Ansell, Stephen M.

Abstract Background: Follicular lymphoma (FL) exhibits significant clinical, cellular, molecular, and genetic heterogeneity. Our understanding of FL biology and molecular classifications of FL, to date, has largely been driven by pathologic classification (Grade 1-3b), genetic classification (m7-FLIPI), or gene expression profiling (IR-1/2; Huet-23), along with limited studies on small cohorts or targeted panels. In order to further understand the biological underpinnings and complexity of FL, large-scale and integrated whole exome sequencing (WES) and RNA sequencing (RNAseq) studies are needed. Using a highly-annotated cohort of 93 FL tumors with matched RNAseq, WES, and CyTOF data, we have explored the transcriptomic signature of purified FL B cells and identified unique molecular subsets that are defined by distinct pathway activation, immune content, and genomic signatures. Methods: Frozen cell suspensions from 93 untreated FL (Grade 1-3b) patients' tumor biopsies, enrolled in the University of Iowa/Mayo Clinic Lymphoma SPORE, were used for the study. DNA was isolated from whole tumor cell suspensions, and RNA was isolated from both whole tumor and B cell-enriched cell suspensions. RNAseq and WES were performed in the Mayo Clinic Genome Analysis Core. RNAseq and WES data were processed using a standard pipeline and novel driver genes were identified using Chasm+ driver analysis. Copy number variants were identified from WES data using GISTIC 2.0. NMF clustering and single sample gene set testing for B cell lineage and tumor microenvironment (TME) signatures were performed in R using the NMF and singscore packages. Results: Unsupervised clustering of RNAseq data identified three distinct expression programs which separated patient B cell samples into 3 groups: Group 1 (G1, n=20), Group 2 (G2, n=24), Group 3 (G3, n=43). While no clinical attributes were defined by any single group, G1 consisted of cases that had less aggressive characteristics (63% Stage I-II, 79% FLIPI 0-1). To identify unique transcriptional pathways driving the three expression programs, we scored gene level contributions to NMF expression programs and employed gene set enrichment analysis. This revealed significant pathway association with type-I IFN signaling (G1), DNA repair and stress response (G2), and epigenetic modulation (G3) as differentiating programs between the 3 groups (FDR q<0.001). VIPER master regulator activity inferencing revealed that these pathways were likely being controlled by differential activity in NF-kB, IRFs, STAT1, BCL6, and FOXO1. Each program significantly enriched for, but were not defined by, portions of specific germinal center programs, such as pre-memory (G1), light-zone-to-dark-zone transition (G2), and a pre-light-zone intermediate (G3). We next assessed the connection between B cell programs and the tumor microenvironment (TME) using available paired CyTOF data on 67 cases, which revealed an active TME in G1, with an abundance of CD8 T cell and NK cell populations, a wide variety of immune content in G2 that consisted mostly of Tfh and myeloid cells, and a poorly populated immune compartment in G3 compared to G1 and G2. Finally, somatic driver mutations and copy number alterations from WES were identified and associated with the three clusters. The three groups distinguished themselves by significant enrichment of copy number alterations (TNFAIP3-loss , 1q23-gain, 1q32-gain) in G2, while 10q-loss and mutations in BCL2 and chromatin modifiers (KMT2D and CREBBP) enriched in G3. G1, overall, had lower alteration burden and had weak associations with any specific alterations, suggesting an alternative mechanism for driving the G1 program. Conclusion: In this study, we have identified three unique FL tumor B cell groups, defined by specific transcriptional programs. Pathways such as inflammation, DNA damage response, and chromatin modification contribute most to the differences between B cell samples and group membership. Additionally, each program associated with specific genetic events as well as TME composition, highlighting potential drivers of these B cell states. This study improves the understanding of the mechanisms driving FL tumors and motivates further investigation into transcriptional consequences of genetic events as well as potential tumor intrinsic factors that may influence the TME. Figure 1 Figure 1. Disclosures Maurer: BMS: Research Funding; Genentech: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees, Research Funding; Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Nanostring: Research Funding. Rimsza: NanoString Technologies: Other: Fee-for-service contract. Link: MEI: Consultancy; Genentech/Roche: Consultancy, Research Funding; Novartis, Jannsen: Research Funding. Habermann: Tess Therapeutics: Other: Data Monitoring Committee; Seagen: Other: Data Monitoring Committee; Incyte: Other: Scientific Advisory Board; Morphosys: Other: Scientific Advisory Board; Loxo Oncology: Other: Scientific Advisory Board; Eli Lilly & Co.,: Other: Scientific Advisor. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding. King: Celgene/BMS: Research Funding. Cerhan: Genentech: Research Funding; Regeneron Genetics Center: Other: Research Collaboration; Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; NanoString: Research Funding. Novak: Celgene/BMS: Research Funding.

Abstract Background Patients (pts) with aggressive B-cell non-Hodgkin lymphoma (NHL) progressing after anti-CD19 chimeric antigen receptor T (CART) cell therapy have poor prognosis and may benefit from new therapy options through clinical trials. However, in a single center report, only 12% of such pts were treated in trials (Chow et al. Am J Hematol, 2019). Identifying the reasons for this low enrollment is needed to design future studies for this population. Here, we evaluated the eligibility criteria for recent landmark trials for relapsed/refractory aggressive B-cell NHL to learn what eligibility barriers are present. Methods Pts with aggressive B-cell NHL who received FDA-approved CART cell therapy at Mayo Clinic (Rochester, Arizona, Florida) since 2018 and progressed after CART cell therapy were identified. The potential eligibility for the following key trials was evaluated: a) polatuzumab + bendamustine + rituximab, b) tafasitamab + lenalidomide, c) selinexor and d) loncastuximab. The eligibility for each trial was retrospectively assessed at the time of disease progression after CART cell therapy based on hemoglobin (Hb), absolute neutrophils count (ANC), platelet count (Plt), renal and liver function tests, ECOG performance status (PS), and central nervous system (CNS) involvement. Results Seventy-five pts had disease progression to axicabtagene ciloleucel (N=73, 97%) or tisagenlecleucel (N=2, 3%) and are included in this analysis. Median time to progression after CART was 2.1 months (IQR: 1.0 - 3.1). Thirteen (17%) pts were treated in clinical trials after progression following CART cell therapy, while 46 (61%) were treated off trials, and 16 (22%) pts never received any treatment after progression. At a median follow-up of 13.6 months (IQR: 9.1 - 26.7) from CART progression, the median overall survival (mOS) from CART progression was 5.8 months (95% CI 3.5 - 10.1) and 53 (71%) pts died. Thirty-eight pts (51%) did not meet eligibility criteria for any of the 4 recent landmark trials. Hematologic impairment was the most common barrier to inclusion of these patients in clinical trials: Hb < 9 g/dL n=23 (31%) or Hb < 10 g/dL n=36 (48%), ANC < 1.0 x 10 9/L n=19 (25%) or ANC < 1.5 x 10 9/L n=32 (43%), and Plt < 75 x 10 9/L n=30 (40%) or Plt < 90 x 10 9/L n=34 (45%). Renal (n=11, 15%) or liver dysfunction (n=5, 7%), CNS involvement (n=8, 11%) and ECOG PS > 2 (n=3, 4%) were less common reasons leading to exclusion from trials. Post CART trial ineligible pts had significantly shorter time to progression (median 1.7 months, IQR: 1.0 - 2.6 vs. 3.0 months IQR: 1.9 - 3.4, p < 0.01) and inferior overall response to CART (45% vs 67%, p = 0.06) compared to pts who met trial eligibility post CART. Baseline Hb (median Hb 9.5 g/dL, IQR: 8.5 - 10.5 vs. 10.9 g/dL, IQR: 9.7 - 12.2, p < 0.01) and Plt (median Plt 106 x 10 9/L IQR: 54 - 165 vs. 201 x 10 9/L IQR: 141 - 243, p < 0.01) were also significantly lower in pts ineligible for trials post CART. There were no significant differences between pts eligible or ineligible for trials with regards to age (median 59 vs. 60 years), number of prior therapies (median 3 vs. 3), prior autologous stem cell transplant (41% vs. 37%), bridging therapy (65% vs. 63%), baseline ANC (median 4,1 vs. 3,0 x10 9/L), or high-grade (grade ≥ 2) cytokine release syndrome (19% vs. 21%) or neurotoxicity (32%, vs. 42%), respectively. Survival after CART progression was significantly shorter (mOS 2.5 months, 95% CI: 1.6 - 5.1) for the 38 pts ineligible for trials compared to pts eligible for trials (mOS 10.6 months, 95% CI: 8.9 - NA), (p < 0.01). In the 59 pts who received therapy post CART progression, the mOS of pts treated on (n = 13) or off (n = 46) trials was 13.8 months (95% CI: 9.2 - NA) vs. 6.6 months (4.9 - 10.7), respectively (p = 0.047). Conclusion Approximately half of the pts (51%) with aggressive B-cell NHL progressing after CART cell therapy would have be excluded from landmark clinical trials. The current hematologic exclusion criteria are a major barrier to enrollment in clinical trials, which would exclude many pts who have disease progression within 3 months of CART cell therapy (ie, primary refractory disease), in whom cytopenia as a toxicity from therapy is prevalent. Given the known delayed hematologic recovery after CART cell therapy and the unmet need of pts progressing to CART cell therapy, the hematologic exclusion criteria should be adjusted to increase trial participation of this population, especially of those with primary refractory disease. Figure 1 Figure 1. Disclosures Munoz: Gilead/Kite Pharma, Kyowa, Bayer, Pharmacyclics/Janssen, Seattle Genetics, Acrotech/Aurobindo, Beigene, Verastem, AstraZeneca, Celgene/BMS, Genentech/Roche.: Speakers Bureau; Janssen: Research Funding; Pharmacyclics/Abbvie, Bayer, Gilead/Kite Pharma, Pfizer, Janssen, Juno/Celgene, BMS, Kyowa, Alexion, Beigene, Fosunkite, Innovent, Seattle Genetics, Debiopharm, Karyopharm, Genmab, ADC Therapeutics, Epizyme, Beigene, Servier: Consultancy; Seattle Genetics: Research Funding; Millennium: Research Funding; Pharmacyclics: Research Funding; Genentech: Research Funding; Incyte: Research Funding; Portola: Research Funding; Merck: Research Funding; Celgene: Research Funding; Gilead/Kite Pharma: Research Funding; Bayer: Research Funding; Seattle Genetics: Honoraria; Physicians' Education Resource: Honoraria; Targeted Oncology: Honoraria; OncView: Honoraria; Kyowa: Honoraria. Murthy: CRISPR Therapeutics: Research Funding. Maurer: Morphosys: Membership on an entity's Board of Directors or advisory committees, Research Funding; Nanostring: Research Funding; Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Genentech: Research Funding; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees. Bennani: Purdue Pharma: Other: Advisory Board; Daichii Sankyo Inc: Other: Advisory Board; Kyowa Kirin: Other: Advisory Board; Vividion: Other: Advisory Board; Kymera: Other: Advisory Board; Verastem: Other: Advisory Board. Paludo: Karyopharm: Research Funding. Wang: Genentech: Research Funding; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; MorphoSys: Research Funding; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees; Eli Lilly: Membership on an entity's Board of Directors or advisory committees; LOXO Oncology: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; InnoCare: Research Funding. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding. Witzig: Karyopharm Therapeutics, Celgene/BMS, Incyte, Epizyme: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene/BMS, Acerta Pharma, Kura Oncology, Acrotech Biopharma, Karyopharm Therapeutics: Research Funding. Nowakowski: Celgene, NanoString Technologies, MorphoSys: Research Funding; Celgene, MorphoSys, Genentech, Selvita, Debiopharm Group, Kite/Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees. Lin: Vineti: Consultancy; Takeda: Research Funding; Sorrento: Consultancy; Novartis: Consultancy; Juno: Consultancy; Legend: Consultancy; Janssen: Consultancy, Research Funding; Bluebird Bio: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Merck: Research Funding; Gamida Cell: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding.

Abstract Purpose: Axicabtagene ciloleucel (axi-cel) is an anti-CD19 chimeric antigen receptor T-cell (CAR-T) therapy utilized for patients with non-Hodgkin lymphoma (NHL) refractory to at least 2 lines of therapy. F-18 fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) is used to evaluate disease extent prior to CAR-T infusion at two time points: pre-leukapheresis (pre-leuk) approximately 6 weeks prior to CAR-T infusion, and pre-lymphodepletion chemotherapy (pre-LD) approximately 1 week prior to CAR-T infusion. We hypothesized that PET/CT characteristics beyond Lugano criteria, such as metabolic tumor volume (MTV), total lesion glycolysis (TLG), SUV maximum (SUVMax), and changes in these parameters from pre-leuk to pre-LD, may predict for progressive disease (PD), death, and treatment toxicity after CAR-T infusion. Methods: Patients with NHL who received axi-cel on a prospective registry at Mayo Clinic Rochester were included. Lesions on pre-leuk and pre-LD PET/CT scans were segmented with a fixed absolute SUVMax threshold of 2.5 using a semi-automated workflow (LesionID, MIM Software Inc.) with manual modification to exclude physiologic uptake as needed. MTV, TLG, SUVMax, number of lesions, and other lesion characteristics were assessed for each PET/CT, and changes from pre-leuk to pre-LD were calculated. Lesions were categorized as either nodal, spleen, bone, parenchymal (i.e. liver, lung), or soft tissue (i.e. subcutaneous, muscle), and MTV was calculated for each category. Univariate Cox modeling was used to associate relative and directional change in metabolic and volumetric PET/CT characteristics with PD and death, after adjusting for bridging therapy. LASSO method was used for multivariable model selection. Pre-LD PET/CT characteristics were also assessed for association with presence and duration of cytokine release syndrome (CRS), grade 3+ immune effector cell-associated neurotoxicity syndrome (ICANS), tocilizumab (toci) use, and corticosteroid use. Results: From 2018-2020, axi-cel was delivered to 69 patients. Histology included diffuse large B-cell lymphoma (57%), transformed follicular lymphoma (23%), or high-grade lymphoma (19%). Pre-leuk and pre-LD PET/CT scans were performed a median of 46 days and 7 days prior to CAR-T infusion, respectively. Forty patients (58%) received bridging therapy between scans, including 9 (13%) receiving radiotherapy. At a median follow-up of 13 months, 39 (57%) had died and 46 (67%) had PD. Sixty patients (87%) developed CRS following CAR-T infusion for a median duration of 5 days. Presence of pre-LD parenchymal disease was associated with longer duration CRS (p=0.032). Thirty-seven patients (54%) developed ICANS for a median duration of 4.5 days, including 12 (32%) with grade 3+ ICANS. Greater pre-LD total MTV was associated with higher risk of grade 3+ ICANS (p=0.042). Greater pre-LD SUVMax was associated with longer duration ICANS (p=0.032). Nineteen (28%) patients required toci. Greater pre-LD total MTV, SUVMax, TLG, and volume of the largest lesion were associated with increased use of toci (p<0.05 for all). Greater pre-LD total MTV and TLG of the largest lesion were associated with increased use of corticosteroid (p<0.05 for each). While no individual pre-leuk or pre-LD PET/CT characteristics were associated with risk of PD or death, increases from pre-leuk to pre-LD in total MTV, total TLG, parenchymal MTV, and nodal MTV were associated with increased risk of PD (Figure 1). Similarly, increases from pre-leuk to pre-LD in parenchymal MTV, nodal MTV, TLG of the largest lesion, and total number of lesions were associated with increased risk of death (p<0.05 for all). LASSO analysis identified increasing extranodal MTV (≥25% increase) and increasing TLG of the largest lesion (≥10% increase) as strong predictors of death (AUC 0.74, Table 1). Kaplan-Meier plots were generated for overall and progression-free survival using these risk factors (Figure 2). Additional patients and follow-up will be presented. Conclusions: Patients with greater pre-LD MTV had higher risk of grade 3+ ICANS and use of toci or corticosteroids. Increasing metabolic disease burden during CAR-T manufacturing is associated with increased risk of PD and death. A two variable risk score using increasing extranodal disease and increasing TLG of the largest lesion may stratify prognosis prior to CAR-T and inform treatment paradigms. Figure 1 Figure 1. Disclosures Bennani: Verastem: Other: Advisory Board; Purdue Pharma: Other: Advisory Board; Daichii Sankyo Inc: Other: Advisory Board; Kyowa Kirin: Other: Advisory Board; Vividion: Other: Advisory Board; Kymera: Other: Advisory Board. Paludo: Karyopharm: Research Funding. Wang: Genentech: Research Funding; LOXO Oncology: Membership on an entity's Board of Directors or advisory committees, Research Funding; Eli Lilly: Membership on an entity's Board of Directors or advisory committees; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; InnoCare: Research Funding; Novartis: Research Funding; MorphoSys: Research Funding; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding. Lin: Gamida Cell: Consultancy; Janssen: Consultancy, Research Funding; Legend: Consultancy; Novartis: Consultancy; Celgene: Consultancy, Research Funding; Sorrento: Consultancy; Bluebird Bio: Consultancy, Research Funding; Takeda: Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Merck: Research Funding; Vineti: Consultancy; Juno: Consultancy.

Abstract Introduction: Up to 40% of newly diagnosed diffuse large B cell lymphoma (DLBCL) will relapse after frontline rituximab, doxorubicin, cyclophosphamide, vincristine, and prednisone (RCHOP), with subsequent poor prognosis. Identification of patients (pts) at high risk of relapse early in the treatment can allow for development of risk adapted therapies to improve outcomes. Positron Emission Tomography scan after 2 cycles of therapy (PET2) has been evaluated as a predictor of relapse but study treatments were heterogenous and results were conflicting. A substudy of CALGB 50303 trial did not find association of PET2 response by Deauville Score (DS) with survival in RCHOP and DA-EPOCH-R treated pts. In the UK National Cancer Research Institute Prospective Study, DS of 5 on PET2 predicted worse progression free survival but not overall survival (OS) in RCHOP-21 and RCHOP-14 treated pts. Here we report impact of PET2 response on outcomes in two large independent, prospective cohorts of newly diagnosed DLBCL treated homogenously with two RCHOP-based regimens of similar efficacy. Methods: Discovery was done in adult pts with DLBCL enrolled into a single arm phase 2 trial of lenalidomide plus standard RCHOP (R2CHOP) (MC078E, NCT00670358). The validation cohort comprised of adult pts with newly diagnosed DLBCL treated with standard RCHOP prospectively enrolled into the Mayo component of the University of Iowa/Mayo Clinic Molecular Epidemiology Resource (MER). Both MC078E and MER cohorts included patients who received at least 3-6 cycles of therapy and had a PET2. Pts who progressed on PET2 were excluded. End of treatment (EOT) PET was done 3-12 weeks after last cycle of therapy. The revised response criteria for malignant lymphoma (Cheson, et al 2007) was used to assess PET in MC078E. In MER, revised response criteria for malignant lymphoma (Cheson et al 2007) or Lugano classification was used, depending on era of diagnosis. Positive PET was defined as FDG uptake above background (Cheson 2007) or DS 4 or 5 (Lugano 2014). Study endpoints were event-free survival (EFS) and OS by PET2 status. Results: Out of 118 pts treated on MC078E, 102 had PET2 (MC078E). The median age at diagnosis was 64 years (range 19-87), 61 (60%) were male, 89 (87%) had advanced stage disease, 46 (45%) had international prognostic index (IPI) of 3-5. 58 (57%) were PET2 Negative (PET2-ve) and 44 (43%) were PET2 Positive (PET2+ve). At EOT PET, 83 (81%) had -ve PET and 15 (15%) had +ve PET. Out of 44 PET2+ve pts, 15 remained +ve at EOT PET. Out of 58 PET2-ve pts, 56 had EOT PET available and all were -ve. Out of 866 DLBCL pts enrolled into MER between August 2005 and June 2015, 621 were treated with RCHOP for 3-6 cycles and 272 had available PET2 (MER). The median age was 65 years (range 55-73), 152 (56%) were male, 174 (64%) had advanced stage, 103 (38%) had IPI 3-5. 186 (68%) were PET2-ve and 86 (32%) were PET2+ve. Out of 235 with EOT PET available, 182 (77%) had -ve EOT PET and 25 (11%) had +ve EOT PET. PET2+ve pts had higher odds of +ve EOT PET (OR: 17.4 (CI 95 8.3-40.0), p<0.001) and progression on EOT PET (OR: 4.3 (CI 95 1.9-10.2), p<0.001) in MER cohort. This analysis was not possible on MC078E as all PET2-ve had -ve EOT PET. In MC078E, 2-year EFS and OS were 69.5% (CI 95 61.1-79.1) and 88.1% (CI 95 82-94.7). In MER, 2-year EFS and OS were 71.6% (CI 95 67.7-76.8) and 82.3% (CI 95 79.3-85.3). Compared to PET2-ve, PET2+ve pts had significantly inferior EFS in both MC078E (HR 4.0, CI 95 2.1-7.88, p<0.0001, figure 1a) and MER (HR 2.9, CI 95 1.9-4.1, p<0.0001, figure 1c). Compared to PET2-ve , PET2+ve pts had a trend towards lower OS in MC078E (HR 2.0, CI 95 0.9-4.9, p=0.1, figure 1b) and a significantly lower OS in MER (HR 2.3, CI 95: 1.5-3.4, p<0.0001, figure 1d). In subgroup analysis of MC078E, PET2+ve pts had lower EFS and a trend towards lower OS in all subgroups except IPI 0-2 (Table 1). In MER, PET2+ve pts had lower EFS and OS in all the subgroups except stage I-II and IPI 0-2 (Table 1). Conclusions: Positive PET2 was associated with increased risk of disease progression and death in newly diagnosed DLBCL. Results of our study provide robust evidence of importance of PET2 as an early predictor DLBCL pts at high risk of progression in two independent prospective cohorts. PET2-guided risk-adapted strategies using chimeric antigen receptor T-cell therapy and bispecific antibodies may potentially improve outcomes, should be explored in clinical trials and results of our study serve as a benchmark for such studies. Figure 1 Figure 1. Disclosures Maurer: Kite Pharma: Membership on an entity's Board of Directors or advisory committees; Genentech: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees, Research Funding; Nanostring: Research Funding; Celgene: Research Funding; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees. Wang: Genentech: Research Funding; Eli Lilly: Membership on an entity's Board of Directors or advisory committees; Novartis: Research Funding; MorphoSys: Research Funding; InnoCare: Research Funding; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; LOXO Oncology: Membership on an entity's Board of Directors or advisory committees, Research Funding; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees. Cerhan: Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; Regeneron Genetics Center: Other: Research Collaboration; NanoString: Research Funding; Genentech: Research Funding. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding. Habermann: Seagen: Other: Data Monitoring Committee; Incyte: Other: Scientific Advisory Board; Tess Therapeutics: Other: Data Monitoring Committee; Morphosys: Other: Scientific Advisory Board; Loxo Oncology: Other: Scientific Advisory Board; Eli Lilly & Co.,: Other: Scientific Advisor. Witzig: Celgene/BMS, Acerta Pharma, Kura Oncology, Acrotech Biopharma, Karyopharm Therapeutics: Research Funding; Karyopharm Therapeutics, Celgene/BMS, Incyte, Epizyme: Consultancy, Membership on an entity's Board of Directors or advisory committees. Nowakowski: Celgene, NanoString Technologies, MorphoSys: Research Funding; Celgene, MorphoSys, Genentech, Selvita, Debiopharm Group, Kite/Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees.

Abstract Our group published a double blind, randomized phase III study (Porrata et al, BBMT 2016; 22: 1017-1023) showing that the infusion of autograft absolute lymphocyte count (A-ALC) ≥ 0.5 x 10 9 cells/kg is a survival prognostic factor for lymphoma patients undergoing autologous peripheral blood hematopoietic stem cell transplantation (APBHSCT). However, a limitation of the study was the short-term follow-up duration of two years post-APBHSCT. To assess if the A-ALC still provide survival benefit we looked at the 121 lymphoma patients enrolled in the phase III from December 10, 2007 until October 12, 2010 survival outcomes with a longer follow-up duration of up to 13 years post-APBHSCT. Since the accrual for the study, 52 patients had died of recurrence lymphoma, 4 patients of therapy-related acute myelogenous leukemia, 3 patients of unknown causes, 1 patient of acute respiratory distress syndrome, 1 patient of anaplastic astrocytoma, and 1 patient of septic shock. The current median follow-up is 86 months (range: 2.1-158.1 months) for the entire cohort and 127.8 months (range: 5.9-158.1 months) for patients still alive. Patients infused with an A-ALC ≥ 0.5 x 10 9 cells/kg continue to experience superior overall survival (OS) (HR = 0.392, 95%CI 0.224-0.687, P < 0.001) and progression-free survival (PFS) (HR = 0.413, 95%CI 0.253-0.677, P < 0.0004). The 10-year OS rates for the A-ALC ≥ 0.5 x10 9 cells/kg patients was 70% (95% confidence interval [CI], 55%-81%) and for the A-ALC < 0.5 x10 9 cells/kg patients was 36% (95% CI, 25%-49%) (Figure 1A). The 10-year PFS rates for the A-ALC ≥ 0.5 x10 9 cells/kg group was 57% (95% CI, 43%-70%) and for the A-ALC < 0.5 x10 9 cells/kg group was 28% (95% CI, 19%-40%) (Figure 1B). Autograft lymphocyte subset analysis including autograft-CD3 (A-CD3), autograft CD4 (A-CD4), autograft CD8 (A-CD8), and autograft natural killer cells (A-NK), showed that the infusion of A-NK was a predictor for OS (HR = 0.518, 95%CI 0.292-0.919, P < 0.02) and PFS (HR = 0.393, 95%CI 0.230-0.670, P < 0.0006). The 10-year OS rates for the A-NK ≥ 0.09 x10 9 cells/kg patients was 67% (95% confidence interval [CI], 50%-80%) and for the A-NK < 0.09 x10 9 cells/kg patients was 42% (95% CI, 31%-54%) (Figure 1C). The 10-year PFS rates for the A-NK ≥ 0.09 x10 9 cells/kg group was 59% (95% CI, 43%-73%) and for the A-NK < 0.09 x10 9 cells/kg group was 32% (95% CI, 23%-44%) (Figure 1D). Both the A-ALC and A-NK were independent predictor for OS [ A-ALC: HR = 0.367, 95%CI 0.195-0.690, P < 0.001) and A-NK: HR = 0.411, 95%CI 0.275-0.892, P < 0.01] and for PFS [ A-ALC: HR = 0.477, 95%CI 0.271-0.840, P < 0.01) and A-NK: HR = 0.490, 95%CI 0.266-0.903, P < 0.02]. With a longer follow-up of 13 years, this study shows that the infusion of A-ALC continues to provide better clinical outcomes to lymphoma patients undergoing APBHSCT. These study findings support our standard practice changed of not only collecting CD34 stem cell for hematologic engraftment, but also A-ALC for lymphoma patients undergoing APBHSCT to improve clinical outcomes. Further, autograft immune effector studies are warranted such as A-NK to develop a more immunocompetent targeted autologous graft verus tumor effect. Figure 1 Figure 1. Disclosures Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding. Paludo: Karyopharm: Research Funding.

Abstract Background: Vaccinations have been hypothesized to play a role in lymphoma etiology, but there are few studies, mixed results, and limited data on lymphoma subtypes. Herein, we investigate the association of vaccinations with risk of major lymphoma subtypes. Methods: We studied 2,461 lymphoma cases and 2,253 controls enrolled from 2002 to 2014. Participants self-reported history of vaccinations against hepatitis A, hepatitis B, yellow fever, and influenza. Polytomous logistic regression was used to estimate OR and 95% confidence intervals (CI), adjusting for potential confounders. Results: After multivariable adjustment, vaccination against influenza was inversely associated with lymphoma (OR = 0.82; 95% CI, 0.66–1.02), which was stronger for last vaccination 1+ years before enrollment (OR = 0.71; 95% CI, 0.56–0.91) and for >5 influenza vaccinations (OR = 0.56; 95% CI, 0.46–0.68). Ever vaccination against hepatitis A (OR = 0.81; 95% CI, 0.66–1.00) but not hepatitis B (OR = 0.97; 95% CI, 0.81–1.18) was associated with lymphoma risk, although more recent vaccinations were inversely associated with lymphoma risk for both hepatitis A (<6 years before enrollment, OR = 0.56; 95% CI, 0.40–0.77) and hepatitis B (<9 years before enrollment, OR = 0.72; 95% CI, 0.55–0.93). Ever vaccination against yellow fever was inversely associated with risk (OR = 0.73; 95% CI, 0.55–0.96), and this did not vary by time since last vaccination. Although there was no overall statistical evidence for heterogeneity of vaccination history by lymphoma subtype, the only statistically significant inverse associations were observed for influenza and yellow fever vaccinations with diffuse large B-cell and follicular lymphoma. Conclusions: Selected vaccinations were inversely associated with lymphoma risk, with time since last vaccination relevant for some of these vaccines. Impact: Vaccinations against hepatitis A, hepatitis B, yellow fever, and influenza are unlikely to increase lymphoma risk.

AbstractBecause there have been a dvances in frontline treatment for mantle cell lymphoma (MCL) over the last 2 decades, we sought to characterize the changes in frontline treatment patterns and their association with outcomes. Patients with newly diagnosed MCL from September 2002 through June 2015 were enrolled in a prospective cohort study, and clinical characteristics, treatment, and clinical outcomes were compared between patients diagnosed from 2002 to 2009 (Era 1) compared with 2010 to 2015 (Era 2). Patient age, sex, and simplified MCL International Prognostic Index (sMIPI) score were similar between the 2 groups. In patients age 65 years or younger, there was less use of rituximab plus hyperfractionated cyclophosphamide, vincristine, doxorubicin, and dexamethasone (R-Hyper-CVAD) (16.1% vs 8.8%) but more use of rituximab plus maximum-strength cyclophosphamide, doxorubicin, vincristine, and prednisone (R-maxi-CHOP) alternating with rituximab plus high-dose cytarabine (R-HiDAC), also known as the Nordic regimen, and R-CHOP alternating with rituximab plus dexamethasone, high-dose cytarabine, and cisplatin (R-DHAP) (1.1% vs 26.4%) and less use of R-CHOP or R-CHOP-like regimens (64.5% vs 35.2%) but more use of R-bendamustine (0% vs 12.1%) in Era 2 (P < .001). These changes were associated with improved event-free survival (EFS; 5-year EFS, 34.3% vs 50.0%; P = .010) and overall survival (OS; 5-year OS, 68.8% vs 81.6%; P = .017) in Era 2. In patients older than age 65 years, there was less use of R-CHOP or R-CHOP-like therapy (39.0% vs 14.3%) and nonstandard systemic therapy (36.6% vs 13.0%) but more use of R-bendamustine (0% vs 49.4%). These changes were associated with a trend for improved EFS (5-year EFS, 25.4% vs 37.5%; P = .051) in Era 2. The shift from R-CHOP or R-CHOP-like regimens to R-bendamustine was associated with improved EFS (5-year EFS, 25.0% vs 44.6%; P = .008) in Era 2. Results from this prospective cohort study provide critical real-world evidence for improved outcomes with evolving frontline patterns of care in patients with MCL.

The World Health Organization Classification of Tumours of Haematopoietic and Lymphoid Tissues (WHO 2017) included updated criteria for diagnosis and classification of post-transplant lymphoproliferative disorders (PTLDs). This study evaluated the clinicopathologic spectrum using WHO 2017 criteria and adult PTLD patients’ outcomes over 30 years between 1987 and 2017 at Mayo Clinic (Rochester, MN). Patients were retrospectively reviewed for clinical features, outcomes, and diagnostic pathology material and classified based on WHO 2017 criteria. A total of 227 patients were diagnosed with PTLD, with a median time from transplant to PTLD of 45 months. PTLD occurred >1 year after transplant in 149 (66%) patients. Monomorphic PTLD was the most common subtype (173, 76%), with diffuse large B cell lymphoma as the commonest morphology (n = 137). Epstein-Barr virus was positive in 61% of total cases and 90% of PTLD that developed within 1 year from transplant. The median event-free survival (EFS) and overall survival for the entire cohort were 21 months (95% confidence interval [CI]: 9–35) and 82 months (95% CI: 39–115), respectively. The EFS or overall survival was not impacted by Epstein-Barr virus status but differed based on WHO subtypes and year of diagnosis. Management changed over time with increased use of rituximab or chemotherapy + immunosuppression reduction as initial therapy. When compared to the matched general population and de novo diffuse large B cell lymphoma, patients not achieving EFS 24 status (no progression/treatment or death within 24 mo of diagnosis) had a worse standardized mortality ratio 16.75 (95% CI: 13.91–20) versus SMR 1.72 (95% CI: 1.26–2.28) in those who achieved EFS24. Cause of death was mostly attributed to non-lymphoma–related causes in those achieving EFS 24.

Abstract Waldenstrom macroglobulinemia (WM) and its precursor IgM gammopathy are distinct disorders characterized by clonal mature IgM-expressing B-cell outgrowth in the bone marrow. Here, we show by high-dimensional single-cell immunogenomic profiling of patient samples that these disorders originate in the setting of global B-cell compartment alterations, characterized by expansion of genomically aberrant extrafollicular B cells of the nonmalignant clonotype. Alterations in the immune microenvironment preceding malignant clonal expansion include myeloid inflammation and naïve B- and T-cell depletion. Host response to these early lesions involves clone-specific T-cell immunity that may include MYD88 mutation–specific responses. Hematopoietic progenitors carry the oncogenic MYD88 mutations characteristic of the malignant WM clone. These data support a model for WM pathogenesis wherein oncogenic alterations and signaling in progenitors, myeloid inflammation, and global alterations in extrafollicular B cells create the milieu promoting extranodal pattern of growth in differentiated malignant cells. Significance: These data provide evidence that growth of the malignant clone in WM is preceded by expansion of extrafollicular B cells, myeloid inflammation, and immune dysfunction in the preneoplastic phase. These changes may be related in part to MYD88 oncogenic signaling in pre–B progenitor cells and suggest a novel model for WM pathogenesis. This article is highlighted in the In This Issue feature, p. 549