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Abstract Background Chimeric antigen receptor T cell (CART) therapy has revolutionized treatment for hematologic malignancies. However, durable remission following anti-CD19 CART therapy (CART19) remains limited to 40–50% of patients, often due to tumor relapse and CART dysfunction (PMID:31501612). We previously demonstrated that tumor-derived extracellular vesicles (EVs) from patients with chronic lymphocytic leukemia (CLL) can directly impair CART function (PMID:33388419). In this study, we aimed to identify tumor-derived EV microRNA (miRNA) cargo associated with clinical CART failure in B cell malignancies and define how they mechanistically drive CART cell dysfunction. Methods To achieve these aims, we profiled tumor-derived EV miRNA cargo using small RNA sequencing (RNAseq) in two independent patient cohorts. Cohort 1 compared plasma-derived EVs from untreated CLL patients to those from healthy donor EVs to identify miRNAs enriched in CLL (n=23). Cohort 2 included patients with diffuse large B cell lymphoma (DLBCL) treated with axicabtagene ciloleucel (CART19, n=12). Here, plasma EV miRNAs were analyzed at baseline (pre-CART treatment) and 1-month post-CART treatment and compared between CART responders (complete remission at 6 months) and nonresponders (no response at 1 month). Enriched miRNAs from both cohorts were identified following miRNA count normalization and differential expression analysis using adjusted p values of ≤0.05. Functional studies were conducted by transfecting CART19-28ζ cells with synthetic miRNA mimics or scrambled controls. CART cells were also generated with stable overexpression of miRNA via lentiviral shRNA delivery. CART function was assessed via in vitro killing, proliferation, apoptosis assays, RNAseq, and in vivo tumor xenograft models. Results In Cohort 1, we identified several miRNAs including miR-125a to be significantly enriched in CLL-derived EVs relative to healthy controls. Similarly, in Cohort 2, miRNA-125a was also identified among the miRNAs enriched in nonresponders vs. responders to CART treatment; Notably, miR-125a was significantly enriched in nonresponders at baseline (pre-CART treatment) and 1-month post-CART treatment (p=0.0177, p=0.0196). To define the functional effects of miR-125a, we delivered synthetic mimics or stable shRNA constructs encoding miR-125a into CART cells. Delivery of miR-125a was confirmed by RT-qPCR (p<0.0001 for mimic vs. scramble, p=0.0069 for shRNA vs. scramble). Here, miR-125a delivery and overexpression impaired CART cytotoxicity/killing of target tumor cells (~25% reduction, p= 0.0039), decreased antigen-specific proliferation (~47% reduction, p=0.0002), and increased apoptosis following antigen stimulation (1.8-fold increase, p=0.0002) as compared to scramble controls in vitro. We next studied how miR-125a impacts CART functions in vivo. Here, tumor-bearing mice treated with miR-125a–overexpressing CART cells (CART sh125a) exhibited accelerated tumor progression (4.1-fold increase, p=0.0019) and significantly reduced survival as compared to mice treated with scramble control CART treatment (CART shScr) (20% vs 80% survival at day 35, p=0.0064), underscoring the dramatic detrimental impact of miR-125a on therapeutic efficacy. To uncover changes in CART gene expression induced by miR-125a delivery, RNAseq was also performed across stimulated CART sh125a vs. CART shScr cells. CART sh125a cells demonstrated broad transcriptional changes, with gene set enrichment of E2F targets, G2/M checkpoint, and apoptosis pathways (FDR p<0.0001, p<0.0001, and p=0.006) further validating the role of miR-125a in disrupting CART cell cycle control, proliferation, and survival. Conclusion In summary, our study identifies miR-125a as a tumor-derived EV cargo that drives CART dysfunction in two separate B cell malignancies (CLL and DLBCL). miR-125a was enriched in both CLL EVs and nonresponders to CART19 therapy at baseline prior and post CART treatment. Functional studies demonstrate that miR-125a delivery and overexpression directly impair CART cytotoxicity and proliferation, increase CART apoptosis, reduce therapeutic efficacy in tumor xenograft models, and disrupt key pathways related to CART cell cycle regulation and survival. These findings position miR-125a as both a key mechanistic driver of CART failure and a potential predictive biomarker for treatment response, while highlighting it as a possible therapeutic target to improve CART outcomes in the clinic.

Abstract Background: Post-transplant lymphoproliferative disorder (PTLD) occurs in up to 30% of high-risk solid organ transplant recipients and is strongly associated with the intensity and duration of immunosuppression. While Epstein-Barr virus (EBV)-positive monomorphic PTLD and diffuse large B-cell lymphoma (DLBCL) share overlapping morphologic features and expression of canonical B-cell markers, they exhibit distinct EBV transcriptional programs. Immunosuppressive regimens, essential for preventing graft rejection, impair EBV-specific cytotoxic T lymphocyte (CTL) responses, thereby promoting EBV-driven lymphomagenesis. We hypothesized that these differences in viral transcription and immune evasion reflect fundamentally distinct immune microenvironments and host responses in EBV-positive PTLD compared to DLBCL. Methods This prospective, non-interventional study has been conducted at Moffitt Cancer Center since 2019. To characterize tumor-specific T-cell responses in EBV-positive PTLD versus DLBCL, peripheral blood mononuclear cells (PBMCs) from enrolled patients were infected with EBV (ATCC VR-1492) to generate autologous, immortalized lymphoblastoid B-cell lines (LCLs). EBV antigen-specific immune responses were quantified using an IFN-γ ELISpot assay targeting EBNA1, LAMP1, LAMP2A, BARF1, and a CEF peptide pool as a control. To optimize cell viability and functional readout post-thaw, we implemented an overnight resting protocol for PBMCs, which demonstrated superior IFN-γ release compared to the conventional 1-hour rest. Results We present pilot data from 11 consecutive patients (55% male; median age 63.4 years), including 3 with PTLD (2 EBV-positive; 2 monomorphic) and 8 with EBV-negative DLBCL. A total of 12 evaluable PBMC samples were analyzed: 7 pre-treatment, 1 mid-treatment, and 4 post-treatment. Successful generation of autologous LCLs was predominantly achieved using pre-treatment samples, whereas samples collected after B-cell–targeted therapy (Rituximab ± CHOP) showed reduced transformation efficiency. Notably, early pre-treatment samples exhibited a relative enrichment of CD27⁺ memory B cells. Baseline flow cytometric profiling of B cells undergoing LCL transformation revealed low CD19 expression (range <1%–15%). Repeat immunophenotyping at 3 weeks identified residual T cells within cultures, suggesting ongoing B-cell clearance. In matched flow cytometry and ELISpot assays from 7 evaluable patients with pre-treatment samples, EBV-positive PTLD cases demonstrated pronounced overexpression of PD-1 and TIM-3, but not LAG-3, alongside markedly diminished T-cell responses to EBV antigens. This distinct immunophenotypic and functional signature suggests T-cell exhaustion or dysfunction, likely driven by prior immunosuppression, which may impair immune surveillance and facilitate EBV-driven lymphomagenesis. Conclusions Our findings reveal distinct immunologic profiles in EBV-positive monomorphic PTLD compared to EBV-negative DLBCL, characterized by immune exhaustion and impaired T-cell functionality. Specifically, overexpression of PD-1 and TIM-3—but not LAG-3—in EBV-positive PTLD correlated with diminished antigen-specific T-cell responses, as measured by ELISpot, underscoring the role of prior immunosuppression in shaping ineffective tumor-specific immunity. Successful generation of autologous LCLs was predominantly achieved from pre-treatment PBMCs, highlighting the impact of B-cell–depleting therapies (Rituximab ± CHOP) on downstream immune profiling feasibility. The persistence of residual T cells in long-term LCL cultures suggests ongoing B-cell clearance and may reflect previously unrecognized immune dynamics in PTLD. Collectively, these data provide novel insights into the immune landscape of EBV-driven PTLD and support the rationale for therapeutic strategies aimed at reversing T-cell exhaustion—such as immune checkpoint blockade or adoptive T-cell therapies—to restore anti-EBV immunity in transplant recipients.

Abstract Background: Recent approvals and clinical trials have established covalent BTK inhibitors (BTKis), including ibrutinib, acalabrutinib, and zanubrutinib, as effective agents for the treatment of mantle cell lymphoma. Multiple BTKi-based regimens are recommended by experts and clinical guidelines in both the first-line and later-line settings. Additional approvals of the noncovalent BTKi pirtobrutinib and multiple CAR T-cell therapies have also advanced the management of patients who have progressed on covalent BTKi therapy. In light of these developments in treatment strategies for mantle cell lymphoma (MCL), this study compares trends in treatment choice among experts and healthcare professionals (HCPs) in an online treatment decision support tool. Methods: An online decision support tool, developed with 5 US-based experts in MCL, was launched in April 2023 and updated in April 2025. The tool provided treatment recommendations for various clinical scenarios involving newly diagnosed (ND) or relapsed/refractory (R/R) MCL, incorporating factors such as age, fitness, previous therapies, and response duration. HCPs entered specific patient characteristics along with their intended treatment choice. The tool then displayed expert recommendations for that scenario, and HCPs were asked whether these recommendations influenced their treatment decision. HCP-entered data and expert recommendations were analyzed to identify common trends and divergence in current BTKi therapy use. Results: The 2023 online tool was used by 119 HCPs who entered 148 patient scenarios, and the 2025 online tool was used by 69 HCPs who entered 96 patient scenarios. In 2023, for patients with ND MCL who had later-stage disease or were not eligible for radiation therapy (n = 75), 64% of expert-recommended treatments included BTKis, with the ECHO and TRIANGLE regimens representing 12% and 17% of recommendations, respectively. In 2025, 81% of expert recommendations were BTKi-based regimens, with ≥3 experts recommending a BTKi regimen in 66 of 67 unique ND case scenarios. The ECHO and TRIANGLE regimen each represented 28% to 29% of expert recommendations. In addition, 51% of recommendations for patients with 17p deletions or TP53 mutations consisted of the BOVen regimen. The percentage of HCPs who indicated that they were considering a BTKi-based regimen in the setting of ND MCL was 17% (13 of 75 ND cases) in 2023 and 66% (44 of 67 ND cases) in 2025. The use of both the ECHO and TRIANGLE regimens by HCPs increased from 5% and 4%, respectively, in 2023 to 19% for each in 2025. In 2025, 6% of HCPs considered the BOVen regimen for patients with TP53 mutation (n = 17). In 2023 and 2025, approximately 50% of the HCP-entered patient cases for previously treated MCL had not received a BTKi (n = 48 and n = 18, respectively). For these scenarios, 94% and 98% of expert recommendations consisted of covalent BTKis in 2023 and 2025, respectively. HCPs selected covalent BTKis for 68% of cases in 2023 and 89% of cases in 2025. For patients with R/R MCL previously treated with a BTKi, CAR T-cell therapy represented 36% of expert recommendations in 2023 (23 scenarios) and 60% in 2025 (18 scenarios). By contrast, 4% and 11% of HCPs considered CAR T-cell therapy for these patients in 2023 and 2025, respectively. For HCPs reporting on the tool's clinical impact (n = 96), 35% indicated expert recommendations changed their intended therapy, 41% stated their treatment plan matched the recommendations, 10% cited barriers to implementing recommendations, and 14% remained undecided on optimal treatment. Conclusions:This analysis highlights the ongoing adoption of expert-recommended treatments into real-world clinical practice. Our data suggest that expert and HCP use of BTKi therapy in the ND MCL setting has increased in recent years. In R/R MCL, CAR T-cell therapy appears to be considered infrequently by HCPs. Barriers to implementation of expert recommendations warrant further investigation. Enhanced decision support tools and targeted educational initiatives could help increase the use of expert treatment recommendations and potentially improve patient outcomes.

Abstract Introduction: Reporting patient outcomes by CAR-T treatment centers is part of the accreditation requirement under the FACT (Foundation for Accreditation of Cell Therapy) Immune Effector Cell (IEC) Program standard. Currently, this is a time-consuming and manual process, making it increasingly difficult to sustain with the growing CAR-T applications and patient volume. The objective of this study is to evaluate how a Large Language Model (LLM) can be used to automate the abstraction and summarization of medical record for CAR-T toxicities. Methods: Clinical data from patients treated with CAR-T between January 2018 and June 2025, including hematology clinical notes, lab results, flowsheets, vital signs, and medication administration record, were used as the source of patient information. The American Society of Transplant and Cell Therapy (ASTCT) CAR-T toxicity grading guideline for cytokine release syndrome (CRS) and immune effector cell associated neurologic syndrome (ICANS) were used to define these toxicities. With the large context window of the LLM (Gemini 2.5 pro), we created a prompt by embedding both the patient data and the ASTCT guidelines for CRS and ICANS, along with an outline of specific information we aimed to abstract from the data. Additionally, the LLM was instructed to provide contextual justification for the data it extracted from patient information. The LLM-generated output included event onset date, resolution date, maximum grade, date of maximum grade, and medications given for management. The CRS and ICANS outcome reports generated by the LLM were then compared to the IEC compliance program data. Any discrepancies identified were reviewed manually. Results: Among patients (pt) treated with CAR-T in the specified timeframe, 47 were selected as training cohort. This cohort included pt with toxicities events, no events, and a mix of events of varying grades. For the test cohort, 66 pts who received CAR-T from March to June 2025 were included. Demographics for the training and test cohorts are reflective of evolving clinical practice (training, test cohorts: median age 69, 65; male 55%, 74%; lymphoma/leukemia 66%, 48%; multiple myeloma 34%, 52%; CD19 CAR-T 46%, 50%). Compared to data from the IEC compliance program, the LLM-generated summaries for CRS events demonstrated an accuracy of 90%, precision 95%, sensitivity 100%, specificity 80%, F1 score 97%, and Matthew's correlation coefficient 87%. For ICANS event, the LLM achieved an accuracy of 91%, precision 92%, sensitivity 92%, specificity 90%, F1 score 92%, Matthew's correlation coefficient 83%. Maximum grade, for both CRS and ICANS, were identified with >90% accuracy. However, dates for CRS and ICANS were less accurate, with the lowest accuracy noted in identifying the event resolution date, 45% for CRS and 67% for ICANS. Medical records were reviewed for all discrepancies between the LLM and the IEC Compliance Program data. The most common discrepancy was a mismatch in event resolution date, determined to be due to differing criteria used by the compliance team and the LLM prompt. Of note, a few discrepancies were attributed to missed information by the IEC Compliance Team, which was correctly identified and categorised by the LLM. An updated LLM prompt (LLMv2) was developed and applied to the test cohort. In version 2, the prompt was revised to include clearer instructions on how to summarize CRS and ICANS events, as well as new instructions on additional data elements to be summarized. The performance of LLMv2 on this cohort for CRS event identification was 100% across all categories (accuracy, precision, sensitivity, specificity, F1 score, and Matthew's correlation coefficient). For ICANS the LLMv2 achieved accuracy of 96%, precision 69%, sensitivity 100%, specificity 93%, F1 score 82%, Matthew's correlation coefficient 80%. Accuracy in identifying event resolution date improved significantly from 64% to 99%. Conclusions: Our study demonstrates that LLMs can significantly reduce the time required to abstract and summarize CAR-T toxicities, while maintaining high accuracy. One limitation of our study is that it is based on data from a single institution. However, plans are already underway to evaluate the use of LLMs in a multi-institutional setting.

Abstract Introduction: Outcomes for FL have markedly improved, and the 10-year (yr) overall survival (OS) for patients (pts) diagnosed in the rituximab era is about 80%. Historically, FL is the leading cause of death in the first decade after diagnosis (dx); however, modern outcomes beyond 10 yrs after dx remain unknown. Here we report long-term outcomes of FL from a large prospective cohort of pts with FL from the rituximab era. Methods: Pts with biopsy-proven FL 1-3A at dx were prospectively enrolled within 9 months of dx from 2002-2015 in the MER. Outcomes of interest were OS, event-free survival (EFS), histologic transformation (HT), and cause of death. HT was defined as subsequent biopsy-proven FL 3B, diffuse large B cell lymphoma, or high-grade B cell lymphoma. Analyses were performed using Cox models and KM curves; cause of death was evaluated using a competing risk approach. A subset analysis was performed in younger (18-59 yrs) vs older (60+ yrs) pts. A landmark analysis was conducted in pts alive at 10 yrs. Results: 1,155 pts with FL 1-3A were enrolled in the MER from 2002-2015. Median age at dx was 60 yrs (IQR 51-69). Clinical characteristics were: 67% stage III/IV, 12% grade 3A, 4% ECOG PS 2-4, and 19% elevated LDH. Initial management was 35% observation (obs), 12% R-monotherapy (R-mono), 39% immunochemotherapy (IC; 43% R-CHOP, 28% R-CVP, 27% BR), and 14% other. FLIPI scores were 40% low, 33% intermediate (int), and 27% high; FLIPI24 risk categories were 49% low, 25% int, and 26% high. At a median follow-up of 14 yrs (IQR 11-18 yrs), 751 events, 148 HTs, and 402 deaths were observed. EFS estimates (95% CI) were: 10-yr: 40% (37-43), 15-yr: 31% (28-35), and 18-yr: 27% (24-31). 15 yr & 18 yr EFS by initial txs were 22% (18-27) & 18% (14-25) for obs, 30% (23-40) & 18% (11-30) for R-mono, and 40% (35-46) & 38% (33-45) for IC. The incidence (95% CI) of HT was 12% (10-14) at 10 yrs, 13% (11-16) at 15 yrs, and 14% (12-17) at 18 yrs. OS (95% CI) for the entire cohort was 77% (75-80%) at 10 yrs, 63% (60-66) at 15 yrs, and 55% (51-59) at 18 yrs. The incidence of non-lymphoma-related death (non-LRD) surpassed lymphoma-related death (LRD) after 12 yrs in pts with known cause of death. Estimates (95% CI) for LRD were 11% (10-13) at 10 yrs, 14% (12-17) at 15 yrs, and 16% (14-19) at 18 yrs, while estimates for non-LRD were at 8% (7-10) at 10 yrs, 17% (15-20) at 15 yrs, and 22% (19-26) at 18 yrs. Among pts diagnosed before age 60, LRD remained the predominant cause of mortality into the second decade following dx, with incidences (95% CI) of LRD vs. non-LRD of 7% (5-9) vs 3% (2-4) at 10 yrs, 10% (8-13) vs 5% (3-8) at 15 yrs, and 13% (9-17) vs 6% (4-10) at 18 yrs, respectively. In patients age >60 non-LRD was the predominant cause of mortality in the second decade. Incidence of LRD vs. non-LRD in those aged ≥60 at dx were 15% (13-19) vs 13% (10-16) at 10 yrs, 18% (15-22) vs 28% (24-32) at 15 yrs, and 20% (16-24) vs 35% (31-41) at 18 yrs, respectively. In the landmark analysis of pts alive at 10 yrs from dx (n=720), median age was 69 yrs (IQR 60-77). 63 pts (9%) had HT prior to landmark. The median number of prior treatments was 1 (IQR 1-2, range 1-8). Risk of death (95% CI) was 19% (15-22) in the next 5 yrs (i.e. 15 yrs from dx) and 29% (24-33) in the next 8 yrs (18 yrs from dx). The risk of LRD vs non-LRD was 4% (3-6) vs 12% (9-15) at 5 yrs and 7% (3-9) vs 18% (10-23) at 8 yrs.Conclusions: Long-term outcomes for pts with FL remain excellent into the second decade from dx. HT risk decreases significantly after 10 yrs, though late HTs still occur. At 15 yrs from dx, 40% of pts remained alive and event-free after 1L IC. Nearly a quarter of pts observed at dx remained treatment-free. The most common cause of death after 10 yrs from dx was from non-lymphoma causes, notably in older pts aging into their 70s and 80s. While younger pts have a lower overall risk of LRD compared to older pts, FL represents the leading cause of death in this population during the second decade following dx. These results provide critical insights into the natural history of FL diagnosed in the modern era.

Abstract Background: Waldenström Macroglobulinemia (WM) is an indolent B-cell lymphoplasmacytic lymphoma characterized by heterogeneous clinical behavior and variable progression patterns. While MYD88L265Pand CXCR4 mutations are frequently encountered, the broader genomic landscape underpinning disease evolution from smoldering WM (SWM) to active treatment naïve WM (TNWM), post-treatment remission WM (PTWM) and relapsed/refractory WM (RRWM) remains incompletely understood. To address this gap, we studied the mutational profile across the WM disease spectrum. Methods We performed whole exome sequencing (WES) on sorted (CD19 and/or CD138) bone marrow aspirates of patients across the spectrum of WM. Paired germline sequencing was performed using peripheral blood mononuclear cells (PBMCs). Unique molecular identifier-tagged reads were deduplicated using fgbio. WES data were processed through the Sarek pipeline. Any valid mutation from either caller, present on the index or in COSMIC was considered. Copy number variations (CNVs) were inferred via CNVkit and summarized at the gene and arm level (≥50% directional change). Mean tumor and germline coverages were 174X and 74X, respectively. Fisher's exact test was used for enrichment and hypergeometric test for overlap analyses. Results A total of 78 high-quality WM samples [15 SWM, 44 TNWM, 13 RRWM, 6 PTWM in remission (all with paired TNWM samples)] were sequenced. The mutational burden varied across disease states (median SWM=1.48 m/Mb, TNWM= 1.12 m/Mb, RRWM = 1.59 m/Mb; p=0.04). Density plots revealed bimodal VAF distributions, consistent with clonal and subclonal architectures in WM. Overall, 77% harbored a MYD88L265P mutation by WES. Among MYD88^WT^ patients, AS-PCR identified MYD88L265P in 4 (25%) not detected by WES, raising the overall mutation rate to 83%, plus one with a non-L265P variant. Low VAF (<10%) MYD88L265P mutations were seen in 6% of matched PBMCs. MYD88 copy number gain was seen in 2 (17%) MYD88WT TNWM patients. CXCR4 mutations were detected in 38% by WES (18% each frameshift and nonsense). Two (4%) CXCR4WT samples were positive by PCR, giving an overall rate of 40%. CXCR4 mutations were more frequent in RRWM (54%) vs TNWM (41%) and SWM (27%), though not statistically significant. Del(6q) and Del(17p) were noted in 16% (n=12) and 7% (n=5) of patient samples. All del(17p) events were noted in TNWM samples and in one paired post-treatment sample. Overall rate of del(17p) and TP53 mutation was 14% (n=11). RRWM was enriched in ARID1A alterations, a gene implicated in chromatin remodeling and plasma cell identity formation [38% (n=5) in RRWM vs. 11% (n=6) in TNWM and SWM], compared to TNWM and SWM p=0.03]. Alterations in NF-kB signaling gene MAP3K14 were more frequent in RRWM (31%, n=4) compared to the SWM/TNWM cohort [(7%), n=4; p=0.036). We noted an enrichment in the TP53 mutation rate in RRMW [n=3, 23%, OR 7.7] compared to TNWM and SWM cohorts [n=2, 4%), p=0.04]. Mutations in FUBP1 (p=0.03), an upstream regulator of MYC, and CARD11 (p=.043), a B-cell signaling scaffold protein were also more frequent in RRWM. Notably, none of the SWM patients harbored an ARID1A alteration (p=0.057), suggesting acquisition during progression. CNV analysis revealed that MAP3K14 amplifications were frequent in RRWM (n=3, 23%) compared to SWM/TNWM [n=2 (4%), p=0.043]. RRWM samples showed increased CD79B mutations (15%) and significant overlap with the C5/ABC diffuse large B-cell lymphoma (DLBCL) genomic cluster (Chapuy et al., Nat. Med. 2018; p=0.007). This overlap remained significant after excluding MYD88L265P (p=0.019), driven by CARD11, CD79B, and IGLL5, suggesting that a subset of RRWM may acquire an ABC DLBCL-like mutational profile. These findings warrant further investigation using transcriptional profiling. Conclusions This study provides a genomic map of WM evolution from precursor to relapse. Increasing somatic mutations and CNVs support stepwise progression. Enrichment of genes involved in chromatin remodeling and plasma cell identity formation (ARID1A), NF-kB or BCR signaling (CARD11, MAP3K14), and DNA damage repair (TP53) were noted at relapse, all of which have been shown to drive aggressive disease biology. Emergence of an ABC-like genotype in a proportion of RRWM indicates convergent evolution with aggressive lymphomas. Transcriptional studies are warranted to explore this further.

Abstract INTRODUCTION The ECHELON-2 trial for newly diagnosed CD30+ peripheral T-cell lymphomas (PTCL) demonstrated superior overall survival with brentuximab vedotin plus chemotherapy (BV-CHP) compared to CHOP. However, total enrollment was restricted to only 30% of patients with non-anaplastic large cell lymphoma (ALCL) histologies and was not powered to analyze survival benefits in this cohort. Thus, the benefit of BV-CHP in non-ALCL patients remains less clear. Adding to this uncertainty, CHOP plus etoposide (CHOEP) remains a standard regimen for many non-ALCL PTCL histologies for patients <60 years of age. Which of these three regimens offers superior outcomes for patients with CD30+ non-ALCL PTCL remains to be determined, is a critical knowledge gap in this area, and could meaningfully inform the management of these patients. METHODS We conducted a retrospective analysis of chemotherapy-naïve CD30+ (≥1%) PTCL from 7 centers in the United States. Histologies were limited to PTCL-NOS and PTCL with a T follicular helper phenotype (PTCL-TFH). Frontline regimens were defined as BV-based (BV-CHP), etoposide-based (CHOEP/EPOCH), novel-CHOP (CHOP/CHOEP + novel drug on a clinical trial), or CHOP. CD30 was considered positive if any expression was reported, and when available, stratified as ≥10% or <10% of the total lymphocyte population. RESULTS The CD30+ PTCL cohort consisted of 194 patients with a median age of 68 years at diagnosis and a male (65%) predominance. Nodal PTCL-TFH (65%) was the most common histology. Most had stage III-IV disease (89%) with a high-intermediate to high-risk IPI score of 3-5 (54%). 18% had an ECOG of ≥2, 45% had ≥2 extranodal sites, and 43% had bone marrow involvement, although biopsies were not performed in all patients. CD30 expression in ≥10% of malignant T cells was observed in 55% of all quantitatively reported cases. Frontline therapy consisted of BV-based (36%), etoposide-based (30%), CHOP (27%), and novel-CHOP (7%). Baseline characteristics and CD30 expression were similar between treatment groups. The ORR was 72% (64% CR, 8% PR), with no differences observed by treatment or histology. On multivariate analysis (MVA), a high LDH was associated with lower CR (OR 2.84, p=0.003). For the patients who demonstrated a CR to frontline therapy, 61% underwent ASCT. With a median follow-up of 26.1 months (IQR 12.3-51.6), the median PFS and OS were 11.4 (9.8-14.2) and 47 (32-60.3) months, respectively. The 2-year PFS and OS were 34.9% (28.1-41.7) and 62% (54.5-68.6), respectively. PFS and OS were similar for PTCL-NOS compared to PTCL-TFH, and AITL fared similarly to non-AITL PTCL-TFH. By treatment, novel-CHOP demonstrated the most favorable PFS (median 41.9 months) and OS (median 68.1 months). Survival curves overlapped continuously with all other treatment regimens and was not statistically significant. For patients <60, PFS and OS were equivocal with BV-based (n=17) compared to etoposide-based (n=26) regimens. On MVA, stage III/IV disease conferred an inferior PFS (HR 2.00, p=0.018) as did an IPI score of 3-5 for OS (HR 2.15, p=0.001). Neither histology nor frontline treatment impacted PFS or OS. The chosen frontline treatment also had no survival impact in key subgroup analyses including patients <60 (n=56) or with CD30-expression ≥10% (n=43). For patients with CR to frontline therapy, ASCT demonstrated a significant PFS benefit (HR 0.59, p=0.028) but no statistically significant difference in OS benefit (HR 0.58, p=0.073). CONCLUSION These data provide valuable insight into the lesser-represented patient population from the pivotal ECHELON-2 trial. In this cohort of CD30+ (≥1%) non-ALCL PTCL, there was no clearly superior standard frontline regimen. The number of patients with quantitively reported CD30 expression was too small for definitive conclusions in the ≥10% CD30+ cohort and retrospective pathology review is ongoing. ASCT for patients in CR offered superior outcomes, supporting this strategy regardless of the frontline regimen, recognizing the limitations of non-randomized, retrospective analyses. Novel-CHOP regimens demonstrated encouraging survival, and clinical trials should maintain priority over standard regimens for patients with CD30+ (1-10%) PTCL-NOS and PTCL-TFH.

Abstract Background Watchful waiting is a common option for pts with asymptomatic FL/MZL. Anti-tumor immunization may delay or even avoid subsequent need for more toxic therapies. EO is designed from non-self-protein sequences derived from gut bacteria, including 4 HLA-A2 CD8 T cell epitopes (synthetic mimic peptides), exhibiting molecular mimicry with specific epitopes on B cell markers (CD20, CD22, CD37, BAFF-receptor). EO also contains a CD4 helper epitope UCP2. EO expands pre-existing memory CD8 T cells recognizing non-self-epitopes from gut bacteria that cross-react with B cell antigens on tumor cells. Methods Cohort 2 (C2; planned accrual 25 pts) of EONHL1-20/SIDNEY includes HLA-A2+ pts with previously untreated FL/MZL not in need of treatment. Pts receive EO (300μg/peptide) SC with adjuvant Montanide, q2 weeks (w) x 4, then q4w, for 12 total doses. For antigen-specific immune responses, peripheral blood mononuclear cells were assayed by flow cytometry using EO-mimic or B cell peptide specific tetramers without in vitro stimulation. IFN-γ ELISPOT was used to evaluate response to UCP2 and anti-CD3. Primary endpoint is objective response rate (ORR) per Lugano 2014. A pre-defined futility boundary was applied (ORR uninteresting=5%/promising=20%). Finding at least 3 of 25 pts with ORR would meet criteria to continue development (chance of 13% and 90% for true ORR of 5% and 20%, respectively). Results As of July 2025, 22 pts had started EO. Median age 59 years (range 32-86); 9 female; 19 ECOG 0/3 ECOG 1; 19 FL/3 extranodal MZL (ENMZL); 3 Ann Arbor stage I-II/8 stage III/11 stage IV; FLIPI low risk 8/intermediate 8/high 6; FLIPI-2 low risk 12/intermediate 7/high 3; 19 GELF neg/3 pos. At a median follow-up for progression of 9.4 months, 9 pts completed EO, 4 stopped for progressive disease (PD), 2 due to PI/pt decision; 7 ongoing. Median treatment duration 38 w (range 4-39). Among 19 evaluable pts, best Lugano response was 3 complete (CR) and 6 partial responses (PR) (ORR 47% [95% CI 24%–71%]; CR-rate 16% [3%-40%]), 6 stable disease (SD), and 4 PD. ORR by PET-CT was 29% (n=14) w6, 39% (n=18) w19, 46% (n=13) w42; corresponding CR rates were 0%, 11%, 15%. Median time to response 17.1 w (range 5.3-41.1). Currently there are only 2 confirmed PD events in pts with prior PR/CR. Among 8 pts with an initial indeterminate response per LyRIC 2016 followed by a confirmatory scan, 4 pts did not have confirmed PD; a possible atypical response pattern rate of 50% on EO (occurring 5.3-41.9 w after start of EO). In 16 immune response evaluable pts, 88% and 81% had expansion of CD8 T cells specific for EO mimic and B cell target peptides, respectively. Expanded specific CD8 T cells had a memory phenotype dominated by effector memory (TEM) and central memory cells. At w5, 7 clinical responders and 7 non-responders were evaluable; more responders had a positive immune response against EO mimic (Chi-square p=0.025) and B cell target (p=0.047) peptides. Max expansion (response sum for 4 EO mimic or 4 B cell target peptides at a single timepoint w3-w8) of specific CD8 T cells (% of all peripheral CD8 T cells) was higher for responders than non-responders both for EO mimic (Mann Whitney p=0.018) and B cell target (p=0.017) peptides. Pts (4) with an initial indeterminate response (LyRIC 2016) had a higher max expansion of B cell target peptide specific CD8 T cells vs 4 pts with a typical progression pattern (Mann Whitney p=0.018) and vs all other 12 pts evaluable for immune response (p=0.029). There was no difference in CD4 T cell response to UCP2 in responders vs non-responders (induction or max immunity w3-w8). Anti-CD3 expansion of T cells indicating T cell intrinsic activation potential did not correlate with clinical response (baseline or max). The most common EO-related adverse events (AEs) were Gr (Grade) 1 (10 pts) and Gr 2 (6 pts) local administration site reactions. Other related AEs in >1 pt were Gr 1 headache (3 pts) and Gr 1-2 fatigue (3 pts). Asthenia lasting 2 days was the only related Gr 3 AE. There were 4 unrelated Gr 3 AEs (gastroenteritis, GI-hemorrhage, inguinal hernia, and syncope). There were no Gr 4-5 AE. ConclusionsEO has a favorable safety profile and is preliminary associated with an ORR of 47%, exceeding the pre-specified boundary for promising activity. The speed and level of expansion of both EO mimic and B cell target peptide specific CD8 memory T cells are associated with objective response. Results will be updated.

Abstract Despite a characteristic indolent course, a substantial subset of follicular lymphoma (FL) patients has an early relapse with a poor outcome. Thus far, efforts to identify factors that predict survival have been unsuccessful. However, we and others have demonstrated the prognostic relevance of CD4+ T cells in the tumor microenvironment (TME) of FL and developed a bio-clinical risk model (called BioFLIPI) that offers improved risk stratification (Mondello et al, BCJ 2021). However, the mechanisms defining different BioFLIPI scores remain to be fully understood. To identify the programs associated with the BioFLIPI scores, we first interrogated the RNA-seq of purified B cells from 67 newly diagnosed FL1-3A (BioFLIPI 1 n=21; BioFLIPI 2-3 n=36; BioFLIPI 4 n=10). We found 1,156 upregulated genes and downregulation of 930 genes in BioFLIPI 4 vs 1, including well-known immune molecules such as CD70, IL10RA, CD69, and CCR6 (FDR<0.05). Gene set enrichment analysis (GSEA) using the MSigDB confirmed a negative enrichment in multiple immune response and interferon gamma signatures and revealed striking positive enrichment for cell proliferation and antigen presentation pathways in BioFLIPI 4 compared to BioFLIPI 1 tumors. The same pathways were dysregulated in BioFLIPI 2-3 but a lower magnitude. To investigate the somatic mutations associated with different BioFLIPI scores, we performed WES of the same 67 FLs and further expanded this cohort for a total of 90 patients (BioFLIPI 1 n=26; BioFLIPI 2-3 n=51; BioFLIPI 4 n=13). We found enrichment for mutations in several regulators of the germinal center in BioFLIPI 4 and 2-3, such as MEF2B (p=0.029), FOXO1 (p=0.038) and IRF8 (p=0.035), suggesting the cooperation of multiple oncogenic events promoting lymphomagenesis. In contrast, BioFLIPI 1 tumors harbored a higher rate of mutations in TNFRSF14 gene, known to enhance anti-lymphoma immune response. To investigate whether BioFLIPI modulates immune signatures of the microenvironment, we performed TME deconvolution by applying CIBERSORTx to bulk RNA-seq of these 67 FLs. We found that FLs with BioFLIPI 4 and 2-3 were enriched for CD4+ Tcm exh (p=0.02), Tem exh (p=0.04), Tfhexh (p=0.07) and NK cells (p=0.01) compared to BioFLIPI 1. In line with this data, CyTOF performed on a subset of these patients (BioFLIPI 1 n=12; BioFLIPI 2-3 n=25; BioFLIPI 4 n=6) confirmed progressive increase of CD4+ Tcm exh (p=0.006), Tem exh (p=0.009) and Tfh exh (p=0.025) cells from BioFLIPI 1 to BioFLIPI 4. Single cell RNA/BCR-seq of 21 FLs (BioFLIPI 1 n=6; BioFLIPI 2-3 n=12; BioFLIPI 4 n=3) corroborated a higher abundance of Tem exh, cytotoxic (CTL) Tem exh, Tfhexh and NK cells in BioFLIPI 4 and 2-3. Conversely, CD8+ naïve T cells were prevalent in BioFLIPI 1 tumors. Differential gene expression in T cell clusters from BioFLIPI 4 vs BioFLIPI 1 FL revealed a marked upregulation of multiple immune genes involved in antigen presentation (e.g., HLA-DRB, HLA-DQA, HLA-DPA/B) and immune response (e.g., ETS1, TNFSF8, IL7R). GSEA showed a positive enrichment for antigen presentation signatures and negative enrichment for TNFα signaling and Oxphos metabolism. Similar findings were observed in BioFLIPI 2-3 FLs. Using CellChat analysis, we found a stronger interaction between malignant B cells and Tem exh and CTL Tem exh cells in BioFLIPI 4 and 2-3 vs BioFLIPI 1 tumors. This was linked to an increased strenght of MHCI-CD8 interaction and concordant decrease of MHCII-CD4. Notably, the suppressive BTLA-TNFRSF14 signaling axis was present in BioFLIPI 4 and 2-3 but not in BioFLIPI 1 FLs. This was accompanied by a decreased signaling through TNF/LTA-TNFRSF1B, CD80/CD86-CD28/CTLA4. Linking the BioFLIPI-specific immunogenicity to lymphomagenesis, we found that FL patients with BioFLIPI 4 had two-three folds higher risk of transformation to an aggressive lymphoma (12% vs 7%) or death (21% vs 3%) than those with BioFLIPI 1, suggesting that this immune dysfunction favors the expansion of a dominant tumor clone and promotes a more aggressive form of FL. Collectively, our findings demonstrate that BioFLIPI scores in FL reflect distinct patterns of tumor immunogenicity that shape the TME. Notably, high BioFLIPI scores are paradoxically associated with enhanced antigen presentation alongside a suppressed immune response. This suggests a sustained antigen-specific T cell response that may drive immune exhaustion, promote tumor progression, and ultimately lead to histologic transformation

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.