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Abstract Introduction: Graft Failure (GF) is a rare but devastating outcome of HCT. Primary GF (PGF), defined as a failure of neutrophil recovery by Day+28, is straightforward to diagnose. Diagnosing secondary GF (SGF) is more challenging, with its broad time-range, multiple confounding diagnoses, and lack of predictive biomarkers. In BMT CTN1703/1801, we analyzed patients receiving RIC HCT for heme malignancies with either Tac/MTX (n=159) or PT-Cy (n=165) GVHD prophylaxis. SGF was defined as donor chimerism <5% after initial donor engraftment. With Tac/MTX, there were 3 PGF and 1 SGF diagnoses. With PT-Cy, there were 4 PGF and 6 SGF. Median SGF diagnosis was Day +64 (range: Day+28-215). There were too few Tac/MTX patients to analyze SGF, but sufficient events with PT-Cy. To identify PT-Cy SGF predictors, we leveraged lymphocyte, T, B, and NK cell reconstitution analysis. In SGF we found an early, profound deficit in the reconstitution of all major lymphocyte populations, including total lymphocytes, T, B, and NK cells, as early as Day+28. This enabled the modeling of a SGF risk classifier based on the Absolute Lymphocyte Count (ALC). Methods: Clinical ALC measurements were performed on all SGF patients (n=6) and on non-GF controls with ALCs available (146 of 155 non-GF patients). Flow cytometry was performed on all PT-Cy SGF patients (n = 6) and from a subset of non-GF controls (n = 18: controls were chosen as patients without relapse or severe GVHD, to reduce confounders introduced by immunologic interventions, and for whom all samples, including from the graft infusion, were available). T, B, and NK counts, as well as T cell subsets, were compared (using Welch's T test) on Days 7, 14, 21, 28, 42, 63, 98, 180, 270, 365, 730, with SGF patients censored on the day of GF diagnosis. To interrogate the optimal ALC cutoff, the cumulative incidence of SGF was computed at Days +28 and +42, with death without GF as a competing risk. Results: We have previously demonstrated that, compared to Tac/MTX, PT-Cy patients exhibited an early decrease in reconstitution of all T cell populations (with normal NK and B cell reconstitution). Here we focused specifically on PT-Cy patients with or without SGF. Graft CD34 counts/kg were not different between SGF patients and non-GF patients (mean CD34/kg = 1.38 x10e6 (SGF) vs 0.67 x10e6 (non-GF, p = 0.61) However, even amidst the overarching early suppression in T cell reconstitution with PT-Cy, SGF patients could be easily distinguished from the larger PT-Cy cohort, based on more profound deficits in ALC, T, B and NK cells reconstitution, measured using 2 strategies: (1) SGF patients demonstrated significant early (Day +28) quantitative defects in the reconstitution of the ALC (mean +/- SEM 262+/-32 cells/µL (non-GF) vs 60 +/- 25 (SGF, p<0.0001), CD4 T cells (62 +/- 12 cells/µL vs 19+/-15, p=0.048), CD8 T cells (15 +/-3 cells/µL vs 3.5 +/-1 p=0.0009), all CD8 T cell subpopulations, as well as NK cells (116+/-31 cells/µL vs 2.9+/-1.4 cells/µL, p= 0.002) and B cells (3.5 +/-1.4 cells/µL vs 0.16+/-0.07 p =0.03). (2) In SGF, there was a significant deficit in the rate of rise of all major lymphocyte populations between Days 28-42-60 vs non-GF, including CD4 T cells (p<0.0001), CD8 T cells (p = 0.0002), B cells (p<0.0001), and NK cells (p =0.048). These discoveries suggested that a classifier could be identified to risk-stratify patients for SGF. We explored an ALC cutpoint, amenable to standard clinical lab analysis. A statistically significant threshold was identified at both Days+28 and +42, with Day+42 being most predictive: A threshold of 120 cells/µL was identified as optimal, with landmark analysis documenting a SGF rate of 34.7% below the cutpoint, and SGF of 1% above it (HR = 45.9, 95% CI 5.7 - 366). Conclusions: Despite the small number of events, PT-Cy patients with SGF demonstrated a distinctive reconstitution trajectory that encompassed an early, substantial, and sustained deficit in all lymphocyte counts, as well as a lack of their longitudinal expansion. This enabled the discovery of a candidate ALC biomarker cutpoint at Day+42 that could distinguish patients who were more likely to develop SGF. If confirmed, these data could generate a predictive biomarker for SGF, which would enable the design of trials evaluating early interventions (e.g. CD34+ boosts, DLI, modification of immunosuppression) to improve outcomes for these patients.

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

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

Abstract Cyclin D1, encoded by CCND1, is a cell cycle regulator, overexpressed in ~15% of multiple myeloma (MM) cases via CCND1::IGH super-enhancer juxtaposition through t(11;14). Cyclin D1 also plays a non-canonical role in transcriptional regulation, but in t(11;14) MM its function in gene regulation remains undefined. We investigated the global transcriptional and epigenomic consequences of CCND1overexpression in t(11;14) MM. To define a CCND1 signature, RNA-seq from two independent primary MM patient cohorts, CoMMpass and Mayo, was utilized to compare high CCND1 t(11;14) cases (≥300 transcripts-per-million [TPM], n=271) vs. low CCND1 hyperdiploid cases (<30 TPM, n=233). Two CCND1 knockout (KO) clones in t(11;14) MM U266B1 were also generated by CRISPR/Cas9, introducing a frameshift insertion (A) after chr11:69641478 (hg38) in exon 1. ATAC-seq and ChIP-seq (H3K4me3, H3K4me1, and H3K27ac) were performed in duplicates, and RNA-seq in triplicates in U266B1 wild-type (WT) and KO. Libraries were sequenced on Illumina NextSeq 2000 (2x51 bp for ChIP/ATAC, 2x150 bp for RNA-seq). Reads were mapped to hg38 by BWA (ChIP/ATAC) or STAR (RNA-seq), peaks called by MACS2 (FDR< 0.01), peak and gene raw counts estimated by featureCounts. Differential peaks (fold-change ≥1.5) and differentially expressed genes (fold-change ≥2) were identified by edgeR (FDR<0.05), including peaks detected in ≥2 samples and genes with TPM ≥0.1 in ≥1 sample. Interactions between promoters and distal regulatory regions were identified using publicly available chromatin interaction data in blood cell types. Pathway analysis was performed using Enrichr. Co-immunoprecipitation was performed in t(11;14) KMS12BM cells. Differential analysis comparing CCND1-high t(11;14) and CCND1-low MM cases in the two patient cohorts identified 21 upregulated and 21 downregulated genes associated with CCND1 expression which were also captured in the wild-typevs. CCND1 KO U266 cells. Enriched pathways (p<0.05) included Notch signaling, early/late estrogen response, epithelial-mesenchymal transition and reduced mitotic spindle and myogenesis. Dysregulated genes included those related to apoptosis, ubiquitin-proteosome, extracellular matrix, adhesion, and immune response, demonstrating a broader role for cyclin D1 in MM beyond cell cycle control. To explore the epigenomic basis of this transcriptional regulation, for each of the 42 differentially expressed genes we examined the changes of histone marks and chromatin accessibility in promoter and the interacting distal regulatory regions in the U266 KO model. Ten of the 21 genes upregulated in CCND1-high (downloaded in KO; e.g., argininosuccinate synthase 1 [ASS1], PMAIP1, MYEOV, CCR7, and DTX1) and 12 of the 21 genes downregulated in CCND1-high (upregulated in KO; e.g., UACA, RASAL2, PTPRZ1, PPT2, and IL23R) showed concordant changes in histone marks and/or chromatin accessibility, predominantly in distal regulatory regions, suggesting a chromatin-mediated mechanism of gene regulation by cyclin D1. The most prominent changes involved H3K27ac, a mark defining active enhancers. As H3K27ac is deposited by histone acetyltransferases CBP, we tested for the possible cyclin D1-CBP interaction. Co-IP confirmed this interaction, suggesting a role for this complex in chromatin remodeling and transcriptional control in t(11;14) MM. One gene notably upregulated in association with CCND1 is ASS1, which encodes a urea cycle enzyme responsible for endogenous arginine synthesis. Metabolomic studies demonstrated KO cells had elevated aspartate and citrulline and lowered arginine and ornithine compared to WT cells (p<0.01) demonstrating impaired urea cycle function. Further, KO cells displayed significantly reduced ASS1 protein expression, cell growth and S-phase entry compared to WT cells in arginine-replete conditions, with both WT and KO cell types further inhibited by arginine depletion (p<0.05). Together, a cyclin D1-associated gene signature was identified supporting its role in t(11;14) MM beyond the CDK4/6 mediated cell cycle control, including a role in metabolic plasticity and survival under arginine depleted conditions. These findings highlight cyclin D1 as a therapeutic vulnerability and open new avenues for personalized treatment strategies.

Abstract Multiple myeloma (MM) is the second-most common hematological malignancy in the United States. Myeloma tumors have significant genetic heterogeneity that impacts disease progression and promotes resistance to treatment. RAS is a key oncogenic driver that activates the mitogen-activated protein kinase (MAPK) and the phosphatidylinositol 3-kinase (PI3K)/AKT pathways..Mutations in genes that code for RAS isozymes, KRAS, HRAS, or NRAS, lead to increased levels of activated GTP-RAS and are associated with the most aggressive forms of cancer. Mutations in the RAS family of genes are most common (40-50%) in myeloma. We and others have reported that RAS mutations may not be disease-initiating but rather arise during disease progression and relapse or as subclonal events that impart selective growth advantage and emerging drug resistance. In addition, non-mutant RAS can also be hyperactivated from upstream signaling (like receptor tyrosine kinases) or loss-of-function mutations in GTPase-activating proteins (GAPs). Given the importance of RAS mutations, allele-specific RAS inhibitors have long been considered an attractive strategy for myeloma treatment. However, multiple studies have reported various mechanisms of resistance to allele-specific RAS inhibitors as well as isoform-specific pan-RAS inhibitors, including newly acquired activating RAS mutations, RAS amplification, unchecked activation of co-expressed wild-type RAS (WT-RAS) isozymes, or acquired bypass mechanisms like new oncogenic fusions. Since MM remains incurable, we sought to improve upon currently available treatments by developing small-molecule inhibitors that preferentially inhibit myeloma cells with activated RAS isozymes. We have created NRasQ61X and KRasG12X mutations by CRISPR-Cas directed edits in a single endogenous RAS allele in human myeloma cell lines (HMCLs) that initially had two wild-type alleles. We found that these mutant-NRAS and mutant-KRAS edited cells have increased proliferation compared to cells with WT-RAS, as well as acquired resistance to several commonly used therapeutics. In this study, we used a triangulation method that combines our drug combination candidate prediction algorithm called ‘secDrug’ and the ‘Direct to Drug’ screening platform that evaluated 84 FDA-approved oncology drugs and emerging therapeutics in these RAS mutant myeloma lines. We identified BIRC5 as a potential target for RAS-mutant myeloma. BIRC5 expression is a key mechanism for the evasion of apoptosis. Notably, oncogenic RAS has been shown to promote MYC stabilization via upregulation of BIRC5. Earlier studies suggested that BIRC5 inhibitors are potent in targeting drug-resistant subclones in hematological malignancies. We performed in vitro cytotoxicity studies and cell-based assays using an in-house panel of HMCLs (n>50) representing WT- and mutant-RAS, as well as innate and acquired response/resistance to the standard of care drugs, proteasome inhibitors (PIs) and immunomodulatory drugs (IMiDs), to confirm the potency of novel selective BIRC5 inhibitors, as single agent (IC50 range 0.22-15.30 nM; Mean 4.431±1.041 nM) and in combination with PIs and IMiDs (Chou-Talalay's Combination Index or CI <0.3, indicating strong synergism). Further, we used bulk and single-cell whole-transcriptomics, siRNA-mediated gene knockdown studies, and functional validation to characterize the treatment-induced genes and molecular pathways underpinning the mechanism of action and drug synergy at the subclone level. Finally, we compared the efficacy of these BIRC5 inhibitors against several RAS inhibitors, including cyclorasin B4-27, a bicyclic peptidyl pan-RAS inhibitor, RMC-6236, a multi-selective noncovalent RAS(on) inhibitor, and ADT-007, a novel, highly potent, and selective pan-RAS inhibitor that we have synthesized, and observed comparable effects on cell death and apoptosis. Ex vivo analysis in bone marrow-derived CD138+ cells from myeloma patients using high-throughput Mass Cytometry (CyTOF or Cytometry by Time-Of-Flight) confirmed the dose-dependent reduction of MCL1, Ki-67, CCND1, c-KIT, and MYC. We will present these results that demonstrate the clinical potential of BIRC5 inhibitors as novel candidates in curbing progression and drug resistance in RAS-mutant myeloma.

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 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: 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: Systemic mastocytosis (SM) comprises a spectrum of subtypes characterized by neoplastic mast cell (MC) infiltration of tissues and release of MC mediators. Non-advanced SM (NonAdvSM), including indolent SM (ISM), smoldering SM (SSM), and bone marrow mastocytosis (BMM) subtypes, is the most prevalent form of SM. NonAdvSM can be associated with debilitating symptomology which can significantly impair quality of life. The gain-of-function somatic KIT c.2447 C>T (p.D816V) mutation is found in up to 95% of patients with SM. Bezuclastinib (CGT9486) is an oral, potent, and selective type 1 tyrosine kinase inhibitor with activity against KIT D816V. Results from Summit (NCT05186753) Part 1 informed the recommended phase 2 dose (100 mg QD bezuclastinib) for Part 2. We report topline results from the 24-week assessment of Summit Part 2. Methods: Summit is a multi-center, randomized, double-blind, placebo (PBO)-controlled Phase 2 trial of bezuclastinib in patients with NonAdvSM who had inadequate symptom control despite best supportive care (BSC) medications. The primary endpoint was 24-week mean change from baseline in Mastocytosis Symptom Severity Daily Diary (MS2D2) total symptom score (TSS) (range 0–110), which is a fit-for-purpose patient-reported outcome measure of NonAdvSM symptom severity. Key secondary endpoints included the proportion of patients with ≥50% reduction in serum tryptase, KIT p.D816V variant allele frequency (VAF), bone marrow (BM) MC burden, and MS2D2 TSS, ≥30% TSS reduction. Patients were randomized 2:1 to receive 100mg QD bezuclastinib + BSC or PBO + BSC. Results: As of May 22, 2025, 179 patients were enrolled in Part 2: 119 were randomized to receive bezuclastinib and 60 to placebo. Patients enrolled were representative of the NonAdvSM population with moderate to severe symptoms. Median age (range) was 51 (23-78) years; 65.9% female; mean (SD) baseline MS2D2 TSS 55.6 (19.8); 82% of patients had ISM, 11% had BMM, and 7% had smoldering SSM. At baseline, median (range) KIT p.D816V VAF in whole blood, BM MC burden, and serum tryptase was 0.25% (0-34%), 10% (1-75%), and 40 (6-692) ng/mL, respectively. Bezuclastinib demonstrated statistically significant superiority to placebo on all primary and key secondary endpoints. At Week 24, bezuclastinib led to significantly greater symptom improvement vs placebo (LS mean [95% CI] MS2D2 TSS change: –24.3 [–27.6 to –21.1] vs –15.4 [–19.6 to –11.2]; placebo-adjusted difference: –8.9 points; P=0.0002). A ≥50% reduction in serum tryptase was achieved in 87.4% of bezuclastinib-treated patients vs 0% on placebo (P<0.0001). Significantly more patients receiving bezuclastinib achieved ≥50% reductions in KIT D816V VAF, serum tryptase, BM MCs (P<0.0001), MS2D2 TSS (P=0.01), and ≥30% reduction in MS2D2 TSS (P=0.0004). Most treatment-emergent adverse events (TEAEs) were low grade (gr; 70% Gr 1) and reversible. The most common TEAEs (≥10%) in any treatment group and occurring in greater frequency in the bezuclastinib arm were hair color changes (69.5% vs 5.0%), altered taste (23.7% vs 0%), nausea (22.0% vs 13.3%), increased ALT/AST (22.0% vs 6.6%), headache (17.8% vs 11.7%), alopecia (11.9% vs 3.3%), and increased ALP (10.2% vs 3.3%). TEAEs (≥10%) that occurred more often in the placebo group were diarrhea (13% vs 18%), dizziness (10% vs 12%), fatigue (7% vs 12%), and arthralgia (6% vs 15%). ALT/AST elevations ≥Gr 3 were experienced by 5.9% of patients. The only hepatic adverse events (AEs) reported were transient lab abnormalities; none required hospitalization. Treatment-related AEs requiring dose reductions occurred in 11% of patients receiving bezuclastinib. All discontinuations (5.9%) due to treatment-related AEs were due to transaminase elevations; all fully resolved. Conclusions: At 24-weeks, bezuclastinib 100 mg QD demonstrated statistically and clinically significant improvements in symptom burden and biomarkers of disease vs placebo in patients with NonAdvSM. The treatment was generally well-tolerated and effective across a population that is representative of the real-world NonAdvSM population, including SSM. These results support the use of bezuclastinib to reduce SM burden and symptoms in pts with NonAdvSM, and a potentially disease-modifying impact.

Abstract Background Chimeric antigen receptor T-cell (CAR-T) and bispecific antibody (BsAb) therapies are both effective for patients with relapsed/refractory (R/R) follicular lymphoma (FL), but differ in treatment schedules and associated “time toxicity,” or contact days spent physically interacting with the healthcare system. While contact days can be estimated from clinical trials, real-world data provides a more nuanced depiction of treatment-related time burden, which may guide treatment decision-making. The comparative time toxicity of CAR-T vs BsAb in R/R FL is not defined. Methods We conducted a multicenter retrospective study of adults with R/R grade 1-3A FL who received standard-of-care CAR-T (axi-cel, tisa-cel, liso-cel) or BsAb (mosunetuzumab, epcoritamab) in the third-line or later setting before Jan 1, 2025. Time toxicity was defined as outpatient or inpatient days with physical health care system contact, counting multiple visits on the same day as only one day. All days after treatment initiation were counted, regardless of disease progression, therapy completion, or relation to FL therapy. Median contact days over 1-year time horizon were compared, stratified by CAR-T vs BsAb, prior lines of therapy (LOT, 2 vs 3+), and time intervals (0-1, 1-3, 3-6, 6-9, and 9-12 months). Progression-free survival (PFS) and overall survival (OS) were calculated from day of CAR-T infusion or day 1, cycle 1 for BsAb. Cox regression and propensity matching (by age, ECOG, refractory to prior LOT, POD24) were used to assess predictors and survival associations with contact days. Results Among 209 patients from 15 U.S. academic centers, median age was 64, 37% were female, 61% received CAR-T (80% axi-cel, 7% liso-cel, 13% tisa-cel) and 39% BsAb (93% mosun, 7% epcor). Most had Grade 1-2 FL (72%), advanced stage (84%), and extranodal disease (51%). Median prior LOT was 3 (range 2-15), 41% were refractory to prior LOT, and 52% had POD24. Median number of BsAb doses was 10 (range 1-36). Patients receiving BsAb were significantly older (p<.01) and had higher CIRS comorbidity scores (p<.02) in both 2 and 3+ prior LOT cohorts, and had higher ECOG scores (p=.01) and were less likely to be refractory to prior LOT (p=.029) in 3+ LOT cohort. There were no differences in POD24 rates between CAR-T and BsAb. Median PFS for the entire cohort was 3.6 yrs; median OS was not reached. In the 2 prior LOT cohort (N=75), 60% received CAR-T and 40% BsAb. With median follow-up of 1.5 years, median PFS was not reached for CAR-T and 1.6 yrs for BsAb (p<.0001). In the 3+ prior LOT cohort (N=134), 62% received CAR-T and 38% BsAb. With median follow-up of 2 yrs, median PFS was 3.6 yrs for CAR-T and 1.6 yrs for BsAb (p=.0044). In propensity matched analysis, PFS was shorter for BsAb in both 2 LOT (HR 9.0, 95% CI 1.14-71.04, p=.037) and 3+ LOT (HR 3.25, 95% CI 1.06-9.97, p=.039) cohorts as compared to CAR-T. There were no significant differences in OS between CAR-T and BsAb. Median contact days were significantly higher for CAR-T vs BsAb in the 0-1 month interval: 19 vs 8 days in 2 LOT (p<.0001) and 18 vs 7 days in 3+ LOT (p<.0001) cohorts. There were no differences in contact days between CAR-T vs BsAb in subsequent time intervals. Over 1 year, CAR-T had significantly more time toxicity than BsAb: median 51 vs 36 contact days in 2 LOT (p<.0001) and 64 vs 38 days in 3L+ LOT (p<.0001) cohorts; these remained significant in the matched analysis. B symptoms (p=.04) and Grade ≥3 cytopenias (p=.007) were associated with higher contact days in 3+ LOT cohort in univariable analysis. Higher contact days were associated with inferior PFS (HR 1.01, 95% CI 1.00-1.02, p=.032) and OS (HR 1.01, 95% CI 1.00-1.02, p=.038) in 3+ LOT cohort regardless of treatment type. Discussion In this large real-world cohort of patients with R/R FL, CAR-T therapy resulted in better PFS but more time toxicity over the first year as compared to BsAb therapy. Excess time toxicity from CAR-T was driven by more contact days in the first month of treatment. This study provides benchmark data for counseling patients about expected time burden of CAR-T (51-64 days) and BsAb (36-38 days) over the first year of these therapies. Further, with superior PFS of CAR-T in this study and minimal impact of time toxicity on survival outcomes, these data can be used to better support shared decision-making in R/R FL by addressing patient preferences regarding both contact days as well as duration of disease control.