funding; Trillium: Research Funding; Seattle Genetics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Affimed: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding. Paludo:Celgene: Research Funding; Verily Life Sciences: Research Funding; Verily Life Sciences: Research Funding; Celgene: Research Funding.

Background: The 2018 iwCLL guidelines recommend close observation of early stage CLL pts who do not meet indications for therapy ("watch and wait" strategy). Prior attempts at early therapeutic intervention in unselected early-stage CLL pts using alkylating agents such as chlorambucil and chemoimmunotherapy failed to show a significant benefit; and these therapies were associated with substantial toxicities. The introduction of Bruton tyrosine kinase (BTK) inhibitors has revolutionized the treatment landscape of CLL. The German CLL Study group recently presented results of the CLL12 study which demonstrated a significant improvement in event-free survival (EFS) among untreated early stage high risk CLL pts who received ibrutinib compared to placebo (median EFS not reached vs. 47.8 months, respectively; Langerbeins, EHA, 2019). Acalabrutinib is a more selective second-generation BTK inhibitor that has fewer adverse events in pts with CLL, and has shown equally impressive clinical activity for CLL pts. We are conducting an investigator initiated randomized phase 2 study to compare acalabrutinib with or without obinutuzumab (a glycoengineered anti-CD20 monoclonal antibody approved in the treatment of CLL) among high risk early stage CLL pts. Study Design: All pts with newly diagnosed (<2 years from registration) previously untreated early stage CLL who do not meet the 2018 iwCLL guidelines for initiation of therapy are eligible for enrollment in this study. Pts undergo risk stratification according to the CLL-International prognostic index (CLL-IPI) which consists of the following 5 variables: age >65 years (1 point), Rai stage I-IV (1 point), del17p and/or TP53 mutation (4 points), unmutated immunoglobulin heavy chain (IGHV) genes (2 points), and serum β2-microglobulin >3.5 g/dL (2 points). Pts with high (4-6) and very high (7-10) risk CLL-IPI are randomly (1:1) assigned to acalabrutinib 100 mg orally twice daily (Arm A) or acalabrutinib with obinutuzumab at a standard approved schedule (Arm B). Treatment with acalabrutinib is continued for a minimum of 2 years unless the patient has unacceptable side effects or withdraws consent. Pts with low (0-1) and intermediate (2-3) risk CLL-IPI score are assigned to an observation arm with follow-up once every 6 months for 2 years, and then according to routine clinical practice (Arm C). Endpoints: The primary endpoint of the intervention arms (Arms A and B) is the achievement of minimal residual disease (MRD)-negative complete remission in the bone marrow after 2 years of therapy. MRD is assessed using an 8-color flow cytometry with a detection limit of 0.01%. The primary endpoint of the observation arm (Arm C) is time to first therapy. Secondary endpoints for all arms are: progression-free survival, overall survival, and safety. Statistical design: A randomized trial comparing the experimental arm (acalabrutinib plus obinutuzumab) against the control arm (acalabrutinib alone) will be conducted as described by Rubinstein. A sample size of 36 pts per arm provides 80% power to detect an improvement in MRD-negative complete response rate from 10% to 30%, using a one-sided test at a significance level of 0.10 (EAST 6.4). We anticipate accruing an additional 8 high/very high risk pts (4 in each arm) to account for ineligibility, cancellation, or major treatment violation. The total enrollment for Arms A and B will be 80 pts. We will enroll 40 pts to Arm C; for a total enrollment of 120 pts. Key correlatives: Comprehensive profiling to assess the innate and adaptive immune system in paired peripheral blood and bone marrow will be conducted in all pts registered to Arms A and B at baseline, 12 and 24 months after enrollment. In addition, bone marrow hematopoietic function will be assessed in all pts at these time points. We will employ a CLL focused custom 61-gene panel to estimate tumor mutational burden as well as mutational profiles for each patient at baseline, 12, and 24 month time points, as well at the time of disease progression. Preliminary results: The trial is registered at clinicaltrials.gov NCT03516617. The trial opened to accrual at all three Mayo Clinic sites (Rochester, MN; Jacksonville, FL; and Scottsdale, AZ) in September 2018. Twenty-eight pts have been registered; the baseline characteristics are shown in Table 1. The trial is expected to complete enrollment in September 2020; and the primary analysis will be available in September 2022. Disclosures Parikh: Janssen: Research Funding; AstraZeneca: Honoraria, Research Funding; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding; AbbVie: Honoraria, Research Funding; Acerta Pharma: Research Funding; Ascentage Pharma: Research Funding; Genentech: Honoraria. Ding:DTRM Biopharma: Research Funding; Merck: Research Funding. Ailawadhi:Pharmacyclics: Research Funding; Cellectar: Research Funding; Takeda: Consultancy; Amgen: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Celgene: Consultancy. Kenderian:Novartis: Patents & Royalties, Research Funding; Tolero: Research Funding; Humanigen: Other: Scientific advisory board , Patents & Royalties, Research Funding; Lentigen: Research Funding; Morphosys: Research Funding; Kite/Gilead: Research Funding. Chanan-Khan:Mayo Clinic: Employment; Ascentage: Research Funding; Millennium: Research Funding; Jansen: Research Funding; AbbVie: Research Funding; Xencor: Research Funding; Pharmacyclics: Research Funding; Merck: Research Funding. Kay:Infinity Pharmaceuticals: Other: DSMB; Celgene: Other: Data Safety Monitoring Board; Agios: Other: DSMB; MorphoSys: Other: Data Safety Monitoring Board. OffLabel Disclosure: Drug: Acalabrutinib Purpose: treatment of CLL