Citations

Abstract Background: Follicular lymphoma (FL) is a germinal center–derived B cell malignancy characterized by the clonal expansion of a dominant malignant B cell population. While prior studies have identified transcriptional subtypes across patients, most analyses have treated B cells within individual tumors as a transcriptionally uniform population. However, this assumption has not been systematically tested using high-resolution, clonotype-resolved transcriptomic data. The broader landscape of intratumoral B cells—including those not belonging to the dominant clone—remains poorly defined, and their roles in disease biology are not well understood. These unexpanded, intratumoral B (ITB) cells may include residual non-malignant populations, early-stage malignant cells, or immune-modulating cells with distinct roles in the tumor microenvironment. It is also unknown whether their presence varies across patients or correlates with clinical features or immune microenvironmental interactions. Methods: We performed integrated single-cell 5′ RNA sequencing and B cell receptor (BCR) repertoire sequencing on 7 newly diagnosed FL 1-3A fresh-frozen lymph node biopsies (Dasari et al., Blood Cancer Discov 2025). Using a high-confidence approach that incorporates heavy and light chain pairing, V and J gene usage, and CDR3 nucleotide junction identity, we classified B cells into two groups: (1) cells belonging to the dominant expanded clone (FL B cells) and (2) all other B cells with detectable and non-expanded BCRs (ITB). These clonal identities were then integrated with single-cell transcriptomic profiles using Seurat and Immcantation pipelines. Differential expression analysis was conducted using edgeR to compare FL B cells to ITB cells across all FL biopsies. Results: After quality filtering, a total of 44,637 single cells were retained across all 7 samples (minimum per sample: 3,847 cells), including malignant and non-malignant B cells as well as diverse tumor microenvironment populations. The proportion of B cells assigned to the dominant FL clone varied substantially across tumors, ranging from 22% to 89%, indicating that some tumors contain a substantial population of ITB cells. In one tumor, we identified two expanded malignant B cell clones comprising 40.6% and 34.4% of all cells. These clones exhibited non-overlapping V and J gene usage (IGHV3-11/IGHJ5 vs. IGHV3-72/IGHJ3), distinct CDR3 junctions, and different immunoglobulin isotypes (IGHG1 vs. IGM). BCL2 was expressed in most cells within both clones (Clone 1: 87.8%, Clone 2: 67.0%), with mean log-normalized expression levels of 1.79 and 0.95, respectively. Both clones formed distinct UMAP clusters and showed transcriptional divergence from ITBs, with 453 differentially expressed genes (DEGs) identified for Clone 1 and 98 for Clone 2 (adjusted p<0.01, |log₂FC|>1, min.pct≥0.25). Additionally, 748 DEGs were identified between the two clones. This evidence of clonal divergence within a single FL tumor reinforces the need to reconsider intratumoral homogeneity in FL and suggests that multiple malignant clones may sometimes coexist. When comparing FL clones to ITB cells across tumors we found that FL clones exhibited a transcriptional program enriched for proliferation and cell cycle regulators, including MKI67 (p<0.005), E2F1 (p<0.0001), CDKN2A (p<0.0001), and CDKN2B (p<0.01), as well as elevated expression of AICDA (p<0.01), EZH2 (p<0.0001), and PD-L1 (p<0.05). As expected, the malignant cells also had higher expression of BCL2 (p<0.01) and CD10/MME (p<0.0001). In contrast, ITB cells demonstrated relatively higher expression of SELL (p<0.0001) and TNFRSF14 (p<0.05), which were significantly downregulated in the FL clone. Conclusions: Together, these findings challenge the prevailing notion that FL tumors are defined by a single homogeneous malignant B cell population. Instead, our data support a model in which multiple transcriptionally and functionally distinct B cell populations coexist within tumors, including dominant clones and a diverse population of ITB cells. This is, to our knowledge, the first study to comprehensively characterize these populations using integrated, lineage-aware single-cell multiomic profiling across FL patients. These insights may ultimately inform new strategies for understanding tumor evolution, immune evasion, and therapeutic targeting in follicular lymphoma.

Abstract Background Adult xanthogranuloma (AXG) is a rare clonal histiocytic neoplasm (HN) with a poorly defined mutational landscape. Clinically and immunophenotypically, AXG can resemble other HNs such as Erdheim-Chester Disease (ECD) which frequently harbor MAPK pathway alterations and carry BRAF V600E mutations in close to 50% of cases. However, due to the rarity of AXG, the prevalence of the BRAF V600E mutation and the broader mutational landscape is not well known. In this study, we characterize the mutational profile of AXG. Methods We conducted a retrospective analysis of patients diagnosed with AXG at our institution between January 1, 2016, and July 15, 2025. The study was approved by the institutional review board. To ensure inclusion of true AXG cases, only patients with a confirmed histopathologic diagnosis and without multisystemic involvement or characteristic imaging findings of ECD, such as symmetric long bone osteosclerosis, were included. BRAF alterations were identified by immunohistochemistry (IHC) and/or next-generation sequencing (NGS). We also performed an extensive literature review of mutational studies in AXG and included cases that underwent comprehensive NGS. Results Seventeen patients with AXG were identified. The median age at diagnosis was 40 years (range: 18–75 years). Out of the 17 patients, 11 (65%) reported the face as the primary site of disease, and 11 (65%) had solitary lesions. Of the 17 patients, 13 (76%) underwent BRAF V600E IHC staining, and none tested positive. Twelve (71%) patients had tissue samples analyzed via NGS, and none exhibited the BRAF V600E mutation. Eight of the 12 (67%) patients with NGS testing harbored other alterations involving the MAPK pathway. These included BRAF fusions (n=3), KRAS mutations (n=2), and individual cases with TRAF7 mutation, ALK1 fusion and FGFR1 fusion. One patient was found to have a mutation in WRN, which is not previously reported in AXG. Three patients had no identifiable pathogenic alterations on NGS. Ten patients were monitored without treatment, 2 underwent surgical resections and 3 received chemotherapy (1 had a complete response [CR], 2 achieved a partial response). One patient with FGFR1 fusion was treated with pemigatinib and achieved a CR for over 3 years. One patient with TRAF mutation obtained a CR after treatment with rituximab. We also identified 51 cases of AXG with adequate mutational testing reported in the literature, which reported findings similar to ours. In a retrospective study from France involving 29 patients, MAPK alterations were observed in 55% of cases: however, only 10% harbored BRAF V600E mutations (1). Another analysis of 270 patients with various HN subtypes included 13 individuals with AXG, none had BRAF mutations. MAP2K1 mutations were seen in 31% of patients (2). Taken together, across a combined cohort of 68 AXG patients, the most common alterations were: KRAS mutations (16%), fusions (14%), MAP2K1 mutations (7%) and BRAF V600E (6%). Among fusions, the most involved gene was BRAF (50%), and GAB2 was the most common fusion partner (n=2). In total, 59% of patients had MAPK alterations. These findings collectively underscore the diverse mutational landscape of AXG and highlight the rarity of BRAF V600E mutations relative to closely related HNs. Conclusion We present a series of AXG cases with mutational profiling, from our institution and the published literature. We demonstrate that MAPK alterations are frequently observed in AXG and are driven by heterogeneous mutations. In contrast to other HNs where BRAF V600E mutations are common, we identified no such mutations in our cohort and found only rare cases in the literature. Our institutional data, along with findings from the existing literature, suggest that AXG may have a distinct molecular profile compared to other HNs. A deeper understanding of its mutational landscape may offer insights into disease biology and identify therapeutic targets. ReferencesAnnabi E, Mahévas T, Chasset et al. Clinical, Histopathologic, and Molecular Features and Treatment of Multiple Xanthogranuloma in Adults. JAMA Dermatol. 2025;161(7):765-768. doi:10.1001/jamadermatol.2025.0886.Durham BH, Lopez Rodrigo E, Picarsic J, et al. Activating mutations in CSF1R and additional receptor tyrosine kinases in histiocytic neoplasms. Nat Med. 2019;25(12):1839-1842. doi:10.1038/s41591-019-0653-6

Abstract Background:Erdheim-Chester Disease (ECD) is a rare, incurable histiocytic neoplasm. Since its recognition in 1930, our understanding of ECD's pathophysiology has evolved. The identification of its clonal nature after 2015 established ECD as a cancer, prompting increased disease awareness and treatment advances. Targeted therapies show promising responses, but changes in ECD mortality over time have not been extensively documented. Methods:A multi-institutional retrospective cohort study analyzed adults with ECD consecutively seen at Mayo Clinic MN, AZ, and FL and the University of Alabama at Birmingham between 2007 and 2024. Clinical and prognostic data were abstracted. Overall survival was estimated using the Kaplan-Meier method and compared to expected survival using U.S. Census data, based on age at diagnosis (by calendar year), date of diagnosis, and sex. Standardized mortality ratios (SMRs) were calculated by dividing the number of observed deaths in the study population by the expected number of deaths using U.S. population data. Risk of death was compared by date of diagnosis (pre- and post-2015) using Cox proportional hazards analysis. Statistical analysis was performed with R software. Results:A total of 159 ECD patients were included (median age 58 years [range 19-82], 65% male). Forty-nine patients were diagnosed between 1990-2014 and 110 between 2015-2024. Median follow-up for the entire cohort was 4.0 years (95% CI: 3.2-4.4). Median follow-up for those diagnosed between 1990-2014 was 10.4 years (CI: 3.2-16.8), compared to 3.5 years (CI: 3.0-4.2) for those diagnosed between 2015-2024. The 5-year overall survival rate was 80% (95% CI: 72-88). Patients with ECD had an increase in mortality over expected, with 28 deaths compared to an expected 11.2, an SMR of 2.5 (95% CI: 1.7-3.6, p<0.001). Of 17 patients with an identified cause of death, death was attributable to ECD in 11 (65%), secondary malignancy in 1 (7%), and unrelated causes in 5 (29%). Cause of death was unknown in 11 patients. Among deaths, 11 (39%) were treated with targeted therapy, 8 (29%) with chemotherapy, and 1 (4%) received both. One patient (4%) received steroids, 1 received immunomodulator and targeted therapy (4%), and 6 (21%) received no disease-directed therapy. Of the patients whose death was related to ECD, 10 (91%) had multisystem disease. For 49 patients diagnosed pre-2015, 14 deaths occurred during the follow-up, significantly higher than the expected 5.2 deaths based on U.S. population data (SMR of 2.7 [95% CI: 1.5-4.4, p=0.001]). Among those diagnosed between 2015 and 2024, 14 deaths occurred, compared to expected 6.1 (SMR of 2.3 [95% CI: 1.3-3.8, p=0.006]). In an age- and sex-adjusted Cox proportional hazards model, diagnosis after 2015 vs. diagnosis prior to 2015 yielded a hazard ratio of 0.59 (95% CI: 0.27-1.31, p=0.19). Conclusion:The mortality rate of ECD patients remains higher than the general population, despite advancements in disease recognition and development of targeted therapies. While our data suggest a possible trend toward improved survival among patients diagnosed after 2015, we did not find statistically significant evidence of decreased mortality compared to those diagnosed prior to 2015. Larger cohorts with longer follow-up periods are needed to draw definitive conclusions regarding mortality.

Abstract Background: De novo secondary central nervous system (CNS) lymphoma (SCNSL), characterized by concurrent systemic and CNS aggressive B-cell lymphoma at diagnosis, is a rare entity with a dismal prognosis. The prognostic significance of the initial anatomical compartment of CNS involvement (parenchymal vs. leptomeningeal) is not well-defined. We sought to analyze outcomes based on CNS localization in a single-institution cohort. Methods We retrospectively reviewed 34 patients with de novo SCNSL (including diffuse large B-cell lymphoma [DLBCL], high-grade B-cell lymphoma, not otherwise specified (HGBCL NOS), and double-/triple-hit lymphoma) treated at the Mayo Clinic between 2002 and 2025. Clinicopathological features, radiologic findings, treatment details, and survival outcomes were abstracted from the medical records. Patients were categorized by the primary site of CNS involvement. Overall survival (OS) and progression-free survival (PFS) were estimated using the Kaplan-Meier method, and groups were compared with the log-rank test. Results The study cohort had a median age of 61.5 years (range 19-79) and a median International Prognostic Index score of 3 (range 2-4). Pathological subtypes included double-/triple-hit lymphoma (n=14, 41.2%), non-germinal center B-cell like (non-GCB) DLBCL (n=11, 32.4%), germinal center B-cell like (GCB) DLBCL (n=8, 23.5%), and HGBCL NOS (n=1, 2.9%). Among patients with available data, 14 (43.8%) were positive for MYC rearrangement, 13 (54.2%) for BCL2 rearrangement, and 10 (45.5%) for BCL6 rearrangement. First-line regimens received by patients included MR-CHOP (n=18, 52.9%), DA-R-EPOCH (n=5, 14.7%), combined CODOX-M/IVAC (n=4, 11.7%), R-CHOP with intrathecal methotrexate (n=3, 8.8%), miscellaneous therapies (n=3, 8.8%), and MRT (n=1, 2.9%). The complete response rate was 58.8% (n=20). Intrathecal chemotherapy was administered to 61.8% of patients, and consolidation with autologous stem cell transplant was performed in 35.3%. Based on the CNS compartment involved, de novo SCNSL (DN-SCNSL) were classified into two subtypes: the leptomeningeal subtype, defined as leptomeningeal involvement with or without parenchymal CNS disease (LM-DN-SCNSL; n=22, 64.7%), and the parenchymal subtype, defined as parenchymal-only CNS involvement (P-DN-SCNSL; n=12, 35.3%). Parenchymal disease was multifocal in 75% of cases, supratentorial in 58.3%, and associated with a midline shift in 30%. Although no tested factors (including pathological subtype, age, sex, and bone marrow involvement) were significantly associated with the anatomical compartment, a non-significant trend was noted for BCL6 rearrangement to be more common in the leptomeningeal group (8/13, 61.5%) than the parenchymal group (2/8, 25.0%) (P = 0.18). Survival outcomes were analyzed for both anatomical and pathological classifications. For the parenchymal versus leptomeningeal cohorts, 2- and 5-year Overall Survival (OS) rates were 75.0% vs. 45.1% and 41.0% vs. 38.7%, respectively (P = 0.34). For Progression-Free Survival (PFS), the 2- and 5-year rates were 48.6% vs. 32.5% and 29.2% vs. 26.0%, respectively (P = 0.53). The 2-year OS rates by pathological subtype were 81.8% for non-GCB DLBCL, 45.8% for DHL/THL, and 37.5% for GCB DLBCL (P = 0.27). Survival outcomes (OS/PFS) were not significantly associated with patient age, sex, pathological subtype, or anatomical compartment. Conclusion DN-SCNSL can be anatomically classified into two subtypes: LM-DN-SCNSL and P-DN-SCNSL. While a prognostic trend favoring the parenchymal subtype was observed, the difference did not achieve statistical significance, a finding likely attributable to the small cohort size. This classification may hold clinical utility for guiding risk stratification, and larger studies are needed to validate these findings and identify the most optimal treatments for each subtype of DN-SCNSL.

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.

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 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: Brentuximab vedotin (BV) was approved by the US FDA for relapsed/refractory (R/R) classical Hodgkin lymphoma (cHL) in 2011 and for previously untreated advanced stage cHL in 2018. The immune checkpoint inhibitors (ICIs) nivolumab and pembrolizumab were approved for R/R cHL in 2016 and 2017, respectively. These novel agents have significantly changed the landscape of cHL management in recent years. In this study, we analyzed data from the National Cancer Database (NCDB) to investigate whether survival outcomes have improved in the novel agent era (2011 and beyond) for patients with cHL in the US. Methods: Patients diagnosed with cHL between 2004 and 2020 were identified in the NCDB. Those with missing survival data were excluded. Three treatment eras were defined based on the timing of FDA approval of novel agents: Chemo era (2004–2010), BV era (2011–2015), and ICI era (2016–2020). Patient and disease characteristics were compared using the Chi-square test. Survival analyses were conducted using the Kaplan-Meier method and Cox proportional hazards model. Results: A total of 85,488 patients with newly diagnosed cHL were identified: 36,150 in the Chemo era, 27,058 in the BV era, and 22,280 in the ICI era. Compared to the chemo era, the BV and/or ICI eras included slightly more patients aged ≥66 (17.3% vs 17.8% vs 19.5%), male (53.6% vs 54.6% vs 53.8%, p=0.042), Black (11.3% vs 12.9% vs 12.5%), Hispanic (9.0% vs 9.9% vs 10.9%), with Charlson-Deyo score ≥1 (14.2% vs 16.1% vs 17.2%), B symptoms (44.1% vs 46.9% vs 46.9%), treated at academic centers (32.4% vs 35.9% vs 36.4%), on Medicaid (9.5% vs 12.2% vs 13.7%) or Medicare (19.3% vs 20.3% vs 21.7%), and with higher income (≥4th quartile by 2008-2012 standard; 34.5% vs 34.3% vs 36.3%) (all p<0.001 except for sex, noted above). Ann Arbor stage data were not available in the ICI era. There were slightly more patients with advanced-stage disease in the BV era compared to the Chemo era (45.4% vs 40.3%, p<0.001). IPS scores were available for only 2,344 patients, with a similar distribution (0–2 vs 3–7) across the three eras (p=0.957). The median follow-up was 6.9 years (95% CI 6.9-7.0). Overall survival (OS) significantly improved in the novel agent eras: the 5-year OS rate was 79.8% (95% CI, 79.4%–81.2%) for patients diagnosed in the Chemo era, 81.9% (95% CI, 81.9%–82.4%) in the BV era, and 84.1% (95% CI, 83.5%–84.8%) in the ICI era (p<0.001). Statistically significant OS improvements were observed across all subgroups, including age (≤40: 92.8% vs 94.9% vs 96.5%, 41-65: 80.5% vs 81.8% vs 84.4%, ≥66: 41.4% vs 46.6% vs 52.7%), sex (male: 78.0% vs 80.0% vs 81.9%, female: 81.9% vs 84.1% vs 86.7%), race (White: 79.9% vs 81.6% vs 83.7%, Black: 77.2% vs 81.2% vs 84.6%, others: 84.5% vs 87.0% vs 89.3%), ethnicity (Hispanic 79.7% vs 82.3% vs 85.1%, Non-Hispanic 80.0% vs 81.9% vs 84.1%), Charlson-Deyo score (0: 83.5% vs 85.4% vs 87.9%, 1: 62.8% vs 68.2% vs 73.2%, 2: 42.5% vs 52.6% vs 58.3%, 3+: 49.0% vs 54.4% vs 51.7%), B symptoms (yes: 74.7% vs 78.9% vs 81.5%, no: 84.3% vs 85.1% vs 87.5%), treatment facility type (academic: 69.8% vs 74.0% vs 77.1%, non-academic: 66.4% vs 67.6% vs 70.2%, unknown: 92.9% vs 95.0% vs 96.5%), insurance type (private: 89.9% vs 91.2% vs 93.4%, Medicare: 46.5% vs 52.3% vs 57.2%, Medicaid: 79.1% vs 84.5% vs 87.7%) and income level (Q1: 74.1% vs 77.1% vs 81.1%, Q2 77.7% vs 80.1% vs 81.3%, Q3 79.8% vs 81.6% vs 85.2%, Q4: 82.8% vs 84.9% vs 87.0%) (all p<0.001). In multivariate Cox regression analysis adjusting for age, sex, race, ethnicity, Charlson-Deyo score, B symptoms, treatment facility type, insurance type, and income level, diagnosis in the BV era (HR = 0.856; 95% CI, 0.827–0.885; p<0.001) and ICI era (HR = 0.666; 95% CI, 0.636–0.698; p<0.001) was independently associated with improved OS compared to the Chemo era. Conclusions: In this large NCDB-based analysis, survival outcomes for patients with cHL significantly improved in the BV and ICI eras compared to the Chemo era. OS improvement was consistent across all subgroups and remained independent of age, sex, race, ethnicity, Charlson-Deyo score, B symptoms, treatment facility type, insurance type, and income level in multivariate analysis. These findings may reflect the positive impact of BV and ICIs on survival in patients with cHL.

Abstract Although follicular lymphoma (FL) typically follows an indolent course, patients with FL who experience early events, such as transformation or progression, have increased risk of death related to lymphoma. The FL24Cx is an algorithm based on a 45-target gene expression profiling (GEP) assay, which was developed and trained using 265 formalin-fixed, paraffin-embedded tissue samples on a reliable platform to predict, at the time of diagnosis, whether a patient will experience an event within 24 months. The modeling also confirmed and relied upon previously reported synergy between immune response (IR) gene expression signatures IR1 and IR2. Once locked, the 5-factor logistic regression FL24Cx model was independently validated in a retrospectively assessed cohort of 232 patients from 2 immunochemotherapy-treated arms of SWOG Cancer Research Network S0016 phase 3 clinical trial, in which it assigned 169 patients to the low-risk group with 29 events before 24 months (17.2%) and 63 patients to the high-risk group with 24 events before 24 months (38.1%). The relative risk of an event within 24 months after registration among patients who were classified into the high-risk group relative to patients who were classified into the low-risk group was 2.2 (95% confidence interval, 1.41 to 3.51). An up-front GEP biomarker, such as the FL24Cx, rigorously validated in a clinical laboratory and with a clinically relevant turnaround time, could identify and steer enrollment of patients at high risk for early events in clinical trials, thus enabling timely interpretation of such trials and increasing the pace of innovation.

ABSTRACT Anaplastic lymphoma kinase‐positive large B‐cell lymphoma (ALK+ LBCL) is a rare, aggressive subtype of diffuse large B‐cell lymphoma with poor outcomes using standard chemotherapy. In this multi‐institutional retrospective study, we analyzed 39 cases of ALK+ LBCL identified at six US academic centers from 2002 to 2024, with treatment including conventional cytotoxic regimens in frontline and biologically informed and nonchemotherapy‐based strategies in the relapsed setting. Ninety‐two percent of patients received frontline anthracycline‐based chemotherapy; 43% received intensified regimens, and 15% underwent upfront autologous stem cell transplantation (ASCT). Despite these approaches, outcomes remained poor. At a median follow‐up of 5.4 years, median event‐free survival (EFS) was 0.6 years (95% CI, 0.4–0.9), and median overall survival (OS) was 1.5 years (95% CI, 1.3–NR). One‐ and five‐year EFS rates were 28% and 17%, while corresponding OS rates were 72% and 42%, respectively. Advanced stage and high IPI scores were associated with inferior outcomes. Twelve patients received ALK inhibitors, with alectinib showing more durable responses than crizotinib. Lenalidomide and immune checkpoint inhibitors also demonstrated activity, including durable complete responses. Five patients underwent allogeneic stem cell transplantation, with three achieving sustained remission. In conclusion, our findings highlight the limited benefit of chemotherapy, even when intensified or followed by ASCT, and support the integration of biologically targeted therapies, which may have contributed to improved OS in our cohort compared to historical outcomes. Prospective, collaborative studies are needed to better understand disease biology and define optimal use of modern therapies in this rare lymphoma.