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Abstract Background: Although progression-free survival (PFS) in early-stage (ES) classic Hodgkin Lymphoma (cHL) is high, there remains a subset of patients (pts) at higher risk of worse outcomes, particularly in those with unfavorable risk disease. Leveraging pt-level data from within the HoLISTIC (Hodgkin Lymphoma International STudy for Individual Care) Consortium, the E-HIPI was developed in clinical trial pts and validated in real-world registry pts to predict 2-year (y) PFS (Rodday. NEJM Evidence 2025). Continuous, objective, and readily measurable pre-treatment variables were considered, with sex, maximum tumor diameter, albumin, and hemoglobin included as significant predictors. Using the E-HIPI, interactive calculators for pt risk, comparison, and stratification were created (https://rtools.mayo.edu/holistic_ehipi/). Although the E-HIPI was developed and validated in both unfavorable and favorable ES cHL pts, the clinical predictors are primarily markers of unfavorable disease. In the development and initial validation cohorts, 2y PFS was 93.7% and 90.3%, respectively, the C-statistic was 0.63 in both cohorts, calibration was strong with slight underprediction of events in the validation cohort, and the E-HIPI outperformed the historic binary classification of patients as favorable or unfavorable using EORTC criteria. However, since pts in the original E-HIPI development and validation were primarily treated with ABVD chemotherapy protocols, additional validation is needed, particularly among pts with unfavorable ES cHL who were treated initially with more intensive chemotherapeutic platforms (e.g., BEACOPP-based). Thus, we conducted an external validation of the E-HIPI in pts treated on recent unfavorable ES cHL GHSG trials. Methods: The validation cohort included 2367 adults (ages 18 to 60y) with newly-diagnosed unfavorable cHL from randomized phase 3 trials conducted by the GHSG (HD14 von Tresckow. JCO 2012; and HD17 Borchmann. Lancet 2021). We calculated the predicted probability of 2y PFS events based on the E-HIPI model equation (scale 1-100%). Model performance was assessed using discrimination and calibration. Discrimination, which is the model's ability to separate high and low risk pts, was assessed using Harrell's C-statistic. Calibration, which is the model's ability to accurately predict absolute risk, was assessed by comparing observed and predicted probabilities of 2y PFS events within quintiles of predicted probabilities and estimating calibration-in-the-large (predicted minus observed event rate) and the calibration slope. Results: For pts treated on unfavorable GHSG trials, mean age was 33y, 95% had stage II disease, mean baseline E-HIPI score (i.e., predicted 2y PFS event rate) was 6.0% (SD=2.3%), and the observed 2y PFS rate was 96.2% (95%CI: 95.4-97.0%). The C-statistic was 0.65 (95% CI: 0.59-0.70), calibration-in-the-large was 0.02, and the calibration slope was 1.08 (95% CI: 0.52, 1.64). Within the lowest risk E-HIPI quintile, the observed 2y PFS event rate was 1.6%, compared with 6.1% in the highest risk quintile. Conclusions: In external validation of the recently published E-HIPI in pts with cHL treated on unfavorable GHSG trials using more intensive BEACOPP-based protocols, discrimination was similar to the original development and validation cohorts. Collectively, the E-HIPI is a treatment-agnostic prediction tool across varied treatment regimens for unfavorable ES cHL pts. Better 2y PFS in the GHSG trials than in the E-HIPI development and initial validation cohorts may have contributed to mild misclassification, likely reflecting differences in treatment regimens. This may be resolved with recalibration or incorporating granular treatment variables into future models. Additional research is needed to understand E-HIPI performance in pts with favorable disease who have even lower event rates as well as to more fully predict individualized pt outcomes across varied chemotherapy platforms and radiation received for all ES cHL pts.

Abstract Introduction The LEO Comorbidity Index (LCI), comprising ten equally weighted comorbidity categories (respiratory, cardiovascular, digestive, hepatic, renal, autoimmune, diabetes, cancer history, HIV, and stroke), has demonstrated prognostic utility in patients with non-Hodgkin lymphomas. However, its predictive accuracy may vary with increasing age, due to age-related rises in comorbidity burden and physiological vulnerability. To investigate these dynamics, we evaluated the age-stratified predictive performance of LCI in patients with large B-cell lymphoma (LBCL), with a focused analysis on individuals aged 80+ years. We also examined which specific comorbidities most strongly influenced overall survival (OS) and developed a simplified, clinically applicable index tailored to this population. Methods We first included adults ≥40 years with newly diagnosed LBCL and recorded comorbidities from the LEO registry (USA, 2015–2020; n=1,652) to assess age-stratified predictive performance of LCI using the C-index. Next, we focused on patients 80+ years (n=263), pooled from the LEO cohort (n=147) and NiHiL registry (restricted to General Hospital, Prague, Czech Republic, 2010–2023; n=116). Comorbidities were collected from patient self-reports (LEO) and/or medical records (LEO/NiHiL). Univariate and multivariate Cox models were used. The primary endpoint was OS. Results Among the total LBCL population (n=1,652), LCI predictive performance improved by age category with C-index for patients <65 of 0.584, 65–79 years 0.579, and ≥80 years 0.647, indicating stronger discrimination in the 80+ group. Subsequent analysis focused on patients aged 80+ years (n=263; median age 83). Within this cohort, 34% had ECOG performance status (PS) 2–4, 66% stage III–IV disease, 59% elevated lactate dehydrogenase, 35% >1 extranodal site involved, and 58% International Prognostic Index (IPI) score of 3–5. A total of 377 comorbidities were reported, averaging 1.43 per patient (1.22 in LEO; 1.61 in NiHiL). LCI distribution was: 0 points in 24% (n=62), 1 point in 33% (n=88), and 2–5 points in 43% (n=113). Higher LCI scores had worse ECOG PS 2–4: 19% (LCI=0), 33% (LCI=1), and 43% (LCI ≥2; P=0.01), and inferior OS (median 6.9 years LCI=0, 3.0 years LCI=1, and 2.8 years LCI≥2, resp.; P=0.02). Presence of ≥1 comorbidity was associated with shorter OS compared to no comorbidities (HR=1.67, P=0.01). The LCI was an independent predictor of OS after adjusting for age (HR=1.18, P=0.01, C-index 0.623), IPI (HR=1.16, P=0.03, C-index 0.628) as well as for recently proposed SENIOR-IPI (HR=1.14, P=0.049, C-index 0.665). When evaluating individual comorbidities, heart disease (HR=1.54, P=0.01), stroke (HR=1.89, P=0.03), and recent malignancy (HR=1.99, P=0.02) were independent predictors of OS. Based on these findings, we developed a simplified LCI (sLCI) for use in 80+ patients incorporating only the three comorbidities (1 point each). Patients were categorized as sLCI: 0 (49%, n=129), 1 (44%, n=115), and 2–3 points (7%, n=19). sLCI scores 0, 1, 2–3 were associated with ECOG PS 2–4 27%, 37%, and 63%, respectively (P=0.01) and inferior OS: median 5.3 years (0), 2.5 years (1), and 1.4 years (2–3; P<0.01). sLCI remained an independent and strong predictor of OS after adjusting for age (HR=1.71, P<0.01, C-index 0.636), IPI (HR=1.66, P<0.01, C-index 0.635), and SENIOR-IPI (HR=1.60, P<0.04, C-index 0.659). The results were consistent in both NiHiL and LEO cohorts and remained significant among patients treated with anthracyclines (sLCI adjusted for age: HR=1.58, P<0.01, C-index 0.607; for IPI: HR=1.53, P=0.01, C-index 0.623; for SENIOR-IPI: HR=1.51, P=0.01, C-index 0.633). Conclusion Comorbidity burden becomes increasingly prognostic with higher age in LBCL patients. In the 80+ individuals, comorbidities – particularly heart disease, recent cancer, and stroke – have an independent impact on OS. While the original LCI captures the impact of broadly defined comorbidities, its prognostic utility attenuates in the 80+ patients, likely reflecting limited relevance of indolent chronic conditions in this population's constrained survival horizon. The sLCI, focused on the most prognostically relevant comorbidities, offers practical risk stratification. Incorporation of sLCI into clinical decision-making – alongside other prognostic indices – could better identify high-risk individuals and guide treatment strategies. Funding: NU21-03-00411, U01 CA195568.

Abstract Introduction: The CAR-T therapies ide-cel and cilta-cel are approved for patients (pts) with relapsed/refractory multiple myeloma (RRMM). The aim of this study was to determine the incidence, subtypes, and associated risk factors for subsequent primary malignancies (SPMs) in MM pts treated with CAR-T therapy in the real-world setting. Methods: A retrospective, multicenter observational cohort study was conducted of pts who received CAR-T therapy between May 2021 and Dec 2024 at 15 centers within the US Multiple Myeloma Immunotherapy Consortium. Logistic models were used for univariable analyses of invasive SPMs (excluding non-melanoma skin cancers). Variables significant at p < 0.10 were included as candidate variables in the multivariable analysis. Time to event endpoints were analyzed using Kaplan-Meier curves. Results: Of n=1460 CAR-T recipients, median follow-up from the time of CAR-T infusion for the entire cohort, ide-cel, and cilta-cel pts was 13.1, 16.9, and 10 months, respectively. A total of 55 invasive SPMs were noted in 53 pts (SPM incidence 3.6%). The incidence rate of SPMs was 4.55 per 1,000 person-years, based on 53 SPMs occurring over 11,646.14 person-years (calculated from CAR-T to the SPM diagnosis, death, or last follow-up). Baseline characteristics were similar for pts with no SPM versus SPM including: age at CAR-T (median 67 vs 65), female (36% vs 43%), Black (13% vs 16%), prior autologous transplant (87% vs 80%), lenalidomide for ≥2 years (31% vs 27%), high risk cytogenetics (23% vs 29%), and known clonal hematopoiesis (7.5% vs 9.9%). Differences were observed in baseline characteristics among pts with SPM versus no SPM for ≥2 prior alkylator lines of therapy (LOT) (82% vs 60%, p=0.002) and median prior LOT (6 vs 5, p=0.008). There was a trend for more patients with SPMs being age ≥70 (35% vs 37%, p=0.074). Of the 53 SPMs, 26 (49%) were myeloid (MDS or AML), 19 (35.8%) were solid, 7 (13.2%) were of T-cell origin, and 1 was a B-cell lymphoma. Of the T-cell SPMs, three were of T-LGL, though one of the T-LGL pts later developed an invasive CNS T-cell lymphoma (CAR-negative). There were four cases of confirmed CAR-positive T-cell SPMs (all pts treated with cilta-cel), of which two were indolent T-cell lymphoma of the GI tract and two were cutaneous PTCL. There was no difference in total incidence of SPMs among pts who received ide-cel (total=4.4%; myeloid=2.2%, T-cell=0.04%) versus cilta-cel (total=3%; myeloid=1.4%; T-cell=0.5%) (p=0.21). Median OS from the time of CAR-T therapy was 40.8 months for pts without SPM compared to 27.6 months for pts with SPM (p=0.4). Median OS did not differ by myeloid, solid, and T-cell subgroup: 26.4, 37.2, and 24 months, respectively (p=0.21). Median time from CAR-T cell to SPM was 12 months overall, and by subtypes of myeloid, solid, and T-cell was 13.2, 9.6, and 9.6 months, respectively (p=0.74). There was no difference in time to any SPM among pts receiving ide-cel versus cilta-cel (p=0.61). An earlier time to diagnosis of myeloid SPM was observed for cilta-cel versus ide-cel (4.8 vs 20.4 months; p=0.003). Median OS from the time of diagnosis of any SPM, myeloid, solid, or T-cell SPM was 9.6, 7.2, 15.6, and not reached in months, respectively (p=0.006), demonstrating that pts diagnosed with myeloid subtype SPM had inferior OS from the time of their SPM diagnosis compared to other subtypes. The cause of death of 4/11 myeloid SPM pts was the myeloid SPM itself. In univariable analysis for the entire cohort, age ≥70 (p=0.079), ≥5 prior LOT (p=0.012), and ≥2 prior alkylator LOT (p<0.001) were associated with higher risk for SPM. In multivariable analysis, ≥2 LOT containing alkylators was associated with higher risk of SPM (p=0.005). For the univariable analysis of the myeloid subgroup, ≥2 prior alkylator LOT (p=0.016) and ≥2 years of lenalidomide maintenance (p=0.063) were associated with higher risk of SPM. In multivariable analysis, ≥2 years of lenalidomide (p=0.065) was associated with a trend toward increased risk of myeloid SPM. Conclusions: With a median follow up of 13.1 months, the incidence of developing a SPM following CAR-T in pts with RRMM was 3.6%, of which approximately half were myeloid malignancies. There was no difference in SPM incidence when comparing the two CAR-T products. Pts treated with ≥2 alkylator LOT had a higher risk of SPM in multivariable analysis and may warrant additional monitoring for SPM development.

Abstract Background Secondary central nervous system lymphoma (SCNSL) is a rare but significant complication, affecting approximately 2–10% of patients with diffuse large B-cell lymphoma (DLBCL), often leading to poor outcomes. The CNS-International Prognostic Index (CNS-IPI) remains a widely adopted tool for estimating CNS relapse risk; however, recent advances in molecular profiling and evolving treatment paradigms have challenged the adequacy of CNS-IPI alone in guiding risk assessment. This study evaluates the prognostic relevance of CNS-IPI in conjunction with molecular and clinical factors, specifically cell-of-origin (COO), gene expression, and frontline treatment regimens. The aim is to refine risk stratification and identify patients at highest risk for SCNSL. Method Building on our previous study, we analyzed data from patients with newly diagnosed DLBCL between 2002 and 2023, enrolled in the Mayo Clinic/University of Iowa Lymphoma Molecular Epidemiology Resource. Patients with primary CNS lymphoma, CNS involvement at diagnosis, or who received CNS-directed therapy were excluded. COO was determined using the Hans algorithm and/or Nanostring profiling. Multivariate cause-specific Cox regression models were used to estimate hazard ratios (HR) and 95% confidence intervals (CIs) for predictors of CNS relapse that were measured at the time of initial DLBCL diagnosis. Cumulative incidence with competing risks and cause-specific Cox models were used to analyze relapse risk. Result We included 2137 patients in our analysis, median age at diagnosis was 63 (IQR 53-72), with 41.6% (n=890) females. The albumin level was below normal in 32.5% (n=350), 64.0% (n=1367) had CNS-IPI of intermediate/high, 37.5% (n=586) had non-germinal center B-cell (GCB) COO, and 14.5% (n=309) were double expressor positive. At a median follow-up of 83 months (IQR 42 -143), 82 (3.8%) SCNSL relapses were observed; the 3 and 5 yrs cumulative incidence for SCNSL from time of DLBCL diagnosis were 3.7% (95% CI 3.0-4.7) and 3.8% (95% CI 3.1-4.8) respectively. In models accounting for death as a competing risk, the 5-year cumulative SCNSL incidence estimate for patients with a CNS-IPI low was 1.5% (95% CI 0.8-2.7), Intermediate was 4.9% (95% CI 3.7-6.4), and high was 6.1% (95% CI 3.8-9.6). The 5-year cumulative SCNSL incidence estimate for patients with non-GCB COO was 5.2% (95% CI 3.6-7.4) compared to 2.4% (95% CI 1.6-3.6; p=0.001) for GCB patients, and the 5-year cumulative SCNSL incidence for double expressor positive patients was 8.6% (95% 5.8-12.6) compared to 1.5% (95% CI 0.8-2.7; p<0.001) for double expressor negative patients. In a multivariable model (including CNS-IPI, COO, double expressor, treatment group, extranodal involvement, and albumin group), CNS-IPI intermediate (HR 2.85 [1.58-5.14]; p<0.001) and high (HR 4.31 [2.15-8.65]; p<0.001), non-GCB COO (HR 2.36 [1.37-4.06]; p=0.002], double expressor (HR 5.56 [2.88-10.73]; p<0.001), and below normal albumin (HR 1.89 [1.02-3.50]; p=0.042) were independently associated with increased risk of SCNSL. The majority of the SCNSL relapse occurred within the first 2 years after DLBCL diagnosis; 81.7% (n=67), with only 6.1% (n=5) occurring after 5 years. For patients who developed SCNSL, the median OS from the time of SCNSL diagnosis was 24 months (95% CI 17-34), with 5 years OS of 31% (95% CI 22-43). These findings are being validated using an external, international cohort, and final analysis will be presented at the time of presentation at ASH. Conclusion In this large, prospectively followed cohort with long-term follow-up data, SCNSL remains a rare but devastating complication of DLBCL, with a 5-year cumulative incidence of 3.8% and it is associated with very poor long-term survival. While CNS-IPI remains a strong predictor of SCNSL risk, our study identifies non-GCB COO and double expressor phenotype as independent, additive molecular risk factors. These findings suggest that current risk stratification tools may underestimate the risk of CNS relapse in molecularly defined high-risk subgroups. Considering the poor outcomes linked to SCNSL and the absence of a connection with frontline treatment types, future research should aim to enhance risk prediction models through molecular profiling and explore prophylactic strategies to reduce the likelihood of SCNSL.

Abstract Introduction: VEXAS (vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic) is an aggressive auto-inflammatory disorder defined by somatic UBA1 mutations. UBA1 mutations arise in hematopoietic stem cells and bias differentiation toward myeloid lineages. Clonal involvement of monocytes and neutrophils in VEXAS is frequent. Recently, natural killer (NK) cells have been recognized within the UBA1 mutant clone; mutated NK cells have an exhausted phenotype and impaired cytotoxicity (Ganesan BioRxiv 2025; Breillat et al, Blood 2025). A unique NK-like T cell type (CD3+CD16+[CD56-] T cells) has a role in the immunopathogenesis of severe COVID-19, resulting in heightened cytotoxicity and tissue damage (Georg et all, Cell 2022). As NK cells do not typically express CD3, and as the activation of inflammatory pathways is not restricted to myeloid cells in VEXAS, (Mizumaki et al, Nat Comm 2025) we sought to assess the CD3+ cell populations for co-expression of CD16 using single-cell (sc) multiomic data from VEXAS patients. Methods: After IRB approval, we performed sc-proteogenomic sequencing using a custom-made gene panel (Tapestri, MissionBio) in 2 VEXAS patients. Libraries were sequenced on an Illumina NovaSeq instrument. In one case, we performed in parallel CITE-Seq in parallel and used canonical correlation analysis (CCA) to integrate these immunophenotypic and transcriptomic data with matching cell populations identified from proteogenomic sequencing. We used pathway analysis (IPA) and gene ontology enrichment (gProfiler), as well as differential gene expression (RNA-seq) to identify significant gene signatures. T-tests with Welch's correction were performed for statistical significance on surface markers from proteogenomic data which were transformed by center log ratio. Our observations were then validated in sc-proteogenomic data from two additional VEXAS patients profiled at the NIH. Results: We used a sc-multiomic strategy to study CD3+ T cell subsets in VEXAS patients. In the first UBA1 mutant (mt) sample, using clusters defined by UMAP overlay of CITE-Seq/proteogenomic data, we defined positive expression of CD3 expression in the non-UBA1mt T cell cluster. We then examined the proteogenomic data (n=700 cells) to identify CD3+ cells (n=89 UBA1mt, n=42 UBA1wt). We then divided the CD3+ fraction into CD56+ vs CD56- to obtain CD3+CD56+ (n=25 UBA1mt, n=12 UBA1wt) and CD3+CD56- (n=64 UBA1mt, n=0 UBA1wt) cells. The CD3+CD56- cells were not only entirely UBA1mt, but also co-expressed CD16, significantly elevated from CD3+CD56+ UBA1wt cells (p<0.0001; and no significance from granulocyte populations): 10% of UBA1mt cells were CD3+CD16+CD56-. This cell subset was detected in an additional 3 VEXAS samples, and, in each case, there was no significant difference between UBA1mt/UBA1wt CD3 expression (both were T cell subsets) and no significant difference in CD56 expression. There was a significant increase in CD16+ expression in UBA1mt over UBA1wt (p<0.0001) cells, but not between UBA1mt cells and other granulocytes. Finally, we assessed the CITEseq data from the first UBA1mt case and focussed on gene expression and pathway differences between CD3+ and CD3+CD16+(CD56-) cell populations. Using IPA, we found top differentially expressed pathways included neutrophil degranulation, inflammation, cell killing, and IL-8 activity. Differentially expressed genes included FCGR3B, TLR2, IL1R2, FCGR2A, CCR1, CXCL8, and CXCR1, some of these overlapping with what was reported in similar cells (CD3+CD16+) detected in COVID-19 (Georg et all, Cell 2022). Conclusion: We identify a unique NK-T cell like [CD3+CD16+(CD56] subset of cells within UBA1mt cells in patients with VEXAS. This cell type has been reported in patients with severe COVID-19 as having increased cytotoxic functions and associated with fatal outcomes. Rare or aberrant cell clusters defined by standard clustering analysis may mis-identify some cell types, especially if they aberrantly express CD3+CD16+, as either marker could be used to pre-gate cells into larger clusters of lymphoid or myeloid cells. Prospective and functional profiling of this cell type in VEXAS patients is ongoing.

Abstract Marginal zone lymphoma (MZL) is an uncommon non-Hodgkin B-cell lymphoma accounting for 7-10% of lymphoma diagnoses. Extranodal MZL (EMZL) of mucosa-associated lymphoid tissue (MALT) is the most common subtype (61%) of MZL. While the mutational landscape, chromosomal aberrations and transcriptome of nodal and splenic MZL have been extensively evaluated, the mutational landscape of EMZL has only been evaluated in a small number of patients and mainly by targeted sequencing. Consequently, the comprehensive genomic landscape of EMZL remains largely uncharacterized. Herein, we performed whole exome sequencing followed by targeted sequencing of potential tumor driver genes, copy number and/or RNA transcriptome analyses in 165 patients with pretreatment EMZL tumors involving 16 anatomic locations. All samples were collected and underwent expert review as part of the Atlas of Blood Cancer Genomes consortium. The most common anatomic locations were ocular adnexa (OAMZL) (n=35), gastric (n=25, including 6 positive for Helicobacter pylori), salivary glands (n=25), and lungs (n=24). Using common criteria for variant mutation calling and significant focal copy number (CN), we identified 1218 variants (1030 missense and 188 truncation mutations) across 174 genes and 2837 CN focal alterations (1614 copy gains and 1223 copy number losses). Of these genes, 44 and 11 were mutated in >5% and >10% of specimens, respectively. We detected variants identified previously by targeted sequencing in EMZL from different locations (e.g. TNFAIP3 (A20) (12%), TBL1XR1 (13%), SPEN (10%), CARD11 (7%), TET2 (7%) and CREBBP (6%)). We detected mutations in KLF2 (10 mutations in 8 EMZL patients) and PTPRD (7 mutations in 7 EMZL patients) that were previously suggested to be specific for splenic and nodal MZL, respectively. We also detected variants not previously reported in EMZL, including a transcriptional factor ZEB2, LRP1B,and others. The most frequently mutated gene in our study (25% of tumors) was IGLL5. Some mutations were limited to specific locations (e.g. ZEB2 mutations seen exclusively in gastric and salivary gland EMZL), while most were observed across all anatomic locations. There was no association between specific mutations and clonal IGHV, in contrast to previous reports. Using Enrichr tool, we observed enrichment of mutations in genes belonging to the B cell receptor activation, NOTCH signaling, Wnt-beta catenin signaling, NF-kB signaling , PI3K AKT signaling, DNA repair and other pathways. Chromosomal and copy number changes were also commonly observed including previously reported trisomy of chromosomes 3 and 18. Combining DNA mutations and CN alterations, the number of genetic lesions per tumor sample in the 174 mutated genes ranged from 0 to 95, with an average load of 17 lesions per case. RNA sequencing was successful in 159 EMZL tumors from 16 distinct anatomic locations. Unsupervised clustering using all genes with a median log2-normalized gene expression value greater than 5 and a standard deviation greater than 1 (1323 genes) demonstrated that the majority of gastric EMZL with and without H. pylori infections clustered together on 2 dendrograms as did most of the samples of OAMZL. Since the clustering could be forced by organ-specific and not tumor-specific gene expression, we next focused on the expression of the 345 genes from the LM22 matrix that passed our transcriptomic row filtering. Unsupervised clustering resulted in clustering of most gastric EMZL irrespective of H. pylori positivity together in the same dendrogram branch, accompanied by few additional EMZL from other anatomic locations. Most of the EMZL samples from other locations did not show preferential co-clustering together. On comparison of gene expression between gastric and OAMZL, there was enrichment of the B-cell receptor signaling pathway, B-cell activation, B-cell naïve and B-cell memory cells, B-cell proliferation and NF-kB signaling in the latter. Immune microenvironment analysis showed a statistically significant increase in resting mast cells and decrease in M1 macrophages in gastric EMZL and increase in regulatory T cells in salivary EMZL. The broad genomic studies reported here underscore the biological similarity of EMZL across anatomical sites with the potential exceptions of gastric EMZL (regardless of H. Pylori status). These data provide valuable genomic and transcriptomic resources to inform future diagnostic and therapeutic strategies.

Abstract Diffuse Large B Cell Lymphoma (DLBCL), the most common subtype of aggressive B-cell Non-Hodgkin Lymphoma (NHL), accounts for 30-40% of newly diagnosed NHL cases. Despite recent progress improving our understanding of molecular features of DLBCL, there is still a high relapse rate (~45%) among patients who undergo standard treatment (R-CHOP). Several groups have identified reproducible molecular clusters of DLBCL although, the biologic significance of many of the specific gene mutations within these clusters is poorly understood. DTX1 mutations are a feature of the BN2/C1 DLBCL classifiers and are among the mutations with unknown significance. BN2/C1 DLBCL are a mixture of ABC, GCB, and Unclassified cell of origin (COO) with a common signature being the presence of genetic alterations in genes known to regulate the NOTCH pathway; yet, these tumors lack transcriptional signatures of traditional NOTCH activation, suggesting a unique and undefined biology driven through non-canonical NOTCH pathway activation. DTX1 is an E3 ubiquitin ligase which directly binds the intracellular domain of the NOTCH receptor (NICD), targeting it for degradation, resulting in suppression of NOTCH pathway activity. We therefore hypothesize that DTX1 mutations lead to NOTCH pathway dysregulation and are a critical driver for a subset of BN2/C1 DLBCLs. Using whole exome sequencing (WES) data from 404 newly diagnosed DLBCL patients, we found 8% of patients with mutations in DTX1. Alterations in DTX1 were localized to the NICD binding domain, WWE1. In silico Alphafold modeling of DTX1 WWE1-interaction with NICD revealed that patient mutations clustered within predicted interacting surfaces with NICD. These findings lead to the hypothesis that mutations in the DTX1 WWE1 domain suppress its ability to bind to and degrade NICD, enhancing NOTCH pathway activation in DLBCL. To address this question, we first compared DTX1 protein expression by immunoblot in DTX1 WWE1 mutant (OCI-Ly3 and SUDHL2) and wildtype (WT) (OCI-Ly7, OCI-Ly19, SUDHL6, and U2932) DLBCL cell lines. We found higher expression of NICD1 (p=0.03) in OCI-Ly3 and NICD2 (p<0.0001) in SUDHL2 cell lines compared to WT. This increase was accompanied by an increase in NOTCH surface expression with higher NOTCH1 (p<0.0001) and NOTCH2 (p<0.0001) expression on OCI-Ly3 and SUDHL2 cells, respectively, compared to WT. To remove variability across cell lines we next used CRISPR to generate DTX1 knock out (KO) models using WT DTX1 DLBCL cell lines U2932 and OCI-Ly19. Analysis of NICD and NOTCH receptor protein expression confirmed our initial finding, showing an 8.5 and 4.8-fold increase of NICD1 and a 6 and 2.5-fold increase of NICD2 expression in the U2932 and OCI-Ly19 DTX1 KO cell lines, respectively, compared to empty vector (EV) controls. An increase in surface NOTCH1, and to a lesser extent NOTCH2, was seen in U2932 (p=0.01 and p=0.07, respectively) and OCI-Ly19 (p=0.001 and p=0.2, respectively) KO cells compared to EV controls. To identify pathways affected by DTX1 mutations, we next performed RNAseq on U2932 EV and KO cell lines. Of interest, we did not detect any significant changes in classical NOTCH driven genes (Hes1, Hey1, etc.), supporting prior studies on BN2/C1 tumors. However, we did identify potential non-canonical NOTCH-target genes that may contribute to lymphomagenesis. Gene expression in KO cells showed upregulation of genes involved in germinal center (GC) processes (AICDA, IRF4; p<0.001) and cellular growth and survival (IL6R, CCND2, STAT5B, BCL2; p<0.0001). Measurement of IL6R by flow cytometry and CyclinD2 by immunoblot further verified DTX1-mediated upregulation of IL6R (p<0.01) and CyclinD2 (p<0.01) for U2932 KO cells compared to EV control. We also observed downregulation of genes contributing to cell death (ex. BAX, CASP8, FAS; p<0.05) in KO cells compared to EV. Together, these novel findings support our hypothesis that DTX1 WWE1 mutations lead to dysregulation of the NOTCH pathway by driving overexpression of NICD and NOTCH, resulting in dysregulated expression of proteins involved in cell cycle, GC reaction, and apoptosis. We further provide new biologic insight into BN2/C1 DLBCL, ultimately highlighting a path toward novel therapeutic targets and the advancement of personalized medicine, as patients harboring these mutations may benefit from new therapies targeting inflammatory pathways, such as CELMoDs.

Abstract Introduction: CD19-directed CAR T-cell (CAR-T) therapy has substantially improved clinical outcomes for adults with relapsed or refractory (R/R) B-cell acute lymphoblastic leukemia (B-ALL). However, notable toxicities are associated with CAR-T, including cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). Variable practice patterns have emerged regarding the use of CRS/ICANS prophylaxis (ppx) via corticosteroids and/or other pharmacologic agents, but the utility of these approaches on reducing CRS or ICANS following CAR-T in B-ALL remains unknown. Thus, we utilized the Real-World Outcomes Collaborative for CAR T in ALL (ROCCA) database to evaluate associations between ppx and the development and severity of CRS or ICANS following brexucabtagene autoleucel (brexu-cel) for B-ALL. Methods: Adult patients (pts) who received standard-of-care brexu-cel for relapsed/refractory B-ALL across 40+ US centers were included. Primary endpoints were the incidence of CRS and ICANS within 28 days of CAR-T infusion. Secondary endpoints included timing of CRS and ICANS onset, progression-free survival (PFS) and overall survival (OS). Univariable and multivariable logistic regression evaluated associations between ppx and incidence of CRS/ICANS; KM and log-rank methods were used for survival analyses. Results: A total of 378 pts were included: 53 pts (14.0%) received CRS/ICANS ppx and 325 (86.0%) received no ppx. Ppx agents included steroids only (26.4%), steroid and anakinra (52.8%), anakinra only (15.1%), and steroid and tocilizumab (5.7%). Pts in the ppx group had a higher proportion of Hispanic pts (64% vs 34%), Ph-like (36% vs 19%) and a lower proportion had 0-5% bone marrow blasts at apheresis (38% vs 53%). The ppx and no ppx groups were similar in age, prior therapies, CAR-T indication, and marrow blasts >50%. Cumulative incidence of any grade (gr) CRS was 94% with ppx and 86% with no ppx (p=0.025), of any gr ICANS was 53% with ppx and 51% with no ppx (0= 0.85). Cumulative incidence of gr 3-4 CRS was 9% in the ppx group and 10% in the no ppx group (p=1.00), of gr 3-4 ICANS was 26% in the ppx group and 29% in the no ppx group (p=0.71). Median time to onset for any gr CRS or any gr ICANS was identical in the ppx and no ppx cohorts (CRS: 5 days, range ppx 1-9 days, no ppx 0-14 days; ICANS: 7 days, ppx 1-20 days, no ppx 0-16 days). Univariate logistic regression analyses showed no significant association between ppx and the incidence of gr 2-4 CRS (OR 1.34, 95% CI: 0.75-2.40, p=0.326) or gr 3-4 ICANS (OR 0.88, 95% CI: 0.46-1.70, p=0.708). Multivariate analysis adjusting for ethnicity, leukemia genetic sub-type, and pre-apheresis disease burden similarly found no significant associations between ppx and gr 2-4 CRS (adjusted OR 1.06, 95% CI: 0.55-2.01, p=0.870) or gr 3-4 ICANS (OR 1.23, 95% CI: 0.59-2.55, p=0.584). When comparing steroid-only ppx (N=14) to steroid combinations or other drug ppx (N=39), there was no significant differences in gr 2-4 CRS (57% vs 44%, p=0.345) or gr 3-4 ICANS (43% vs 21%, p=0.115). Comparing cumulative incidence of dexamethasone (dex) exposure, pts in the ppx group had numerically greater dex exposure than pts in the no ppx group, with median (range) dosing of 182 mg (10-1386mg) and 100mg (1-4000mg), respectively. Finally, we found no significant differences in PFS or OS based on ppx. Median PFS was 9.6 months in the ppx group vs 13.3 months in the no ppx group (p=0.646) and median OS was 17.2 months in the ppx group vs 34.4 months in the no ppx group (p=0.170). Conclusions: In this large cohort of adult patients with R/R ALL receiving brexu-cel CAR-T therapy, prophylaxis intended to prevent CRS/ICANS was ineffective at reducing CRS/ICANS incidence, time to onset, or overall steroid exposure. Furthermore, PFS and OS were comparable between patients who received prophylaxis and those who did not. In the absence of prospective trials in B-ALL, these data suggest that current strategies of CRS/ICANS prophylaxis has limited benefit.

Abstract Introduction: Epcoritamab (epco) and glofitamab (glofit) are bispecific antibodies (BsAbs) approved for the treatment of patients (pts) with relapsed or refractory (r/r) large B-cell lymphomas (LBCLs). Their use is associated with relatively high response rates, with some patients experiencing prolonged remission. It is unclear whether continuous treatment beyond 12 months for pts in remission is beneficial, as continued immunosuppression may result in additional toxicity. We sought to report the outcomes of pts with prolonged remission and survival following BsAb administration. Methods: We performed a multicenter retrospective study including 21 US centers evaluating pts with r/r LBCLs receiving commercially available epco or glofit between 2023 and 2025. Baseline characteristics and outcomes were extracted from medical records. Efficacy and survival outcomes were assessed by site investigators and included overall response rate (ORR), complete and partial response (CR, PR) rates. Pts who responded to BsAbs and had ≥365 days of follow-up from initiation of BsAb treatment were included in the analysis. Results: As of May 15, 2025, a total of 312 pts with r/r LBCLs were treated with BsAbs (epco n=193, glofit n=119) with a median age of 66 years (interquartile range [IQR] 59-73) at BsAb start. Most were male (64.5%), had advanced stage disease (77.4%) and had ECOG performance status of ≤1 (93.3%) at BsAb start. Of 207 pts who had initiated treatment with BsAb ≥12 months prior to data cutoff, we identified 31 pts (15.0%) who had a response to BsAbs (19 epco, 12 glofit) and were alive without progression at 12-months post-BsAb initiation and included them in this landmark analysis. Of the cohort of 19 pts treated with epco, 6 discontinued due to reasons other than disease progression including CAR-T cell therapy (n=2), secondary malignancy (n=2), allogeneic transplant (n=1), or other reasons (n=1). Thirteen of 19 pts received ≥12 months of epco treatment, and, with a median follow-up of 16 months from the start of BsAb, 12 of 13 pts continued receiving epco beyond 12 months with one pt discontinuing after 12 months (observed for an additional 41 days prior to censoring). Of the cohort of 12 pts treated with glofit, 8 pts were observed after completing all planned therapy and 4 patients underwent allogeneic transplant. Among all 31 BsAb-treated patients alive and in remission at 12 months, at the time of data cutoff, 5 pts (12.9%) had progressed (2 previously treated with epco and 3 with glofit). Three of the 4 pts who underwent allogeneic transplant after prior glofit treatment experienced disease relapse. A total of 24 pts (77.4%) were alive at the time of last follow-up, with the causes of death being disease progression (n=1), secondary malignancy (n=1), infection (n=1), and unknown cause (n=4). Conclusions: In this large cohort of r/r LBCL pts treated with BsAbs monotherapy in the standard of care setting, a relatively small proportion of pts (15%) achieve the 12 month PFS landmark. In the absence of robust evidence for what constitutes best practice, different strategies are employed, including continuation of BsAb, observation as well as consolidation with allogeneic transplant or CAR T-cell therapy. Additional follow-up will be reported to help guide clinical decision making regarding the optimal management strategy for this high risk pt population.

Abstract Background Myelodysplastic syndromes (MDS) develop from the acquisition of somatic mutations over years or decades. While some mutations are random stochastic events, others derive from extrinsic agents that promote genomic instability, including environmental exposures. Agent Orange (AO) is a phenoxy herbicide used by the U.S. military as a defoliant during the Vietnam War (1962-71), often diluted with gasoline to promote aerosolization, contaminated with the carcinogen dioxin during the manufacturing process, and linked to various cancers. We studied AO as a risk factor for MDS. Methods The prospective National Heart, Lung, and Blood Institute National MDS Natural History Study includes patients (pts) with suspected or recently diagnosed MDS enrolled from 6/2016-6/2024. Bone marrow samples underwent central pathology review, resulting in diagnoses including MDS, MDS/myeloproliferative neoplasm overlap (MDS/MPN), or clonal cytopenia of undetermined significance (CCUS). Pts completed detailed assessment for AO exposure and other risk factors for MDS development. Associations between AO exposure, mutation prevalence, and key covariates (demographics, diagnosis, military service, clinical history, cytogenetics and smoking) were assessed using univariate tests of association, multivariable regression and Cox regression models for survival and progression. Results Among 2115 enrolled pts, 1191 (56%) had a myeloid malignancy or precursor condition and 130 (6.1%) reported AO exposure, the majority (96%) male. Compared to unexposed pts, AO exposed pts were more likely to derive from the 1945-54 birth cohort (p<.001), of age to serve in Vietnam, and to have an ultimate diagnosis of MDS or CCUS vs. a non-clonal diagnosis (57% vs. 44%, p=.046). AO exposure was more common among Blacks (12% vs 6%, p=.02), specifically Black males (21% vs 9%, p=.006). AO exposure was marginally associated with International Prognostic Scoring System (IPSS)-R poor-risk cytogenetics (p=.066) and lower baseline platelet count (p=.072). In multiple regression analyses, risk of AO exposure was significantly higher for the 1945-1954 birth cohort (OR [95% CI]=10.3 [4.4-30.6], p<.001), among those with military service (OR=24.1 [11.9-55.8], p<.0001), and for Blacks vs Whites (OR=2.6 [1.2-5.5], p=.017). The crude risk of AO exposure trended higher for patients with MDS compared to idiopathic cytopenia of undetermined significance (ICUS; OR=2.1 [0.9-6.0],p=.13), but not in multivariable analysis (OR=1.3 [0.5-4.4, p=.60]). AO exposure trended toward an association with younger age at MDS diagnosis (p=.06) and toward having a prior primary malignancy (49% vs. 41%, p=.09): Compared to non-AO exposed pts, AO exposed pts had higher rates of prior prostate cancer (16% vs. 8%), notable given its documented association with AO exposure. AO exposure was not associated with a history of or intensity of cigarette smoking (p=.67). After accounting for age, diagnosis, sex, and military service, AO exposure was significantly associated with increased numbers of pathogenic variants in 53 genes (OR=1.2 [1.0-1.4], p=.02) and with having Very Poor/Poor risk IPSS-R cytogenetics (OR=3.7 [1.2-11.1], p=.02). AO exposed and non-exposed pts had similar overall survival (HR=1.1 [0.8-1.7], p=.50), but those exposed to AO had a higher risk of disease progression in the first two years following diagnosis (HR =1.9 [1.2-2.8], p=.004). AO exposed pts appeared more likely to have del (5q) (15% vs. 8%) and del (20q) (13% vs. 5%) karyotypic abnormalities, and TP53 (7.7% vs. 4.5%), STAG2 (5.1% vs. 2.8%), and NRAS mutations (3.4% vs. 1.7%), although sample sizes were small. Focusing on gene pathways, AO exposed pts appeared more likely to have abnormalities in RAS signaling (10.3% vs. 5.7%), cell cycle (7.7% vs. 4.5%), and cohesion complex pathways (6.0% vs. 3.1%), but less likely to have abnormalities in cytokine receptor pathways (0% vs. 4.5%). ConclusionsIn our representative national cohort of pts with at least one cytopenia, and for the first time, we demonstrated that AO exposure is associated with younger age at MDS diagnosis, ultimate MDS diagnosis, genetic complexity of MDS, increased risk of disease progression, and with Black race, despite Black individuals comprising just 16% of men who served in the Vietnam War and being less likely to have MDS than white individuals. AO should formally be recognized as a risk factor for the development of MDS.