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Introduction: Myelodysplastic syndromes (MDS) occur due to the acquisition of mutational events over time. Tobacco smoking is a risk factor for MDS and has been associated with distinct genetic mutations in solid cancers. We investigated the association between smoking intensity and duration and the number and types of genetic mutations in MDS using a large prospective cohort. Methods: The prospective NHLBI/NCI National MDS Natural History Study includes individuals with suspected or recently diagnosed MDS enrolled between June 2016-August 2023. Patient (Pt) bone marrow samples underwent central pathology review, resulting in diagnoses including MDS, MDS/myeloproliferative neoplasm overlap (MDS/MPN), or precursor conditions, such as clonal cytopenia of undetermined significance (CCUS). Self-reported smoking data were collected at enrollment. Smoking intensity (i.e., light, medium, and heavy) was defined per CDC definitions. Included mutations were those manually annotated to be pathogenic for MDS. Mutation frequency and prevalence, as well as associations with smoking history and other key covariates, were assessed using univariate tests of association and multivariable regression models for counts and proportions. Rates of disease progression were compared between groups using survival analysis methods for cumulative incidence incorporating non-disease death as a competing risk. Results: Of 1898 evaluable pts, 52% (N=979) had a history of cigarette smoking [MDS: 58% (252/436), MDS/MPN: 57% (52/91), CCUS: 57% (230/405)], and 18% still smoked at diagnosis. The mean ± SD cigarettes per day was 15.8 ± 12.5 and the mean ± SD smoking years was 29.8 ± 16.9 years. Compared to non-smokers, smokers were more often males (68% v 54%, p<0.001) in the 70-79 year age group (45% v 34%, p<0.001). Similar proportions of those with and without a smoking history had MDS (41% v 37%, respectively). Within MDS, there was no association between smoking and MDS prognostic risk per revised international prognostic scoring system. Compared to light smokers [1-10 pack-years (PY)], heavy smokers (30+ PY) were more often male (81% v 62%, p<0.001) and had higher rates of cardiovascular disease (38% v 20%, p<0.001). In univariate analyses, smokers and non-smokers had similar numbers of mutations (mean ± SD: 2.0 ± 2.7 in both groups). Pts with CCUS had the least number of mutations (1.5 ± 1.2), followed by MDS (2.3 ± 1.8), and MDS/MPN overlap (3.3 ± 1.8). Within disease groups, smokers and non-smokers had similar numbers of mutations. Mutation prevalence was higher among smokers v non-smokers in gene pathways for chromatin modification (15% v 11%, p<0.01) and RNA splicing (26% v 19%, p<0.001) and for individual genes ASXL1 (12% v 8%, p<0.01), SF3B1 (9% v 6%, p<0.05), U2AF1 (6% v 3%, p<0.05) and ZRSR2 (2% v 1%, p<0.05). In multivariable regression models, after adjustment for sex, age and disease group, smokers had significantly more mutations on average than non-smokers (2.0 v. 1.4, p=0.04). Moreover, the number of mutations increased significantly with PY smoked (p=0.006), and those at the 75th and 90th percentiles of PY had 1.8 and 3.5 times the number of mutations, respectively, compared to non-smokers, indicating a dose-response relationship. After adjustment, mutation prevalence increased with PY smoked in the gene pathways for chromatin modification and RNA splicing (p<0.03 for both) and for the genes ASXL1 and ETNK1 (p<0.05 in both cases). The five-year cumulative incidence of disease progression was significantly higher among long-term smokers compared to non-smokers/those with shorter smoking history (mean [95% CI] proportion progressed, 20+ years vs <20 years smoking: 27% [19%-36%] vs 18% [13%-24%], p < 0.05). Overall survival was significantly lower for smokers compared to non-smokers for CCUS pts [HR 1.91, 95% CI (1.03-3.55), p=0.04] but not for MDS [HR 1.21, 95% CI (0.53-1.30), p=0.41]. Conclusions: In this prospective, national cohort, tobacco smoking was associated with distinct genetic mutations related to MDS, suggesting smoking potentially contributes to its multi-step molecular pathogenesis. A dose-response relationship was also demonstrated, as was an association with progression and survival. Our data suggest that pts with a new MDS diagnosis who are also smokers should be counseled to stop smoking, as it appears to contribute to the acquisition of new genetic mutations that can lead to progression.

Background: The rising incidence of PCNSL in the elderly represents an unmet need with an undefined standard approach [Villano Br J Cancer 2011]. High-dose methotrexate-based (HD-MTX) therapy is feasible and effective in older patients, but outcomes in this population remain poor. Despite high response rates to HD-MTX induction therapy, poor candidacy for intensive consolidative therapy results in transient disease control that may benefit from maintenance strategies [David Am J Hematol 2023]. Lenalidomide (len) has demonstrated activity in PCNSL even at low doses and represents a potential alternative to consolidation considering its extensive use in maintenance settings [Vu Br J Haematol 2019]. Anecdotal activity in PCNSL by checkpoint inhibitors such as nivolumab (nivo) has been reported [Nayak Blood 2017], and its immune response may be enhanced by len [Görgün Clin Cancer Res 2015]. A051901 evaluates the feasibility of the addition of len and nivo to rituximab (R) and HD-MTX as first line induction therapy followed by len-nivo maintenance in elderly patients with PCNSL not eligible for intensive consolidation. Study Design and Methods: This is a single-arm phase 1 multicenter US study (NCT04609046) conducted by the Alliance for Clinical Trials in Oncology with a traditional 3+3 design. Eligible patients are 18 years of age or older with untreated diffuse large B-cell lymphoma PCNSL diagnosed through brain biopsy or resection, or cerebrospinal (CSF) or vitreous fluid not considered candidates for high dose chemotherapy consolidation. This study is available to all eligible patients, regardless of race, gender, or ethnic origin. Patients must have adequate end-organ function including creatinine clearance of at least 50 mL/min. Use of systemic corticosteroids for disease control to be tapered after initiation of therapy is allowed. Induction consists of six 14-day cycles with rituximab 500 mg/m2 i.v. on day 1, HD-MTX 3g/m2 i.v. on day 2. In the most recent treatment schedule, a 5-day course of lenalidomide PO at different dose levels (dose level (DL) 1 = 10 mg, DL2 = 15 mg, DL3 = 20 mg) is initiated immediately after adequate clearance of HD-MTX. Once a maximum tolerated dose (MTD) of len is defined, a subsequent cohort will evaluate the addition of nivo 240 mg i.v. to the day 14 of the induction cycle of R-HD-MTX plus len at the MTD. Patients who present any clinical benefit from induction with at least stable disease by International PCNSL Collaborative Group response criteria are eligible for maintenance - twelve 28-day cycles of therapy with len 15 mg PO from day 1 to day 21 (regardless of dose during induction) +/- nivo 480 mg i.v. on day 1 (for those who received len and nivo during induction). The primary endpoint of the induction therapy is the MTD of len when given in combination with R-HD-MTX; the primary endpoint of maintenance is its feasibility, defined as the proportion of patients able to remain on maintenance for at least 6 cycles. As of July 2024, 16 patients have been enrolled with a maximum expected sample size of 47 patients with the assumption of 75% of patients being eligible to proceed with maintenance and 50% of those who begin maintenance not progressing in the first 6 cycles. Overall response, adverse events, progression-free and overall survival will be evaluated in all eligible patients with a focus on the outcome of patients treated at the MTD. For patients who consent to biobanking, diagnostic tissue, peripheral blood and CSF from different timepoints are collected and banked with planned exploratory analyses including whole exome sequencing, circulating tumor DNA, proteomics, metabolomics. Support: U10CA180821, U10CA180882. https://acknowledgments.alliancefound.org.

Background and Significance Diffuse large B-cell lymphoma (DLBCL) and other LBCLs account for 35-40% of non-Hodgkin lymphoma cases in North America, Europe, and East Asia. Rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP), typically administered for 6 cycles, is the standard therapy for DLBCL and is curative in ~60-70% of patients (pts). However, 30-40% of pts have relapsed/refractory (RR) DLBCL following treatment with R-CHOP, with poor clinical outcomes. International Prognostic Index (IPI) scores of 3-5 are used to identify high-risk (HR) pts who are more likely to be RR following treatment. Additionally, pts with IPI scores of 1-2 who also have bulky disease and/or very high lactate dehydrogenase levels (LDH), have been identified as a HR subset with similar outcomes to pts with an IPI score of 3 (Maurer et al. ASH 2023, #4512). First-line therapy represents the greatest opportunity to address the unmet need for these pts. Golcadomide (GOLCA) is a potential first-in-class oral cereblon E3 ligase modulator (CELMoD™) agent purposefully designed for the treatment of lymphoma. GOLCA co-opts cereblon to induce targeted degradation of the transcription factors Ikaros/Aiolos, inducing deep, rapid, and extensive tumor killing, independent of cell of origin, and enhanced immunostimulatory activity. In the phase 1b study CC-220-DLBCL-001, GOLCA combined with R-CHOP was well tolerated, showing promising activity and combinability with high rates of durable responses irrespective of cell of origin in pts with previously untreated aggressive BCL, including those with HR disease (Hoffmann et al. EHA 2024, S235). Additionally, GOLCA has shown encouraging efficacy and safety profiles in pts with RR DLBCL, both as a monotherapy (Michot et al. ICML 2023, P90) and in combination with rituximab (Chavez et al. ASH 2023, P4496). The efficacy and safety data observed in early-phase studies suggest promising activity and a manageable safety profile. This supports further investigation of the GOLCA + R-CHOP combination in the phase 3 setting. Here, we present the study design of GOLSEEK-1, a multicenter, randomized, double-blind, placebo-controlled phase 3 study (NCT06356129) comparing the efficacy and safety of GOLCA + R-CHOP vs placebo + R-CHOP in pts with previously untreated HR LBCL. Study Design and Methods Approximately 850 pts with previously untreated LBCL will be randomized 1:1 to either GOLCA + R-CHOP or placebo + R-CHOP. Pts must have a histologically confirmed diagnosis of LBCL according to WHO 2022 classification, including: DLBCL, not otherwise specified (NOS) including ABC and GCB subtypes; high-grade B-cell lymphoma with MYC and BCL2 rearrangements, or NOS; T-cell/histiocyte-rich LBCL; Epstein-Barr Virus-Positive DLBCL. Other key inclusion criteria include an IPI score of 1 or 2 considered HR (LDH > 1.3 × upper limit of normal and/or bulky disease, defined as a single lesion of ≥ 7 cm [Maurer et al. ASH 2023, #4512]), or IPI score ≥ 3; and measurable disease as defined by the Lugano classification. Key exclusion criteria include other lymphoma subtypes such as primary mediastinal LBCL; primary cutaneous DLBCL-leg type, grade 3b follicular lymphoma (FL); transformed indolent lymphoma; anaplastic lymphoma kinase (ALK)-positive LBCL; primary effusion lymphoma; and Burkitt lymphoma, as well as documented or suspected central nervous system involvement. Randomization will be stratified by IPI score (1-2 with risk factors and 3 vs 4-5) and bulky disease (> 7 cm vs ≤ 7 cm). After a screening period of ≤ 4 weeks, pts will receive GOLCA (0.4 mg) or placebo orally once daily for 7 consecutive days in each of 6 cycles in combination with R-CHOP in 21-day cycles. The primary endpoint of this study is progression-free survival (PFS) in untreated HR LBCL, assessed by investigator based on the Lugano Response Criteria. Key secondary endpoints include PFS in untreated non-high-grade BCL, event-free survival in pts with untreated HR LBCL, independently assessed complete metabolic response rate, undetectable minimal residual disease by PhasED-Seq (defined as undetectable circulating tumor DNA levels at treatment end), and overall survival. Patient follow-up will occur for up to approximately 67 months after beginning treatment. This study is recruiting at 293 sites in 37 countries, across the United States, Europe, Latin America, and East Asia.

Background and Significance: Systemic mastocytosis (SM) is a rare heterogeneous disease characterized by the aberrant accumulation of neoplastic mast cells (MC). In about 95% of adult patients, SM is driven by a gain-of-function mutation (D816V) in exon 17 of KIT. Advanced SM (AdvSM) is a life-threatening form of SM and includes three subtypes: aggressive SM (ASM), SM with an associated hematologic neoplasm (SM-AHN), and mast cell leukemia (MCL). Despite improvement in disease control with approval of tyrosine kinase inhibitors (TKIs), there is still unmet need for improved tolerability and efficacy in AdvSM treatments. Bezuclastinib, an oral and selective type 1 TKI that potently inhibits KIT D816V, is being studied in patients diagnosed with AdvSM in the Apex study (NCT04996875). Results from the Part 1 dose optimization portion of Apex were presented previously. Part 1 randomized 32 patients 1:1:1:1 to receive bezuclastinib at 50, 100, or 200 mg BID or 400 mg QD. Initial results from the Part 1 dose optimization portion of the Apex trial in patients with AdvSM demonstrated encouraging safety profile and signs of clinical activity, as well as deep reductions across biomarkers of MC burden including bone marrow MC burden, serum tryptase levels, and KIT D816V variant allele fraction (VAF). In addition, 94%, 93%, and 100% of patients demonstrated ≥50% reduction in serum tryptase, KIT D816V VAF, and bone marrow MC burden, respectively. Exposure achieved with 100 mg BID of bezuclastinib original formulation resulted in optimal efficacy and safety outcomes. 150 mg QD of an optimized formulation is expected to deliver bezuclastinib exposures consistent with the 100 mg BID of the original formulation. Part 2 is further evaluating the efficacy and safety of bezuclastinib in patients with AdvSM at the selected Part 2 dose of 150mg QD of the optimized formulation. Study Design and Methods: Apex is a multicenter, Phase 2 open-label study of bezuclastinib in patients with AdvSM as defined per the WHO criteria. Enrollment includes previously treated and treatment-naïve patients. Part 2 is enrolling approximately 65 patients including up to 15 patients without measurable mIWG C-findings. The Part 2 expansion portion of the Apex study is designed to evaluate the efficacy and safety of bezuclastinib in patients with AdvSM, including ASM, SM-AHN, or MCL. Key eligibility criteria include measurable disease (centrally adjudicated) according to modified IWG-MRT-ECNM criteria and clinically acceptable laboratory values including platelet count ≥50,000/µL. The primary efficacy endpoint of Part 2 is overall response rate (ORR = complete response [CR] + complete remission with partial hematologic recovery [CRh] + partial response [PR] + clinical improvement [CI]) per mIWG-MRT-ECNM criteria according to mIWG-MRT-ECNM response criteria and will be confirmed by a Central Response Review Committee. Secondary endpoints include further characterization of safety and tolerability, pure pathologic response, biomarker response (including changes in bone marrow MC burden, serum tryptase level, and KIT D816V mutational burden), duration of response, time to response, progression-free survival, and overall survival (OS). Apex Part 2 is actively enrolling. Study sites are enrolling in North America, Asia-Pacific, and Europe. In addition, a high-risk SM-AHN sub-study assessing the safety and feasibility of the combination of bezuclastinib 150 mg QD and azacitidine may enroll up to 20 patients who are currently receiving or indicated for azacitidine and have biopsy-proven SM with an associated high- or very high-risk myeloid neoplasm. Patients with SM-AHN from Part 1 or Part 2 who have demonstrated AHN progression may enroll in an additional rollover cohort to receive bezuclastinib with concomitant azacitidine or hydroxyurea.

Background Mantle cell lymphoma (MCL) is more common in males, with a male to female ratio of approximately 3:1. However, it is unclear whether disease characteristics and survival outcomes differ by sex. Additionally, the impact of race and ethnicity in MCL is understudied due to underrepresentation of minorities in clinical studies and trials. In this study, we utilized the National Cancer Database (NCDB) to examine patient and disease characteristics and survival outcomes of MCL by sex, race and ethnicity. Methods Patients diagnosed with MCL in 2004-2020 were identified from NCDB. Patient and disease characteristics were compared between groups using Chi-squared tests. Overall survival (OS) analysis was performed using the Kaplan-Meier method and the Cox proportional hazards model. Results A total of 35,135 patients was included. The median follow-up was 83.0 months (95% CI 81.9-84.1). 24,980 (71.1%) patients were male and 10,155 (28.9%) were female. Females had more elderly (age ≥65: 65.9% vs 59.0%; p<0.001), lower Charlson-Deyo Score (CDS ≥2: 7.0% vs 8.6%; p<0.001) and fewer stage III-IV diagnoses (80.5% vs 82.6%; p<0.001). Females were less likely to receive upfront treatment (80.7% vs 85.3%; p<0.001), treatment at academic centers (36.8% vs 40.9%; p<0.001) or transplant (11.0% vs 13.7%; p<0.001). Compared to males, females were more likely to live in metropolitan areas (83.7% vs 81.6%; p<0.001), had similar incomes, had more Medicare (60.4% vs 53.1%) and fewer private insurance (33.2% vs 38.6%; p<0.001). Female patients had better OS, with a median OS of 76.0 (95% CI 72.4-79.6) vs 67.8 months (95% CI 65.9-69.6; p<0.001). In the multivariable Cox model adjusting for age, race, ethnicity, CDS, stage, upfront treatment (vs surveillance or no treatment), facility (academic vs nonacademic), transplant, residence (metropolitan vs urban or rural) and insurance, female sex remained associated with superior OS (HR 0.84, 95% CI 0.793-0.890; p<0.001). For race, 32,399 (92.2%) patients were White, 1,465 (4.2%) were Black, 942 (2.7%) were others and 329 (0.9%) were unknown. Compared to White patients, Black patients had fewer elderly (52.9% vs 61.7%; p<0.001), higher CDS (≥2: 11.4% vs 7.9%; p<0.001), similar stage III-IV (80.7% vs 82.1%; p=0.276) and upfront treatment (84.7% vs 84.0%; p=0.074), were more likely to be treated at academic centers (50.6% vs 38.9%; p<0.001), were less likely to receive transplant (11.1% vs 13.0%; p=0.042), were more likely to live in metropolitan areas (91.0% vs 81.5%; p<0.001), had lower income, had more uninsured (4.4% vs 2.0%) and Medicaid (9.8% vs 3.7%) and fewer Medicare (47.4% vs 56.0%; p<0.001). Black and White patients had similar OS, with a median of 67.9 (95% CI 57.5-78.2) vs 69.6 months (95% CI 67.8 vs 71.3; p=0.697). In the multivariable Cox model, Black vs White race was not associated with OS (HR 1.086, 95% CI 0.952-1.240; p=0.219). For ethnicity, 31,717 (90.3%) patients were non-Hispanic, 1,894 (5.4%) were Hispanic and 1,534 (4.3%) were unknown. Hispanics had fewer elderly (51.3% vs 61.5%; p<0.001), lower CDS (≥2: 6.4% vs 8.2%; p=0.018), similar stage III-IV (81.2% vs 82.1%; p=0.467), were more likely to receive upfront treatment (86.0% vs 83.9%; p<0.001), more likely to be treated at academic centers (49.9% vs 39.5%; p<0.001), equally likely to receive transplant (13.0% vs 13.1%; p=0.943), more likely to live in metropolitan areas (95.4% vs 81.6%; p<0.001), had lower income, had more uninsured (9.6% vs 1.8%) and Medicaid (15.2% vs 9.6%) and fewer Medicare (40.3% vs 55.9%; p<0.001). Hispanics had better OS, with a median OS of 84.4 (95% CI 71.7-97.1) vs 70.5 months (95% CI 68.7-72.2; p<0.001). However, in the multivariable Cox model, Hispanic ethnicity was not associated with OS (HR 0.952, 95% CI 0.839-1.080; p=0.448). Conclusion This study is the first of its scale to demonstrate that female MCL patients have superior survival outcomes compared to males. It also demonstrated that neither Black race nor Hispanic ethnicity appears to be associated with worse survival outcomes. Despite its size, the NCDB is limited in the treatment information and disease characteristics it provides, including MIPI score, Ki-67, blastoid/pleomorphic morphology, and TP53 status. Thus, additional real-world dataset studies are needed to gain a deeper understanding of potential differences in sex, race and ethnicity with regards to disease characteristics and survival outcomes.

Background In 2013, we published the first International Working Group (IWG) risk model for survival in polycythemia vera (PV), which included 3-tiered age categories, leukocytosis (≥15 x 109/L), and venous thrombosis, as risk variables (Leukemia. 2013;27:1874). In the current study, we examined the individual prognostic contribution from specific leukocyte components and mutations, in order to construct a more contemporary clinical risk model in PV and assess its interaction with genetic risk factors. Methods Study patients were retrospectively recruited from the Mayo Clinic, USA (N=1,007) and the University of Florence, Italy (N=514), in order to serve as discovery and validation cohorts, respectively. Diagnostic criteria were according to the International Consensus Classification (Blood 2022;140:1200). Mutations were screened by next-generation sequencing (NGS). Conventional statistical methods were employed (JMP Pro 17.0.0, SAS Institute, Cary, NC, USA) and optimal cut-points for age, absolute neutrophil (ANC), lymphocyte (ALC), and monocyte (AMC) counts were determined by Receiver Operating Characteristic (ROC) analysis. Akaike Information Criterion (AIC) and ROC plots were used to estimate predictive accuracy. Results Presenting features in the Mayo discovery cohort (N=1,007) included: median age 62.2 years; males 50.7%; median leukocyte count 10.8 x 109/L; leukocyte count ≥15 x 109/L 19%; palpable splenomegaly 32%; pruritus 34%; diabetes 16%; hypertension 61%; arterial thrombosis 14%; and venous thrombosis 14%. ANC, AMC, and ALC information was available in 736 patients with respective median (range) values of 7.6 (1.6-30), 0.6 (0-4.1), and 1.54 (0.19-6.9) x 109/L. At a median follow-up of 8.9 years for the Mayo discovery cohort, 372 (37%) deaths, 46 (4.6%) leukemic transformations, and 200 (20%) fibrotic progressions were recorded. Multivariable analysis (MVA) employing ROC-determined cutoff values revealed adverse survival impact for age >70 years (HR 18.3; p<0.01), age 50-70 years (HR 4.9; p<0.01), AMC ≥0.8 x 109/L (HR 1.5; p<0.01), ANC ≥8 x 109/L (HR 1.5; p<0.01), arterial thrombosis (HR 1.5; p<0.01), diabetes (HR 1.4; p=0.04), and male sex (HR 1.3; p=0.05). A similar MVA applied to the Florence validation cohort (N=514) confirmed significance for age (p<0.01), ANC (p<0.01), AMC (p=0.04), and arterial thrombosis (p<0.01), but not for male sex (p=0.8) or diabetes (p=0.15). Accordingly, age >70 years (4 points), age 50-70 years (2 points), ANC ≥8 x 109/L (1 point), AMC ≥0.8 x 109/L (1 point), and AT (1 point) were included in a revised IWG survival model using the Mayo cohort and validated by the Florence cohort: very low risk (0 points; N=67; median 37 years), low risk (1 point; N=55; median 29.2 years), intermediate risk (2-3 points; N=308; median 20.2 years), high risk (4-5 points; N=217; median 11.5 years), and very high risk (6-7 points; N=88; median 6.3 years). 20-year survival prediction performance of the revised IWG model (AIC 204; AUC 0.88) was superior to that of the 2013 IWG version (AIC 350; AUC 0.86). Mutation information at diagnosis/chronic phase was available in 270 Mayo patients: ASXL1 10%; SRSF2 4%, IDH2 2%, TP53 2%, RUNX1 1.4%. MVA of mutations identified SRSF2 (p<0.01), IDH2 (p=0.01), and ASXL1 (p=0.05), as risk factors for overall survival. The presence of any one adverse mutation was more likely in patients with AMC ≥0.8 x 109/L (24% vs. 7% incidence; p<0.01). In all-inclusive MVA, independent risk factors for OS were age >70 years (HR 14.7), age 50-70 years (HR 6.2), any one adverse mutation (HR 3.4), and ANC ≥8 x 109/L (HR 2.3), but not AMC ≥0.8 x 109/L (p=0.9), arterial thrombosis (p=0.24), or abnormal karyotype (p=0.4). Leukemia-free survival was adversely affected by SRSF2, RUNX1, TP53, and ASXL1 mutations and myelofibrosis-free survival by SRSF2 mutation. Conclusions: The currently proposed revised IWG risk model for survival in PV is globally applicable and based on four easily accessible clinical variables (Age, ANC, AMC, and arterial thrombosis). NGS-derived mutation information overshadows the prognostic relevance of monocytosis, provides additional prognostic information for overall survival, and assists in predicting leukemic and fibrotic transformations.

Introduction: Laboratory identification of a lupus anticoagulant (LAC) requires evidence of: a) prolongation of a phospholipid-dependent screening test, usually a LAC-responsive dilute Russell's viper venom time (DRVVT) or activated partial thromboplastin time (APTT); b) inhibition on mixing with normal pooled plasma (NPP); c) confirmation of phospholipid-dependent inhibition by repeating the prolonged test with excess phospholipid. Despite decades of assay development and re-design and numerous attempts at standardization, diagnosis of a LAC remains challenging due to the heterogeneity of antiphospholipid antibodies, the marked variations in reagents, inconsistencies in post-analytic processes, and not least, the multitude of interferences, such as anticoagulant drugs, which influence test results. Guidelines recommend interruption of anticoagulation, if possible, prior to LAC testing to prevent obtaining false test results. While this is attempted in some instances for direct-acting anticoagulants, it is typically not considered for warfarin, and it is also not always possible. Our laboratory has observed a concerning pattern of potentially false-negative DRVVT screen/ confirm ratios in samples collected from patients on warfarin anticoagulation or with a factor deficiency (e.g. hypoprothrombinemia). The goal of this study is to replicate this observation using in vitro dilution experiments, mixing LAC-positive samples with either NPP or warfarin plasma. Methods: DRVVT Screen, Mix and Confirm assays (Precision Biologic, Dartmouth, NS) were performed using archived LAC-positive plasmas from 5 unique patients not on anticoagulation, and titered with normal pooled plasma (NPP) (Precision Biologic, Dartmouth, NS) to a screen/confirm ratio of 1.20-1.35, near the assay cutoff for DRVVTC (<1.20) and analyzed on the ACL TOP 750 (Werfen, Bedford, MA). Warfarin donor plasma was then mixed in the same dilution scheme with each of the LAC-positive plasmas so that the final dilution factors for LAC-NPP and LAC-Warfarin contrived samples were the same. The DRVVT screen/ confirm ratios of the LAC-NPP and LAC-Warfarin plasma contrived samples were compared. Additionally, a DRVVT Mix Screen and Mix Confirm were performed after mixing in a 1:1 ratio with NPP. Results: The average prothrombin time (PT) in the LAC-Warfarin samples was significantly longer than the LAC-NPP samples (20.7±8.5s vs 10.6±0.2s, p=0.03). All 5 LAC-NPP contrived samples had a positive DRVVT screen/ confirm ratio >1.20, while all of the LAC-Warfarin contrived samples had a negative DRVVT screen/ confirm ratio (1.26±0.04 vs 1.02±0.11, p<0.01). When the DRVVT screening time was divided by the DRVVT Mix Confirm time, 4 of the 5 LAC-Warfarin contrived samples reverted to positive using a cutoff of 1.20 (values of 1.30, 1.21, 1.21, 1.02 and 1.23 for LAC-Warfarin samples) and a similar pattern was observed with the LAC-NPP samples (values of 1.32, 1.29, 1.27, 1.14, 1.27, respectively, for LAC-NPP samples). Conclusion: This study confirms our anecdotal observation that warfarin and/ or factor deficiencies in the common pathway can result in a false-negative DRVVT screen/ confirm ratio using the Precision Biologic LA Sure and LA Check reagents, similar to findings described for apixaban. The DRVVT assay is widely considered to be the most sensitive or responsive to LAC and this in vitro observation raises questions about whether negative DRVVT screen/ confirm ratios can reliably be used to exclude the presence of a LAC in patients on warfarin using this reagent system. Larger studies are required using pre-treatment and on-treatment paired specimens to confirm these findings, and to further explore the utility of the DRVVT Screen/Mix Confirm ratio in this patient population.

Introduction The pathogenic role of somatic non-coding (nc) single nucleotide variants (SNVs) is underexplored in multiple myeloma (MM) and additional characterization of these regions has the potential to provide significant new insights into disease progression. To investigate the role of ncSNVs and their relationship with MM pathogenesis, we have characterized a novel series of WGS from 294 cases of MGUS, SMM, and MM using computational tools optimized to identify functional driver SNVs in these regions. We hypothesize the ncSNVs that co-localize to sites of super-enhancers (SEs) active in plasma cells (PC) are sites of high functional impact SNVs and these mutations lead to the dysregulated expression of genes that should be silent at the terminally differentiated stage of PCs, providing a selective advantage that shapes the fitness of the MM genomic landscape. Methods We analyzed 294 high-coverage matched tumor/normal pairs (80x tumor and 40x normal) derived from 21 MGUS, 86 SMM, 167 NDMM and 40 RRMM. In addition to previously sequenced samples, newly sequenced patients were obtained from NYU Langone Health, Memorial Sloan Kettering Cancer Center, University of Alabama at Birmingham and University of Miami following IRB-approved informed consent. DNA was extracted from CD138+ purified bone marrow plasma cells using standard approaches. We used the MGP1000 (https://github.com/pblaney/mgp1000) to process sequencing data which employs a union-consensus mechanism for determining the final set of variants. We collected enhancer elements (E/SEs) active in GC B-cells, ABC-DLBCL and GBC-DLBCL (Bal, et al. Nature, 2022) and PC specific E/SEs (Loven, et al. Cell 2013). FunSeq2 was used to score ncSNVs. GRAM was used to predict how variants alter TF binding and gene expression in a subset of 6 cases with paired WGS in our series and will expand this analysis on a validation set of 263 NDMM and 93 RRMM cases from University-Hospital Heidelberg enrolled in the GMMG-HD6 clinical trial. Results We identified 1,952,232 high-quality SNVs with 18,199 (0.93%) accumulating in 280 focal sites we termed “mutationally enriched regions” or MERs. To discern SNVs in MERs with the highest potential for imparting a selective advantage, we clustered mutations based on the density of FunSeq2 impact scores which uses reference data contexts on sequence conservation, modification of transcription factor (TF) binding, and gene linkage to regulatory elements and network hubs from pan-cancer studies. We show that MERs are enriched for ncSNVs with high impact scores (mean=2.57) compared to random similarly-sized regions of the genome (Fisher's exact test P<9.7e-12, OR=10.10 [3.88-37.40]). The high impact ncSNVs (hi-ncSNVs) in MERs (n=220) account for 8.09% of all hi-ncSNVs and are present in 46.3% of cases (136/294) with some patients having up to 7. The proportion of cases carrying a MER hi-ncSNVs was similar across disease stages (MGUS=42.9%, SMM=46.5%, MM=40.7%, and RR=47.5%). Analysis of the VAF of MER hi-ncSNVs shows a minor shift towards more clonal versus subclonal mutations (53.6% vs 46.4% VAF>=0.25) suggesting some high impact mutations are acquired in the GC but additional hi-ncSNV are acquired later in PC development, providing evidence that hi-ncSNVs accumulate in MERs throughout disease progression. We mapped these hi-ncSNVs to associated genes then intersected the loci with E/SEs active in GCBs and PCs to determine their functional context. This approach identified 12 genes affected by hi-ncSNVs including the previously identified nc-drivers NEAT1, MIR142, ZCCHC7, and IGLL5 as well as the PC differentiation genes IRF8, BACH2, proliferation genes RHOH, SPRED2, known coding MM drivers CCND1, ZFP36L1, and chr1q genes BTG2 and CROCC. We predicted the effect of ncSNVs on expression through modulation of TF binding at this set of putative nc drivers in MM and identified a trend towards increase in expression of SPRED2, CCND1, NEAT1, and IGLL5 compared to non-mutated cases (P=0.089). We will present data on the validation of this set of genes on a larger set of data derived from the Heidelberg group. Conclusions We identified a set of 12 putative nc driver genes in MM that modify expression and have the potential to significantly alter the pathogenesis of MM by providing a selective survival advantage. We will present the impact of these by clinical stage and on outcome.

Introduction Venetoclax + rituximab resulted in a 2-year progression-free survival estimate of 85% in the mostly 2nd-line, post-chemotherapy setting of the MURANO clinical trial (Seymour NEJM 2018). Short remissions with venetoclax in patients (pts) with prior cBTKi treatment (tx) for CLL are reported. However, these cohorts have included heavily pre-treated pts. Here, we report outcomes with venetoclax-based regimens in a contemporary cohort with cBTKi-exposed CLL and no prior chemotherapy. Methods We conducted a retrospective study of pts who received venetoclax for relapsed CLL after prior cBTKi tx at Mayo Clinic and across 8 centers in France. Pts with any prior chemotherapy tx were excluded. Pts were grouped as cBTKi-resistant (CLL disease progression on cBTKi) and cBTKi-exposed (any prior cBTKi tx but without disease progression). Overall survival (OS) was analyzed as the time from initiation of venetoclax until date of death or last known to be alive. Time to next therapy or death (TTNTD) after venetoclax was defined as the time from venetoclax initiation until the earliest date of next tx or death. Cox proportional hazards regression models were used to estimate associations of factors with OS and TTNTD. Results A total of 85 pts received venetoclax, including: venetoclax monotherapy (n=13, 15%), venetoclax + rituximab (n=45, 53%), and venetoclax + obinutuzumab (n=27, 32%). Patient characteristics at the time of venetoclax start were as follows: median age 69 years (interquartile range [IQR] 62-77), 59 (69%) male, 45% (33/73 evaluated) with TP53 disruption (del(17p) or TP53 mutation), 82% (46/56 evaluated) with unmutated IGHV, and 41% (15/37 evaluated) with complex karyotype (CK; ≥3 clonal structural or numerical abnormalities on karyotype). The median prior lines of therapy was 1 (IQR 1, 2); 32 (38%) pts had received prior anti-CD20 monoclonal antibody and 8 (9%) pts had received 2 prior cBTKi. Prior cBTKi tx was stopped for a reason other than disease progression in 46 (54%) pts (cBTKi-exposed) and due to CLL progression in 39 (46%) pts (cBTKi-resistant). TP53 disruption, unmutated IGHV, and CK were more common in the cBTKi-resistant subgroup. Among pts with cBTKi-resistant CLL, 60% (12/20 evaluated) had a BTK and/or PLCG2 mutation. Median follow-up from start of venetoclax-based therapy was 20 months. The median TTNTD and OS for the entire cohort was 36 (95% CI 29-not evaluable [NE]) and 68 (95% CI 39-NE) months, respectively. Among the 46 pts with cBTKi-exposed CLL, the median duration of prior cBTKi tx was 6.7 months (IQR 1.8, 23.7). The median TTNTD and OS from venetoclax start were both 78 months in pts with cBTKi-exposed CLL. The 24-month TTNTD and OS estimates were 73% and 81%, respectively. Among the 39 pts with cBTKi-resistant CLL, the median duration of prior cBTKi tx was 42.3 months (IQR 23.4, 60.1). The median TTNTD from venetoclax start in pts with cBTKi-resistant CLL was 30 months. The 24-month TTNTD estimate was 65% in the cBTKi-resistant subgroup, 53% with venetoclax monotherapy (n=5), 62% with venetoclax + rituximab (n=30), and 100% venetoclax + obinutuzumab (n=4). The median OS from venetoclax initiation was 39 months overall in pts with cBTKi-resistant CLL. The 24-month OS estimate was 84% in the cBTKi-resistant subgroup overall, 53% with venetoclax monotherapy, 87% with venetoclax + rituximab, and 100% with venetoclax + obinutuzumab. On a univariate analysis in the whole cohort, only TP53 disruption was associated with shorter TTNTD (HR 2.23; 95% CI 1.02-4.87; P=0.04) and only older age was associated with shorter OS (HR 1.05; 95% CI 1.007-1.095, P=0.02). On a univariate analysis in the cBTKi-resistant subgroup, only TP53 disruption was associated with shorter TTNTD (HR 6.68; 95% CI 1.51-29.46; P=0.01) and OS (HR 7.95; 95% CI 1.02-61.97; P=0.04). Duration of prior cBTKi exposure (as a continuous variable) was not associated with survival outcomes in the cBTKi-resistant subgroup. Conclusions Pts with chemotherapy-naïve, cBTKi-treated CLL had worse than expected outcomes with venetoclax-based tx in a mostly 2nd-line tx cohort, particularly pts with cBTKi-resistant CLL. The frequency of high-risk disease features, shorter duration of disease control with their initial cBTKi tx, and small cohort size warrant caution in generalizing these results to all pts with cBTKi-resistant disease. Novel tx trial strategies in 1st- and 2nd-line settings remain a high priority for high-risk pts.

Background: Flow cytometry (FC) is widely utilized for the identification of minimal residual disease (MRD) in chronic lymphocytic leukemia (CLL), providing an essential laboratory indicator for prognostic assessment and therapeutic management. Unfortunately, the high level of expertise required, long manual analysis time, and complexity of FC data files limit the offering of this testing to selected reference laboratories. Methods: We developed an artificial intelligence (AI) pipeline to automatically enhance unaltered FC files, minimizing the expertise and manual analysis time needed to detect CLL MRD on a single-tube 10-color panel (CD5, CD19, CD20, CD22, CD38, CD43, CD45, CD200, kappa and lambda). Raw FC files corresponding to peripheral blood or bone marrow specimens from 166 CLL MRD positive cases (MRD < 5%, median = 0.17%, 122 patients), and 61 MRD-negative cases (45 patients) were processed through our CCADDAS (Clustering and Classification of All events, Dimensionality reduction, Downsampling and Aberrancy Scaling) pipeline on a cloud environment (Google Vertex AI). Automated processing steps included elimination of acquisition errors (FlowCut), state-of-the-art clustering (PARC), dimensionality reduction (UMAP), cluster-based anomaly detection compared to negative controls (15 bone marrow aspirates and 14 peripheral bloods), and cluster-informed downsampling with preservation of low-event subsets. In addition, a deep neural network (DNN) trained on expert-defined subpopulations from negative controls was included for automatic gating of normal subsets (Tensorflow v2). AI-enhanced data files were analyzed using a general purpose flow cytometry analysis software (Kaluza v 3.5, Beckman Coulter), and %MRD estimates compared to reported results based on expert analysis of original FC files. Results: Cluster-informed downsampling reduced the number of cells per case to be manually analyzed from 1.1 million to 165,010 cells on average (85% cellularity reduction); resulting in a smaller FC data file (from 62.1 MB to 15.2 MB; 75% data reduction). Importantly, low-level MRD events were adequately preserved after downsampling (median 100% retention for both MRD<0.01% and MRD 0.01-1%). True number of events were accurately estimated on gated subsets using an “upsampling factor” parameter [observed # events x mean (upsampling factor)]. Gating of normal subsets was completely automated using a DNN classifier parameter. Rapid identification of suspected MRD was aided by an AI-generated “aberrancy scale” parameter that discriminated CLL MRD (mean ± 2SD: 969 ± 144) from background B-lymphoid cells (mean ± 2SD: 395 ± 401) (p<0.0001) (AUC = 0.98), with a performance superior to CD5 (AUC = 0.93), CD20 (AUC = 0.83), CD43 (AUC = 0.8) and CD200 (AUC = 0.7). Immunoglobulin light chain-positive CLL MRD was visually identified on a pre-calculated UMAP plot as a single-colored cluster, after dual coloring for kappa and lambda. The use of AI-enhanced files reduced manual analysis time from 11.6 minutes (SD = 4.5) to 0.8 minutes (SD = 0.4) per case, on average (p < 0.01) (93% reduction). CLL MRD was detected in all positive cases above clinically relevant threshold (≥0.01%, as recommended by NCCN guidelines), and in 17 of 21 (81%) cases below this threshold, with excellent quantitative correlation with conventional analysis on original FC files (linear regression slope = 1.02, intercept = 0.001%, R squared = 0.98, P < 0.0001). Conclusion: We introduce a largely unsupervised AI pipeline that transforms raw CLL-MRD FC data into a markedly smaller, AI-annotated and software-agnostic FC file, including comparison to normal controls. This CCADDAS pipeline simplifies and accelerates detection of CLL-MRD in clinical diagnostics, reducing number of cells analyzed by 85% and manual analysis time by 93%, without impacting test performance. Moreover, CCADDAS can be utilized for any laboratory-developed CLL-MRD assay, and its small-sized export is compatible with any clinical FC software, computing platform and analysis strategy. Adoption of CCADDAS is likely to facilitate the implementation of CLL MRD FC analysis by more clinical laboratories.