Cerhan, James R.

Abstract Background: CD20 antibody plus alkylator and/or anthracycline based immunochemotherapy (IC) is a standard frontline therapy for patients with follicular lymphoma (FL) with 10-year event-free survival (EFS) and overall survival (OS) rates of approximately 50% and 80% respectively in long-term follow-up of clinical trials. Currently available clinical prognostic indices for FL have been designed using PFS and OS endpoints. Early events, commonly defined as progression of disease within 24 months (POD24) or early transformation to a more aggressive histology, are associated with inferior outcomes and increased risk of death due to refractory FL. Timely identification of the minority of patients with elevated mortality risk might enhance clinical management and research strategies. The FLIPI24 Consortium was created to develop a clinical prognostic index using early events as the primary endpoint. We report the outcomes for the pooled cohort and investigate the implications of therapy patterns on potential model development. Methods: Individual patient data were pooled and harmonized from 11 prospective observational cohorts from Europe, North America, and Australia. Patients who were diagnosed with grades 1-3A FL and initiated frontline IC were eligible. EFS was defined as time from start of IC to progression, relapse, retreatment (2nd line), histologic transformation, or death due to any cause. Early events were defined using status at 24 months from start of IC. OS was defined as time from start of IC to death due to any cause. Kaplan Meier curves and Cox proportional hazards models were used to evaluate outcomes by clinical features and therapy types. Results: 9006 patients were abstracted and harmonized, 6111 patients initiated frontline IC between 2002 and 2018 and were included in this analysis. Median age at diagnosis was 61 years (IQR 52-69) and 50% were male. Complete FLIPI data were available in 5637 patients (92%) and 46%, 32%, and 22% were low, intermediate, and high risk, respectively. IC type was 3079 R-CHOP or like (50%) , 1529 R-CVP or like (25%), 918 R-bendamustine (B-R) or like (15%), and 585 fludarabine or other alkylator based IC (10%); 3187 received CD20 antibody maintenance (52%). Patients receiving R-CHOP were younger, more frequently grade 3A, and more frequently had elevated LDH; differences in other characteristics by IC type were not clinically meaningful. At median follow-up of 42 months (IQR 17-72), 2647 patients (43%) had an event (any) and 1494 patients (25%) died. Median survival after an early (non-death) event was 49 months (95% CI: 41-58); 5-year OS was 46% (95% CI: 43-49) compared to 89% (95% CI: 88-90) in patients without POD24. Across all IC types, EFS estimates at 2 and 10 years from start of IC were 80% (95% CI:79-81) and 49% (95% CI:48-51) and OS estimates were 92% (95% CI: 91-92) and 70% (95% CI: 69-72), respectively. FLIPI was highly associated with both EFS (c-statistic=0.61) and OS (c-statistic=0.65) from the initiation of IC (both p<0.0001). There were significant differences in EFS and OS by IC type (both p<0.0001) and use of maintenance was associated with prolonged EFS in landmark analyses at both 6 and 12 months from initiation of IC (both p<0.0001). Treatment patterns changed significantly over the study timeframe. Use of B-R and/or maintenance increased to 30% and 70% respectively in N=2937 patients treated in 2010-2018 (Era2) compared to <1% and 40% respectively in N=3174 patients treated 2002-2009 (Era1). EFS was significantly higher for Era2 compared to Era1 (HR=0.77, 95% CI: 0.71-0.83), which remained significant after adjustment for FLIPI (EFS HR=0.82, 95% CI: 0.76-0.89). However, the association between treatment eras and overall survival was weaker (HR=0.89, 95% CI: 0.79-0.99) and not significant after adjusting for baseline FLIPI (OS HR=0.99, 95% CI: 0.88-1.10). Conclusion: EFS and OS from this large pooled analysis of observational cohorts is similar to long-term follow-up of randomized clinical trials in the IC era and support the use of these data for model development. Modeling efforts for early events should adjust for initial IC selection and use of maintenance therapy. Utilization of bendamustine and/or maintenance therapy increased over the study timeframe from 2002-2018, and Era2 was associated with improved EFS but not OS. This cohort provides comprehensive and robust observational data to define clinical predictors in IC treated patients. Figure 1 Figure 1. Disclosures Maurer: 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; BMS: Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees; Nanostring: Research Funding. Flowers: Janssen: Research Funding; Takeda: Research Funding; National Cancer Institute: Research Funding; Biopharma: Consultancy; BeiGene: Consultancy; Amgen: Research Funding; Celgene: Consultancy, Research Funding; Xencor: Research Funding; Acerta: Research Funding; Bayer: Consultancy, Research Funding; Sanofi: Research Funding; 4D: Research Funding; Adaptimmune: Research Funding; Allogene: Research Funding; EMD: Research Funding; TG Therapeutics: Research Funding; Burroughs Wellcome Fund: Research Funding; Kite: Research Funding; AbbVie: Consultancy, Research Funding; Cellectis: Research Funding; Denovo: Consultancy; Cancer Prevention and Research Institute of Texas: CPRIT Scholar in Cancer Research: Research Funding; Karyopharm: Consultancy; Gilead: Consultancy, Research Funding; Genmab: Consultancy; Epizyme, Inc.: Consultancy; Novartis: Research Funding; Nektar: Research Funding; Morphosys: Research Funding; Iovance: Research Funding; Spectrum: Consultancy; Pfizer: Research Funding; Ziopharm: Research Funding; Guardant: Research Funding; Eastern Cooperative Oncology Group: Research Funding; SeaGen: Consultancy; Pharmacyclics/Janssen: Consultancy; Genentech/Roche: Consultancy, Research Funding; Pharmacyclics: Research Funding. Villa: Janssen: Honoraria; Gilead: Honoraria; AstraZeneca: Honoraria; AbbVie: Honoraria; Seattle Genetics: Honoraria; Celgene: Honoraria; Lundbeck: Honoraria; Roche: Honoraria; NanoString Technologies: Honoraria. Weibull: Jansen-Cilag: Other: part of a research collaboration between Karolinska Institutet and Janssen Pharmaceutica NV for which Karolinska Institutet has received grant support. Ghesquieres: Janssen: Honoraria; Mundipharma: Consultancy, Honoraria; Roche: Consultancy; Celgene: Consultancy, Honoraria; Gilead Science: Consultancy, Honoraria. Kridel: Gilead Sciences: Research Funding. Gandhi: Janssen: Research Funding; Novartis: Honoraria. Cheah: Celgene: Research Funding; TG Therapeutics: Consultancy, Honoraria, Other: advisory; Loxo/Lilly: Consultancy, Honoraria, Other: advisory; AstraZeneca: Consultancy, Honoraria, Other: advisory; AbbVie: Research Funding; Beigene: Consultancy, Honoraria, Other: advisory; Ascentage pharma: Consultancy, Honoraria, Other: advisory; Gilead: Consultancy, Honoraria, Other: advisory; MSD: Consultancy, Honoraria, Other: advisory, Research Funding; Janssen: Consultancy, Honoraria, Other: advisory; Roche: Consultancy, Honoraria, Other: advisory and travel expenses, Research Funding. Hawkes: Gilead: Membership on an entity's Board of Directors or advisory committees; Merck Sharpe Dohme: Membership on an entity's Board of Directors or advisory committees; Antigene: Membership on an entity's Board of Directors or advisory committees; Regeneron: Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squib/Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck KgA: Research Funding; Specialised Therapeutics: Consultancy; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Roche: Membership on an entity's Board of Directors or advisory committees, Other: Travel and accommodation expenses, Research Funding, Speakers Bureau; Janssen: Speakers Bureau. Seymour: Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sunesis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AstraZeneca: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Mei Pharma: Honoraria, Membership on an entity's Board of Directors or advisory committees; Morphosys: Honoraria, Membership on an entity's Board of Directors or advisory committees; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Research Funding, Speakers Bureau. Freeman: Amgen: Honoraria; Celgene: Honoraria; Sanofi: Honoraria, Speakers Bureau; Incyte: Honoraria; Abbvie: Honoraria; Teva: Research Funding; Roche: Research Funding; Janssen: Honoraria, Speakers Bureau; Seattle Genetics: Honoraria; Bristol Myers Squibb: Honoraria, Speakers Bureau. Clausen: Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel expences ASH 2019; Gilead: Consultancy, Other: Travel expences 15th ICML ; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Wahlin: Gilead Sciences: Research Funding; Roche: Consultancy, Research Funding. Link: Novartis, Jannsen: Research Funding; Genentech/Roche: Consultancy, Research Funding; MEI: Consultancy. Ekstroem Smedby: Janssen Cilag: Research Funding; Takeda: Consultancy. Sehn: Genmab: Consultancy; Novartis: Consultancy; Debiopharm: Consultancy. Trněný: Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses; Portola: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; 1st Faculty of Medicine, Charles University, General Hospital in Prague: Current Employment; Celgene: Consultancy; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses; Bristol-Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses; Amgen: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accommodations, Expenses; MorphoSys: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Honoraria; Gilead Sciences: Consultancy, Honoraria, Other: Travel, Accommodations, Expenses; Incyte: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. El-Galaly: ROCHE Ltd: Ended employment in the past 24 months; Abbvie: Other: Speakers fee. Cerhan: Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; Regeneron Genetics Center: Other: Research Collaboration; Genentech: Research Funding; NanoString: Research Funding.

Abstract Introduction Monoclonal B-cell lymphocytosis (MBL), monoclonal gammopathy of undetermined significance (MGUS), and clonal hematopoiesis (CH) are three common premalignant hematological conditions. MBL is a precursor to chronic lymphocytic leukemia (CLL), MGUS is a precursor to both multiple myeloma (MM) and Waldenström macroglobulinemia (WM), and CH is a possible precursor to myeloid disease. All three conditions are independently associated with aging. Furthermore, there is evidence that all three conditions are associated with increased risk of infection. The relationship among these conditions, the prevalence with which they co-exist, and the association between the number of premalignant conditions and risk of infection is unknown. Methods Study participants from the Mayo Clinic Biobank, a large-scale biorepository of adult patients, provided a peripheral blood sample between 7/14/2009 to 06/18/2015. Individuals were screened for MBL using eight-color flow cytometry capable of detecting clonal B-cells to the 0.005% level. MGUS was screened using a matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) assay. CH was screened using a targeted sequencing panel of 42 CH-associated genes with at least 1000x read depth and the ability to detect variant allele fractions down to 1%. All study participants resided in Olmsted County, Minnesota, the county that includes Mayo Clinic. Serious infection, defined as hospitalization due to infection, was abstracted from medical records from the time of sample collection through 12/31/2020 or date of death. The medical record abstractor collecting data was blinded to condition. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for the association between each of the conditions. Cox regression was used to estimate hazard ratios (HR) and 95% CI to assess the association between number of premalignant conditions with risk of infection. All analyses were adjusted for age at sample collection and sex. Results A total of 407 individuals (55% male, median age 68 years) were screened for all three conditions. The prevalence was 19.9% (n=81) for MBL, 14.5% (n=59) for MGUS, and 25.6% (n=104) for CH. When we evaluated the association between each of the conditions, we found no evidence of an association between the prevalence of CH and risk of MBL (OR=0.79, 95% CI: 0.43-1.42), CH and risk of MGUS (OR=1.24, 95% CI: 0.66-2.27), or MGUS and risk of MBL (OR=1.32, 95% CI:0.66-2.52). The prevalence of co-existence of these conditions was assessed by grouping individuals based on their condition or conditions (Figure 1A). We found that 197 (48.4%) study participants had at least one premalignant condition and 10.6% had two or more. Individuals with 2 or more conditions were the oldest (median age 74 years), followed by 1 condition (median 69 years) and 0 conditions (median 67 years, P-trend <0.001). Sex was not significantly different across the groups, with 55%, 58%, and 47% male for 0, 1, and 2 conditions, respectively. Medical record abstraction identified 97 serious infection events in 80 individuals. Medical records were not available on 7 individuals. The most common infections were urinary tract (20 events), pneumonia (14 events), and cellulitis (14 events). Median follow-up time was 10.6 years (range 0.1-11.5 years). Compared to individuals with no condition, MBL (HR=1.75, 95% CI: 1.06-2.88) and MGUS (HR=1.75, 95% CI: 1.04-2.93) were associated with increased risk of serious infection. We found no evidence of an association with CH (HR=1.15, 95% CI: 0.71-1.87). When grouped by the number of conditions, we observed a significant trend (P-trend <0.01, Figure 1B) in risk of serious infections by the number of conditions: individuals with 1 condition had a 35% increased risk of infections (HR=1.35, 95% CI:0.83-2.20) and individuals with 2 or more conditions had a 2.6-fold increased risk (HR=2.58, 95% CI: 1.37-4.84). Discussion At least one premalignant condition was present in nearly 50% of the study population, with CH being the most prevalent. No evidence of a relationship between any of the three conditions was observed. However, we found increased susceptibility to serious infections as the number of conditions increased with individuals with at least two conditions had 2.6-fold increased risk of infections. Figure 1 Figure 1. Disclosures Parikh: Pharmacyclics, AstraZeneca, Genentech, Gilead, GlaxoSmithKline, Verastem Oncology, and AbbVie: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics, MorphoSys, Janssen, AstraZeneca, TG Therapeutics, Bristol Myers Squibb, Merck, AbbVie, and Ascentage Pharma: Research Funding. Dispenzieri: Takeda: Research Funding; Alnylam: Research Funding; Pfizer: Research Funding; Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy; Janssen: Consultancy, Research Funding. Murray: Mayo Clinic: Other: Has received patents for the Mass-Fix technology which has been licensed to the Binding Site with potential royalties.. Kumar: Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Oncopeptides: Consultancy; Beigene: Consultancy; Novartis: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Antengene: Consultancy, Honoraria; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Roche-Genentech: Consultancy, Research Funding; Bluebird Bio: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Carsgen: Research Funding; Amgen: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Cerhan: Regeneron Genetics Center: Other: Research Collaboration; Genentech: Research Funding; Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; NanoString: Research Funding. Kay: TG Therapeutics: Research Funding; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Targeted Oncology: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Abbvie: 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; Sunesis: Research Funding; MEI Pharma: Research Funding; Pharmacyclics: 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; Rigel: Membership on an entity's Board of Directors or advisory committees; Tolero Pharmaceuticals: Research Funding; Genentech: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Behring: Membership on an entity's Board of Directors or advisory committees; CytomX Therapeutics: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees. Shanafelt: Genentech, Pharmacyclics: Research Funding.

Abstract Introduction: Low-grade B-cell lymphomas (LGBCL), aside from follicular lymphoma and chronic lymphocytic leukemia/small lymphocytic lymphoma, account for approximately 10% of B-cell non-Hodgkin lymphomas and consist of several subtypes. While a majority of LGBCL cases have an overall favorable prognosis, we have previously shown that cases who have an event (relapse or progression, transformation, or re-treatment) within 24 months of diagnosis (EFS24) have an inferior overall survival (OS) compared to those achieving EFS24 (Tracy et al., AJH 2019;94:658-66). However, the underlying biological characteristics associated with early failure and aggressive disease across LGBCL subtypes are unknown. In this study, we used matched transcriptomic, genomic, and immune profiling data from LGBCL cases, the largest cohort to date, and asked whether there were unique biological phenotypes across different LGBCL subtypes and whether we could identify signatures associated with aggressive LGBCL. Validation of the prognostic utility of this signature was performed on a previously published, independent cohort of 63 pre-treatment LGBCL cases. Methods: Tumors from 64 newly diagnosed LGBCL patients from the Molecular Epidemiology Resource of the University of Iowa/Mayo Clinic Lymphoma Specialized Program of Research Excellence were included in this study (SMZL (n = 48), NMZL (n = 6), LPL (n = 5), B-NOS (n = 3), EMZL (n = 2)). RNA sequencing (RNAseq) data from 61 LGBCL tumors and 5 benign CD19+CD27+ memory B samples was subjected to NMF clustering to define groups. Differential expression and pathway analysis were used to identify biological characteristics of each cluster. CIBERSORT was used to identify immune cells in the tumor microenvironment. Whole exome sequencing (WES) was performed on 61 tumor-normal pairs. Singscore was used to assign a single score per patient representing gene expression of the survival-associated transcriptomic signature identified in this study. Results: NMF analysis of RNAseq data identified 5 clusters of patients, denoted LGBCL1-5 (Fig 1A). Patients from the same diagnostic subtype did not exclusively cluster together, with all LGBCL clusters comprised of patients from multiple subtypes (Fig 1B). Exploring the association between patient cluster and outcome, we observed significantly inferior event-free survival (EFS) (HR 2.24; 95% CI 1.01-4.98) and overall survival (OS) (HR 5.59; 95% CI 2.00-15.63) in LGBCL5 patients compared to LGBCL1-4 (Fig 1C). In addition, 80% of the transformation cases in our cohort were classified as LGBCL5 (Fig 1D). Differential expression and pathway analysis showed distinct processes significantly upregulated in each cluster (FDR < 0.05), with LGBCL5 demonstrating enrichment of cell cycle and mitosis pathways. CIBERSORT identified increased immune cell content in LGBCL3 and LGBCL5 compared to other clusters, with high frequencies of mast cells in both (p = 0.0002), increased CD8 T cells in LGBCL3 (p < 0.0001), and increased T follicular helper cells in LGBCL5 (p = 0.004). WES identified previously reported alterations in NOTCH, NFkB, and chromatin remodeling pathways and novel variants in LGBCL, including mutations in HNRNPK, CLTC, HLA-A, HLA-B and HLA-C. Assessment of alterations by cluster showed significant enrichment of TNFAIP3 (OR 5.54; 95% CI 1.20-28.14) and BCL2 alterations (OR 5.49; 95% CI 1.07-32.02) in LGBCL5 cluster. Finally, we identified a cell cycle-related transcriptomic signature of 108 genes upregulated in LGBCL5 and EFS24 failure cases. Cases with high expression of this signature showed significantly inferior EFS (HR 14.25; 95% CI 4.90-41.38) and OS (HR 7.82; 95% CI 2.40-25.44) compared to cases with low expression in our discovery cohort. This observation was reproduced in an independent validation cohort, where patients with high expression of this signature demonstrated significantly inferior EFS (HR 5.70; 95% CI 1.49-21.79) and OS (HR 10.07; 95% CI 2.00-50.61). Conclusions: In this study, we are the first to define mechanisms of pathogenesis in LGBCL with shared transcriptomic, genomic, and immune profiles present across LGBCL subtypes. We then further defined a gene expression signature associated with inferior patient outcome, with application of this signature to an independent validation cohort demonstrating proof of concept and utility of this signature as a prognostic marker in LGBCL patients. Figure 1 Figure 1. Disclosures Maurer: Morphosys: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: 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; BMS: Research Funding; Nanostring: Research Funding. Paludo: Karyopharm: Research Funding. Habermann: Tess Therapeutics: Other: Data Monitoring Committee; Morphosys: Other: Scientific Advisory Board; Incyte: Other: Scientific Advisory Board; Seagen: Other: Data Monitoring Committee; Loxo Oncology: Other: Scientific Advisory Board; Eli Lilly & Co.,: Other: Scientific Advisor. Link: MEI: Consultancy; Genentech/Roche: Consultancy, Research Funding; Novartis, Jannsen: Research Funding. Rimsza: NanoString Technologies: Other: Fee-for-service contract. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: 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 Introduction: Novel therapeutic agents such as immune checkpoint inhibitor (ICI) and brentuximab vedotin (BV) are active in classic Hodgkin lymphoma (cHL), including in patients that relapse after autologous stem cell transplant (ASCT). However, optimal management strategy is unclear for patients with relapsed or refractory (RR) cHL post-ASCT. The aim of the study is to determine the impact of novel agents relative to conventional therapy and allogeneic stem cell transplant (allo-SCT) on survival outcomes of patients with cHL who relapsed after ASCT. Methods: Patients with RR cHL who underwent ASCT between 06/1993 and 10/2017 at 3 Mayo Clinic sites were included. Clinical characteristics, treatment information, and outcome data were abstracted. For patients who relapsed after ASCT, the post-relapse progression free survival (PFS) and overall survival (OS) were analyzed using the Kaplan-Meier method and Cox proportional hazards models. Statistical analyses were done in JMP v15.2.1 and EZR v1.54. Results: A total of 332 patients with RR cHL who underwent salvage therapy and ASCT were identified. After a median post-ASCT follow-up of 8.6 years (range 6.8-9.7), 136 (41%) patients had a relapse or disease progression after ASCT. Patient characteristics of the 136 cases are summarized in the Table. The median age at post-ASCT relapse was 34 years (range 20-73), and 77 (57%) were male. 59 (43%) relapsed within 6 months and 77 (57%) relapsed after 6 months following ASCT. 59 (45%) had an extranodal site involvement at relapse. 14 (10%) had therapy with ICI or BV as salvage therapy prior to ASCT or maintenance therapy post-ASCT. The median post-relapse PFS and OS was 0.8 (95% CI 0.6-1.1) and 3.2 years (95% CI 2.2-5.5) years, respectively. Compared to patients who relapse after 6 months, patients who relapsed within 6 months of ASCT had worse post-relapse PFS (median 0.5 [0.3-0.7] vs 1.3 [0.9-1.9] years, p=0.0003) and OS (median 1.3 [0.5-2.2] vs 6.4 [3.7-10.4] years, p=0.0003). Extranodal site involvement at relapse was not associated with post-relapse PFS (median 0.7 [0.5-1.2] vs 0.9 [0.6-1.3] years, p=0.28) but was associated with worse post-relapse OS (median 2.7 [1.5-4.2] vs 6.4 [2.6-NA] years, p=0.006). Prior therapy with ICI or BV was not associated with post-relapse PFS (median 0.6 [0.3-NA] vs 0.8 [0.6-1.1] year, p=0.8) and OS (median NR [1.0-NA] vs 3.2 [2.2-5.5] years, p=0.5). After post-ASCT relapse, the median lines of subsequent therapy were 2 (range 1-12). For first post-ASCT salvage therapy, novel agents (ICI or BV), compared to other therapies, were associated with superior post-relapse PFS (median 1.7 [0.7-3.6] vs 0.7 [0.5-1.0] years, p=0.004) and OS (median 7.6 [4.7-NA] vs 3.2 [2.2-5.6], p=0.02). Allo-SCT following first post-ASCT relapse (n=9) was not associated with improvement in post-relapse PFS (median 2.2 years [0.3-NA] vs 0.8 [0.6-1.1] years, p=0.1) or OS (median NR [0.5-NA] vs 5.1 [3.2-7.3] years, p=0.7). Patients who received ICI or BV at any point post-ASCT relapse had significantly better post-relapse OS (median 7.6 [4.3-16.7] vs 2.2 [1.4-3.7] years, p=0.004) compared to those who never received any novel agent (Figure 1A). In contrast, allo-SCT at any point post-ASCT relapse (n=27) did not improve post-relapse OS (median 5.6 [2.7-NA] vs 4.7 [2.7-7.3] years, p=0.3) (Figure 1B). In multivariate Cox regression models adjusted for age and sex, exposure to ICI and/or BV was associated with superior post-relapse OS (HR 0.5, 95% CI 0.3-0.8, p=0.007); however, allo-SCT was not associated with improvement in post-relapse OS (HR 0.8, 95% CI 0.4-1.5, p=0.5). Conclusions: Patients relapsing within 6 months of ASCT and those with extranodal involvement at relapse had inferior OS after post-ASCT relapse. Prior therapy with novel agents did not impact post-relapse survival outcomes. In the setting of post-ASCT relapse, novel therapeutic agents significantly improved survival outcomes while allo-SCT did not. Future multicenter studies are needed to explore the role of novel agents and allo-SCT in patients with RR cHL post-ASCT relapse. Figure 1 Figure 1. Disclosures Wang: Eli Lilly: Membership on an entity's Board of Directors or advisory committees; InnoCare: Research Funding; MorphoSys: Research Funding; Genentech: Research Funding; Novartis: Research Funding; LOXO Oncology: Membership on an entity's Board of Directors or advisory committees, Research Funding; Incyte: 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. Paludo: Karyopharm: Research Funding. Tun: Gossamer Bio, Acrotech: Consultancy; Mundipharma, Celgene, BMS, Acrotech, TG therapeutics, Curis, DTRM: Research Funding. Cerhan: Regeneron Genetics Center: Other: Research Collaboration; Genentech: Research Funding; Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; NanoString: Research Funding. Habermann: Tess Therapeutics: Other: Data Monitoring Committee; Morphosys: Other: Scientific Advisory Board; Incyte: Other: Scientific Advisory Board; Seagen: Other: Data Monitoring Committee; Loxo Oncology: Other: Scientific Advisory Board; Eli Lilly & Co.,: Other: Scientific Advisor. 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, MorphoSys, Genentech, Selvita, Debiopharm Group, Kite/Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene, NanoString Technologies, MorphoSys: Research Funding. Ansell: Bristol Myers Squibb, ADC Therapeutics, Seattle Genetics, Regeneron, Affimed, AI Therapeutics, Pfizer, Trillium and Takeda: Research Funding.

Abstract Introduction: Non-Hodgkin lymphoma (NHL) constitutes ~40% of hematologic malignancies and, in 2020, resulted in 19,940 deaths in the USA. The most common NHL subtypes are diffuse large B-cell lymphoma (DLBCL), including primary mediastinal large B-cell lymphoma (PMBCL), and follicular lymphoma (FL). Although a majority of patients respond to standard-of-care therapy, many patients with NHL eventually relapse, highlighting the need for additional treatments. Real-world data regarding the safety and efficacy of emerging therapies in the relapsed/refractory (R/R) population, and the association between treatment patterns and patient outcomes, are limited. These data could provide unique insights to clinical and health-related quality of life (HRQoL) outcomes in patients with DLBCL, FL, or PMBCL treated with emerging therapies, especially novel options such as chimeric antigen receptor (CAR) T cell therapies. Methods: The Connect ® Lymphoma Disease Registry (NCT04982471) is a US-based, multicenter, prospective observational cohort study of patients with R/R NHL (DLBCL, FL, and PMBCL). Approximately 2100 patients ≥ 18 years of age from ~200 community oncology (~80%) or academic (~20%) sites will be enrolled over a ~3-year period. Patients with histologically confirmed NHL subtypes will be enrolled into 1 of 4 cohorts: first R/R DLBCL, second R/R DLBCL, first R/R FL, or first R/R PMBCL (Figure). Patients will be required to have begun second- (first R/R) or third- (second R/R) line systemic treatment within 60 days prior to enrollment. Patients receiving treatment for any active malignancy other than DLBCL, FL, or PMBCL at the time of enrollment, or who are diagnosed with any other malignancy in the 6 months prior to enrollment, will be excluded. All treatment and management decisions will be determined by the practicing clinicians. Patients may undergo hematopoietic stem cell transplantation, CAR T cell therapy, or other treatments at other sites while participating in this study. Patients will be followed from enrollment for up to 5 years or until death, withdrawal of consent, loss to follow-up, or study termination, whichever occurs first. Data collection will occur at enrollment (baseline) and then every ~3 months. The main objectives of the Connect ® Registry are to describe patient characteristics, practice patterns, and factors associated with treatment choice, sequencing, and effectiveness in NHL subtypes. Secondary objectives include describing treatment regimen safety, patient-reported outcomes (PROs) including HRQoL, and healthcare resource utilization outcomes. Exploratory objectives include tumor and blood biomarker evaluation and understanding the availability of social support and its impact on long-term treatment decision-making. Case report forms will be used to collect clinical and treatment data, including baseline demographics, clinical characteristics, treatment details and response, and socioeconomic factors. Outcome measures for efficacy will be progression-free survival, event-free survival, objective response rate, time to next treatment, and overall survival. The availability of social support will be assessed via a specific questionnaire administered at baseline. General (EQ-5D-5L) and disease-specific (FACT-Lym) questionnaires will also be administered. Patients may also optionally agree to release tumor biopsies and blood samples for biomarker analysis. Clinicians will be required to report serious adverse events (AEs), secondary primary malignancies, and confirmed COVID-19 infections within 24 hours. Non-serious AEs of interest include grade 1-3 cytokine release syndrome, grade 1-3 neurotoxicity, grade 3 colitis, grade 3 arrhythmia, grade 3 hemorrhage. Other AEs of interest to be collected include grade 3 hypogammaglobulinemia, prolonged grade 3 cytopenia, and grade 3 infections. Data collected in the Connect ® Registry will increase understanding of the association between emerging therapies and patient outcomes for R/R DLBCL, FL, and PMBCL. Study support: Bristol Myers Squibb Figure 1 Figure 1. Disclosures Flowers: Amgen: Research Funding; Janssen: Research Funding; Biopharma: Consultancy; Ziopharm: Research Funding; Burroughs Wellcome Fund: Research Funding; Nektar: Research Funding; Karyopharm: Consultancy; Iovance: Research Funding; Allogene: Research Funding; AbbVie: Consultancy, Research Funding; Cellectis: Research Funding; Pfizer: Research Funding; Sanofi: Research Funding; BeiGene: Consultancy; Kite: Research Funding; EMD: Research Funding; Genentech/Roche: Consultancy, Research Funding; Morphosys: Research Funding; Adaptimmune: Research Funding; Novartis: Research Funding; Epizyme, Inc.: Consultancy; Spectrum: Consultancy; Pharmacyclics/Janssen: Consultancy; Acerta: Research Funding; 4D: Research Funding; Denovo: Consultancy; Celgene: Consultancy, Research Funding; Guardant: Research Funding; Genmab: Consultancy; Gilead: Consultancy, Research Funding; Bayer: Consultancy, Research Funding; SeaGen: Consultancy; Cancer Prevention and Research Institute of Texas: CPRIT Scholar in Cancer Research: Research Funding; Takeda: Research Funding; National Cancer Institute: Research Funding; TG Therapeutics: Research Funding; Eastern Cooperative Oncology Group: Research Funding; Xencor: Research Funding; Pharmacyclics: Research Funding. Andorsky: Celgene/Bristol Myers Squibb: Research Funding; AbbVie: Consultancy; Celgene/Bristol Myers Squibb: Consultancy; AstraZeneca: Other: served on steering committees; Epizyme: Research Funding; AbbVie: Research Funding. Burke: SeaGen: Consultancy, Speakers Bureau; X4 Pharmaceuticals: Consultancy; Bristol Myers Squibb: Consultancy; Verastem: Consultancy; AstraZeneca: Consultancy; MorphoSys: Consultancy; Adaptive Biotechnologies: Consultancy; Roche/Genentech: Consultancy; Epizyme: Consultancy; Kura: Consultancy; AbbVie: Consultancy; Beigene: Consultancy, Speakers Bureau; Kymera: Consultancy. Cerhan: Genentech: Research Funding; NanoString: Research Funding; Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; Regeneron Genetics Center: Other: Research Collaboration. Grinblatt: Astellas Pharma, Inc.: Consultancy; Bristol Myers Squibb: Consultancy; Astra Zeneca: Consultancy; AbbVie: Consultancy. Toomey: Bristol Myers Squibb: Consultancy. Zelenetz: Gilead: Honoraria, Research Funding; Verastem: Honoraria; Novartis: Honoraria; MEI Pharma: Honoraria, Research Funding; SecuraBio: Honoraria; Abbvie: Honoraria, Research Funding; MorphoSys: Honoraria; Pharmacyclics: Honoraria; AstraZeneca: Honoraria; LFR: Other; Genentech/Roche: Honoraria, Research Funding; NCCN: Other; MethylGene: Research Funding; Beigene: Honoraria, Other, Research Funding; BMS/Celgene/JUNO: Honoraria, Other; Amgen: Honoraria; Gilead: Honoraria; Janssen: Honoraria. Sullivan: Bristol Myers Squibb: Current Employment, Current holder of individual stocks in a privately-held company. Flick: Bristol Myers Squibb: Current Employment. Kiselev: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company, Current holder of individual stocks in a privately-held company. Kaplan: Bristol Myers Squibb: Current Employment. Ahn: Bristol Myers Squibb: Current Employment.

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 Yttrium-90 ibritumomab tiuxetan [(90)Y-IT; Zevalin] is a radio-immunoconjugate (RIC) which targets CD20. This study evaluates the utilization and cost-effectiveness of (90)Y-IT in the first line treatment for patients with previously untreated low-grade FL (UFL) and marginal zone lymphoma (UMZL) treated at our institution with (90)Y-IT. Methods We utilized the Advanced Text Explorer (ATE) and the Lymphoma SPORE databases to identify two groups of patients with UFL, WHO grade 1-2, and UMZL who received treatment with either (90)Y-IT or bendamustine plus rituximab (BR) at Mayo Clinic Cancer Center between January 2003 and December 2019. We excluded all patients who had >25% bone marrow involvement with lymphoma for the BR group as this was a requirement for (90)Y-IT treatment. Inverse propensity weighting was utilized to balance the groups for baseline patients and disease characteristics. We use progression-free survival (PFS) as a denominator for the cost effectiveness/utilization evaluation. We identified meaningful and retrospectively measurable outcomes to compare between the groups. we extracted the following data; number of clinic visits in the first year after therapy, emergency room visits, number of hospital admissions, number of hospitalization days, numbers of days on the floor and ICU, number of infections, number of neutropenic fever hospitalizations, number of C-difficile events, number of blood products transfusions, overall use of growth factors due to therapy induced neutropenia, average number of times a growth factor was used, and the number of therapeutic use days. We defined days of therapeutic use as the number of days a treatment was administered on. We also calculated the average cost of the induction treatment when utilizing either (90)Y-IT or BR. The therapeutic cost included only the cost of the medications/therapies and their administration. Results Our cohort consists of a total of 143 patients - 64% (92/143) received BR and 36% (51/143) received (90)Y-IT (see Table-1 for clinical characteristics).The median follow-up from the time of therapeutic administration for the (90)Y-IT group was 5.3 years (95% CI; 4.2, 6.2) with one death and 4.7 years (95% CI; 3.9, 4.9) for the BR group with 6 deaths. The ORR was 100% in (90)Y-IT group with 94% achieving complete response (CR) while ORR in the BR group was 98% with 95% achieving CR. Rituximab maintenance was utilized in 33% of BR patients compared to only 6% in patients who received (90)Y-IT, p=0.002. After utilizing inverse propensity weighting (Figure-1), 5 years PFS was 76% for the (90)Y-IT group and 75% for the BR group, p=0.63 (Figure-2). We evaluated the average treatment effect of (90)Y-IT compared to BR on utilization outcomes, Table-2. (90)Y-IT required an average of 4.5 clinic visits less within the first year after treatment compared to BR group, p<0.001. (90)Y-IT patients had an average of 10 days less of therapeutic use days compared to the BR group, p<0.001. Patienta had similar admission rates to the hospital in both groups. However, when patients were admitted to the hospital in the first year after treatment, those who received (90)Y-IT spent an average of 1.5 days less in the hospital compared to the BR group, p=0.046. The overall use of growth factors was 40% less in the (90)Y-IT group as compared to the BR group, p<0.001. The therapeutic cost of induction of (90)Y-IT was 54% less than that of 6 cycles of BR. Transformation to a high grade of lymphoma was seen in 4 patients in the BR group and 2 patients in the (90)Y-IT group. There was only one case of myelodysplastic syndrome in the BR group and none in the (90)Y-IT group. Conclusion Radio-immunoconjugate therapy with (90)Y-IT is a very convenient and cost-effective treatment for low-grade UFL and UMZL. This is especially important amidst the COVID-19 pandemic as it requires less contact with the health system with decreased number of therapeutic days, clinic visits, use of growth factors and number of hospitalization days. The cost of the therapeutic agents and their administration was also significantly lower for the (90)Y-IT which could help reducing the burden on the health system. Figure 1 Figure 1. Disclosures Cerhan: Regeneron Genetics Center: Other: Research Collaboration; Genentech: Research Funding; Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; NanoString: Research Funding. Tun: Mundipharma, Celgene, BMS, Acrotech, TG therapeutics, Curis, DTRM: Research Funding; Gossamer Bio, Acrotech: Consultancy. OffLabel Disclosure: We are describing the use of Yttrium-90 ibritumomab tiuxetan in the first line setting in comparison to the bendamustine plus rituximab which is the standard of care

Abstract Introduction: Chronic lymphocytic leukemia (CLL) is characterized by multiple copy number alterations (CNA) and mutations that are central to disease pathogenesis, prognosis, risk-stratification, and identification of response or resistance to therapies. Fluorescence in situ hybridization (FISH) is gold standard in the clinical laboratory for detecting prognostic CNAs in CLL (e.g. deletion 17p13 (del(17p), deletion 11q23 (del(11q), deletion 13q14 (del(13q), and trisomy 12). Most clinical FISH assays have high specificity and sensitivity, but the technique can detect a limited number of alterations per assay. Importantly, next-generation sequencing (NGS) techniques have become more readily available for clinical applications and are increasingly being used for screening not only mutations, but also copy number abnormalities in multiple genes and chromosomal regions of interest in hematologic malignancies. Here, we evaluated the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) using a custom targeted NGS assay for detecting common prognostic chromosomal alterations in CLL and high-count monoclonal B-cell lymphocytosis (MBL), the precursor to CLL. Methods : We designed a SureSelect DNA targeted sequencing panel, covering all exons of 59 recurrently CLL mutated genes and additional amplicons across regions affected by clinically relevant CNAs. All CLL (N=534) and MBL (N=162) patients had pre-treatment peripheral blood mononuclear cells (PBMC) collected within two years of diagnosis. DNA was extracted in cases with purity >80% of CD5+/CD19+ cells. Clinical FISH data was available within 100 days of NGS in all untreated CLL and MBL cases. PatternCNV was used to detect clinically relevant CNAs in chromosomes 11, 12, 13 and 17. We performed a principal component analysis on the CNA calls, excluding chromosomes 11, 12, 13, and 17 to identify clusters of samples. Each cluster was then independently rerun with PatternCNV and the results from chromosomes 11, 12, 13, and 17 were extracted and further analyzed. We excluded samples with low tumor metrics identified by FISH (less than 20% of cells with del(17p), del(11q), trisomy 12 and del(13q)). Results: We sequenced a total of 696 patients of whom 162 were MBL and 534 were untreated CLL. The most commonly mutated genes were NOTCH1 (11.0%), TP53 (8.7%), SF3B1 (7.7%), ATM (4.1%), and CHD2 (3.8%). Based on CNA analyses from the NGS data, we identified 59 (9.1%) individuals with del(17p), 88 (13.4%) individuals with del(11q), 128 (20.0%) individuals with trisomy 12, and 329 (53.0%) individuals with del(13q). All 696 individuals had FISH panels conducted, with 39 (5.6%) individuals with del(17p), 68 (9.8%) individuals with (11q), 119 (17.1%) with trisomy 12, and 295 (42.4%) with del(13q). When we compared our CNA analyses with the FISH data, we found high concordance 95.0% for del(17p), 92.7% del(11p), 94.3% for trisomy 12, and 88.2% for del(13q). For del(17p) we found a sensitivity of 93.9%, specificity of 95.4%, PPV of 52.5%, and NPV of 99.7%. Del(11q) revealed a sensitivity of 88.1%, specificity of 94.0%, PPV of 59.1%, and NPV 98.8%. We found a sensitivity of 93.8%, specificity of 95.6%, PPV 82.0%, and NPV of 98.6% for trisomy 12 and for del(13q) we found a sensitivity of 92.6%, specificity of 90.9%, PPV of 91.7%, and NPV of 93.8%. We found lower PPVs in del(17p) and del(11q) likely due to lower prevalence of these chromosomal abnormalities. Conclusion: Here we show a high sensitivity, specificity, and NPV when comparing targeted sequencing with FISH. FISH panel testing is widely used in clinical practice to characterize highly prognostic chromosomal abnormalities in CLL. Comprehensive genetic profiling with NGS has become increasingly important in the work up of hematologic malignancies and provides additional prognostic and predictive information, including clinically relevant mutations such as TP53, SF3B1, and NOTCH1, tumor mutation load and mutations associated with resistance to chemo-immunotherapy and targeted therapies, such as BTK or BCL2 inhibitors, that FISH cannot offer. We show that NGS can infer clinically relevant CNA in cases without FISH testing while also providing additional clinically relevant information. Figure 1 Figure 1. Disclosures Cerhan: Regeneron Genetics Center: Other: Research Collaboration; Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; NanoString: Research Funding; Genentech: Research Funding. Parikh: Pharmacyclics, MorphoSys, Janssen, AstraZeneca, TG Therapeutics, Bristol Myers Squibb, Merck, AbbVie, and Ascentage Pharma: Research Funding; Pharmacyclics, AstraZeneca, Genentech, Gilead, GlaxoSmithKline, Verastem Oncology, and AbbVie: Membership on an entity's Board of Directors or advisory committees. Kay: Genentech: Research Funding; MEI Pharma: Research Funding; Sunesis: Research Funding; Acerta Pharma: Research Funding; Abbvie: 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; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharmaceuticals: Research Funding; Rigel: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; CytomX Therapeutics: Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Research Funding; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Targeted Oncology: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Behring: Membership on an entity's Board of Directors or advisory committees.

Abstract Background Diffuse large B-cell lymphoma (DLBCL) that fails to achieve a complete response (CR) or relapses early after standard immunochemotherapy (IC, e.g., R-CHOP or similar) is referred to as primary refractory DLBCL and has a poor prognosis. The clinical course with regards to frontline IC is heterogenous, and different definitions have been used in literature, e.g., progressive or refractory during therapy (narrow definition), or not achieving complete remission at the end of IC, or relapsing within 6 or 12 months after completing IC (broad definition). A small proportion of patients may still have chemosensitive disease and be able to achieve durable disease control with salvage chemotherapy followed by autologous stem cell transplant (ASCT). However, it is challenging to identify such patients, with clinical and molecular predictors highly needed. In this study, we examined the association of time to refractory status with survival outcomes in patients with primary refractory disease. Methods Adult patients with newly diagnosed DLBCL between 2002 and 2015 and seen at Mayo Clinic Rochester were identified from the prospective Molecular Epidemiology Resource (MER) cohort study of the University of Iowa/Mayo Clinic Lymphoma SPORE. The current study included patients with primary refractory disease, which was defined as no response to frontline IC (primary progression), partial response (PR) at end of treatment (EOT PR), or relapse with 12 months after achieving CR at EOT (early relapse). Clinical characteristics, treatment and response data, and follow-up data were abstracted from MER and collected by medical record review if needed. Clinical characteristics between groups were compared using Chi-square test. Overall survival (OS) was defined as the time from confirmation of refractory disease to the time of death from any cause and was analyzed using the Kaplan-Meier method. Results Out of 949 newly diagnosed DLBCL patients, 122 (12.8%) had primary refractory disease, 36 with primary progression, 36 with EOT PR, and 50 with early relapse. The baseline clinical characteristics are summarized in Table 1. No significant differences in age, gender, ECOG performance status, number of extranodal sites, stage, International Prognostic Index, or cell of origin were found between the 3 groups. The proportion of MYC2 and BCL2/BCL6 rearrangements or Myc/Bcl2 double expressor was small and not different among the 3 groups. Salvage therapies were mainly platinum based high-dose chemotherapy (e.g., R-ICE, R-DHAP, or similar) for systemic disease, MTX-based therapy for CNS relapse, or radiotherapy or resection for localized disease (Table 1). The response to salvage chemotherapy was significantly different between the 3 groups. The CR/PR rate was 8.6%/28.6% for patients with primary progression, 16.7%/46.7% for patients with EOT PR, and 35.6%/33.3% for patients with early relapse (P<0.01, Table 1). At a median follow-up time (of living patients) of 113 months, 93 patients had died. The 2-year OS was 13.9% for patients with primary progression, which was significantly worse compared to that of patients with EOT PR (2-year OS 41.7%) or early relapse (2-year OS 44%), (P=0.001)(Figure 1A). In patients with early relapse, the 2-year OS was not significantly different among those who relapsed with 3 months, between 3-6 months, or between 6-12 months (Figure 1B). Conclusion Our data suggest that broadly defined primary refractory DLBCL has heterogenous survival outcomes. DLBCL patients with primary progressive disease represent an ultra-high risk group that has particularly poor survival outcomes with current standard salvage regimens. Novel therapies such CAR T-cell therapy or targeted agents should be studied in this patient population. In contrast, patient who only achieve PR at EOT and those who relapse within 1 year of achieving CR had better OS. A fraction of these patients may still have chemosensitive disease and benefit from salvage chemotherapy and ASCT. The survival difference in the two groups also has important implications for clinical trial design. The definition of primary refractory DLBCL in clinical trials should be carefully and clearly defined. When evaluating novel therapies in single arm trials, the benchmark for efficacy (i.e., historical outcomes) may differ according to the population included in the trial (e.g., time to refractory status). 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. Bennani: Vividion: Other: Advisory Board; Kyowa Kirin: Other: Advisory Board; Daichii Sankyo Inc: Other: Advisory Board; Verastem: Other: Advisory Board; Purdue Pharma: Other: Advisory Board; Kymera: Other: Advisory Board. Cerhan: Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; NanoString: Research Funding; Regeneron Genetics Center: Other: Research Collaboration; Genentech: Research Funding. 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. 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. Wang: Genentech: Research Funding; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees; Novartis: 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; MorphoSys: Research Funding; LOXO Oncology: Membership on an entity's Board of Directors or advisory committees, Research Funding. Nowakowski: Celgene, MorphoSys, Genentech, Selvita, Debiopharm Group, Kite/Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene, NanoString Technologies, MorphoSys: Research Funding.

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.