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Abstract Background. Uproleselan (GMI-1271) is an antagonist of E-selectin, an adhesion molecule expressed on endothelial cells in the vascular niche of the bone marrow. Engagement of E-selectin by acute myeloid leukemia (AML) blasts, which express E-selectin ligand, activates cell survival pathways and promotes resistance to chemotherapy. In multiple preclinical AML tumor models, blockade of E-selectin with uproleselan enhanced the efficacy of chemotherapy. Methods. We conducted a phase (P) 2/3 study in which subjects age ≥ 60 years with untreated, FLT3 unmutated AML were randomized to receive conventional chemotherapy with or without uproleselan. Induction chemotherapy consisted of 7+3 (cytarabine + daunorubicin) +/- uproleselan with a second induction cycle with 5+2 +/- uproleselan administered for residual AML. Uproleselan 800 mg IV was administered as a single dose 24 hours before the first dose of chemotherapy and then every 12 hours until 48 hours after the completion of chemotherapy. Post-remission therapy consisted of up to 3 cycles intermediate-dose cytarabine 2 gm/m2 IV d1-5 +/- uproleselan. Allogeneic transplant was performed at the discretion of the treating physician. The primary endpoint was event-free survival (EFS) for P2 and overall survival (OS) for P3. Results. The study enrolled 267 patients between March 2019 and November 2021, with a median age of 66.9 years (IQR 63.8-69.9). 32% were classified as 2017 ELN intermediate risk, 41% as adverse risk, with 62 (29%) having complex karyotype / mutated TP53. The P2 analysis was to be performed when at least 191 events were observed. However, as the required events had not been observed > 5 years after study initiation and 3 years after completion of P2 enrollment, an independent statistician was consulted, and the analysis plan was amended to conduct the P2 EFS analysis in November 2024. With a median follow-up of 53.1 months, the EFS was not significantly different between the two arms (HR 0.90, 95% CI 0.70-1.23, P=0.58). As the study did not meet its P2 EFS endpoint, enrollment in the P3 was not initiated. There was no significant difference in OS between the 2 arms (HR 0.99, p=0.94) with a median OS in the uproleselan arm of 23.6 months (95% CI 15.1-35.4 mo) vs 19.8 months (14.6-36.3) for the control arm. The overall rate of CR/CRi after induction was 65% (CR: 60%) in the uproleselan arm versus 63% (CR: 55%) in the control. MRD results by either local or central assessment in patients achieving a CR/CRi were available for 129 patients with the MRDneg rate of 81 % (95% CI 69.5-89.9%) in the uproleselan arm vs 67% (54.3-78.4%) in the control arm (p=0.053), The 30-day mortality was 5.3% for uproleselan vs 8.1% in the control. Forty-eight (36%) patients in the uproleselan arm and 55 (40%) in the control arm underwent alloHCT, including 37 (27%) and 29 (22%) in CR1, respectively (p = 0.34). In patients undergoing alloHCT in CR1, those randomized to uproleselan and allografted in CR1 had an HR 0.71 (95% CI 0.34-1.47; P=0.35) compared to the control arm. Expression of E-selectin ligand on AML blasts was performed by flow cytometry, with subjects having an E-selectin ligand expression above the median having a trend towards worse median OS 16.2 (95% CI 11.4-24.3) vs 32.2 (15.9-57.8) months, but was not affected by treatment arm. In both univariate and multivariate analyses, WBC at baseline, ELN genetic risk group, and TP53/complex karyotype were found to be associated with EFS. A subgroup analysis identified an improvement in EFS favoring uproleselan in patients with mutated ASXL1 (HR 0.25, 95% CI 0.08-0.78, p<0.017). Conclusions. Although the addition of uproleselan to intensive chemotherapy was associated with a higher rate of MRDneg CR/CRi in older adults with AML, uproleselan failed to improve EFS or OS and did not overcome the adverse outcomes associated with higher E-selectin expression on AML blasts. The median OS of 20-24 months with an overall 3-year OS of almost 40% for patients treated on this study exceeds previous CALGB / US Cooperative Group studies (median OS ~12 months, 3-year OS ~20%) and continues to support a role for intensive chemotherapy in the management of older adults with AML. Furthermore, this study suggests a potential benefit for uproleselan in patients harboring ASXL1 mutations, which may warrant further investigation. ClinicalTrials.gov Identifier: NCT03701308

Abstract Introduction: Teclistamab is the first FDA approved BCMA-directed bispecific antibody for the treatment of relapsed and refractory multiple myeloma (RRMM). With BCMA-targeting CAR-T therapies, cytokine release syndrome (CRS) is a risk factor for cardiotoxicity. Teclistamab was associated with fatal cardiovascular adverse events (CVAEs) in a recent US pharmacovigilance database analysis, but this analysis was limited by reporting bias. Therefore, the aim of our study is to conduct a multicenter study to define the real-world incidence of CVAEs in RRMM patients treated with teclistamab. Method We performed a retrospective multi-center cohort study of patients receiving teclistamab at 5 medical centers. Baseline oncologic and cardiovascular characteristics (including vital sign and echocardiographic data) were collected. Baseline cardiovascular disease (CVD) was defined as presence of coronary artery disease, congestive heart failure, severe or symptomatic valvular heart disease, or stroke at baseline. CVAE was collected and categorized based on CTCAE v5.0 by each institution. Major adverse cardiovascular event (MACE) was a composite outcome with any of the following: congestive heart failure, asymptomatic cardiomyopathy (interval LVEF drop >10% to resultant LVEF less than 50%), coronary artery disease requiring intervention, stroke or cardiovascular death. Arrhythmia was a composite outcome with any of the following: atrial tachyarrhythmia, ventricular tachyarrhythmia or bradyarrhythmia. Median follow-up was calculated through reverse Kaplan-Meier method. Multivariable Cox regression analysis was used to define the relation between MACE and survival. Cause of death was categorized as myeloma-related death or non-myeloma-related deaths (i.e. CRS, infection or cardiovascular death). Cause-specific Cox regression was performed to define relationship between MACE and cause of death. Results In a cohort of 219 patients treated with teclistamab with median follow-up of 20.1 months, 7.3% (N=16) developed MACE, 7.3% (N=16) developed arrhythmia and 12.8% (N=28) developing any MACE or arrhythmia. MACE occurred at a median of 4.5 days (IQR 2.25-15.75 days) after teclistamab step-up. The incidence of MACE was 16.4% in patients with baseline CVD versus 2.7% in those without baseline CVD (p<0.001). Patients who developed MACE had inferior ECOG performance status (PS) (PS >=2: 62.5% vs. 27.7%; p=0.008). Additionally, baseline hemoglobin level (9 vs 10g/dL; p=0.072) was numerically lower in MACE, compared to no MACE. There was no difference in age, sex, bone marrow (BM) plasma cell burden, ferritin, C-reactive protein or LDH levels between MACE vs. no MACE group. Patients who developed MACE had lower baseline diastolic blood pressure (67.7 vs 73.8mmHg; p=0.041) and numerically lower LVEF (51.4 vs 59.3%; p=0.059; baseline echocardiogram performed in 86% of all cohort). Patients who developed MACE had similar incidences of CRS (Grade >=2: 25.0 vs 16.7%; p=0.620) and immune effector cell-associated neurotoxicity (ICANS) grade 2 or higher (12.5 vs 7.5%; p=0.812). In multivariable Cox regression analysis, MACE was independently associated with inferior overall survival (HR 2.72; 95% CI 1.41-5.25; p=0.003), after adjusting for baseline CVD, age, high BM burden, extramedullary disease, and plasma cell leukemia. In cause-specific multivariable Cox regression analysis, MACE was independently associated with non-myeloma-related death (HR: 10.77 95% CI 4.39- 26.41; p<0.001) but not with myeloma-related death (1.54; 95% CI 0.64- 3.70; p=0.336). Conclusion In conclusion, in this large, real-world multicenter study, we observed that MACE occurred in over 7% of patients following teclistamab for RRMM, typically within 2 weeks of initiation. MACE was significantly associated with increased non-myeloma-related mortality. In contrast to CAR-T therapy, CRS or ICANS were not associated with MACE, whereas majority of patients who developed MACE had ECOG PS >=2 or baseline cardiovascular disease. More studies are necessary to define mechanisms and strategies to reduce these MACE and improve survival. Patients with baseline cardiovascular disease or poor performance status may benefit from cardiovascular optimization before and during teclistamab therapy.

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 Introduction: cBTKi have made a substantial impact in pts w/ MCL, but pts who develop PD while on treatment w/ cBTKi have historically had poor responses to subsequent lines of therapy (LOT). Brexucel, lisocel, and the non-covalent BTKi pirto have been approved in this population. While two RW studies have substantiated the benefit of brexucel, similar data for pirto are lacking. Accordingly, we aimed to evaluate the outcomes of pts treated w/ pirto in the RW setting. Methods: We performed a multi-center retrospective cohort study of adult pts w/ a diagnosis of MCL who experienced PD after any approved cBTKi and subsequently received pirto. Pts who received pirto w/ bridging intent and those who switched to pirto due to intolerance of cBTKi were excluded. The 95% exact binomial confidence intervals (CI) were calculated for overall response rate (ORR) and complete response rate (CRR). Progression-free survival (PFS) and overall survival (OS) were defined as the time from pirto start to PD or death, whichever occurred first, and the time from pirto start to death, respectively, and calculated w/ the Kaplan-Meier method. The log-rank test was used to compare survival curves. A multivariate (MV) Cox proportional hazard model was built to calculate adjusted hazard ratio (aHR). Analyses were performed w/ SAS, version 9.4. Results: Data on 111 pts w/ MCL treated across 21 institutions were collected. Median (mdn) age was 72 (range 33 – 93) years. Twenty-seven pts (24%) were female, 3 (3%) were Asian, 5 (5%) Black, 9 (8%) Hispanic, 86 (77%) White. Among the 53 (48%) pts w/ available MIPI-c at diagnosis, 28 (53%) pts were high-risk. Ki67 at diagnosis was available in 84 (76%) pts: of those, 58 (69%) had a Ki67 ≥30%, and 41 (49%) ≥50%. TP53 mutational status was available in 70 (63%) pts: 33 (47%) had documented TP53 mutation and 10/52 (19%) pts had a disease w/ complex karyotype. Pts had a mdn of 3 (range 1 – 9) prior LOT (n=106). Ninety-one pts (86%) received chemo-immunotherapy (CIT), 16 (15%) autologous stem cell transplant, 19 (18%) venetoclax (ven), 29 (27%) chimeric antigen receptor T-cell, 4 (4%) allogeneic stem cell transplant. For cBTKi, 39 (35%) pts received ibrutinib, 56 (50%) pts acalabrutinib, 33 (30%) pts zanubrutinib, and 17 (15%) pts received more than one cBTKi. The mdn time from the last dose of cBTKi to pirto start was 55 (range 0 – 2587) days, w/ 51 (46%) pts who switched from a cBTKi directly to pirto. Thirty (27%) pts had no response (stable disease or PD as best response) to cBTKi, and 40 (36%) pts had no response to the last LOT. Two (2%) pts received pirto in combination w/ CIT, 8 (7%) w/ an anti-CD20 monoclonal antibody (mAb), 11 (10%) w/ ven ± a mAb, while 86 (77%) pts as single agent. In 104 (94%) pts, pirto was given at full dose, 10 (9%) pts had a subsequent dose reduction. A total of 35 serious (grade ≥3) adverse events (AE) were documented in 27 (24%) pts: 4 (4%) pts had a serious bleeding AE, 5 (5%) pts a serious cardiac AE, 10 (9%) a serious GI AE, and 16 (14%) a serious infectious AE. Ninety-eight (88%) pts were evaluable for response. The ORR was 40% (95% CI 30% – 50%) w/ a CRR of 29% (95% CI 20%– 39%). At the last follow-up, 29 (26%) pts remained on pirto w/ a mdn treatment duration of 15.1 months (range 0.4 – 26). Fifty-eight (52%) pts died, 35 (78%) because of PD. At a mdn follow-up of 15.8 (range 0.4 – 26) months among survivors, the mdn PFS was 4.7 months (95% CI 3.3 – 8.2) and the mdn OS was 13 months (95% CI 9.2 – not available). Using the log-rank test, age (quartile groups), number of LOT (1-2 vs. 3-4 vs. 5+), time from cBTKi to pirto (quartile groups), Ki67≥30%, and high MIPI-C did not result in a statistically significant difference in PFS (p>0.05). Presence of TP53 mutation was associated w/ a non-statistically significant adverse trend in PFS (p=0.0585). No response to cBTKi and Ki67≥50% were associated w/ a statistically significant inferior PFS in log-rank test (p=<0.05), which persisted in a MV Cox regression model (aHR 2.4, 95% CI 1.4-4.2, and aHR 2.6, 95% CI 1.6-4.4, respectively). Conclusions: This is the first RW report on pirto in MCL pts. In this high-risk population, ORR to pirto was comparable to the BRUIN trial, while PFS was significantly worse, especially in pts w/ no response to cBTKi and w/ a high Ki67. However, prolonged remissions were seen in a subset of pts, suggesting that a better characterization of this population w/ durable benefit from pirto is needed.

Abstract Background: Prognostication for patients with non-transformed relapsed/refractory (R/R) follicular lymphoma (FL) is not well defined. Progression of disease within 24 months (POD24) and number of lines of prior therapy are commonly used to benchmark outcomes and for trial eligibility in this space. However, a comprehensive model for risk prediction in R/R FL is lacking. Here we utilize patients from the LEO Consortium for Real World Evidence (CReWE) and Iowa/Mayo Clinic Lymphoma SPORE MER to develop a clinical prediction model for R/R FL. Methods: Patients with grade 1-3A FL were prospectively enrolled at diagnosis in the MER and/or initiated second line or later therapy (2L+) for non-transformed FL at one of the 8 LEO Centers from a previous LEO CReWE study (Casulo et al, Lancet Haem 2022). All available lines of therapy were abstracted; lines of therapy after histologic transformation were not used in the analyses. A management plan of observation was considered as a type of therapy in the 1L setting but not in the 2L+ setting. Clinical variables and outcomes were abstracted at each line of therapy. Variables considered for modeling included demographics, clinical labs, treatment history, and pertinent clinical variables (including FLIPI and FLIPI24 components). Multiple imputation was used to address missing data in modeling; beta-2 microglobulin (B2M) was unable to be imputed due to the amount of missing data. Index therapy was defined as the date of initiation of a line of therapy (2L, 3L or 4L) for non-transformed FL. The primary endpoint for model development was the time from index therapy until the histologic transformation or lymphoma-related death (HT/LD). Cox proportional hazards models were used for model development. Modeling was first performed separately for each line of therapy and then evaluated across lines. Bootstrapping on imputed datasets was used to assess optimism in model performance. Results: N=1001 patients initiated 2L+ therapy and were utilized for modeling. Of these patients, N=654 initiated 3L and N=344 initiated 4L therapy. Median age at index therapy was (60, 61, and 62) for lines 2-4, respectively. Median follow-up by line of therapy was 8.2, 6.1, and 6,1 years and number of HT/LD events for modeling was 272, 154, and 88, respectively. Observed outcomes decreased modestly as the line therapy increased: median event-free (1.6, 1.5, and 1.2 years) and overall survival (17.6 years, 14.5 years, and 12.3 years), for lines 2-4, respectively. 5-year estimates of HT/LD by line of therapy were 21.6% (95% CI: 18.9-24.3), 23.7% (95% CI: 19.9-27.4) and 29.3% (95% CI: 23.3-34.7), respectively. A clinical prediction model was independently developed for each line of therapy; the final model for each line consisted of the same variables: increasing age, male sex, higher LDH, lower hemoglobin, higher white blood cell count, prior immunochemotherapy exposure, and shorter time since initial diagnosis. The parameter estimates for these variables were broadly similar across the different lines of therapy. The model output is an individual patient's risk of HT/LD. Patients with high-risk FLP-R, as defined using the upper quartile of FLP-R risk scores for each line, had observed 5 year HT/LD rates of 43%, 44% and 51% in lines 2-4, respectively. In contrast, patients with the lower quartile of FLP-R risk scores had observed 5 year HT/LD rates of 10%, 6% and 8% in lines 2-4, respectively. The optimism-corrected c-statistic for the FLP-R model across all lines of therapy was 0.685. This added significant information beyond FLIPI diagnosis (c=0.533) FLIPI at index line (c=0.563), the line of therapy (c=0.525), POD24 status (c=0.578), or all 4 variables combined (c=0.614). Conclusions: The FLP-R model identifies a group of patients with non-transformed FL in the R/R setting who are at very high risk of transformation and/or lymphoma-related death across lines of therapy. FLP-R features 4 of the 5 components of the 1L FLIPI24 prediction model (B2M was unavailable for modeling) with the addition of sex, treatment history and time since initial diagnosis. The number of prior therapies is not sufficient to identify high-risk populations for clinical trial enrichment in the R/R FL setting and model discrimination for FLP-R was greatly improved over FLIPI and/or POD24 across lines of therapy. A Shiny app will be provided for model implementation; external validation is planned.

Abstract Introduction: MyeloMATCH (mM), is an National Cancer Institute (NCI)-sponsored precision medicine initiative for newly diagnosed AML/MDS. It consists of an initial screening study (Master Screening and Reassessment Protocol, or MSRP) that involves centralized testing of bone marrow/whole blood, leading to assignment into several genetically driven treatment subprotocols within the mM portfolio. MSRP employs karyotype, 8-15 probe fluorescence in situ hybridization (FISH) and NCI-myeloid (NMAv2) assays to determine ploidy, translocations and mutational status needed for accurate disease subclassification, risk stratification as well as for theragnostic determination. NMAv2, a rapid next generation sequencing assay (TAT<48 hrs), interrogates 45 DNA and 35 RNA fusion driver genes to report 1661 hotspot DNA mutations and 779 targeted RNA fusions, including all relevant fusions in AML except Inv3/t(3;3)/MECOM rearrangement (Yeung et al, 2025). The initial mM MSRP workflow relied on karyotype and FISH assay results to identify fusion positive AML/MDS as per the current testing guidelines/ recommendations as well as to abide by the FDA's requirements under the investigational device exemption (IDE). Here we present concordance analysis between karyotype, FISH and NMAv2 assay to identify relevant fusions in AML/MDS. Methods: First 400 participants enrolled in the mM MSRP were included in this analysis. We examined the results from karyotype analysis analyzing 20 metaphase cells, 8-15 probe FISH analyzing 500 nuclei per probe, and NMAv2 curating fusion read counts greater than 100, performed at the mM labs to determine the prevalence of fusions in this cohort. Concordance analysis was performed to determine clinical utility of the NMAv2 assay to report relevant fusions at the time of initial diagnosis. The concordance analysis excluded biomarkers including Inv3/t(3;3)/MECOM rearrangement, KMT2A-PTD and other rare fusions that are beyond the scope of detection by NMAv2 and/or FISH assay. Results: Of the 400 patients analyzed in this cohort (median age 64, [range 20-95]; 43% female; 15.5% non-white; 9.5% Hispanic), translocations/fusions were reported in 67, 73 and 95 patients by karyotype, 8-15 probe FISH and NMAv2, respectively. The karyotypic analysis reported inv(16)/t(16;16) [15], t(11q23) [13], t(9;22) [10], inv3/t(3;3) [9], t(8;21) [6], t(15;17) [5], t(6;9) [4], t(21q22) [3], t(9q34) [1] and t(10;11) [1]. The FISH reported inv(16)/t(16;16) CBFB::MYH11 [15], t(11q23) KMT2A rearrangement [14], t(9;22) BCR::ABL1[10], inv3/t(3;3) MECOM rearrangement [10], t(8;21) RUNX1::RUNX1T1 [7], t(15;17) PML::RARA [5], t(6;9) DEK::NUP214 [5], t(21q22) RUNX1 rearrangement [3], t(11p15.4) NUP98 rearrangement [3], and t(9q34) ABL1 rearrangement [1]. The NMAv2 reported KMT2A-PTD [26], CBFB::MYH11 [15], KMT2A fusion [14], BCR::ABL1[12], RUNX1::RUNX1T1 [8], PML::RARA [5], DEK::NUP214 [5], RUNX1 fusion [4], NUP98 fusion[3], t(9q34) ABL1 fusion [1], PICALM::MLLT10 [1] and ETV6::MECOM [1]. The concordance analysis between NMAv2 and karyotype assay demonstrated positive percent agreement(PPA) of 100%, negative percent agreement(NPA) of 96.81% and overall agreement (OA) of 97.25% when using karyotype as reference. The concordance analysis between NMAv2 and FISH assay demonstrated PPA of 100%, NPA of 98.81% and OA of 99% when using FISH as reference. Of the 12 cases with discrepant results, 7 were due to presence of cryptic translocations missed by karyotype assay, 3 had suboptimal specimen submitted for karyotype/FISH analysis, 1 had false positive BCR::ABL1 fusion reported by NMAv2 due to low level contamination and 1 had minor subclonal population of leukemic blast with BCR::ABL1 fusion detected only by NMAv2. Conclusion: NMAv2 shows high concordance with karyotype and FISH assays which are the most commonly utilized assays to identify fusions/translocations in AML/MDS. NMAv2 is a faster, relatively cheaper and sample conserving method to identify fusions and is less prone to false negative results than karyotype/FISH assay from suboptimal specimen acquisition and testing. Based on the results above, mM MSRP workflow has been amended with FDA concurrence such that a combination of NMAv2, karyotype and MECOM breakapart FISH assay will be used to identify relevant fusion variants in all patients enrolled in mM, whereas additional specific FISH assay will be limited to cases where discrepant results between karyotype and NMAv2 are reported.

Abstract Introduction: Iron deficiency (ID) is a global epidemic with discrepant definitions of both ID and anemia in pregnancy. Iron requirements increase during pregnancy and deficiencies should be corrected to avoid adverse maternal-fetal outcomes. Current guidelines recommend only screening for ID during pregnancy in the presence of anemia despite the global epidemic of ID in reproductive-age females and availability of ferritin as a high-value biomarker. To address this unmet need and gap in care, we implemented a standardized approach to screening and treating ID in pregnancy. Methods: In March 2024 at the ASH Quality Improvement Training Institute, our multidisciplinary team with representatives from hematology, obstetrics, anesthesiology, and patient blood management developed a quality improvement (QI) initiative to standardize an approach to screening and treating ID in pregnancy. After local dissemination and education of the standardized care pathway via patient/provider handouts and divisional presentations, obstetric providers paired ferritin testing with two standard hemoglobin assessments in early (8-12 weeks gestation) and late (24-28 weeks gestation) pregnancy to minimize lab draws and optimize logistics. The process was facilitated by modifying prenatal order sets in the electronic medical record. ID was defined as a ferritin <50 mcg/L and anemia was defined as a hemoglobin <11 g/dL. If ID was present in early pregnancy, oral iron supplementation was offered; if ID was present in late pregnancy, an IV iron infusion (low molecular weight iron dextran, 1 gram) was offered regardless of anemia status. Results: Obstetric data were captured pre-intervention from January 2023 – February 2024 (n=2097 pregnancies) and post-intervention from March 2024 – June 2025 (n=2429 pregnancies). Ferritin screening rates improved from 10% (205/2097) to 63% (1534/2429). Of those ferritin tests, 66% demonstrated ID in the pre-intervention cohort and 69% demonstrated ID in the post-intervention cohort. Anemia rates by measured hemoglobin during pregnancy were 25% in both the pre-intervention and post-intervention cohorts despite 92% having documentation of prenatal vitamins containing iron (PNV). Iron dextran infusion rates improved from 0.9% (18/2097) to 21% (507/2429). Of those receiving IV iron dextran, 39% had documentation of both PNV as well as additional oral iron supplementation. Overall, the median hemoglobin improved from 10.7 to 11.8 g/dL in those receiving IV iron dextran. This included increases from 12.0 to 12.8 g/dL in those without anemia and from 11.2 to 12.1 g/dL in those with ferritin 30-50 mcg/L after IV iron. Prior to initiation of this QI project, 3.1% of pregnancies (65/2097) required a blood transfusion during admission for delivery. After initiation of this project, 2.7% of pregnancies (65/2429) required a blood transfusion, of which 46 did not receive IV iron and 33 did not have a ferritin checked. Conclusions: ID in pregnancy is underrecognized and undertreated. Through a multidisciplinary QI initiative, screening for ID improved from 10% to over 60% of pregnancies within one year of project initiation. Over the same period, there was a 20-fold increase in the number of IV iron dextran infusions resulting in an increase in median hemoglobin by over 1 g/dL and a signal for decreased transfusion requirements. This occurred despite almost universal supplementation with a PNV. This standardized approach to screening and treating ID was performed by the obstetrics teams and could be implemented within varied practice models. Given the potential implications for reevaluation of appropriate reference ranges and equitable prenatal care globally, additional studies are warranted to better characterize ID in pregnancy as well as clinical sequelae for both mothers and infants. Simultaneously, discussions are needed around current guidelines and recommendations for both screening and treating ID in pregnancy.

Abstract Introduction Short diagnosis-to-treatment interval (DTI) is associated with aggressive disease biology and inferior outcomes in diffuse large B-cell lymphoma (DLBCL), and is recognized as a potential source of selection bias in clinical trials if not properly addressed. However, its prognostic significance in follicular lymphoma (FL) remains poorly characterized. We aimed to evaluate the prognostic significance of DTI in newly diagnosed FL patients who received frontline (1L) immunochemotherapy (IC), using a large international dataset and an independent external validation cohort. Methods For the discovery dataset, we evaluated patients diagnosed between 2002 and 2018 from ten observational cohorts as part of the FLIPI24 Consortium. External validation was conducted using data from patients enrolled in the Lymphoma Epidemiology of Outcomes (LEO) Cohort between 2010 and 2015. All patients had FL grade 1–3A and received 1L IC within 100 days of diagnosis. Patients with a concurrent DLBCL were excluded. Missing baseline laboratory values were addressed via multiple imputation. The primary endpoint was event-free survival at 24 months (EFS24); secondary endpoint was 5-year overall survival (OS), both calculated from treatment initiation. DTI was analyzed as continuous (via splines) and dichotomized variable (≤14 vs >14 days; as defined in DLBCL). Results In the discovery cohort (n=3,907), median age was 61 years (IQR 53–69), and 50% were male; 49% of patients were high-risk according to FLIPI, 26% according to PRIMA-PI, and 38% according to FLIPI24. Included patients received R-CHOP (54%), R-CVP (26%), or B-R (20%) as 1L treatment, followed by anti-CD20 maintenance in 60%. The median DTI was 30 days (IQR 17–48). Using the 14-day cut-off, 851 patients (22%) had short DTI. These patients had more adverse baseline characteristics, including B symptoms (42% vs 32%, P<0.01), ECOG performance status ≥2 (15% vs 8%, P<0.01), elevated LDH (51% vs 40%, P<0.01), hemoglobin <12 g/dL (30% vs 17%, P<0.01), and elevated β2-microglobulin (56% vs 44%, P<0.01). Prognostic indices (PIs) were also more frequently high-risk in the short-DTI group: FLIPI (56% vs 47%), PRIMA-PI (36% vs 24%), and FLIPI24 (51% vs 34%, all P<0.01). Spline modeling showed a decreasing EFS24 rate with increasing DTI, reaching a plateau at 30–40 days. In logistic regression model, each additional week of DTI improved EFS24 (OR 0.92, P<0.01). DTI attenuated but remained prognostic after adjusting for PIs (OR 0.93 for FLIPI, 0.95 for PRIMA-PI, 0.96 for FLIPI24, all P<0.01). When analyzed as a dichotomized variable, short DTI was associated with inferior EFS24: OR 1.74 adjusted for FLIPI, 1.63 for PRIMA-PI, and 1.53 for FLIPI24 (all P<0.01). The 2-year EFS of short vs long DTI groups was 71% vs 82% (HR 1.50, 95% CI 1.34–1.67, P<0.01), 5-year OS was 80% vs 86% (HR 1.38, 95% CI 1.21–1.56, P<0.01), and the 5-year cumulative risk of histologic transformation was 7.7% vs. 5.4% (P<0.01). In the validation cohort (n=516), median age was 61 years (IQR 52–69 years), 55% were male; 36% of patients were high-risk according to FLIPI; 29% according to PRIMA-PI, and 33% according to FLIPI24. Patients received B-R (59%) or R-CHOP (41%) as 1L treatment. The median DTI was 31 days (IQR 19–48), 84 patients (16%) had DTI ≤14 days. Similar patterns were observed; patients with short DTI had adverse baseline characteristics, PIs, and shorter 2-year EFS (72% vs 84%, HR 1.69, 95% CI 1.13–2.55, P=0.01). DTI remained associated with EFS24 when analyzed as a continuous variable (per week: OR 0.88 unadjusted, 0.90 with FLIPI, 0.89 with PRIMA-PI, and 0.89 with FLIPI24), and dichotomized (≤14 vs >14 days: OR 1.83 adjusted for FLIPI, 1.88 for PRIMA-PI, and 1.73 for FLIPI24). Conclusion Short DTI, defined as ≤14 days (observed in 22% of FL patients vs 46% in DLBCL), is a strong and independent predictor of inferior outcomes in newly diagnosed FL patients treated with IC. While DTI correlates with adverse baseline features and established PIs, it retains independent prognostic value. Although a 14-day threshold is reasonable for risk modeling, DTI contains greater informational value when modeled as a continuous variable. Among PIs, FLIPI24 most strongly attenuated the DTI effect, underscoring its superior discriminative power over FLIPI and PRIMA-PI. Clinical trials designs should mitigate any potential barriers to enrollment of FL patients requiring urgent therapy.

Abstract Introduction: CD20xCD3 bispecific antibodies (BsAb) have been approved for use in relapsed/refractory (RR) large B-Cell lymphomas (LBCLs) with manageable toxicities. The main adverse events of clinical interest are cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). The risk factors for CRS and ICANS are not well understood. Knowledge of variables that contribute to increased risk may help clinicians identify and tailor management for high-risk patients (pts) and increase the comfort level for providers using these therapies in community practices. Methods: We performed a multicenter retrospective study at 21 US centers evaluating pts with RR LBCLs receiving commercially available epcoritamab (epco) or glofitamab (glofit) between 2023 and 2025. We obtained baseline characteristics, safety and efficacy outcomes. Univariate analysis was performed to identify associations between CRS, ICANS, and clinical variables of interest. Results: As of May 31, 2025, a total of 312 pts with RR LBCLs were treated with BsAb, Epco n=193 (62%), Glofit n= 119 (38%); median age 68; 63% male; 70% ECOG PS 0-1. Most common histologic type was diffuse large B-cell lymphoma, not otherwise specified (DLBCL, NOS) (n=239, 84%) followed by high-grade B-cell lymphoma (HGBL) (n=46, 16%). 179 pts (57%) were previously treated with chimeric antigen receptor T-cell (CAR-T) therapy, with 47% receiving CAR-T <6 months (mo) prior to BsAb. Among pts with prior CAR-T, CRS with CAR-T therapy of any grade occurred in 63%, with 26% ≥ grade 2. ICANS of any grade (G) occurred in 25% of pts (9.4% ≥ G3). Overall and complete response (ORR and CR) rates to BsAb were 51% and 29%, respectively. With a median follow up of 5 mo, median progression-free and overall survival (PFS and OS) were 2.3 and 7.3 mo, respectively. With BsAb treatment, CRS of any grade occurred in 117 (39%) patients: 24% G1, 8.7% G2, 4% G3, 1% G4 and 1% G5. The max grade CRS occurred most frequently after the third dose of epco (35%) and the first dose of glofit (23%). CRS was managed with additional steroids in 24% of pts and tocilizumab in 22%. 13% of pts experienced ICANS: 5.8% G1, 3.4% G2, 2% G3, 1% G4 and 0.3% G5. Factors that increased the risk for any grade CRS included: bulky disease ≥ 7.5 cm at time of BsAb treatment (OR 2.04, 95% CI 1.17 – 3.55, p = 0.012), elevated LDH (OR 2.56, 95% CI 1.45– 4.76, p = 0.002) and treatment with epco compared to glofit (OR 1.69, 95% CI 1.04- 2.77, p = 0.036). As G ≥2 CRS generally requires inpatient monitoring and management, we next compared the risk factors between pts with no CRS or G1 CRS and G ≥2 CRS. Factors associated with increased risk for high grade CRS included: bone marrow involvement by lymphoma (OR 3.47, 95% CI 0.97 – 11.3, p = 0.043), platelet count ≤ 75 (OR 2.46, 95% CI 1.21 – 4.87, p = 0.011), ≥ 2 extra nodal sites (OR 2.04, 95% CI 1.07 – 3.97, p = 0.032) and ≥G2 CRS with prior CAR-T (OR 3.35, 95% CI 1.13 – 9.97, p = 0.027). Factors that increased the risk for ICANS included: bulky disease (OR 2.67, 95% CI 1.28 – 5.49, p = 0.008), elevated Cr ≥ 1.5x ULN (OR 3.79, 95% CI 1.25 – 10.4, p = 0.012), elevated AST/ALT ≥ 3x ULN (OR 4.65, 95% CI 0.92 – 19.9, p = 0.042), low albumin (OR 2.85, 95% CI 1.49 - 5.5, p = 0.002), and co-occurrence of CRS with BsAb (OR 9.1, 95% CI 3.85- 25, p < 0.001). No other clinical variables including older age, histologic subtype, ECOG PS, B symptoms, IPI score, cell of origin or histologic subtype, baseline labs such as ALC, CRP, fibrinogen or D-dimer were significantly associated with CRS or ICANS risk. There was no difference in ORR or CR rates in patients who experienced CRS or ICANS. Conclusions: Our analysis of pts treated with commercial BsAb for LBCL shows an increased risk for CRS and ICANs based on clinical variables that are routinely obtained at baseline including tumor bulk, sites of disease, laboratory parameters, and history of prior CRS with CAR-T therapy. Differences in baseline populations receiving epco and glofit treatments in this real-world analysis have been previously reported (Brooks et al, Blood 2025) and the comparative risk for CRS between these treatments remains unclear. Future plans including multivariable analysis may allow for development of a predictive model to identify pts at high risk of CRS and ICANS with BsAb treatment, potentially leading to prospective clinical trials evaluating prophylactic interventions for high-risk pts.

Abstract Introduction: Epcoritamab (epco) and glofitamab (glofit) are bispecific antibodies (BsAbs) approved for the treatment of patients (pts) with multiply relapsed or refractory (r/r) large B-cell lymphoma (LBCL). Though response rates are relatively high, most patients (pts) eventually experience progression of disease (POD). We sought to investigate the treatment patterns and clinical outcomes following POD post-BsAb for r/r LBCL Pts, as this has not previously been described. Methods: We performed a multicenter retrospective study including 21 US centers evaluating pts with r/r LBCL 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, progression-free survival (PFS) and overall survival (OS), analyzed using the Kaplan Meier method. Results: As of May 15, 2025, a total of 312 pts with r/r LBCLs were treated with BsAb, of whom a total of 168 (53.8%) pts experienced POD [104 of 193 (53.8%) treated with prior epco and 64 of 119 (53.8%) treated with prior glofit]. Pts with POD had a median age at BsAb start of 67 years (interquartile range [IQR] 58-76), most were male (68.4%), and the most common histology was diffuse large B-cell lymphoma not otherwise specified (n=122 [71.8%]). Sixty-seven of 168 pts (39.9%) with POD after BsAb had experienced primary refractory disease defined as failure to achieve PR or CR to frontline therapy. A total of 102 (60.7%) pts with POD to BsAb had received chimeric antigen receptor (CAR) T-cell therapy prior to BsAbs, with 33.3% of these pts being refractory to CAR T and 30.4% progressing within 6 months of CAR T-cell infusion. The median time to progression following BsAb start was 48 days. Following POD, 70 pts received no further anti-lymphoma therapy. Among 98 pts receiving subsequent therapy, 85 initially received systemic therapy and 13 initially received local therapy with radiation (concurrently with systemic therapy in 8 pts). The most commonly-used next line of systemic therapies included: loncastuximab tesirine in 19 pts (ORR 16.7%, all PR); commercial CAR T in 11 pts (ORR 50% [CR 36.4%, PR 18.2%); tafasitamab with lenalidomide in 7 (no responses); and other chemotherapy in 46 pts (ORR 27.6% [CR 24.1%]). The median follow-up time from POD was 9.2 months among survivors (95% confidence interval [CI] 7.8-13.3). Among those who initiated subsequent-line therapy following BsAbs, the median progression-free survival (PFS2) was 1.9 months (95% CI 1.5-2.4) and median overall survival (OS) from initiation of subsequent-line therapy was 3.9 months (95% CI 2.4-5.5). The estimated 1-year OS following initiation of next therapy was 12%. Conclusions: We report the outcomes of largest cohort of pts with POD post-BsAbs in r/r LBCL. Progression events occurred early after initiation of single agent BsAbs, and almost half of pts who progressed did not receive subsequent therapy. For those who received standard subsequent-line therapy after POD, response rates and survival outcomes were poor. Pts with POD after BsAB should be strongly considered for clinical trials of novel therapeutics or combination therapies.