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Background: Recently, large B-cell lymphomas (LBCLs) have undergone major shifts in classification and treatment paradigm, particularly with the advent of CD19-targeted chimeric antigen receptor T cell therapy (CAR-T). Initially approved as third-line treatment in LBCL in 2017, as of early 2022 CAR-T is indicated for second-line therapy (2L) in patients with relapsed or refractory (R/R) disease within 12 months of frontline treatment or who are not candidates for autologous stem cell transplant (ASCT). Given this quickly changing landscape, we aimed to describe disease characteristics, patterns of care, and survival outcomes in patients with R/R LBCL receiving two or more lines of systemic therapy across modern treatment eras. Methods: We developed a database of patients with R/R LBCL from 8 U.S. academic centers in the Lymphoma Epidemiology of Outcomes (LEO) Cohort study (NCT02736357) and Consortium for Real World Evidence (CReWE). Unlike the SCHOLAR-1 dataset (M Crump et al, Blood 2017), our cohort included any patient receiving 2L, regardless of timing of progression/relapse. For this analysis, eligible patients were aged ≥18 years and received 2L between 2002-2022. Patients with histologic transformation, post-transplant lymphoproliferative disorder, primary CNS lymphoma, primary mediastinal B-cell lymphoma, Burkitt lymphoma, or plasmablastic lymphoma were excluded. Prognostic factors, therapy details (including intent for ASCT and/or CAR-T), and outcomes, including treatment response, event-free survival (EFS), and overall survival (OS), were abstracted for all lines of therapy. Treatment eras were defined as pre-CAR-T (2002-2010), CAR-T available via clinical trial (2011-2017), and post-FDA approval of CAR-T (2018-2022). Results: Of 1760 patients initiating 2L for R/R disease, 1523 were eligible for analysis. Median age at start of 2L was 62 (interquartile range [IQR] 53-70), and 65% were male; 11% were non-White, and 8% were Hispanic. High-grade subtypes comprised 16% of all cases. IPI was available for 1013 patients at time of 2L therapy, with 54% having IPI 3-5. Median time from diagnosis to 2L was 8.7 months (IQR 5.6-18.5), with 834 patients not having achieved complete response (CR) to 1L, 285 patients relapsing <12 months after 1L, and 404 patients relapsing ≥12 months after 1L. The median number of total lines of therapy received was 4 (range 2-18), with 586 and 347 receiving ASCT and CAR-T, respectively, at any line of treatment. At a median follow-up of 48 months from the start of 2L, 926 patients (61%) had died. Progressive lymphoma was the primary cause of death in 75% of deceased patients, with 8% of reported deaths due to therapy. 2L was received at an academic medical center in 83% cases, and 209 patients (14%) received 2L on a clinical trial. ASCT and/or CAR-T was planned at 2L for 989 patients (65%), of whom 463 ultimately received ASCT, 88 received CAR-T, and 21 received allogeneic transplant at 2L. 494 patients were not considered for ASCT or CAR-T at 2L, and 40 were unknown for ASCT/CAR-T intent. Breakdown by treatment era (n = 1518 with available treatment start date) is shown in the Table. Median EFS from start of 2L was 4.2 months (95% confidence interval [CI]: 3.8-4.8). Median OS from start of 2L was 18 months (95% CI: 17-22), and 2- and 5-year OS estimates were 46% (95% CI: 44-49%) and 35% (95% CI: 33-38%), respectively. EFS and OS improved significantly for patients initiating 2L between 2011-2017 compared to 2002-2010. However, EFS and OS in the 2018-2022 era remained similar to 2011-2017 (Figure). Conclusions: To our knowledge, this study is the first-ever large-scale attempt to describe patterns of care and outcomes in LBCL 2L in the modern era, inclusive of all treatment approaches. The rich and unique LEO CReWE dataset captures evolving practice approaches over time in terms of both intent for and receipt of cellular therapies. Likely reflecting the rapid development of many novel immune effector cell products and bispecific antibodies, we observed increased enrollment on 2L clinical trials in the 2018-2022 period, including a substantial proportion of patients receiving CAR-T in 2L. Importantly, survival increased in treatment eras during which CAR-T was available. Ongoing analyses of factors associated with improved survival will be presented at the meeting.

Introduction: DH/THL also classified as high-grade B cell lymphomas (HGBCL) with MYC and BCL2 and/or BCL6 rearrangements have higher risk of progression after initial treatment and poor response to salvage therapies compared to diffuse large B cell lymphoma (DLBCL), NOS. Recently, CART cell therapy has shown encouraging responses in treatment of relapsed refractory (R/R) DLBCL. In this retrospective study, we evaluated whether survival of (R/R) DH/THL is improved in the CART era. Methods: In this multicenter retrospective study, adult pts (pts) with R/R DH/THL after anthracycline-based therapy were included. Demographic and clinical variables were obtained from electronic health records. Study objectives was overall survival (OS) at 2 year landmark. We utilized full propensity score matching to compare progression free survival (PFS) and OS of CART with 2 nd line chemoimmunotherapy. Results: 278 DH/THL pts treated between 2010-2020 were included. Median age was 63 years (range 52-74), 163 (58%) were male, 119 (43%) were classified as DLBCL and 116 (42%) as HGBCL; 40 (14%) were transformed from follicular lymphoma. 225 (82%) had advanced stage, 161 (67%) had elevated LDH, 85 (33%) had bulky disease, 74 (59%) had B symptoms. 105 (38%) pts treated for relapsed disease before 2018 were included in the pre-CART era cohort. 168 (60%) pts treated from 2018 onwards were included in the CART era cohort. 102 (60%) pts in CART cell era received CART cells, 40 (14%) received polatuzumab vedotin (pola), 10 (3.5%) received loncastuximab tesirine, tafasitamab and bispecific antibody each. Characteristics at relapse were similar in both groups. Median follow up was 8.9 (0.2-146) months. 2-year OS estimate was 36% (CI 95: 30-42%) in entire population. Patients treated in CART cell era had significantly higher OS (2 yr OS: 43% [CI 95: 35-53]) compared to pts treated in pre-CART cells era (2-year OS: 24% [CI 95: 16-34], p=0.0006) (Figure 1). In multivariable analyses, increasing age (HR = 1.02 (CI 95: 1.01, 1.04), p=0.003), extranodal disease (HR = 1.41 (CI 95: 1.00, 1.99), p<0.001), elevated LDH (HR = 1.57 (CI 95: 1.11, 2.24), p=0.01) were associated with inferior OS. Increasing time to relapse (HR = 0.98 (CI 95: 0.97, 0.99), p<0.001) was associated with superior OS. BCL6 rearrangement did not affect OS. When adjusted for these factors, treatment with CART cells was associated with higher 2 yr OS (HR = 0.33 (CI 95: 0.22, 0.49), p<0.001). Treatment with polatuzumab (HR = 1.07 (CI 95: 0.71, 1.6), p=0.07) was not significantly associated with OS in univariable analysis. 102 pts underwent CART cell therapy at any point for relapse; 94 (93%) were refractory to prior chemotherapy. 62 (60%) responded and 52 (50%) had CR after CART cells. 2-year PFS and OS after CART cell therapy were 28% (CI 95: 19-40) and 40% (CI 95: 30-53), respectively. Increasing time to CART was associated with inferior OS (HR: 1.02 (CI 95: 1.0-1.03, p=0.03) but not PFS (HR: 1.02 (CI 95: 0.99-1.04), p=0.2). 219 (79%) pts received curative intent salvage chemotherapy for 2 nd line. 2-year PFS and OS were 15% (CI 95: 11-20) and 38% (CI 95: 31-45), respectively. 21 pts received CART cell therapy for 2 nd line. 2 year PFS and OS in this small number of pts were 52% (CI 95: 35-79) and 70% (CI 95: 52-94), respectively. Due in part to the small number of pts who received CART cells in 2 nd line, we utilized full propensity score matched analysis to compare each patient in CART cell group to all possible matched controls in salvage chemotherapy group. Variables matched were age, LDH, extra nodal disease and time to relapse. In propensity score matched analysis, pts who received CART cells had significantly higher 2 year PFS (HR: 10.5 (CI 95: 3.4-17.5), p=002) and 2 year OS (HR: 7.5 (CI 95: 1.4-13), p=0.01). Conclusions: Survival of r/r DH/THL appears to have improved in the era of CART cell therapy. About 2/3 of pts refractory to chemotherapy respond to CART cells, and in multivariable analysis, receipt of CART cells was associated with improved OS. Increasing time to CART cells was associated with inferior survival. In a propensity score matched analysis utilizing full matching, CART cell therapy in 2 nd line was associated with significantly higher 2 year PFS and OS compared to curative intent salvage therapy. Other CD 19 and CD 20 targeting agents approved after CART cell therapy might contribute to favorable survival, effect of these agents could not be assessed because of small numbers.

Background: We previously reported thatearly events in follicular lymphoma (FL), defined as progression of disease within 24 months (POD24) or early transformation to a more aggressive histology, are significantly associated with increased risk of lymphoma related death. To refine clinical management, the FLIPI24 prognostic model was developed to predict the risk of early events after starting immunochemotherapy (IC) (Maurer et al, 2022). The FLIPI24 model was found to be significantly superior to standard clinical models for prediction of both event-free survival at 24 months (EFS24) and overall survival (OS) in internal and external validation sets of patients receiving IC. We sought to evaluate the prognostic ability of the FLIPI24 model in patients with FL not receiving IC. Methods: The cohort consists of prospectively enrolled patients in the University of Iowa/Mayo Clinic SPORE Molecular Epidemiology Resource (MER) and the multicenter Lymphoma Epidemiology of Outcomes (LEO) Cohorts. Data were collected from medical records by standard protocol with all events verified by medical record review. Eligible patients were those diagnosed with grades 1-3A FL and initiated observation, rituximab monotherapy, radiation, or other non-IC therapy. The FLIPI24 model utilizes 5 continuous variables: age (linear 60-90 years with inflection at age 75), HGB (linear 8-17 g/dL), WBC (linear 4-11x10 9/L), LDH/ULN (linear 0.5-5), and B2M (linear 1-10 mg/L). FLIPI24 risk is grouped as follows: low risk (≤10%], low-average risk (10-15%], average risk (15-20%], high risk (20-40%], very high risk (>40%) for an early event. EFS was defined as time from diagnosis to progression, relapse, (re)treatment, histologic transformation, or death due to any cause. OS was defined as the time from diagnosis until death from any cause. Cox models and Kaplan Meier curves were used to evaluate association between FLIPI24 and EFS or OS. Results: 1542 patients initiating non-IC management approaches at diagnosis from 2002-2020 were identified. 51% were >60 years (IQR 52-70), and 49% were male. Most patients (86%) had FL grade 1-2. 61% of patients met any criteria for high tumor burden per GELF, BLNI, or GITMO based on available variables. Treatment approaches were 833 observation (54%), 315 rituximab monotherapy (20%), 186 radiation (12%), and 208 other non-IC approaches (14%). At median follow-up of 58 months, EFS24 was 73.8% (95% CI: 71.6%, 76.1%), 5-year OS was 90.9% (95% CI: 89.3%, 92.5%) and 253 (16%) patients died. The FLIPI24 score identified poor outcomes among patients with high/very high-risk score (FLIPI24 >20%), with median EFS of 1.8 years (95% CI, 1.3, 3.28) and 5 year OS of 65.1% (95% CI: 55.9-75.8) (Figure 1). When evaluating patient subsets, for patients with high tumor burden (defined based on available variables) and high/very high-risk score, median EFS was 1.6 years and 5 year OS was 64.6% (95% CI: 54.9%-76.1%). Among patients with low tumor burden FL and high/very high-risk score, median EFS was 2.0 years (95% CI: 0.84-NA) and 5 year OS was 66.2% (95% CI: 42.4%-100%). Patients undergoing observation with high/very high-risk score similarly had shortened median EFS of 1.53 years (95% CI: 1.25-NA) and 5 year OS of 68.9% (95% CI: 56.4%-84.1%). The FLIPI24 had superior concordance for OS (c=0.726) compared to the FLIPI (c=0.646) when evaluated in patients not treated with IC. Results were comparable in the subsets of patients observed (c=0.706 vs 0.596) and receiving rituximab monotherapy (c=0.764 vs 0.721). Conclusion: The FLIPI24 model has been previously validated to provide an individual risk score at diagnosis for the likelihood of experiencing an event within 24 months from starting IC. Here we demonstrate that a high FLIPI24 score predicts for poorer outcomes following non-IC strategies including observation, treatment with radiation, and rituximab monotherapy. The FLIPI24 has better prognostic performance for OS than FLIPI in this non-IC population. High FLIPI24 in patients not treated with IC identifies a patient population who should be considered for IC and/or novel frontline therapies when feasible.

Background Limited stage (stage I−II) disease is an uncommon presentation of mantle cell lymphoma (MCL), and its optimal management remains controversial. A British Columbia study (Leitch, Ann Oncol, 2003) and a Surveillance, Epidemiology and End Results (SEER) study (Murthy, Clin Lymphoma Myeloma Leuk, 2014) suggested the importance of radiotherapy (RT). A National Cancer Database (NCDB) study in the pre-BTK inhibitor (BTKi) era showed that chemotherapy (Chemo) plus RT (Chemo+RT) improved overall survival (OS) compared to Chemo or RT alone (Gill, Int J Radiat Oncol Biol Phys, 2015). However, a retrospective International Lymphoma Radiation Oncology Group study (Dabaja, Ann Oncol, 2017) reported comparable OS with Chemo+RT vs Chemo or RT alone. The potential differences in OS with different frontline therapy modalities may be modified by subsequent therapies for relapsed or refractory (R/R) disease. In this study, we used the NCDB data to analyze frontline treatment patterns and outcomes of limited stage MCL in the pre-BTKi vs BTKi eras. Methods The NCDB was queried to identify patients with stage I−II MCL diagnosed in 2004−2020. Because the first BTKi ibrutinib was approved by the FDA for R/R MCL in November 2013, we defined 2004−2013 as pre-BTKi era and 2014−2020 as BTKi era. Frontline treatment modalities were categorized to RT alone, Chemo alone, or Chemo+RT. Survival analysis was performed using the Kaplan-Meier method and the Cox proportional hazards model. Results Among 32,746 patients with newly diagnosed MCL in 2004−2020, 3,836 (11.7%) presented with stage I−II disease, with 2,428 having treatment information available. For patients diagnosed in the pre-BTKi era (n = 2005), 195 (9.7%) received RT alone, 1472 (73.4%) received Chemo alone, and 338 (16.9%) received Chemo+RT. For patients diagnosed in the BTKi era (n = 423), 45 (10.6%) received RT alone, 320 (75.7%) received Chemo alone, and 58 (13.7%) received Chemo+RT. Patients in the RT alone group were older (P <0.001) and had more females (P <0.001), but there were no statistically significant differences in Charlson-Deyo score, international prognostic index, or treating facility type (academic vs non-academic). For patients with stage I disease, in the pre-BTKi era, patients treated with Chemo+RT (n = 182) had improved OS compared to those treated with RT alone (n = 141) or Chemo alone (n = 647), with a 5-year OS of 75.4% vs 71.8% vs 61.4% (P <0.001). Similar results were observed in the BTKi-era, with a 5-year OS of 83.6% vs 69.5% vs 62.9% (P <0.001) for patients treated with Chemo+RT (n = 31), RT alone (n = 30), or Chemo alone (n = 130), respectively. After adjusting for age and sex, Chemo+RT was associated with improved OS compared to Chemo alone (pre-BTKi era, HR = 0.59, 95% CI = 0.46−0.75, P <0.001; BTKi era, HR = 0.34, 95% CI = 0.14−0.79, P = 0.013), but not compared to RT alone (pre-BTKi era, HR = 0.62, 95% CI = 0.23−1.68, P = 0.343; BTKi era, HR = 0.77, 95% CI = 0.56−1.05, P = 0.10) (Figure 1A). For patients with stage II disease, in the pre-BTKi era, patients treated with Chemo+RT (n = 156) had improved OS compared to those treated with RT alone (n = 54) or Chemo alone (n = 825), with a 5-year OS of 70.0% vs 47.3% vs 58.4% (P <0.001). In the BTKi-era, patients treated with Chemo+RT (n = 27) or RT alone (n = 15) both had improved OS compared to those treated with Chemo alone (n = 190), with a 5-year OS of 77.2% vs 78.8% vs 61.9% (P = 0.004) . After adjusting for age and sex, Chemo+RT was associated with improved OS compared to Chemo alone in BTKi era only (pre-BTKi era, HR = 0.85, 95% CI = 0.67−1.07, P = 0.165; BTKi era, HR = 0.49, 95% CI = 0.25−0.95, P = 0.034), but not compared to RT alone (pre-BTKi era, HR = 0.78, 95% CI = 0.53−1.13, P = 0.185; BTKi era, HR = 0.97, 95% CI = 0.35−2.67, P = 0.952) (Figure 1B). Conclusions Treatment pattern for limited stage MCL has not changed significantly from the pre-BTKi era to the BTKi era, with approximately 15% of patients receiving Chemo+RT, 10% RT alone and 75% Chemo alone. In the BTKi era, Chemo+RT appeared to be associated with better OS compared to Chemo alone but not compared to RT alone. Interpretation of the results requires caution because (1) patient numbers are small in Chemo+RT and RT alone groups, (2) longer follow-up may be needed, and (3) selection of therapy was not random, eg, patients receiving Chemo alone may have had higher disease burden such as bulky disease and/or non-contiguous stage II involvement but these details are not available in NCDB.

Introduction Golcadomide (GOLCA, CC-99282) is an orally available cereblon E3 ligase modulator (CELMoD ®) that potently degrades target proteins Ikaros and Aiolos, enhancing antiproliferative, apoptotic, and immunomodulatory activity and preferentially distributing to lymphoid organs. In a phase 1 study, GOLCA monotherapy previously demonstrated a manageable safety profile with promising clinical activity in relapsed/refractory non-Hodgkin lymphoma (Michot Blood 2021). In the ongoing CC-220-DLBCL-001 study (NCT04884035), GOLCA dose finding is underway in patients with previously untreated aggressive B-cell lymphoma (BCL), in combination with R-CHOP in 21-day (D) cycles (C), at a variety of GOLCA dose levels (DLs) and schedules: DL-1 = 0.2 mg D1-7, DL1 = 0.4 mg D1-7, and DL2 = 0.4 mg D1-10. Here, we report Ikaros degradation, immune modulation, circulating tumor DNA (ctDNA) assessment, and baseline tumor genomics. Methods Peripheral blood was collected to analyze Ikaros and Aiolos levels in T cells by flow cytometry (C1D1, C1D7, and C2D1). Immune phenotyping of T and natural killer (NK) cells was performed by flow cytometry (C1D1, C1D15, C2D1, and C3D1). ctDNA levels were analyzed by the PhasED-Seq assay (timepoints C1D1, C2D1, C3D1, and end of treatment [EOT]; Kurtz Nat Biotechnol 2021); somatic variants were filtered by performing PhasED-seq on buffy coats. Pretreatment biopsies were analyzed by whole genome sequencing and whole transcriptome sequencing. DL1 (0.4 mg D1-7) and DL2 (0.4 mg D1-10) data were pooled. Results Ikaros levels in T cells at 5 hours after the first dose had a 1.1% median increase with 0.2 mg and 44% median decrease with 0.4 mg; by C1D7 pretreatment, Ikaros substantially decreased with both DLs (median: 0.2 mg, 87% decrease; 0.4 mg, 83% decrease). Ikaros differences between 0.2 mg and 0.4 mg were not substantial. By C2D1, Ikaros levels recovered to baseline. Based on preclinical benchmarks, steady-state Ikaros degradation in T cells suggested that direct tumor cell killing by GOLCA was achieved. Changes in T and NK cell phenotypes in peripheral blood included activation, increased proliferation, increased T effector memory and regulatory cell levels, and decrease in naive T cells. Changes were seen by C1D15 and maintained at C2D1 and C3D1. Overall, immune changes between 0.2 mg and 0.4 mg dose levels were not substantially different. Phased variant data from ctDNA and buffy coats were evaluable for 34 patients (0.2 mg, n =15; 0.4 mg, n = 19). Baseline ctDNA levels were similar between the 0.2 mg and 0.4 mg cohorts and, consistent with prior studies, correlated with International Prognostic Index and cell of origin. Previously reported landmarks such as early molecular response (EMR; ≥ 2 log decrease) at C2D1 and major molecular response (MMR; ≥ 2.5 log decrease) at C3D1 were assessed (Kurtz J Clin Oncol 2018) . A high fraction of patients designated high risk by pretreatment ctDNA (≥ 2.5 log haploid genome equivalents [HGE]/mL; Kurtz J Clin Oncol 2018) were clinical responders. Patients who achieved minimal residual disease (MRD) negativity on treatment generally remained MRD negative at subsequent timepoints. At C2D1, the EMR and MRD negativity rates for 0.2 mg were 73% (11/15) and 20% (3/15), respectively; for 0.4 mg these rates were 83% (15/18) and 44% (8/18). At C3D1, the MMR and MRD negativity rates for 0.2 mg were 83% (10/12) and 42% (5/12), respectively; for 0.4 mg these were 83% (10/12) and 58% (7/12). Although ctDNA differences between 0.2 mg and 0.4 mg were not substantial, numerically greater ctDNA changes were seen with 0.4 mg GOLCA + R-CHOP vs 0.2 mg GOLCA + R-CHOP and vs R-CHOP and R-CHOP-like regimens from other cohorts ( Figure). Insufficient samples were available to draw conclusions about EOT, but additional ctDNA data will be presented. Whole genome and transcriptome sequencing data from GOLCA + R-CHOP-treated patients will be shown. Conclusions Pharmacodynamic biomarkers and ctDNA levels indicate that both tumor-intrinsic and immune-modulating mechanisms of action of GOLCA remain relevant in combination with R-CHOP in previously untreated aggressive BCL. ctDNA data during treatment are consistent with the efficacy noted on clinical restaging. Translational data demonstrate the potency of GOLCA and will support future frontline clinical trial designs in patients with untreated aggressive BCL. Study support: Celgene, a Bristol-Myers Squibb Company

Background Diffuse large B cell lymphoma (DLBCL) is the most common aggressive lymphoid malignancy in adults. Though standard immunochemotherapy regimens can result in clinical remission and cure in a majority of patients, approximately 30% of patients are primary treatment resistant or eventually relapse (rrDLBCL), and their prognosis is very poor. Recent molecular classification by large scale genomic and transcriptomic profiling of newly diagnosed DLBCL tumors has resulted in a deeper understanding of disease drivers, however, the molecular heterogeneity of rrDLBCL is yet to be fully explored. Therefore, in this study, we used an unsupervised approach to better define transcriptional and genetic programs in rrDLBCL samples hypothesizing that molecular stratification within this high-risk group may lead to a better understanding of this disease, which remains an unmet need, and a more personalized therapeutic approach. Methods Data used in this study included RNA (n=143) and whole exome (n=126) sequencing data from available FFPE tumor samples at the time of a relapse (any line of treatment, r1-r10 relapse timepoints included in analysis, one per patient), consented to the Molecular Epidemiology Resource (n=61), banked in the Mayo Lymphoma Biobank (n=50), or consented to the CC-122-ST-001 clinical trial (n=32, NCT01421524). Unsupervised clustering was performed on protein coding gene expression values using the non-negative matrix factorization (NMF) approach. NMF was carried out by performing 200 runs on cluster sizes from 2 to 6. Cell of origin (COO) was determined using the method described by Reddy et al. The tumor microenvironment was analyzed using CIBERSORTx and Lymphoma Microenvironment Classification (LME). Genetic classification was done using LymphGen. Results In order to identify unique transcriptional programs in rrDLBCL, we implemented NMF and consensus clustering to define an ideal quantity of stable patient clusters. We identified 4 rrDLBCL patient clusters (rrC1-rrC4) as the most stable solution, based on consensus clustering selection criteria of iterative NMF runs. While relapse timepoint was not associated with individual clusters, we did observe significant differences in tumor characteristics between the clusters. COO classification found that rrC1 and rrC4 were enriched for GCB-DLBCL while rrC3 was enriched for ABC-DLBCL classification (P < .001). To explore the biologic programs in each cluster, we used pathFindR, which leverages protein-protein interaction networks to identify disease related pathways, rrC1 and rrC4 were defined by pathways involved in cell cycle and mismatch repair; oxidative phosphorylation in rrC2; and MAPK and NF-kB in rrC3. Next, LME classification was done to define patterns in the tumor microenvironment and we found a significant difference between groups (P < .001), with rrC2 and rrC4 tumors enriched for a depleted TME, while rrC1 and rrC3 had a more immune rich or inflammatory TME. This was supported by CIBERSORTx analysis identifying significant differences (P > .001) in abundance of CD8 T cells, memory CD4 T cells, and M1 macrophages between clusters, with rrC4 having the lowest abundance. We then explored genetic patterns in each cluster. Gene level mutation enrichment analysis showed BCL7A mutation exclusively in C4 (6/6, P = .03). The clusters were not associated with LymphGen classification. Lastly, our recently published high risk signature classification that is associated with early clinical failure and is characterized by metabolic dysregulation, a depleted TME, T53 alterations, and poor outcome, was significantly different between the groups (P = .03) with enrichment for high-risk cases in rrC4. In summary, we show for the first time that rrDLBCL patients can be classified into four gene expression clusters that are associated with distinct pathway, TME, and genetic programs. These clusters should now be tested to learn if they can help select patients for newer therapies for rrDLBCL such as CAR-T and bispecific antibodies.

Background: The goal of clinical trial eligibility criteria is to identify a population of patients that have high risk disease or have unmet needs with standard of care therapy. Frontline trials of diffuse large B-cell lymphoma (DLBCL) include patients with International Prognostic Index (IPI) scores of 3-5 as a way to identify a high risk population. Trials typically include patients with IPI score=2, and sometimes IPI score=1, to expand the eligible patient population. However, broader patient populations must be balanced by the potential inclusion of low-risk patients with excellent outcomes to standard of care therapy, leading to potentially underpowered trials. IPI is a sum of dichotomous variables which makes implementation easy but can result in heterogeneity in outcomes within IPI scores. This heterogeneity may be caused by unequal prognostic information across IPI variables, loss of information within IPI variables due to the use of cutoffs, as well as information captured by variables that are not included in the IPI. In prior modeling of outcomes in DLBCL (Maurer et al, AJH 2016), we identified that: i) LDH has a strong prognostic ability beyond the upper limit of normal (ULN) and ii) bulky disease is an independent variable for prognosis. Here we evaluate if the presence of either of these two variables, easily captured at diagnosis within the current standard clinical work-up, can identify a high-risk subset of patients within the population of those with IPI scores of 1-2. Methods: Patients with newly diagnosed lymphoma were enrolled within 6 months of diagnosis in the LEO Cohort at 8 academic medical centers from 2015-2020 and prospectively followed. Inclusion criteria for this analysis was aggressive B-cell lymphoma typically included in frontline trials (e.g. DLBCL, high grade B-cell lymphoma, FL3B), IPI 1-5, frontline therapy with rituximab and anthracycline-based chemotherapy, stage II-IV disease and ages 18-80 years. Event-free survival (EFS) was defined as the time from diagnosis until progression, initiation of 2 nd line therapy, or death due to any cause; EFS was evaluated at 24 months (EFS24). Very high LDH was defined as LDH>1.3xULN based on prior modeling (Maurer et al, AJH 2016) and bulky disease was defined as maximum tumor diameter (MTD) of 7cm or greater. IPI 1 and 2 were first evaluated separately and then combined due to similar outcomes in patients with very high LDH and/or bulky disease. High risk IPI1-2 was defined as the presence of either bulky disease and/or very high LDH within an IPI score of 1-2. Confirmation was performed in a similar cohort of patients enrolled in the Iowa/Mayo SPORE Molecular Epidemiology Resource (MER) from 2002-2015; bulky disease was defined using a 10cm cutoff per availability in MER data collection forms. Results: 1560 patients from LEO were analyzed; median age was 64 years (IQR: 54-71), 42% were female and 83% had stage III/IV disease; subtype was DLBCL, NOS in 1335 (86%). IPI was 1-2 in 766 patients, 3 in 496 patients and 4-5 in 298 patients ( table). 391 (51%) with IPI1-2 had either bulky disease and/or very high LDH (high risk IPI1-2) and 375 had low-risk IPI1-2. EFS24 in high risk IPI1-2 (71.6%, 95% CI: 67.2-76.3) was significantly inferior to IPI1-2 without bulky disease or very high LDH (85.2, 95% CI: 81.7-88.9 logrank p=0.0035, figure) and similar to patients with IPI3 (70.7%, 95% CI: 66.8-74.9). Consistent results were observed in 1014 patients analyzed in the MER using a higher cutoff for bulky disease (10cm) due to data availability ( table). Patients with high risk IPI1-2 had significantly shorter diagnosis to treatment interval (DTI) in both the LEO (per-week OR=0.83, 95% CI: 0.77-0.88) and MER (per-week OR=0.77, 95% CI: 0.68-0.87) cohorts compared to low risk IPI1-2, both p<0.0001). In sensitivity analysis, LEO results were similar when performed in the subset of patients with DLBCL, NOS. Conclusion: The presence of either bulky disease and/or very high LDH at presentation identifies a high-risk subset of patients with IPI 1-2 that have similar outcomes to patients with IPI 3 disease. These simple criteria can be easily implemented within existing clinical trial diagnostic work-ups. Future trial designs in frontline aggressive B-cell lymphoma should include patients with IPI 3-5 and patients with IPI 1-2 with either bulky disease and/or very high LDH to better define a high-risk population of patients for clinical trial eligibility.

Introduction: Despite governmental and industry-sponsored efforts, clinical trial participation among rural residents and racial and ethnic minorities remains low. The NIH Revitalization Act of 1993 directed the NIH to establish guidelines for inclusion of women and minorities in clinical research. In 2015, the Food and Drug Administration launched an action plan to improve the quality of demographic subgroup data collection, identify barriers to enrollment, employ strategies to increase participation, and promote transparency of related data. However subsequent studies (Green et al. Health Aff. March 2022, Kanapuru et al. Blood Advances. March 2022.) showed no improvement in participation of racial minorities, including Blacks and Hispanics since this plan was enacted. Various complex system- and individual-based factors, including lack of clinical trial availability; lack of diversity in the investigator work force; scant patient and provider awareness of clinical trials; lack of trust in the health care system; and issues with access to care-often driven by financial, geographic, or social constraints (Allison et al. Cureus. Apr 2022.), and stringent eligibility criteria are deemed responsible. The Leukemia & Lymphoma Society (LLS) IMPACT (Influential Medicine Providing Access to Clinical Trials) research grant strives to bridge this unrelenting care gap. Methods: The LLS IMPACT program includes a 5-year research grant which was launched in 2021. The IMPACT grants support the establishment of clinical trial networks involving academic cancer centers (“Hubs”) linked to community clinics and oncology centers (“Spokes”). The program's overall goal is to provide patients access to trials through participation at the community sites. Initially, 3 institutional sites were selected to participate. These institutions had unique and tailored strategies to improve engagement of underrepresented patients, including black, indigenous, people of color, Hispanic, Latina/Latino, and people from rural communities in vastly different climates and local cultures. The IMPACT grant expanded to encompass 4 additional sites given the imminent needs and clamor of the hematology clinical trials community (Figure 1A). The catchment areas and strategies employed at each institution are summarized in the table (Figure 1B). Results: At the start of the grant period, focus was on building clinical research infrastructure and opening non-interventional clinical trials to teach personnel about clinical research and create relationships with patients. Other programs such as webinar series, tumor boards, technological advancements, and educational workshops were also established to enhance engagement among physicians, match patients to clinical trials, and to provide clinical trial education to potential patients. One trial that has seen early success is the CHIVE IMPACT trial, a non-interventional registry and biorepository which has enrolled 24 patients at a rural and underserved site as of July 2023. The purpose of CHIVE is to enroll patients who have clonal hematopoiesis (CH) or are at risk of CH and follow prospectively in efforts to understand risk of progression and potential for early intervention. The Universal Protocol is another biorepository trial which has more than tripled its enrollment number at a community site between 2021 and 2022. Of the 63 patients enrolled in 2022, 66% of them identified as a race other than White. As our core goal is to increase access to interventional trials, we hope to bring industry sponsored phase II and phase III studies to underrepresented areas that serve a broad patient population. Lack of financial resources, lack of transportation and distance to trial sites, and residual distrust of the medical community (e.g., legacy of Tuskegee experiments) are barriers the grantees are focused on overcoming to enroll the intended populations into clinical trials. Conclusion: The innovative strategies employed to expand access to clinical trials for underrepresented population at the various institutions through the LLS's IMPACT research grant can be utilized during clinical trials design and implementation phases to improve generalizability of clinical trials in hematologic malignancies. In the third year of this program, 7 participating sites are engaging impactful strategies (Figure 1B) which will be reported at the end of the grant period.

Background: Emavusertib (CA-4948) is a novel oral inhibitor of interleukin-1 receptor-associated kinase 4 (IRAK4), which is essential for toll-like receptor (TLR) and interleukin-1 receptor (IL-1R) signaling in B cell proliferation. Additional inhibitory activity against FMS-like tyrosine kinase 3 (FLT3) and CDC-like kinases (CLK1/2/4) is also present in emavusertib. IRAK4 forms a Myddosome complex with MYD88 adaptor protein and drives overactivation ofnuclear factor-kappa B (NF-κB), causing inflammation and tumor growth. Emavusertib has been reported to be well tolerated and active as monotherapy in heavily pretreated patients with relapsed/refractory (R/R) non-Hodgkin lymphoma (NHL) (Nowakowski 2020). Preclinical studies demonstrated that tumor resistance and survival via IRAK4 activation could be delayed or reversed. Emavusertib crossed the blood-brain barrier in a murine PDX model of PCNS lymphoma, blocked the activated IRAK4 pathway, and induced tumor response and prolonged survival (von Roemeling 2022). In combination with Bruton tyrosine kinase (BTK) inhibitors, emavusertib showed in vitro synergy and re-sensitization of resistant cell lines, overcoming BTK resistance (Guidetti 2023a and 2023b). In vivo synergy in B-cell NHL was also demonstrated. Adaptive chemotherapy treatment resistance through IRAK4 upregulation and activation was also described in other disease models (Melgar 2019, Li 2019). This abstract presents preliminary efficacy and safety data of emavusertib + ibrutinib in R/R NHL patients. Aim:Assessment of safety and clinical activity of emavusertib in combination with ibrutinib. Methods: This is an ongoing open-label trial (NCT03328078) of emavusertib as monotherapy and in combination with ibrutinib. Part A1 - completed; dose escalation of emavusertib as monotherapy; the recommended phase 2 dose (RP2D) is 300 mg BID with continuous oral dosing (Nowakowski 2020). Part A2 - completed; dose escalation of emavusertib in combination with ibrutinib at 420 and 560 mg QD (Joffe 2022). Part B - ongoing; an expansion cohort of PCNSL patients with resistance to prior BTK inhibitors for additional safety and efficacy related to exposure: emavusertib at 100 or 200 mg BID + ibrutinib at 560 mg QD in 28-Day cycles. Results:As of 19 July 2023, 18 heavily pretreated NHL (including five PCNSL) patients received emavusertib at 100, 200, or 300 mg BID in combination with full ibrutinib doses per label. Median age was 63.5 years (range 50-92). Median number of prior lines of anti-cancer therapies was 3 (range 1-10). Eleven of 18 patients failed prior BTK inhibitors. Median treatment duration was 95.5 days (21-587 days), suggesting acceptable safety and tolerability. No DLTs were observed at the 200 mg BID dose level, and two reversible DLTs (stomatitis and syncope) were observed at the 300 mg BID dose level. The preliminary efficacy data of 16 evaluable patients in combination with ibrutinib showed 5 CRs (2 MCL, 3 PCNSL) and 1 PR (1 CLL). All 3 PCNSL patients with CR were previously treated with BTK inhibitors. Conclusion: The combination ofemavusertib plus ibrutinib (ema+ibr) is well tolerated with an acceptable long-term safety profile and promising efficacy, showing several objective responses in heavily pretreated and/or BTK inhibitor resistant patients. Emavusertib may have the potential to overcome BTK inhibitor resistance and the combination of ema+ibr has the potential to show increased anti-cancer activity compared to ibrutinib monotherapy.

Background: Understanding the symptoms and quality of life (QOL) over time of adults with follicular lymphoma (FL) is important for treatment decision-making and clinical management. However, there are limited population-level data on the long-term QOL of adults with FL. We aim to describe the real-world, long-term QOL of adults with newly diagnosed FL up to 5/6 years after diagnosis. Methods: We used the Mayo Clinic/Iowa Molecular Epidemiology Resource (MER) and the multi-institutional Lymphoma Epidemiology of Outcomes (LEO) to identify adults with grade 1-3A FL who completed QOL surveys at baseline and follow-up. Participants with lymphoma were prospectively enrolled within 9 months of diagnosis in the MER cohort from 2002-2015 and within 6 months of diagnosis in the multi-institutional LEO cohort study across 8 cancer centers from 2015-2020. The LEO/MER cohort studies systematically collected information on disease status, QOL, health behaviors, and functional assessment. Treatments, disease relapses, and deaths were verified by medical record review. Treating physicians determined clinical management. QOL was measured using the Functional Assessment of Cancer Therapy-General (FACT-G) at years 1, 2, 3, and 5/6 post-diagnosis. A higher FACT-G total score (range 0-108) indicated better QOL across 4 subscales (range): physical (0-28), social/family (0-28), emotional (0-24), and functional (0-28) well-being. We categorized participants based on their frontline management at time of diagnosis: “observation” (surveillance), “treatment” (systemic treatment with immunotherapy +/- chemotherapy), and “local” (radiation) groups. We employed a generalized linear mixed model to evaluate and compare the changes in QOL scores (as a continuous variable) from baseline for the observation, treatment, and local groups, adjusting for sex, race/ethnicity, age, FLIPI risk, and cohort (i.e., LEO or MER). We also evaluated QOL changes by FLIPI risk. Results: Our study included 1,544 participants with FL and QOL data. At the time of enrollment, median age was 61 years (range 19-91), 88% were non-Hispanic White, and 49% were female. Based on initial management, 529 (34%) were in the observation group, 880 (57%) were in the treatment group, and 135 (9%) were in the local group. FLIPI risk was high for 17% in the observation group, 29.3% in the treatment group, and 3% in the local group. The mean (standard deviation) baseline FACT-G total score was lowest in the treatment group with the following baseline scores: 86 (13) for the observation group, 83 (14) for the treatment group, and 88 (12) for the local group (Table 1). The observation and local groups reported a greater worsening of their baseline FACT-G total score vs the treatment group at both the 2-year (-1.2, -0.8 vs +1.8, respectively) and 5/6 year (-5.4, -6 vs. -1.6, respectively) timepoints (Figure 1). This appeared to be driven by worsened physical and functional well-being in the observation (-1.3, -2.2, respectively) and local (-0.9, -2.4, respectively) groups vs the treatment group (0, -0.3, respectively). These differences were statistically significant between the observation vs treatment groups. There were no statistically significant differences in the other subscales, i.e., social/family and emotional well-being, by frontline management. Social/family well-being decreased across all groups by 5/6 years (-2.3 in observation, -2.2 in treatment, and -3 in local, p<0.05). Regardless of FLIPI risk, the total FACT-G scores decreased within each FLIPI risk group at 5/6 years (-4.4 for low, -3.8 for intermediate, and -4.9 for high, p<0.05). This was primarily due to worsened social/family well-being (-2.4 for low, -2.2 for intermediate, and -3 for high, p<0.05) at 5/6 years. There was no statistically significant difference in QOL between FLIPI risk groups. Conclusion: This is one of the first and largest studies with real-world longitudinal QOL data for FL. Our study suggests that frontline systemic treatment initially improved QOL and resulted in a lower degree of QOL decline over time. Social/family well-being decreased over time regardless of frontline management or FLIPI risk. Further research is warranted to explore the impact of timing and specific systemic treatments on QOL, incorporate the patient/caregiver experience to address social/family well-being, and identify the clinical significance of our findings.