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Introduction: CD20xCD3 bispecific antibodies (BsAbs) represent a major advance in the treatment of relapsed or refractory (r/r) large B-cell lymphoma (LBCL). In their pivotal trials, epcoritamab (Epcor) and glofitamab (Glofi) showed an overall response rate (ORR) and complete response rate (CRR) of 52-63% and 39%, respectively, in patients (pts) with r/r LBCL after 2 or more prior lines of therapy (LOT). Data on the efficacy and safety of BsAbs in standard of care (SOC) setting is limited. Here, we report our multicenter retrospective study on SOC BsAbs for the approved indication in r/r LBCL. Methods: All pts who received SOC BsAbs for r/r LBCL at four cancer centers in Florida were included. Pts who died before the first response evaluation were considered to have disease progression. Median follow up time was calculated using reverse Kaplan Meier (KM) method. Univariate analysis (UVA) and multivariate analysis (MVA) of response rates were done using logistic regression. UVA and MVA of PFS and OS were done using Cox proportional hazard model. Median PFS (mPFS) and median OS (mOS) were estimated using KM method. Results: As of June 1, 2024, a total of 69 pts received SOC BsAbs for r/r LBCL (43 epcor and 26 glofi). Forty pts (58.0%) were male; median age was 66 years (range 32-89); ECOG >= 3 in 14 (20.3%) pts; transformed indolent lymphoma in 20 (29.0%); Richter transformation in 3 (4.4%); HGBL with MYC/BCL2 rearrangements (double-hit lymphoma [DHL]) in 12 (17.4%); bulky disease>10cm in 33 (47.8%); IPI score >= 4 in 15 (21.7%). Pts received a median of 3 prior LOT (range 2-12); 46 (66.7%) had primary refractory disease; 40 (58.0%) received prior CD19 CAR-T therapy; 35 pts (50.7%) would not have met the inclusion criteria of the pivotal trials due to: ECOG>=3 (n=14), thrombocytopenia (n=11), neutropenia (n=2), CNS involvement (n=6), recent infection (n=6), prior CAR-T within 30 days (n=1), and CrCL<45 (n=2). Among the 69 pts, 65 were evaluable for response. At a median follow up of 7 months, the ORR and CRR were 52.3% and 26.2%, respectively. Median PFS was 4.2 months (m) (95%CI: 2.8-6.9). Median OS was 6.2m (95%CI: 5.9-not reached [NR]). The ORRs in pts without prior CAR-T (CART-naive), progressed after achieving CR/PR to prior CAR-T (CART-R), and not achieving CR/PR to prior CAR-T (CART-NR) were 13/25 (52.0%), 18/24 (75%), and 3/16 (18.8%), respectively, p<0.01. In the UVA of ORR, the following factors were associated with lower response: CART-NR (18.8% vs 63.3%, p<0.01) and ECOG >=3 (21.4% vs 60.8%, p=0.01). Bulky disease, IPI >=4, DHL, >=4 prior lines of therapy, DLBCL subtype or BsAb type was not associated with response. In MVA, only CART-NR was a significant predictor of lack of response to BsAb (odds ratio 5.6, 95%CI: 1.3-24). In the UVA of PFS, CART-NR and ECOG >=3 were associated with shorter mPFS (1.9m [95%CI: 0.6-3] vs 5.4m [95%CI: 4.0-NR] in CAR-T non-responders vs responders; 1.1m [95%CI: 0.4-3.2] vs 5.4m [95%CI: 3.2-NR] in ECOG>=3 vs <3). In the MVA, CART-NR and ECOG>=3 were associate with shorter PFS (HR 2.7, p<0.01 and 2.5, p<0.02, respectively). One of the 3 pts with Richter transformation had continuous PR at 5 months. Cytokine release syndrome (CRS) occurred in 21 pts (36.2%), including 4 (5.8%) grade (Gr) >= 3. Immune effector cell-associated neurotoxicity syndrome (ICANS) occurred in 12 pts (17.4%) with 6 (8.7%) Gr >= 3. Gr3-4 neutropenia was observed in 18 pts (26.1%); Gr3-4 thrombocytopenia in 10 (14.5%). Infection all grades and Gr >= 3 occurred in 26 pts (37.7%) and 19 pts (27.5%), respectively. Among them, bacterial infection was identified in 13, COVID in 5, fungal in 2, and CMV in 1 patient. Conclusion: BsAbs had comparable efficacy in SOC setting as in the pivotal trials. CRS and ICANS were mostly low-grade; however, a high incidence of serious infection was observed. Pts with no response to prior CAR-T also had poor BsAbs response. This could reflect a common mechanism of resistance to immunotherapy, either due to tumor characteristics or host T-cell exhaustion. Longer follow-up is needed to evaluate the durability of response.

INTRODUCTION Atrial fibrillation (AFib) is a recognized complication in patients with chronic lymphocytic leukemia (CLL) treated with Bruton tyrosine kinase inhibitors (BTKis). Early detection and management of AFib are critical due to its association with increased morbidity and mortality. Traditional detection methods, such as intermittent EKGs and wearable devices, often capture only brief snapshots of cardiac activity, potentially missing episodes. Recent advances in artificial intelligence (AI) have enabled the development of algorithms that analyze electrocardiograms (EKGs) to predict AFib risk. These algorithms can potentially identify patients with undetected AFib and assess risk at a single point, reducing the need for continuous monitoring. This study evaluates the utility of an AI-enabled EKG algorithm in predicting AFib in patients with CLL treated with ibrutinib and acalabrutinib. METHODS Patients with CLL treated with ibrutinib and acalabrutinib were identified from a single-center database. Patients with CLL who received BTKi therapy at Mayo Clinic between 2015 and 2024 with available EKGs in the EMR were included. Patients were excluded if they received BTKi for non-CLL indications or if patients with CLL had documented AFib without accompanying EKGs in their medical records. An AI-enabled EKG algorithm developed by Attia et al. (Lancet, 2019) was used to estimate AFib probability (AFibAI). EKGs were categorized into pre-treatment, during treatment, and post-treatment phases. Mean values of all EKGs within each phase were used for analysis to reduce heterogeneity. Paired t-test was used for continuous variables and ROC analysis was used to evaluate diagnostic performance. A p-value of <0.05 was used for statistical analysis. RESULTS The analysis included 383 individual CLL patients (74% male, median age71; ace/ethnicity not available), of which 79 were treated with acalabrutinib and 304 with ibrutinib, with a total of 5844 EKGs analyzed. The AFibAI was significantly higher in EKGs with documented AFib compared to other EKGs, mostly normal sinus rhythm (0.5710 vs. 0.1857, p <0.001). Pre-treatment AFibAI was higher in patients who ultimately developed AFib after starting BTKi treatment compared to those who did not. Mean AFibAI at baseline was 0.2176 for those who developed AFib and 0.0986 for those who did not (p <0.001; difference between means: -0.1191 +/- 0.02005, 95% CI: 0.-0.1585 - 0.0796). Differences of baseline AFibAI were similar when stratified by BTKi. Trends in AFibAI scores indicated a significant increase during and after BTKi treatment in patients who developed AFib, with mean score of 0.2176 at baseline to 0.4064 post-treatment (p<0.001). In patients who did not develop Afib during BTKi therapy, there was minimal increase of AFibAI scores from 0.1041 at baseline to 0.1620 post-treatment (p = 0.0002). The ROC analysis showed an area under the curve of 0.7280 (SE = 0.03911, 95% CI: 0.6514 to 0.8047, p <0.001), indicating fair discriminatory ability. The sensitivity at the optimal threshold (0.1202) was 65.45% and the specificity was 74.59%, with a Youden's Index of 0.4004. To achieve a sensitivity of ≥90% for detecting patients who ultimately develop AFib, a threshold of 0.2368 was established (specificity of 41.82%). DISCUSSION Our study demonstrates the efficacy of an AI-enabled EKG algorithm in estimating atrial fibrillation risk among CLL patients treated with BTKis. We demonstrated that baseline AFibAI was notably higher in patients who ultimately developed AFib, suggesting that it could potentially identify patients at elevated risk before the onset of AFib. Early identification would allow for closer monitoring and timely intervention, potentially mitigating complications. Pending validation with an external cohort, the 90% sensitivity threshold could help identify the patients at highest risk, where other treatment options could be considered. The trend across different treatment phases revealed a significant increase in scores during treatment, indicating that AFibAI is responsive to changes induced by BTKi therapy and suggest its utility for patient monitoring. Practical questions remain about its impact on clinical decision-making and management. Future prospective studies should confirm the validity of identifying high-risk patients and its role in both treatment decisions and patient outcomes.

Introduction: Acute kidney injury (AKI) due to cast nephropathy is a medical emergency that leads to a diagnosis of myeloma in less than 3% of cases, but up to 30% of patients develop kidney impairment during the course of their disease. Currently, studies aiming to identify parameters that correlate with kidney function recovery and response to myeloma are limited due to small sample size or single center reports. We have therefore initiated an international collaboration and collected a large number patients (pts) from 16 participating centers. Objectives: To assess the impact of pts and disease characteristics and treatment-specific factors on renal outcome and overall survival and to validate the IMWG criteria for renal response in pts with cast nephropathy and newly diagnosed MM. Patients and Methods: Three-hundred forty-three pts (median age: 65.5 range 35-93 yrs) with newly diagnosed MM and an eGFR <40ml/min/1.73m2 have been selected from 704 pts that had been enrolled in the database hosted by RedCap. Eligibility criteria were a diagnosis of AKI due to cast nephropathy diagnosed either by kidney biopsy (n=119) or on clinical criteria (AKI in the setting of involved free light chain concentration of ≥500 mg/L), newly diagnosed multiple myeloma, >2 cycles of therapy, time and type of therapy, best eGFR and best myeloma response available. Results: Median follow up was 36.9 months. Myeloma therapy resulted in renal CR, and PR as defined by the IMWG criteria in 131 (38.2%) and 57 (16.6%) pts, respectively, 54 (15.7%) and 82 (23.9%) pts had minor response or no response, respectively. Nineteen (5.5%) pts were not classifiable by the IMWG response criteria (pts with eGFR 15-<30, with increase to eGFR to ≥30-<40). An eGFR of >60, ≥30-<60, ≥15-<30, and <15ml/min was achieved by 131 (38.2%), 112 (32.7%), 67 (19.5%), and 33 (9.6%) pts respectively. Myeloma response (≥VGPR) correlated significantly with renal response (≥PRrenal) (OR 1.64, CI 1.05-2.56, p=0.03) and with OS compared to no myeloma response (median 89.7 vs. 39.7 months, HR 2.12, CI 1.55-2.89, p<0.0001). A >50% reduction in FLCs from baseline to treatment cycle 2 (OR 5.92, CI 2.15-19.23, p=0.001) and cycle 3 (OR 5.25, CI 2.15-19.25, p=0.006) were strongly associated with renal response Median OS was 69.6 months (CI 55.4-89.7). Forty-three pts died within the first 12 months of treatment and additional 146 during further FU. Pts with a best GFR of >15ml/min had a significantly longer OS compared to those with GFR <15ml/min (median: 77.9 vs 31.9 months, HR 1.85, CI 1.16-2.94, p=0.01). The comparison of survival of pts with different renal response groups and with the best eGFR showed no statistically significant difference (log rank p=0.1, long rank p=0.057, respectively). Other factors that correlated with longer OS were bortezomib-based therapy (77.9 vs. 44.0 months, HR 1.59, CI 1.05-2.38, p=0.03), M-protein isotype with κ as compared to l light chain type (84.9 vs. 51.4 months, HR 1.47, CI 1.09-2.00, p=0.013), and higher hemoglobin (HR 1.16, CI 1.06-1.26, p=0.001). In contrast, hypercalcemia which was noted in 101 (29.4%) pts (HR 1.10, CI 1.03-1.18, p=0.005), ISS stage III vs. I-II (57.8 vs. 126.2 months, HR 2.26, CI 1.22-4.17, p=0.009), and ECOG status 3+4 vs. 2 vs. 0+1 (24.4 vs. 44.6 vs. 103 months, HR 2.83, CI 2.15-3.74, p<0.0001) were associated with shorter OS. Hypercalcemia, correlated with renal response (OR 1.27, CI 1.12-1.44, p=0.0002), and best eGFR ≥46.4 ml/min (median dichotomized) (OR 1.28, CI 1.14-1.46, p<0.0001). 119 (34.7%) pts required initial dialysis, OS was significantly longer in those who achieved best eGFR levels of >15ml/min. (77.6 vs 31.9 months, HR 0.54, CI 0.34-0.86, p=0.01); 64 (53%) pts discontinued dialysis. Conclusion: Myeloma response correlated with renal response as defined by IMWG criteria. A >50% reduction in FLCs from baseline to treatment cycle ≥2 was strongly associated with renal response. OS was longer in pts with renal response, in pts receiving bortezomib-based therapy, and in pts with kappa light chain M-proteins. Hypercalcemia was frequent (29.4%), and associated with higher renal response rate and best eGFR, but shorter OS. Pts on dialysis who achieved eGFR >15ml/min had better survival. Fast diagnostic work up, rapid treatment initiation and achieving significant myeloma response (≥VGPR) is essential to prevent irreversible kidney damage. Including novel immunotherapies may further improve outcome.

Background : Maintaining oxygen delivery during conditions of hypoxia is important, particularly for patients with hemoglobinopathies.Evidence in comparative physiology indicates that high hemoglobin-oxygen (Hb-O2) affinity serves as a beneficial hematological adaptation to chronic hypoxia exposure. The improved hypoxia tolerance is likely due to an increase in arterial oxygen saturation with high Hb-O2 affinity. However, the relationship between high Hb-O2 affinity and hypoxia tolerance in humans is not well understood. Etavopivat is a potent, selective, once-daily, oral activator of the red blood cell (RBC) pyruvate kinase isozyme (PKR), with a half-life of ~13 hours, under investigation for the treatment of sickle cell disease (SCD) and other hematological conditions. Etavopivat has a multimodal mechanism of action in RBCs by decreasing 2,3-diphosphoglycerate (2,3-DPG) levels to increase Hb-O2 affinity and increasing adenosine triphosphate (ATP) levels to improve RBC health. In Phase 1 trials etavopivat increased Hb-O2 affinity in healthy volunteers (HVs; Forsyth et al. Clin Pharmacol Drug Dev 2022) and patients with SCD (Saraf et al. Blood Adv 2024) in room air. Aim: To investigate arterial oxygenation changes with etavopivat under conditions of moderate and severe hypoxia in HVs. Methods: HVs visited the laboratory for assessments at baseline and following 7 days of etavopivat exposure (400 mg once daily). Participants completed rhythmic handgrip exercises (rest, 10% and 20% maximum voluntary contraction [MVC]) during graded hypoxic exposure, breathing room air (21% O2), moderate hypoxic gas (15% O2), and severe hypoxic gas (10% O2), resulting in acute duration (~12 minutes) of exposure to each level of hypoxia. Hb-O2 affinity was assessed by partial pressure of oxygen at 50% Hb saturation (P50), measured using dual-wavelength spectrophotometry at a standardized pH (~7.4) and temperature (37 ºC). Arterial catheterization was used to collect samples for fractional oxygen saturation (FO2Hb) and Hb and to measure arterial blood pressure. Blood gases were analyzed after 5 minutes of resting exposure to each inspirate, then ~2.5 minutes after commencing each of the 3-minute handgrip exercises (10% followed by 20% MVC). Liquid chromatography-tandem mass spectrometry was used to evaluate 2,3-DPG and ATP levels in whole blood. Data for FO2Hb and heart rate were analyzed using separate repeated measures 2 (treatment) x 3 (intensity) ANOVA for each inspirate and all other hematological data pre vs post etavopivat were analyzed using paired-sample t-tests. Statistical significance was set at P<0.05. Data presented are mean ± standard deviation. Results: Sixteen HVs (five women) aged 32 ±8 years were enrolled. After 7 days of oral once-daily 400 mg etavopivat, P50 decreased from 28.6 ±1.6 at baseline to 24.8 ±1.3 mmHg (P<0.001). Hb concentration remained unchanged from baseline (14.6 ±1.1 g/dL), post etavopivat (14.5 ±1.1 g/dL; P>0.05). FO2Hb at rest decreased from 96.0% ±0.6 under normal oxygen conditions to 74.6% ±6.7 during severe hypoxic exposure; however, this decrease in FO2Hb was mitigated post etavopivat exposure (79.7% ±5.2, P<0.001). A similar mitigation of the FO2Hb decrease was observed during the handgrip exercise (20% MVC, P<0.001). Concentrations of 2,3-DPG decreased and RBC ATP increased following etavopivat exposure during both normoxia and moderate hypoxia (P<0.001). Mean arterial pressure was lower post etavopivat exposure under normoxia, but not during moderate or severe hypoxia. Heart rate showed no change post etavopivat exposure during normoxia and hypoxia (P>0.50). Etavopivat was well tolerated with no unexpected adverse events reported. Conclusions: Etavopivat enhanced FO2Hb during brief hypoxic episodes with an apparent relationship to hypoxia severity for which the greatest improvements were observed at more severe hypoxic exposure. In SCD, high Hb-O2 affinity is beneficial for maintaining Hb ‘R’ state, thereby reducing the risk of polymerization and associated sickling. Increased Hb-O2 affinity, together with maintenance of a high FO2Hb under hypoxic conditions, demonstrates etavopivat's ability to promote oxygen exchange and subsequent delivery. Together with projected improvement of RBC health, also achieved via PKR activation, this indicates a potential clinical benefit with etavopivat for hemoglobinopathies and beyond.

Background Venetoclax + hypomethylating agent (Ven-HMA) therapy results in favorable response rates (CR/CRi 66%) and overall survival (OS; median 14.7 months) in unfit patients with newly-diagnosed acute myeloid leukemia (ND-AML; N Engl J Med 2020;383). However, there is substantial heterogeneity in individual patient outcomes based on response to treatment. The objective of the current study was to develop a genetic risk model to predict survival outcome in treatment responders and non-responders, analyzed separately, and also account for allogeneic stem cell transplant (ASCT). Methods Treatment-naïve AML patients receiving Ven-HMA, outside of a clinical trial, at the Mayo Clinic, USA (MN, AZ, FL) were retrospectively recruited. Molecular studies (48-gene panel) were performed by next-generation sequencing. Response was assessed according to the 2022 European LeukemiaNet (ELN) criteria (Blood 2022;140). Standard statistical analyses were performed using JMP Pro (Version 17.0.0). Results 400 ND-AML patients (median age 73 years, 64% male, 60% de novo) received Ven-HMA. ELN cytogenetic risk included favorable 2%, intermediate 60%, or adverse 38%. Mutations involved TP53 in 26%, TET2 19%, RUNX1 19%, SRSF2 18%, ASXL1 18%, DNMT3A 15%, K/NRAS 13%, NPM1 12%, IDH2 12%, FLT3-ITD 10%, IDH1 7% and DDX41 in 4% of informative cases. 153 (38%) patients achieved CR, 94 (24%) CR with incomplete count recovery (CRi), resulting in CR/CRi in 247 (62%) patients. CR/CRi rates were higher with NPM1 (86% vs 59%), IDH2 (77% vs 60%), and DDX41 mutations (93% vs 61%) and lower with TP53 (45% vs 67%), FLT3-ITD (41% vs 64%), RUNX1 (49% vs 65%) mutations and adverse karyotype (48% vs 71%), with all retaining significance in multivariable analysis. CR/CRi rate was highest (87%) in 75 patients with one or more favorable mutations (NPM1, IDH2, DDX41) and no unfavorable mutation (TP53, FLT3-ITD, RUNX1). CR/CRi rate was lowest in 171 patients with at least one unfavorable mutation and no favorable mutation (44%; p<0.01). After a median follow up of 10.5 months (0.5-66), 105 relapses (43% of patients in CR/CRi), 248 (62%) deaths and 65 (16%) ASCT were documented. Univariate analysis for transplant-censored OS disclosed superior survival in patients achieving CR/CRi (median 21 vs 3.6 months; HR 5.4, 95% CI 4.1-7.1). Among patients achieving CR/CRi, IDH2 mutation was associated with superior (median not reached vs 20.5 months) and male gender (median 17.6 vs 29.2 months), TP53 mutations (median 11.9 vs 24.3 months) and adverse karyotype (median 12.6 vs 29.4 months) with inferior survival; multivariable analysis resulted in HRs (95% CI) of 2.1 (1.3-3.4) for male gender, 2.1 (1.2-3.8) for adverse karyotype, and 2.5 (1.1-5.7) for absence of IDH2 mutations. Male gender did not show an association with karyotype, or TP53 mutations (p>0.1). Accordingly, an HR-weighted genetic risk model was generated with assignment of one point each to male gender, adverse karyotype, and absence of IDH2 mutation: high risk = 3 risk factors (n=38; median 9.6 months; 3-year survival 0%); intermediate risk = 2 risk factors (n=129; median 22 months; 3-year survival 38%); and low-risk = ≤1 risk factor (n=78; median not reached; 3-year survival 69%; p<0.01). In patients bridged to ASCT (n=60), post-transplant survival was inferior in the presence of ≥ 2 risk factors (n=42; median 46 months) vs. ≤1 risk factor (n=18; median not reached; p=0.1). In patients not achieving CR/CRi, risk factors for OS included male gender (median 3.4 vs 6.1 months), adverse karyotype (median 3.3 vs 4.5 months) and TP53 mutation (median 3.1 vs 4.5 months) while those with IDH2 mutations lived longer (median 8.4 vs 3.4 months). In multivariable analysis, HRs (95% CI) were 1.9 (1.3-2.9) for male gender, 2.0 (1.4-2.9) for adverse karyotype, and 2.1 (1.1-4.3) for absence of IDH2 mutations. OS was shortest for non-responders harboring 3 risk factors (n=45; median 3 months; 1-year survival 0%) and longer for those harboring two (n=80; median 6 months, 1-year OS 15%) or ≤ 1 risk factor (n=25; median 14 months; 1-year OS 56%; p<0.01). Conclusion The current study describes a molecular profile for predicting response to Ven-HMA in ND-AML and also introduces a novel approach to survival prediction that considers treatment response as the starting point. In both responders and non-responders, male gender and adverse karyotype were identified as unfavorable and IDH2 mutation favorable risk factor for OS.

Background: Anaplastic large cell lymphomas represent a group of T-cell lymphomas that have long been broadly classified by the presence or absence of ALK fusion proteins (ALK+ or ALK−, respectively). However, recent discovery of extensive additional molecular heterogeneity has both promoted refinement of disease classification and uncovered new opportunities for biomarker-guided targeted therapy. In addition to recognition of a new genetic subtype, ALK− ALCL with DUSP22 rearrangement (R), a new molecular classification has been proposed based on the recent discovery of 2 overarching molecular types of ALCL, defined by the presence (Type I) or absence (Type II) of a gene expression signature highly enriched for JAK-STAT3 activation. BCL2 is a mitochondrial membrane protein that functions to inhibit the actions of pro-apoptotic proteins such as BAX and BAK and can be targeted clinically by BCL2 small molecule inhibitors. BCL2 has been reported to be expressed more frequently in ALK− ALCL than in ALK+ ALCL, but its expression in the context of current molecular findings is unknown. Methods: ALCLs were centrally reviewed and classified by current WHO/ICC criteria. BCL2 was performed using IHC and scored as positive if ≥30% of tumor cells showed staining. DUSP22-R was assessed by fluorescence in situ hybridization (FISH) using a breakapart probe set and a dual-color, dual-fusion (D) probe set for the most common DUSP22 translocation, t(6;7)(p25.3;q32.3). pSTAT3Y705 IHC, which is >90% accurate for Type I/II assignment based on gene expression, was performed and scored based on a previously validated cut-off of ≥30%. Results: We evaluated 217 ALCLs (148M/69F; age: mean, 57 y; range, 5-93 y), including 55 systemic ALK+ ALCLs, 127 systemic ALK− ALCLs, and 35 primary cutaneous (pc) ALCLs. Overall, 86/217 cases were positive for BCL2 (40%). BCL2 was positive in 67/127 ALK− ALCLs (53%) and 15/35 pcALCLs (43%; P=NS), but in only 4/51 ALK+ (7%; P<0.0001). DUSP22-R was present in 90 cases (63 ALK− ALCL and 27 pcALCL). BCL2 was positive in 57/90 cases with DUSP22-R (63%) compared to 29/127 without DUSP22-R (23%; P<0.0001). Among 85 cases with DUSP22-R and informative D-FISH testing, BCL2 was positive in 24/36 cases with t(6;7)(p25.3;q32.3) (67%) and 31/49 cases without t(6;7)(p25.3;q32.3) (63%; P=NS). Among 213 cases with informative pSTAT3Y705 staining, BCL2 was positive in 13/88 pSTAT3+ cases (Type I, 15%) and 70/125 pSTAT3− cases (Type II, 56%; P<0.0001). Conclusions: We identified a complex pattern of BCL2 expression across ALCLs that strongly correlates with a recently introduced molecular classification based on gene expression profiling. While our findings are in keeping with the previously reported low expression in ALK+ ALCL, we found that the higher expression in both systemic ALK− ALCL and pcALCL is particularly associated with DUSP22-R and the absence of pSTAT3Y705 expression (Type II ALCLs). The discovery of 2 overarching types of ALCL associated with the presence or absence JAK-STAT3 pathway activation represents a new conceptual framework for classifying ALCL and understanding its therapeutic vulnerabilities. Of note, previous data demonstrated that Type II ALCLs are enriched for epigenetic alterations and particularly overexpress the histone methyltransferase EZH2. Correlation between BCL2 expression and EZH2 expression also is observed in other lymphomas such as diffuse large B-cell lymphoma, where dual targeting with EZH2 and BCL2 inhibitors has been proposed. Thus, our findings provide further rationale for stratifying Type I and Type II ALCLs and identify BCL2 as a differentially expressed oncoprotein that might represent a target for precision therapy approaches.

Introduction: Telomere biology disorders (TBD) are multisystemic accelerated aging syndromes due to abnormal telomere length (TL) shortening and increased cancer risk. Pediatric-onset TBD is characterized by severely shortened TL and specific associations with germline pathogenic variants mainly in DKC1, TINF2, PARN genes and characteristic clinical features [bone marrow failure (BMF), abnormal nail/skin/oral mucosa]. Adult-onset TBD is genetically distinct (predominantly, TERT, TERC, and RTEL1 mutations) with varied organ involvement [interstitial lung disease (ILD), BMF, cirrhosis, or bone disease] and heterogenous outcomes. In our previous study of predominantly adult patients with short telomeres, multiple organ involvement (Mangaonkar A et al. Blood Cancer J 2021) predicted poor overall survival (OS). We sought to validate these findings in a larger, well annotated adult cohort of TBD patients. Methods: Patients with suspected TBD underwent comprehensive clinical and molecular evaluation through our TBD-dedicated clinic after regulatory approval. TL was assessed through clinical flow cytometry fluorescence in-situ hybridization (FlowFISH).Clinical and laboratory features, including pulmonary imaging, lung volumes/function testing, hepatic imaging (MR elastography/fibroscan) and bone density assessments were retrospectively abstracted. Germline and somatic genetic testing was performed on peripheral blood through targeted panels for known TBD and myeloid genes respectively. Cox proportional hazard model was used to identify significant variables that also retained independent prognostic impact. Results: Overall, 122 patients met criteria for TBD as defined by lymphocyte TL (LTL) <=10th percentile and/or a presence of a germline-TBD variant; 34 patients LTL <1st percentile, 84 1st and the 10th percentile (27 with TBD-germline variants) and 4 with only TBD-germline variants. Median age at diagnosis was 56 (18-77) years, with 72 (59%) males. Clinical features included presence of ILD (n=81, 66%), BMF (n=39, 32%), cirrhosis/hepatic fibrosis (n=19, 38%), bone disease osteopenia/osteoporosis/fractures, n=53, 70%), MDS/AML (n=11, 9%), non-hematological cancer (n=38, 31%), and head and neck cancer (n=2). Germline pathogenic variants were detected in 22 (18%), most frequently in TERT (n=10), RTEL1 (n=7) and TERC (n=2), while variants of uncertain significance (VUS) were seen in 35 (29%) patients, especially in TERT (n=20), TERC/RTEL1(n=6), NAF1 (n=4). Somatic variants in hematopoietic cells were detected in 37 (30%) patients with frequent alterations seen in DNA damage response and repair (PPM1D/TP53, n=11), and splicing component (U2AF1/SF3B1/ZRSR2, n=9) genes. At last follow-up [median of 3 (0-18) years], there were 26 (21%) deaths (most commonly, progressive ILD-18, cancer of lung/breast/pancreas-3, transplant-related complications-2). After censoring patients at the time of any transplantation (lung transplant-26, liver transplant-5, bone marrow transplant-8), the Kaplan-Meier estimate of median OS was not reached. Univariate survival analysis found adverse OS predicted by older age at diagnosis (P=0.006), presence of ILD (P=0.0002), hepatic fibrosis/cirrhosis (P=0.02), and somatic DNA repair variants (P=0.03). Multivariate model analysis found that only presence of ILD retained independent prognostic impact (HR=2, P=0.02). Among radiographic ILD subtypes, UIP was the most common (51%), followed by NSIP (10%), and others (6%), with median FEV1 of 2L (range: 0.5-4.6), FVC 2.4L (0.7-6.2), and TLC 4L (1.9-7.4). TBD-ILD patients were older (P<0.0001) with a male preponderance (P=0.03), 52 (64%) with multi-organ involvement, and had a less severe hematological phenotype [lower incidence of BMF (P<0.0001) and fetal hemoglobin elevation (P=0.01)], more frequent bone disease (P=0.0009), relatively longer telomeres in lymphocytes (P=0.04), and no particular association with any germline or somatic genetic alterations. Conclusions: Presence of ILD is an independent and significant predictor of adverse survival in adult TBD. Within adult TBD, patients with ILD represent a unique clinical subtype without any obvious genetic or pathologic correlates. Focusing on definitive therapeutic measures in this subgroup of adult TBD has the best chance to alter natural history and improve outcomes.

Introduction The tumor ecosystem in multiple myeloma (MM) involves complex interactions among various cell types, including clonal plasma cells (PCs) and immune cells. Previous research has indicated that the bone marrow (BM) microenvironment's metabolite and lipid profiles differ between MM patients and those with precursor conditions. This study aims to explore if differences in cell composition, metabolic phenotype of clonal PCs, and the spatial organization of various cell types are linked to the early versus late progression of high-risk smoldering MM (SMM) to MM. Methods We identified high-risk SMM patients using the IMWG 20-2-20 criteria, focusing on early progressors (EP), who progressed to MM within one year, and later progressors (LP), who progressed after more than four years. Using a high-dimensional single-cell spatial imaging platform, CODEX (CO-Detection by indEXing), we identified clonal PCs and immune cell types as well as their metabolic phenotypes at the single-cell level, in paired FFPE BM samples at SMM diagnosis and at the time of progression to MM. Our validated panel included markers such as CD3e, CD4, CD8, CD14, CD20, CD31, CD38, CD45, CD66a, CD68, CD138, HLA-DR, ASCT2, pNRF2, GLUT1, LDHA, ATPA5, CPT1A, and Citrate synthase. We employed single-cell segmentation, artifact cleanup, signal thresholding, and spatial analysis. Repeated measure models accommodated multiple regions of interest (ROIs) per patient and accounted for potential intrapatient correlation, while Poisson models estimated incidence rate ratios (RR) of cell types. Spatial statistical models evaluated cell type segregation and integration at the time of SMM diagnosis. Results Single cell events were acquired from 6 unique SMM patients who had paired FFPE BM samples from the time of their SMM diagnosis and at the time of their progression to MM. There were 3 EP SMM patients (Time to Progression (TTP):8, 8, 10 mos) and 3 LP SMM patients (TTP: 51, 58, 117 mos). The median number of single cell events identified per patient slide sample was 104,390 (Range: 24,357 - 314,877). We identified 8 main cell types: PCs, CD4+ T-cells, CD8+ T-cells, B-cells, granulocytes, Monocyte/Macrophages and two groups of other immune cells. The PCs and the remainder of the non-PCs were further classified based on the expression of the following metabolic markers: ASCT2 (Glutamine importer), CPT1A (Fatty acid metabolism), GLUT1 (Glucose importer), LDHA (Glycolysis), Citrate synthase and ATPA5 (Oxidative Phosphorylation). There was a higher RR of granulocytes (RR 2.1, CI 1.6-2.8, p<0.001) in EP compared to LP samples at the time of SMM diagnosis, but a lower RR of CD4 T cells (RR 0.40, CI 0.3-0.6, p< 0.001). Focusing on metabolic phenotypes of the PCs, we observed higher incidence RR of most metabolic markers: ASCT2 (RR=1.77; p=0.032), ATPA5 (RR=1.25; p<0.001), CPT1a (RR=2.42; p=0.015), and LDHA (RR 2.13; p<0.001) in EP compared to LP samples at the time of SMM diagnosis. However, GLUT1 had a lower incidence RR in EP patients (RR=0.79; p<0.001). The same modeling for non-PCs at the time of SMM diagnosis yielded higher expression of LDHA (RR=1.98; p<0.001) and ASCT2 (RR=3.3; p=0.002). Using the x and y coordinates and the corresponding phenotype classifications, we performed spatial statistical modeling based on spatial point processes to generate aggregated measures of how different types of cells of interest interacted. CD4 T cells were more isolated in LPs compared to EPs (p =0.046). Segregation indices for PCs and CD4 T cells indicated that they were more integrated/collocated in EPs. Granulocytes were more isolated in EPs although the difference was not as pronounced (p= 0.07). PCs were more integrated with granulocytes (p=0.06) and B cells (p=0.07) in LP patients. Further analyses of paired samples at the time of progression to MM will be reported at the time of the presentation. Conclusion This study is the first to provide whole-slide, single-cell, spatial proteomic characterization of clonal PCs and immune cells in the FFPE BMs of high-risk SMM patients with varying progression times to MM. Distinct metabolic pathway markers in clonal PCs and their spatial relationships with immune cell subsets are closely associated with the risk of progression to MM. These findings illuminate the complex interactions between the metabolic states of clonal PCs and their spatial orientation relative to immune cells in the pathogenesis of MM.

Background and significance: Paroxysmal nocturnal hemoglobinuria (PNH) is a rare condition caused by a somatic mutation in the PIG-A gene, leading to complement-mediated hemolysis and severe complications such as anemia and thrombosis. Patients often experience fatigue, dyspnea, and abdominal pain, impacting their daily lives and emotional well-being. This study aims to comprehensively explore the impact of PNH on health-related quality of life (HRQoL), alongside real-world treatment utilization and symptom burden patterns, especially as new treatments become available to this patient population. These results are based on interim baseline data from currently enrolled study participants, providing an initial assessment of their PNH disease experience. This analysis does not include any data collected prospectively during the data collection period. Study design and methods: This ongoing, prospective, observational study (NCT06411626) aims to enroll at least 128 US-based participants aged 18 or older with PNH, regardless of treatment usage. Participants are recruited through clinician-based referrals, patient advocacy organizations, and community-based online channels. All activities can be completed remotely using the Folia Health app, the single site for this study. This app-based study aims to comprehensively assess patient-reported symptom burden, treatment use patterns, and impacts of PNH on health and FACIT-Fatigue through self-reported home-reported outcomes (HROs). Participants will track symptoms and treatment use, including recently approved treatments (e.g., iptacopan, danicopan, crovalimab). HROs consist of participants' self-identified symptoms and personalized treatment plan that are tracked longitudinally against self-reported baselines. Semi-structured interviews and collaborative feedback sessions with PNH patients and clinicians yielded a comprehensive outcomes inventory for tracking key health outcomes specific to PNH. This inventory includes the ability to track infusion treatments and denote flare-ups in fatigue. Participants can customize their data collection to track symptoms in additional domains beyond those initially suggested (e.g., respiratory or immune). At enrollment, participants report baseline health status and select their relevant symptoms and treatments to routinely track for 6 months. Monthly in-app surveys will collect data on overall health and the FACIT- Fatigue. The Folia app allows participants to visualize symptoms trends, set treatment reminders, and generate reports for their care team. Results: Enrollment began on June 11, 2024. As of July 22, 2024, an interim data analysis was conducted on 20 participants; 65% (n=13) enrolled through online community-based channels and 35% (n=7) enrolled through clinic referrals. Participants selected 37 distinct symptoms and measurements and 26 distinct treatments to track over the 6-month period. The most common symptoms selected at baseline include fatigue (n=19), brain fog (n=17), and dark colored urine (n=15). PNH treatments selected for tracking include iptacopan (n=9), ravulizumab (n=5), eculizumab (n=4), and pegcetacoplan (n=3). The mean baseline FACIT- Fatigue score (n=18) was 35.7 and the median was 40 (IQR= 16). Further descriptive analyses stratified by primary treatment use will be conducted assessing characteristics of symptom burden, satisfaction with treatments-in-use, and self-reported impact on HRQoL. Conclusions: Initial interim baseline data of recently enrolled participants with PNH show a variable disease experience. This app-based, observational study aims to establish a new real-world data source to understand patient priorities related to symptom variability, treatment patterns and preference, and impacts of condition management on HRQoL.

Background: In 2015 the first B-cell acute lymphoblastic leukemia (B-ALL) patient receiving CAR T-cell therapy in Europe was reported to the EBMT registry. Today, the EBMT registry counts with more than 9000 patients treated with CAR T-cell therapies across all indications. Here, on behalf of the GoCART coalition, we present the outcomes of the largest European cohort of B-ALL patients treated with autologous, second generation, CD19-targeted CAR T-cells to date. Methods: Adult and paediatric patients with B-ALL received treatment with CAR T-cell therapy using either academic or commercially available products in 40 centres across 17 different countries. Safety was retrospectively assessed as per ASCTC 2019 consensus grading and CTCAE, and efficacy as per NCCN guidelines. Relapse incidence was defined as haematological relapse or progression after CART with non-relapse mortality as competing event. Leukemia free survival (LFS) was defined as being alive without occurrence of relapse. Follow-up includes patients treated from 2016 to Dec 2023 until data cutoff in June 2024. Results: A total of 345 patients (173 adults and 172 pediatrics) received therapy from 2016 to 2023 with tisagenlecleucel (65.2%), varnimcabtagene autoleucel (25.8%), brexucabtagene autoleucel (5.5%), and others (3.5%). Median age at infusion was 18 yrs. (range, 1.1-78.2) and 41.7% were females. High-risk features were identified including cytogenetic/genomic high-risk as per ELN guidelines (33.8%), relapse after allo-HCT (57.7%), early relapse (<1 year) after prior allo-HCT (30.4%), ≥3 prior treatment lines (55.5%) including prior exposure (and refractoriness) to blinatumomab and inotuzumab in 27.3% (34%) and 28.8% (32.3%), respectively. Median time from diagnosis to CART infusion was 2.8 years (0.1-17.9). Median time from last relapse prior CART to infusion was 2 months (range, 0.9-38.4). Bridging therapy was administered in 86.4% (298) of patients based on high or low intensity chemotherapy (32.1% or 26.5%, respectively), inotuzumab-ozogamicin (13.4%), TKI (8.2%), involved-site therapy (intrathecal chemotherapy, radiotherapy, orchiectomy) (3.5%), and blinatumomab (2.6%), alone or in combination. Prior to infusion, 34.7% had more than 5% BM blast count, 16.3% had circulating blasts in PB, and 20.6% had extramedullary disease. Lymphodepletion was performed in all but one patient, based on fludarabine and cyclophosphamide regimens. The reverse Kaplan-Meier median follow-up was of 2.2 years. The incidence of any grade (and severe) CRS was 71.6% (14.5%), and for ICANS was 15.7% (7.6%). The cumulative incidence of MRD-negative CR at month +3 was 76.9% (71.9-81.1), followed by a 2-year overall survival of 64.6% (58.7-69.8), leukemia-free survival of 48% (42.1-53.7), and relapse incidence of 45.5% (39.6-51.2). Non-relapse mortality at 2 years was 6.5% (4-9.6), 2-year cumulative incidence of subsequent HSCT of 33.3% (28-38.7) and second CAR-T infusions of 12.4% (8.8-16.6). Allogeneic HSCT after CAR-T was performed in 113 cases including 67 (59.3%) HSCT-naïve patients, due to molecular or overt disease relapse (60.9%), and other non-relapse reasons including suboptimal CAR-T persistence/B-cell aplasia (19.1%), pre-CAR-T high-risk features (13.6%), second malignancies (1.8%), and others. Second CAR-T infusions were performed in 39 cases due to molecular or overt disease relapse (79.5%) or suboptimal CAR-T persistence/B-cell aplasia in the absence of relapse (20.5%). Conclusions: The results from this European study demonstrate that CD19-targeted CAR T-cell therapy is an effective treatment for patients with high-risk B-cell ALL, providing substantial leukemia-free survival and overall survival rates despite the high-risk nature of the patient population. The necessity for bridging therapies and subsequent consolidative approaches, such as HSCT and second CAR T infusions, underscores the complexity and tailored nature of managing R/R B-ALL. These findings support the continued use and further investigation of CAR T-cell therapy in diverse clinical settings, emphasizing the importance of post-infusion strategies to sustain long-term remission. This will provide deeper insights into the factors influencing outcomes and help refine treatment protocols to improve patient care.