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Abstract Background: Rural/nonmetropolitan (nonmetro) counties face known barriers to comprehensive cancer care compared with metropolitan (metro) counties, which may impact the outcomes for lymphoma patients. We evaluated the impact metro vs nonmetro status on outcomes after a diagnosis of non-Hodgkin lymphoma (NHL) in the context of clinical, demographic, and lifestyle factors. Methods: Of 7724 participants enrolled in the prospective LEO cohort study from 2015-2020, 7610 (98.5%) had their county of residence at diagnosis assigned a RUCC (2013) code. We compared outcomes of participants from metro (defined as RUCC 1-3, which are central counties with ≥1 urban areas of ≥50,000) vs nonmetro counties (RUCC 4-9, which are counties with smaller urban areas as well as completely rural). We estimated hazard ratios (HRs) and 95% confidence intervals (CI) from univariable and multivariable Cox models for associations of metro status with overall survival (OS). Cause of death (lymphoma [including treatment related], non-lymphoma, unknown) was assessed using a competing risk approach. Results: Compared with metro counties (N=6096), LEO participants from nonmetro counties (N=1514) were older (median age 64 vs 62 years; p<0.001), more likely to be non-Hispanic white (94% vs 75%; p<0.001) and married (84% vs 75%; p<0.001), and less likely to have completed graduate or professional school education (16% vs 27%; p<0.001). There were no notable differences (>5%) by metro status for sex, employment status, NHL subtype, stage, performance status, abnormal lactate dehydrogenase (LDH), international prognostic index (IPI), number of comorbidities, time from diagnosis to treatment interval (DTI) or participation in a clinical trial. Compared with LEO participants from metro counties, those from nonmetro counties had inferior OS at 5 years (74.5% vs 78.4%; HR=1.23, CI 1.10-1.37; p<0.001). The OS association only slightly attenuated after adjustment for age, sex, race/ethnicity and NHL subtype (HR=1.20, CI 1.07-1.34; p=0.002), and held in models that adjusted for clinical prognostic factors (stage, NHL subtype, IPI, DTI), socioeconomic status (SES; education, marital status), health status (comorbidity, frailty), or lifestyle factors (smoking, body mass index). Using a competing risk model, the cumulative incidence of death at 5 years due to lymphoma (16.9% vs 14.1%; p=0.002) and non-lymphoma (5.9% vs 3.9%; p=0.002) was higher for participants from nonmetro vs metro counties, respectively. For participants <65 years, nonmetro vs metro status had inferior OS (HR=1.40, CI 1.17-1.67; p<0.001). This association remained after adjustment for age, sex, race/ethnicity and NHL subtype (HR=1.36, CI 1.14-1.63; p<0.001), as well as after adjustment for clinical prognostic, SES, health status, or lifestyle factors. The cumulative incidence of death at 5 years due to lymphoma was higher in participants from nonmetro vs metro counties (15.1% vs 11.5%; p=0.002), while there was no difference by metro status for non-lymphoma related deaths (2.1% vs 1.7%; p=0.47). In contrast, for participants age 65+ years, there was no differences by metro status for OS (HR=1.04, CI 0.91-1.20; p=0.56). After adjustment for age, sex, race/ethnicity and NHL subtype, participants from nonmetro areas had inferior OS (HR=1.12, 0.97-1.29) although this was not statistically significant (p=0.13), and was attenuated in models adjusting for clinical, health status, or lifestyle factors. The cumulative incidence of death at 5 years due to lymphoma was no different in participants from nonmetro vs metro counties (18.9% vs 18.0%; p=0.37), while non-lymphoma related deaths were higher in nonmetro counties (9.9% vs 6.8%; p=0.017). Conclusion: LEO participants from nonmetro vs metro counties had inferior OS overall, although this was predominately observed for younger (<65 years) participants. These associations did not appear to be explained by demographic, NHL subtype, clinical, SES, health status, or lifestyle factors. Of particular note, the risk of death due to lymphoma was higher in nonmetro areas for participants <65 years but not those 65+ years, while the risk of death due to other causes was higher in nonmetro areas for participants 65+ years but not those <65 years. These findings require further study, particularly related to barriers to care, and suggest the potential need for age-specific strategies to optimize outcomes for NHL patients from nonmetro/rural areas.

Abstract Background: Glofit, a CD20/CD3 bispecific antibody, has shown efficacy in prospective trials, including the Phase III STARGLO study evaluating glofit plus gemcitabine/oxaliplatin (GemOx) in transplant-ineligible patients (pts) with R/R large B-cell lymphoma (BCL). However, concerns raised by the FDA's Oncology Drug Advisory Committee regarding the generalizability of the STARGLO data to U.S. pts underscore the need for real-world evidence. We report real-world outcomes of Glofit-GemOx in U.S. pts with R/R aggressive BCL. Methods: We conducted a multicenter retrospective review across 8 U.S. academic centers, identifying 31 pts with R/R aggressive BCL treated with Glofit-GemOx outside clinical trials. Baseline characteristics, treatment history, and outcomes were abstracted from medical records. Results: At Glofit-GemOx initiation: median age was 72 years (range, 34–88); 90% had stage III/IV disease. Histologic subtypes included DLBCL in 58% (n=18), high-grade BCL in 29% (n=9), PTLD/DLBCL in 6.5% (n=2), follicular lymphoma (FL) grade 3B in 3.2% (n=1), and Burkitt lymphoma (BL) in 3.2% (n=1). Germinal center B-cell phenotype was seen in 80% of evaluable cases. Double- (n=8) or triple-hit (n=1) cytogenetics were observed in 31% (n=9). Elevated LDH was present in 74%, and 16% had B symptoms. Median ECOG performance status was 1 (range, 0–3), and 23% (n=7) had received prior CAR T-cell therapy. Pre-treatment biopsy was performed in 77% (n=24) with CD20 expression tested in 74% (n=23). CD20 expression was negative in 3 pts by flow cytometry and/or immunohistochemistry. Pts received a median 1 prior line of therapy (range, 0-6); Glofit-GemOx was administered as 1L in 7% (n=2), and 2L in 58% (n=18). Median 4 cycles (range, 1-11); both 1L pts had prior FL (1 and 3 prior lines for FL). Twelve pts remain on therapy, 2 on Glofit monotherapy. Four pts were unevaluable (2 death pre-assessment; 2 pending evaluation). Among 27 evaluable pts, ORR was 78% (21/27) and CR rate was 41% (11/27). Among CD20- negative cases on pre- Glofit-GemOx biopsy (n=3), ORR was 33% (1/3), with 1 CR lasting 3.5 months. Of 11 pts who progressed on Glofit-GemOx, 6 were rebiopsied; 1 showed CD20 loss, 1 was previously CD20-negative. Among the 24 pts who received Glofit-GemOx as destination therapy, ORR of 75% (15/20 evaluable). Among pts with prior CAR T (n=7), the ORR and CR rate were both 43% (3/7). None received Glofit-GemOx within 30 days of CAR T-cell infusion; 4 received within 6 mo; 2 of whom achieved CR. Seven pts (24%) received Glofit-GemOx as bridging to CAR T. ORR pre-CAR T was 86% (6/7); 4 pt successfully proceeded to CAR T, 2 are pending infusion, and 1 progressed after 2 cycles and transitioned to alternate therapy. Three pts were evaluable post-CAR T with an ORR of 100% (3/3) and CR rate of 67% (2/3). At data cutoff, 23/31 pts were alive. Full PFS and OS data will be presented at ASH. Notable individual responses included a patient with relapsed BL post–DA-EPOCH-R who received Glofit-GemOx as 2L therapy and achieved a 6 mo CR without consolidation before progression. Another patient treated with Glofit-GemOx in the 7L setting after prior allogeneic transplant achieved a 3 mo CR prior to progression. CRS occurred in 58% (18/31), with grade ≥3 in 13% (4/31), including 2 possible treatment-related deaths. One occurred in a frail patient after the 1st dose, though neutropenic fever was present prior to Glofit administration. The second followed influenza A infection, respiratory failure, and possible grade 4 ICANS after the 2nd dose; attribution to CRS vs. infection was unclear. ICANS occurred in 10% (3/31), with one possible grade ≥3 case. Conclusions: This is the first U.S.-based real-world analysis of Glofit-GemOx, including more U.S. pts than the STARGLO trial, appear to demonstrate comparable response rates, potentially supporting its use as both bridging and destination therapy. Notable toxicities, including CRS, were observed, with 2 possible treatment-related deaths, with plausible alternate non-treatment related causes. Favorable responses were seen in bridging therapy and high-risk subgroups (transformed, HGBCL) which were excluded in the STARGLO trial. These findings support the real-world utility of Glofit-GemOx in the management of R/R aggressive BCL but underscore the need for caution due to associated toxicities. Further real-world and prospective evaluation are warranted, particularly in rare subgroups and as bridging therapy.

Abstract The current European Leukemia Net guidelines (ELN22) classify AML patients with intermediate-risk cytogenetics and MDS-associated mutations (MDSm, mutations in ASXL1, BCOR, EZH2, RUNX1, SF3B1, SRSF2, STAG2, U2AF1, ZRSR2) as adverse-risk but do not use MDSm+ to alter the risk stratification of patients who otherwise classify as favorable-risk. NPM1 mutations (NPM1+) are one of the most common alterations in AML and remain a favorable-risk biomarker for patients without co-occurring FLT3-ITD mutations or adverse-risk cytogenetics (NPM1+/ITD-/ARcyto-). However, prior studies have shown that older patients (≥65 years) with favorable-risk AML, including NPM1+/ITD-/ARcyto- genotype, have significantly higher relapse rates and decreased survival despite receiving comparable intensive chemotherapy regimens to their younger counterparts. Given that MDSm frequency increases with age in patients with NPM1+ AML, it raises the question as to whether MDSm contribute to poorer outcomes in older patients. To date, there have been differing results in retrospective studies examining the effect of MDSm on NPM1+ AML. Some cohorts demonstrate worse outcomes in those that have NPM1+/MDSm+ AML (Chan et al., Blood Adv. 2024), whereas others do not show a significant difference in NPM1+ AML with or without MDSm (Eckardt et al., Leukemia 2023; Othman et al., Blood 2024; Ruhnke et al., Blood Adv. 2025). We examined the mutational landscape in a large group of pre-treatment, diagnostic specimens from 271 patients, which included 119 patients enrolled in SWOG clinical trials (SWOG-9031, SWOG-9333, S0106, and S0112), 96 patients from the UW/FHCC Hematopoietic Repository, and 56 patients from the BeatAML cohort. All patients were treated with curative intent as per standard practice or on clinical trials and had adequate cytogenetic information and long-term follow-up data. Event-free and overall survival (EFS, OS) were estimated using the Kaplan-Meier method and compared using Cox regression models stratified by cohort. MDSm+ occurred in 17% of patients, with the most common mutations being in SRSF2 (7%) and SF3B1 (3%). To assess the impact of MDSm on outcomes of favorable-risk NPM1+ AML, we performed univariate analyses comparing OS and EFS for NPM1+ AML grouped by ELN22 favorable risk/MDSm-, ELN22 favorable/MDSm+, and ELN22 intermediate/adverse risk. Compared to NPM1+/MDSm- (n=116), favorable-risk NPM1+/MDSm+ (n=33) had worse OS with HR 2.0 [95% CI (1.1, 3.3), p=0.008] and had similar OS to those that are classified as ELN22 intermediate/adverse risk (n=122). There was no significant difference in EFS or complete remission rates between NPM1+ favorable risk with and without MDSm (p=0.36 and p=0.6, respectively). When we grouped the ELN22 favorable risk patients by age (<65 years vs. 65+ years), MDSm+ in younger patients did not show a difference for OS (HR 0.99, p=0.98). Older ELN22 favorable-risk patients (≥65) had poor OS regardless of presence of MDSm compared to younger MDSm- patients: older MDSm- (n=91) with HR 2.4, 95% CI (1.3, 4.6), p=0.005 and older MDSm+ (n=25) with HR 3.5, 95% CI (1.9, 6.3), p<0.0001. There was a trend toward worse OS in MDSm+ compared to MDSm- older patients, but this was not statistically significant (HR 1.42, p=0.33). Since most MDSm are in splicing factor genes (SF3B1, SRSF2, U2AF1, ZRSR2), we examined the effect of splicing factor mutations vs. other MDSm+ in ELN22 favorable risk and did not find a significant difference in OS (HR=1.01, p=0.97). Those with non-splicing MDSm+ had worse EFS compared to MDSm- and splicing MDSm+ (HR 4.12, p=0.0037), although no difference in OS. In this study, MDSm+ in the context of favorable-risk NPM1+ AML are associated with worse OS in a univariate analysis. However, this difference is likely due to the increased prevalence of MDSm with increasing age and overall worse outcomes of NPM1+ AML in older patients. When stratified by age, older NPM1+ AML patients had worse OS than younger NPM1+ patients overall, although presence of MDSm trended toward even worse OS in older patients. In younger patients, MDSm+ are not associated with a significant difference in OS, which is a similar finding compared to prior studies. Our findings suggest that NPM1+ AML is not necessarily “favorable-risk” in older patients, particularly with concurrent MDSm. Therefore, further understanding of the underlying biology of age in the context of NPM1+ AML is needed to improve outcomes for older patients.

Abstract BACKGROUND Ivosidenib is an oral inhibitor of mutant isocitrate dehydrogenase type I (IDH1) currently approved for the treatment of IDH1 mutated acute myeloid leukemia and myelodysplastic syndrome (MDS). Hematopoietic stem and progenitor cells carrying preleukemic mutations, referred to as clonal hematopoiesis (CH), are the origin of myeloid neoplasms (MN). Individuals who have cytopenias and CH, but do not meet diagnostic criteria for a hematologic malignancy, are classified as having Clonal Cytopenias of Undetermined Significance (CCUS), a condition associated with a high risk of progression to MN. While CCUS patients (pts) can have multiple mutations, they show lower mutational burden on average compared to MN. Thus, we hypothesized that treatment with ivosidenib would improve cytopenias in IDH1-mutant CCUS. METHODS; We performed a decentralized phase II single-arm study to characterize the safety and efficacy of ivosidenib in IDH1-mutant CCUS (NCT0503044). Drug was shipped to pts with local oncologists performing standard-of-care clinical exams supplemented by study team lead interviews for adverse event monitoring. Research labs were drawn by local providers or through Quest. QT corrected interval (QTc) was monitored through a mobile electrocardiogram device (AliveCor). Eligible patients were aged ≥ 18 years and had confirmed IDH1-mutant CCUS with at least 6 months of unexplained cytopenias (hemoglobin<10 g/dL, platelets<100 x109/L or absolute neutrophil count <1.8 x109/L). The primary endpoint was hematologic response of at least 8 weeks in duration based on the IWG 2006 criteria for MDS. RESULTS 20 pts with IDH1-mutant CCUS have been enrolled. Most were male (70%) with a median age of 66 (range 41-79). Overall, 74% had a self-reported race of non-Hispanic white, 11% of Hispanic white, 5% of Asian and 11% of black or African American. Most pts presented with neutropenia (95%) including some with co-occurring thrombocytopenia (21%). One pt presented with anemia and thrombocytopenia without neutropenia. Prior to treatment, the average number of co-mutations beyond IDH1 was 2 (range 0-3), with most pts (74%) harboring a co-occurring spliceosome gene mutation. The IDH1 variant allele fraction (VAF) was lower in the blood (mean=19%, range 3-35%) than in the bone marrow (mean=31%, range 18-43%) in most (93%) patients. Out of the 20 enrolled pts, 17 received at least 8 weeks of therapy at the time of our data cutoff (7/29/2025) and were included in the efficacy analysis. Grade ≥3 adverse events (AEs) occurred in five patients (26%) including two with grade ≥3 treatment-related adverse events (pancytopenia and sepsis in the first pt, rash in the second pt). The most common all-grade treatment-related adverse events were nausea (n=5, 26%), prolonged QTc (n=3, 16%), anemia (n=3, 16%), and diarrhea (n=3, 16%). There were no instances of reported differentiation syndrome. Overall, 82% of pts achieved a hematologic response (14/17) including improvement in neutropenia (88%) and thrombocytopenia (75%). With a median follow-up of 16 months (range 0.6-24 months), the median duration of hematologic response was not reached. Among responders, 86% had a continued response at one year. Two pts progressed to MDS after 4 and 17 months of treatment characterized by recurrence of cytopenias and the emergence of new clones. A surveillance bone marrow biopsy was performed at 18 cycles for the 8 pts who remained on treatment with none showing disease progression. Most pts (90%, N=9/10) treated for at least 12 months had a decrease in IDH1-mutant CH VAF over time and 40% (N=4/10) showed IDH1 mutation clearance (VAF <2%) with a median time to clearance of 9 months. Among those with decreasing IDH1 clonal burden, all had a corresponding decrease in other co-occurring mutations present at baseline with one responder showing emergence of a newly detectable CHEK2 mutation without disease progression. CONCLUSIONS Decentralized trials represent a feasible solution for the conduct of clinical trials in rare hematologic neoplasms and precursor conditions. Ivosidenib was well-tolerated and induced durable hematologic remissions in IDH1-mutant CCUS. Most pts showed a reduction in clonal burden with mutation clearance commonly seen with long-term treatment demonstrating that ivosidenib modifies the natural history of IDH1-mutant CCUS.

Abstract B cell maturation antigen (BCMA)-targeted chimeric antigen receptor T (CART) cell therapies have emerged as a potentially curative treatment for multiple myeloma (MM). However, 50-70% of patients relapse within 3 years. The MM tumor microenvironment (TME) is highly immunosuppressive with an abundance of bone marrow (BM) cancer-associated fibroblasts (CAFs), which contribute to BCMA-CART cell failure. Therapeutic targeting of BM-CAFs has been beset by 1) an incomplete understanding of CAF interactions with CART cells and other BM cells and 2) toxicity risks due to prolonged depletion of healthy fibroblasts and inefficient drug delivery to the BM. To elucidate how BM-CAFs drive BCMA-CART resistance, we performed single cell RNA sequencing (scRNAseq) of baseline BM aspirates from responders (R, n = 6) and non-responders (NR, n = 6) to BCMA-CART cell therapy. NR BMs were enriched for inhibitory CAFs (iCAFs) that highly express fibroblast activation protein (FAP). Spatial analyses of BM cells revealed greater iCAF-iCAF and iCAF-inhibitory macrophage interactions in NR. These findings suggest that FAP+ iCAFs in NR are abundant in the BM and exhibit significant interactions with immunosuppressive macrophages. Next, we sought to validate our scRNAseq data in preclinical models. Xenograft mice were intravenously (IV) engrafted with luciferase+ (luc+) BCMA+ OPM2 cells and/or patient-derived (pd) BM-CAFs (1x106 each). Following engraftment, mice received 1x106 BCMA-CART cells (IV). BCMA-CART cells eradicated tumors in mice engrafted with OPM2 cells, but not in mice engrafted with pdBM-CAFs and OPM2 cells (p<0.01). In NSG and humanized mice (NSG mice engrafted with human CD34+ cells in the first 48 hours of life), tumor growth was significantly accelerated in the presence of pdBM-CAFs (NSG: p<0.01; humanized: p<0.001). BCMA-CART, OPM2, and pdBM-CAF co-cultures also showed significant increases in immunosuppressive cytokines including IL-1Rα, IL-4 and IL-10 and inhibited CART cell proliferation compared to co-cultures without pdBM-CAFs (IL-1Rα, IL-10: p<0.01; IL-4: p<0.001; proliferation: p<0.05). To overcome CAF-mediated CART dysfunction, we engineered BCMA-CART cells to secrete molecules to target BM FAP+ iCAFs and remodel the MM-TME (STriKEs). We designed two BCMA-CART-STriKE strategies: 1) a tri-specific composed of IL-15, anti-FAP, and anti-CD16 molecules to activate innate immune cells to kill CAFs and 2) bi-specific anti-FAP, anti-SIRPα molecules linked to an antibody Fc region (Fc fusion) targeting the CD47/SIRPα axis to induce phagocytosis of FAP+ iCAFs. We hypothesized that BCMA-CART-STriKEs would surmount CAF-mediated immunosuppression without toxicity. We generated BCMA-CART-STriKEs from healthy human donor T cells. CAR expression, STriKE secretion, and binding were confirmed via flow cytometry. Co-cultures of BCMA-CART-STriKEs, donor-matched macrophages, OPM2 cells or BCMA+ MM1S cells, and pdBM-CAFs showed significantly higher OPM2 or MM1S killing (p<0.001), immune cell activation (p<0.01), and phagocytosis (p<0.05), compared to control BCMA-CART cells secreting IL-15 or Fc fusions targeting only FAP or only SIRPα. Next, we assessed BCMA-CART-STriKE efficacy in vivo. NOD-SCID-γ-/- (NSG) mice received 1x106 pdBM-CAFs and 1x106 luc+ OPM2 or luc+ MM1S cells via IV or subcutaneous (SQ) injection. Mice were randomized after confirming tumor engraftment (via bioluminescence imaging for IV or tumor caliper for SQ) and received IV treatment with 1x106 BCMA-CART-STriKEs (or controls) and 5x105 donor-matched macrophages or CD16+ immune cells. BCMA-CART-STriKE-treated mice achieved total tumor clearance. Treatment with BCMA-CART cells secreting IL-15 led to lethal weight loss despite tumor clearance while BCMA-CART cells secreting Fc fusions targeting only FAP or SIRPα failed to eradicate tumors. Lastly, we assessed the potential toxicities of BCMA-CART-STriKEs in humanized mice engrafted with OPM2 cells and pdBM-CAFs (1x106 each). CART cells expressing BCMA and FAP CARs (BCMA-FAP CART) served as a control. BCMA-FAP CART treatment resulted in significant toxicity and weight loss while BCMA-CART-STriKE treatment did not (p<0.01). In summary, we have identified iCAF interactions with immunosuppressive immune cells as key contributors to BCMA-CART cell failure and designed novel BCMA-CART-STriKEs that overcome this failure in MM preclinical models. These findings support the translation of BCMA-CART-STriKEs to a phase I clinical trial.

Abstract Introduction Marginal zone lymphoma (MZL) is an indolent and heterogenous disease. Several prognostic models have been proposed to assess outcomes in MZL, including FLIPI, IPI (primarily designed for overall survival [OS]), and MZL-specific scores such as MALT-IPI (event-free survival [EFS]) and MZL-IPI (progression-free survival). FLIPI24 is a recently developed prognostic index for patients with follicular lymphoma (FL) treated with first-line (1L) immunochemotherapy (IC), identifying a high-risk population with inferior survival and increased risk of lymphoma-related death. FLIPI24 has also demonstrated robust performance in the entire FL population, including patients under observation. This study aimed to evaluate the prognostic utility of FLIPI24 in patients with MZL and to compare its performance with other established indices (FLIPI, MZL-IPI, IPI, MALT-IPI). Methods We pooled harmonized data from newly diagnosed MZL patients with complete available FLIPI24 variables (age, white blood cell count [WBC], hemoglobin [HGB], serum lactate dehydrogenase [LDH], and beta-2-microglobulin [B2M] levels) treated with 1L IC. Data were collected from three prospective international cohorts: NiHiL (Czech Republic; n=897; enrolled 2005–2023), LEO (USA; n=62; 2015–2020), and MER (USA; n=32; 2010–2015), forming a pooled cohort of 991 1L IC-treated patients. The analysis was then extended to include all newly diagnosed MZL patients (n=2,116), regardless of treatment. The primary endpoint in the 1L IC-treated cohort was EFS at 24 months (EFS24), and for all MZL patients, it was OS. Secondary endpoints included OS24 for 1L IC treated cohort, lymphoma-related mortality by FLIPI24 risk groups, and comparative prognostic performance of FLIPI, IPI, and MALT-IPI, by C-statistics; performance of MZL-IPI was assessed on a subgroup of NiHiL patients with available data (n=877 all MZL, n=485 1L IC-treated). Results Among the 991 1L IC-treated patients, the median age at diagnosis was 66 years (range 22–94); 47% were male; 11% had ECOG performance status ≥2, 68% clinical stage III–IV, 42% elevated LDH, 40% IPI 3–5, 42% FLIPI 3–5, and 62% MALT-IPI 2–3. The median B2M level was 2.8 mg/L, WBC 7.0 × 10⁹/L, and HGB 13.1 g/dL. MZL subtypes were: 64% extranodal (EMZL), 22% nodal (NMZL), and 14% splenic (SMZL). Most common 1L IC regimens were R-CVP (46%), R-CHOP-like (32%), R-chlorambucil (9%), and B-R (9%). FLIPI24 stratified patients into low- (18%), intermediate- (37%), and high-risk (45%) groups. High-risk patients were older (median 54 vs 65 vs 71 years for low-, intermediate-, and high-risk groups, respectively; P<0.01), had more frequent adverse baseline features, and were more likely to have the SMZL subtype (2% vs 7% vs 25% for low-, intermediate-, and high-risk groups, respectively; P<0.01). After a median follow-up of 7.2 years, EFS24 was 89%, 85%, and 65% (P<0.01) across low-, intermediate-, and high-risk groups; OS at 2 years was 98%, 97%, and 79%; and OS at 5 years was 96%, 91%, and 62%, resp. (P<0.01). The 5-year cumulative incidence of lymphoma-related death was 13% in high-risk vs 6% in low-/intermediate-risk groups. FLIPI24 showed better prognostic accuracy for EFS compared with FLIPI, MZL-IPI, IPI and MALT-IPI (C-index: 0.640 vs 0.630, 0.622, 0.620 and 0.603, resp.), as well as for OS (C-index: 0.710 vs 0.672, 0.641, 0.663, 0.652, resp.). Prognostic performance was consistent across MZL subtypes. In the extended cohort of 2,116 newly diagnosed MZL patients (47% receiving IC, 17% rituximab monotherapy, 11% radiotherapy, 8% surgery, 2% antibiotics; 15% observed), FLIPI24 stratified patients into low- (24%), intermediate- (39%), and high-risk (37%) groups. OS at 2 year was 99%, 97%, and 83%, at 5 years it was 96%, 91%, and 62%, resp. (P<0.01). The 5-year cumulative incidence of lymphoma-related death was 12% in high-risk vs 4% in low-/intermediate-risk patients. FLIPI24 outperformed other indices (OS C-index: 0.754 vs MZL-IPI 0.654, FLIPI 0.700, MALT-IPI 0.694, IPI 0.699). Conclusion FLIPI24 demonstrates strong and consistent prognostic performance across all MZL subtypes, identifying ~40% of patients as high-risk with significantly worse survival and increased lymphoma-related mortality. The FLIPI24 outperforms FLIPI, MZL-IPI, IPI, and MALT-IPI in predicting outcomes and may serve as a practical tool to guide risk-adapted management and selection of patients for novel therapies in MZL. Funding: NU21-03-00411, P50 CA97274, U01 CA195568.

Abstract Introduction Elevated levels of fetal hemoglobin (HbF) ameliorate sickle cell disease (SCD) manifestations. BEAM-101 is an investigational cell therapy comprising ex vivo base-edited autologous CD34+ hematopoietic stem and progenitor cells (HSPCs) that directly target the HBG1/2 promoters to disrupt BCL11A binding, switching production from sickle (HbS) to majority anti-sickling HbF. We present ongoing data from the BEACON study (NCT05456880), a Phase 1/2, single-arm, open-label study evaluating a single dose of BEAM-101 in individuals with SCD and severe vaso-occlusive crises (sVOCs). Methods Eligible patients were aged 12–35 years with SCD and ≥4 sVOCs in the 2-year period prior to informed consent. After mobilization with weight-based or tiered fixed-dose plerixafor, autologous CD34+ HSPCs were collected by leukapheresis and genetically modified with an adenine base editor. Following conditioning with pharmacokinetically adjusted myeloablative busulfan (target cumulative AUC 80 hr*mg/L), patients received a single dose of BEAM-101 (≥3.0×106 viable CD34+ cells/kg). Patients were then monitored for neutrophil and platelet engraftment, adverse events (AEs), total Hb, Hb fractions, % F-cells, hemolysis markers, sVOCs, and additional protocol endpoints for up to 24 months. Results As of June 16, 2025, enrollment has been completed and 46 patients have initiated mobilization. Of the 26 patients who have received BEAM-101, mean duration of follow-up was 6.2 (range 1.0–18.7) months. Baseline demographics were: age 18–34 years, 24 βS/βS genotype, 21 self-reported Black/African American, and 11 female. One patient, who successfully engrafted and obtained stable HbF levels >60%, withdrew consent 5 months post-infusion. For the 26 treated patients, the median number of stem cell collection cycles was 1 (range 1–4); 18 (69.2%) required a single cycle, 4 required 2 cycles, and 4 required >2 cycles. Target cell dose was achieved with a median of 3 (1–12) collection days. Patients received a mean BEAM-101 dose of 8.4 (range 3.2–23.4) ×106 viable CD34+ cells/kg. By the data cut, patients achieved neutrophil (n=26) and platelet (n=24) engraftment at a median of 18 (12–30) days and 19 (11–50) days, respectively, with a median duration of 7 (4–17) days of neutropenia. Of the 24 evaluable patients, 9 (37.5%) achieved platelet engraftment without requiring platelet transfusion through the transplant process. No patients had ≥Grade 3 AEs or serious AEs related to BEAM-101. One patient died due to respiratory failure, assessed as likely related to busulfan conditioning, 4 months post-infusion as previously reported. Mean total Hb increased to 12.1 (range 9.0–14.7) g/dL by Month (M) 1 (n=24), 15.6 (11.9–18.6) g/dL by M6 (n=11), and was sustained through follow-up. Four patients had total Hb levels above the normal range beyond M6 without any associated clinical manifestations or need for therapeutic intervention. Erythropoietin levels trended towards normal in all patients, including those with elevated total Hb. Mean endogenous HbF (HbF/[HbF+HbS]) was >60% and HbS was <40% by M1, which was sustained through last follow-up. At M6, mean % F-cells were 99.2% (97.0–99.9; n=10) and mean HbF/F-cell was 20.8 (18.0–23.9; n=9) pg, exceeding the protective threshold of 10 pg against sickling. Peripheral blood editing was at a mean of 68.5% by M3 (n=16), 69.6% by M6 (n=10), and 72.8% by M12 (n=5). Hemolysis markers and sickling parameters normalized or improved for all patients. No patients experienced any investigator-reported sVOCs post-engraftment. Conclusions The BEAM-101 treatment process is characterized by a low number of mobilization and collection cycles and high editing efficiency, resulting in rapid neutrophil and platelet engraftment and robust pancellular HbF expression, with durability observed up to 18 months. Additionally, there is a corresponding reduction in HbS levels to <40%, and improvements or resolution of hemolysis parameters and anemia, along with resolution of investigator-reported sVOCs post-engraftment. The safety profile of the BEAM-101 treatment regimen is consistent with busulfan conditioning, autologous HSCT, and underlying SCD. These results demonstrate the potential for base editing of the HBG1/2 promoters as a safe and effective therapeutic modality for the treatment of SCD that also has the potential to minimize hospitalization and treatment process burden for patients, families, and sites.

Abstract Background: In R/R DLBCL/FL, T-cell engager therapy (TCET) using chimeric antigen receptor T-cell therapy (CART) or bispecific antibodies (BsAbs) are promising options. Patients (pts) with R/R disease post TCET experience dismal outcomes with overall survival (OS)< 5 months (mos). Lonca, an antibody drug conjugate (ADC) targeting CD19 (FDA approved for R/R DLBCL and beneficial in R/R FL) has been increasingly used post-TCET. RWDA of Lonca is limited, especially regarding: 1) impact of CD19 expression on activity, 2) adverse events (AEs) in non-clinical trial setting, and 3) impact of sequencing Lonca and TCET. Thus, we conducted a RWDA of Lonca efficacy and toxicity in R/R DLBCL and FL pre- and post-TCET. Methods: We conducted a multicenter retrospective study of R/R DLBCL or FL pts ≥18 years who received Lonca from 2017 to 2025 at 10 US academic sites. Demographic, pathological, treatment, and AEs were collected. Efficacy outcomes included overall response rate (ORR), complete response (CR), partial response (PR), stable disease (SD), and progressive disease (PD). Progression-free survival (PFS) and OS were analyzed by Kaplan-Meier method. CD19 expression by immunohistochemistry (IHC) and/or flow cytometry (FC) prior to Lonca administration was correlated to outcomes. Results: Among 120 pts (DLBCL n= 101, FL n=19), all but 2 pts received Lonca monotherapy. At a median follow-up of 6.1 mos, median PFS and OS were 2.6 mos and 6.7 mos, respectively for the entire cohort. For DLBCL, median age was 66 years (18-89). Median prior lines of therapy (LOT) were 4 (1-11). ORR was 37.7% (CR: 17%, PR: 20.7%), SD: 6%, and PD: 56%. Median PFS was 2.1 mos, and median OS was 5.8 mos. For FL, median age was 62 years (28-88). Median prior LOT was 6 (2-8). ORR was 49.4% (CR: 28%, PR: 21.4%), SD: 14%, and PD: 35.7%. Median PFS was 6.7 mos, and median OS was 6.8 mos. OS by best response (entire cohort) was 11.3 mos and 11.8 mos in those who had CR and PR, respectively, 10.6 mos in SD and 3.5 mos in those with PD. Lonca LOT (2nd-12th line) was not associated with improved OS (p=0.58). Bulky disease (>7.5 cm) was not associated with worse OS (p=0.07). PD to Lonca was associated with PD at 2nd line treatment (OR: 4.3; 95% CI: 1.7–10.9) and 3rd-line treatment (OR: 4.2; 95% CI: 1.5–11.5), elevated lactate dehydrogenase (OR: 1.9; 95% CI: 1.2–2.9), and each subsequent increase of extranodal sites >1 prior to Lonca (OR: 1.5; 95% CI: 1.04–2.1). Among pts with available CD19 status prior to Lonca administration, 28 were FC-positive and 22 were IHC-positive. Of the CD19 FC-positive pts (n=23), 22% (5/23) achieved CR, 26% (6/23) had PR, 8% (2/23) had SD, and 43% (10/23) developed PD. Of the CD19 IHC-positive pts (n=20): 15% (3/20) achieved CR, 20% (4/20) had PR, 5% (1/20) had SD, and 60% (12/20) developed PD. Among all CD19-negative pts (n=7), two achieved CR, one had SD, and four with PD. Any grade AE was seen in 84% of pts. Any grade ≥3 (G3) AE was seen in 62% of pts. Notable G3 AEs included: anemia (35%), lymphopenia (34%), neutropenia (21.6%), thrombocytopenia (20%), infection (17%), fatigue (9%), peripheral edema (5%), pleural effusion (4%), photosensitivity (2.5%), and pruritus (2.5%). Treatment discontinuation due to AEs occurred in 17% (n=21) of pts. Fifty-five pts (50 DLBCL, 5 FL) received both Lonca and CD19 directed CART (Pre-Lonca n=54; Post-Lonca n=1). There was no significant difference in PFS or OS between pts who received CART and those who did not (PFS: 2.7 mos vs 3 mos; OS: 7.4 mos vs 5 mos). BsAb was used in 41 pts (34 DLBCL, 7 FL) (Pre-Lonca n=30; Post-Lonca n=11). No significant difference in PFS or OS was observed between pts who received BsAb pre- or post-Lonca. There was also no significant difference in PFS between pts who received a BsAb (2.2 mos) and those who did not (2.9 mos), nor in OS.Conclusion: In this large RWDA of Lonca, pts who achieved any form of clinical response experienced a significantly longer OS than previously reported for heavily pre-treated pts. Lonca was predominantly administered after TCET; however, there was no significant difference in efficacy between pts who received CART and BsAbs and those who did not. CD19 positivity and earlier utilization of Lonca did not appear to have an impact on response rates. Our findings support a role for Lonca in the treatment of R/R DLBCL pts not candidates for TCET. This RWDA highlights the need to further investigate the sequencing of Lonca in R/R DLBCL and FL.

Abstract Introduction The International Prognostic Index (IPI, NEJM, 1993) has guided risk stratification in large B-cell lymphoma (LBCL) for over three decades. Its simplicity and clinical utility have driven its widespread adoption, even in the era of precision medicine. However, the prognostic value of the IPI and its components may not be uniform across the age spectrum of LBCL patients. We evaluated the contemporary prognostic performance of the IPI in a large international cohort, focusing on age-stratified performance and the relative contributions of its individual components, grouped as patient- and disease-related factors. Methods We harmonized and pooled data from 6,941 patients with newly diagnosed systemic LBCL treated with R-CHOP-like regimens (R-CHOP, R-miniCHOP, DA-EPOCH-R, R-CHOEP, R-CHOP+X) with complete IPI data from three prospective cohorts: NiHiL (Czech Republic, n=4,590; 2010–2023), LEO (USA, n=1,789; 2015–2020), and MER (USA, n=562; 2010–2015). IPI components included age, ECOG performance status (PS) as patient-related, and Ann Arbor clinical stage, serum lactate dehydrogenase (LDH), and extranodal (EN) involvement as disease-related factors. Prognostic performance was evaluated using multivariable Cox regression models and C-statistics. Age-stratified analysis was performed for: ≤40 years (7%; n=492), 41–60 years (28%; n=1,909), 61–80 years (59%; n=4,080), and >80 years (7%; n=460). The primary endpoint was overall survival (OS). Results In the pooled cohort, the median age was 66 years (range 18–95). Compared to the original IPI cohort (n=3,273), our cohort was older (age >60 years: 66% vs 41%) but otherwise comparable: ECOG PS 2–4 (25% vs 24%), clinical stage III–IV (63% vs 66%), elevated LDH (60% vs 52%), and >1 EN involvement (32% vs 30%). In multivariable analysis, age (≤60 vs >60 years) was the strongest predictor of OS (HR=2.78; vs HR=1.96 in original IPI report), followed by ECOG PS (HR=2.07; vs 1.80), clinical stage (HR=1.50; vs 1.47), LDH (HR=1.41; vs 1.85, all P<0.01); EN involvement was not significant (P=0.50, HR=1.03 vs 1.48). Risk group distribution shifted from the original IPI: 28% were low-risk (0–1 factor; vs 35%), 23% low-intermediate (2; vs 27%), 24% high-intermediate (3; vs 22%), and 25% high-risk (4–5; vs 16%). Corresponding 2-year OS rates were 95%, 86%, 78%, and 63%, superior to those of the original IPI cohort (87%, 67%, 55%, 44%; pre-rituximab era). Age was associated with an increasing risk of mortality, with a more pronounced rise beyond 60 years. In a piecewise Cox model, the HR per year was 1.04 for ages ≤60 (linear), 1.05 for 61–69 (accelerated), and 1.06 for ≥70 years (exponential, all P<0.01). ECOG PS retained prognostic significance across age groups: HRs were 1.87 (P=0.06) for ≤40 years, 1.63 (P<0.01) for 41–60, 2.22 (P<0.01) for 61–80, and 1.43 (P<0.01) for >80 years. The strength of other IPI components declined with age. Clinical stage showed decreasing impact: HR 2.08 (P=0.09), 1.97 (P<0.01), 1.49 (P<0.01), and 1.31 (P=0.05). LDH was significant only up to age 80 years: HRs were 2.07 (P=0.04), 1.96 (P<0.01), 1.32 (P<0.01), and 1.21 (P=0.13). EN involvement was non-significant across all groups: HRs were 1.37 (P=0.34), 1.26 (P=0.05), 0.98 (P=0.74), and 1.06 (P=0.67). The IPI C-statistics was 0.676 overall and declined with age: ≤40 years (0.708), 41–60 years (0.683), 61–80 years (0.641), and >80 years (0.598). We next stratified the IPI factors into patient- (age, ECOG PS) and disease-related (clinical stage, LDH, EN involvement). In patients ≤40 years, disease-related factors outperformed patient-related (C-index 0.693 vs 0.602), as in the 41–60 group (C-index 0.677 vs 0.589). In patients aged 61–80, predictive values were comparable (0.613 vs 0.622). In >80-year-olds, both declined substantially (0.580 vs 0.568). Conclusion The IPI remains a valuable prognostic tool in LBCL, particularly among younger patients. However, its overall predictive accuracy declines with age. In patients ≤60 years old, prognosis is primarily driven by disease-related factors, suggesting a role for molecular classifiers to enhance risk stratification. In older patients, incorporation of additional patient-level factors, such as comorbidities and nutritional status could be considered. These findings underscore the need for more individualized prognostic tools for LBCL patients. Funding: NU21-03-00411, P50 CA97274, U01 CA195568, Charles University Haematology-Oncology Cooperatio Program.

Abstract Background: Recent advances in computer vision have given rise to image foundation models (FMs), large-scale neural networks pre-trained on millions of unlabeled histopathology patches, which can learn generalizable representations of tissue morphology. In many cancers, these FMs have predicted genetic mutations and prognoses directly from histology, suggesting that morphology encodes “hidden” molecular information. In lymphoma, this field is nascent but growing.General-purpose histopathology FMs have limited representation of lymphoid morphology. We developed and evaluated LymphoVision, a lymphoma-specialized image foundation model pretrained with self-supervised learning, to extract clinically meaningful features from routine hematoxylin and eosin (H&E) histology. Methods: LymphoVision was pre-trained using knowledge distillation and consistency (DINOv2) on over 37 million multi-resolution patches (5x, 10x, 20x, 40x) sampled using a density-aware strategy from 31,211 H&E whole slide images (WSIs) from 9,155 archival lymphoma and reactive lymphoproliferative cases. To ensure diverse, representative samples, our patch sampling method uses an efficient graph-based clustering algorithm and prioritizes morphologically informative regions by clustering patch embeddings and performing density sampling within each cluster. The pretrained encoder was evaluated using a clustering-constrained attention multiple instance learning (MIL) framework on three diagnostic tasks: (1) cell-of-origin (COO) classification in diffuse large B-cell lymphoma (DLBCL), distinguishing germinal center B-cell (GCB) from non-GCB subtypes based on the Hans immunohistochemistry algorithm; (2) follicular lymphoma (FL) grading, differentiating low-grade (grades 1–2) from high-grade (grade 3); and (3) multiclass lymphoma subtype classification across six categories: DLBCL, FL, marginal zone lymphoma (MZL), mantle cell lymphoma (MCL), classical Hodgkin lymphoma (CHL), and benign/reactive lymphoid conditions. WSI-level labels were derived from pathology reports, and none of the evaluation cases were included in pretraining. Models used a ViT-Giant LymphoVision backbone to generate 20x patch embeddings, followed by MIL using 50% training data and 2-fold cross-validation (25% validation, 25% test). Performance was assessed using area under the receiver operating characteristic curve (AUC), accuracy, recall (sensitivity) and F1 score. Results: For DLBCL COO classification (total n=358 cases), LymphoVision achieved a mean test AUC of 0.93 (range 0.92–0.94), accuracy of 84.5% and F1 of 0.85 across two independent test folds (n=91 per fold, 50% GCB). These results outperformed general-purpose FMs on the same task and cases, including Virchow-v2 (AUC 0.85) and UNI-v2 (AUC 0.88), despite those models being pretrained on 10–100 times more images. For FL grading (total n=660 cases), the test set in each fold included 166 cases (18% grade 3), yielding a mean test AUC of 0.88 (range 0.87–0.90), accuracy of 89.2% and F1 of 0.80. In multiclass lymphoma subtype classification (total n=1,176 cases), the test set included 296 cases per fold. LymphoVision achieved a mean test AUC of 0.98 (range 0.97-0.99), mean test accuracy of 87.1% and mean F1 of 0.84. Class-wise recall was 92.0% for DLBCL (n=112), 88.2% for FL (n=72), 77.2% for MZL (n=29), 70.8% for MCL (n=35), 87.5% for CHL (n=24), and 95.8% for benign/reactive lymphoid conditions (n=24). Conclusion: LymphoVision is a lymphoma-specialized FM trained using self-supervision that achieves high diagnostic accuracy across multiple clinically meaningful tasks using weak supervision and standard H&E images, suggesting the encoder has learned fine-grained lymphoma morphology. Based on historical benchmarks from the 1997 International Lymphoma Study Group classification project, expert hematopathologists achieved diagnostic agreement rates of 55% to 84% using H&E morphology alone for the non-Hodgkin lymphoma (NHL) entities included in our multiclass task. LymphoVision approached or exceeded these benchmarks. These findings underscore the value of our approach using disease-specialized pretraining and intelligent patch sampling for data-efficient histopathology learning. LymphoVision has the potential to augment diagnostics, enable scalable AI-powered classification in real-world workflows, and serve as a foundation for prognostic and theragnostic applications. External validation and multimodal integration are ongoing.