Citations

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.

Introduction: Survival of children with relapsed/refractory (r/r) acute myeloid leukemia (AML), myelodysplastic syndromes (MDS) and juvenile myelomonocytic leukemia (JMML) remains dismal, and successful treatment approaches are limited. Myeloid leukemias frequently have high telomerase expression, and neoplastic progenitor cells have relatively shorter telomeres compared to normal tissues due to the balance between frequent malignant cell division and compensatory increased telomerase activity. In one study, the 5-year overall survival (OS) in children with AML and lower telomerase activity was 88% compared to 43% for those with higher activity, suggesting potential prognostic and therapeutic importance of telomerase in this population (Verstovsek Cancer 2003). Imetelstat is a first-in-class telomerase inhibitor approved by the FDA in 2024 for the treatment of adult patients with low-to-intermediate-1 risk myelodysplastic syndromes (LR-MDS) with transfusion-dependent anemia who are r/r/ineligible for erythropoiesis-stimulating agents. . Imetelstat has also been shown to drive AML cells into ferroptosis (Bruedigam Nature Cancer 2024). The Children's Oncology Group (COG) previously conducted the ADVL1112 Phase 1 study of imetelstat monotherapy in children with r/r solid tumors or lymphomas (Thompson CCR 2013). Imetelstat was administered intravenously on Days 1 and 8 of a 21-day cycle. The recommended phase 2 dose (RP2D) was 268 mg/m2. Imetelstat was well-tolerated with no grade >3 non-hematologic toxicities and one dose-limiting thrombocytopenia observed in a subject treated at the RP2D. In preclinical studies, imetelstat was active against leukemia stem cells in pediatric AML patient derived xenograft models (Barwe J Clin Med, 2022). Methods: PEPN2312 is an open-label, multi-center phase 1 study of imetelstat in combination with fludarabine/high dose cytarabine (FLA) for patients with AML in second or greater relapse, refractory to re-induction after first relapse, or r/r MDS or JMML (NCT06247787). The primary objective of this study is to estimate the maximum tolerated dose (MTD) and/or RP2D of imetelstat in combination with FLA in this patient population. Secondary objectives include toxicity assessment, pharmacokinetics, clinical response/minimal residual disease assessments per standard criteria, and OS. Exploratory analyses will be conducted to analyze telomerase activity in peripheral blood mononuclear cells, conduct pharmacodynamic studies, and evaluate any changes in cytogenetic and mutational abnormalities. Eligible patients must be between the ages of 1 to 18 at the time of study enrollment with Lansky/Karnofsky performance status of ≥50. Patients with leukemia must have platelet count >25,000/µL and hemoglobin >8 g/dL (transfusions allowed). Patients known to have a congenital bone marrow failure syndrome are excluded. This study will use the Rolling 6 design to estimate the MTD/RP2D. The starting dose of imetelstat (DL1) is 212 mg/m2 IV over 2 hours (80% of the single-agent RP2D) given on days 1 and 8 of a 28-day cycle in combination with FLA administered days 2-6. Premedication for infusion reactions with an antihistamine and corticosteroid are required prior to each dose of imetelstat. Patients may receive up to 2 cycles of therapy in the absence of progressive disease or unacceptable toxicity as graded by CTCAE version 5.0. Response assessment will be performed via morphology and central flow cytometry analysis for patients with AML and standard response criteria for patients with JMML or MDS (Niemeyer Haematologica 2015; Zeidan Blood 2023). One dose escalation to 268 mg/m2 (DL2) will be explored if DL1 is deemed safe. Intra-patient dose escalation is not permitted. Pharmacokinetic sampling will be performed during cycle 1. Once the MTD/RP2D is determined, further assessment of safety and preliminary activity of imetelstat and FLA chemotherapy will occur in an expansion cohort of up to 6 additional patients treated at the MTD/RP2D. PEPN2312 was activated in July 2024 and will enroll at 21 participating COG/PEP-CTN sites.

Introduction: Epcoritamab (Epcor) is a novel subcutaneous CD3xCD20 bispecific antibody (bsAb) that is currently approved as monotherapy for the treatment of adults with relapsed or refractory (R/R) large B-cell lymphoma after ≥2 systemic therapies. The combination of Epcor with standard treatment regimens has been shown to be safe and efficacious; Epcor in combination with gemcitabine and oxaliplatin (Epcor+GemOx) has provided deep and durable responses with favorable survival outcomes in a transplant-ineligible R/R diffuse large B-cell lymphoma (DLBCL) patient (pt) population, of which 99% were from the US and Europe (EPCORE NHL-2; NCT04663347). Another CD3xCD20 bsAb, intravenous glofitamab, has been studied in combination with gemcitabine and oxaliplatin (Glofi+GemOx) in the randomized STARGLO trial (NCT04408638) and demonstrated benefit over rituximab plus GemOx (R-GemOx), despite not demonstrating superiority over R-GemOx in patients from the US and Europe. In the absence of head-to-head data, this study used matching-adjusted indirect comparisons (MAICs) to assess the comparative efficacy of Epcor+GemOx vs R-GemOx and vs Glofi+GemOx. Methods: Individual pt-level data from EPCORE NHL-2 arm 5 and aggregated data from pts in each of the STARGLO arms were used to conduct an MAIC. Logistic propensity score models were used to weight Epcor+GemOx-treated pts to create matched cohorts with the R-GemOx and Glofi+GemOx arms separately. Weighting was conducted based on the distribution of baseline characteristics and prognostic factors such as age, sex, Eastern Cooperative Oncology Group performance status, previous therapies, and primary refractory status. Overall response rate (ORR), complete response (CR) rate, progression-free survival (PFS), and overall survival (OS) were compared for Epcor+GemOx vs R-GemOx, and vs Glofi+GemOx. Results: A total of 103 pts treated with Epcor+GemOx (median follow-up: 13.2 months) were compared to 91 pts treated with R-GemOx and 183 pts treated with Glofi+GemOx (median follow-up: 20.7 months), although differences in median follow-up time limited comparisons of longer-term survival outcomes. Match-adjustment mitigated differences in baseline characteristics across the 3 cohorts. After adjustment, Epcor+GemOx demonstrated a significant 44.8% advantage in ORR over R-GemOx (85.4% vs 40.7%), with a 110% increase in the likelihood of achieving a response (odds ratio [OR] 2.1; 95% CI 1.6-2.8; P<0.0001). Epcor+GemOx also demonstrated a significant 43.2% advantage in CR rate over R-GemOx (68.5% vs 25.3%), with a 170% increase in the likelihood of achieving a CR (OR 2.7; 95% CI 1.8-4.1; P<0.0001). With the current follow-up, Epcor+GemOx demonstrated superior PFS vs R-GemOx (hazard ratio [HR] 0.37; 95% CI 0.22-0.63; P<0.001), corresponding to a 63% reduction in the risk of progression. Median OS was not reached [NR] for Epcor+GemOx vs 13.9 months for R-GemOx, corresponding to a 43% reduction in the risk of mortality (HR 0.57 [95% CI 0.33-0.98]; P=0.04). After adjustment, Epcor+GemOx demonstrated a significant 15% advantage in ORR over Glofi+GemOx (83.3% vs 68.3%), with a 20% increase in the likelihood of achieving a response (OR 1.2; 95% CI 1.0-1.4; P=0.021). Epcor+GemOx demonstrated a trend toward higher CR rate than Glofi+GemOx (66.8% vs 58.5%; OR 1.1; 95% CI 0.90-1.5; P=0.277). Adjusted median PFS and OS for Epcor+GemOx, with limited follow-up and substantial censoring, was 12.9 months and NR, respectively. For Glofi+GemOx with longer follow-up, PFS and OS were 13.8 months and 25.6 months, respectively. Conclusions: Results show significantly superior efficacy for all outcomes with Epcor+GemOx vs R-GemOx from STARGLO. Epcor+GemOx also provided superior ORR and a trend toward higher CR rates vs Glofi+GemOx, indicating potential for better long-term efficacy outcomes. The Epcor+GemOx survival data are still maturing given shorter follow-up time, preventing a robust comparison of survival vs Glofi+GemOx. Findings support the efficacy of Epcor+GemOx as an alternative therapeutic regimen in transplant-ineligible patients with R/R DLBCL.

Introduction: The combination of chemotherapy and immunotherapy, commonly referred to as chemo-immunotherapy (CIT), has long been a cornerstone in the treatment of lymphoma. Although this approach has resulted in successful treatments for many patients (pts), a significant number continue to experience unfavorable results, underscoring the urgency for improved treatments. There is still a significant gap in knowledge about the immune profile of lymphoma pts, specifically in terms of (1) how their immune phenotype compare to those of healthy individuals and (2) how treatment affects their immune system. This study aimed to compare the immune profiles of lymphoma pts (at baseline) to that of matched healthy controls, and track the changes in the immune system during and after lymphoma treatment. Methods: Pts with newly diagnosed, untreated lymphoma, without prior history of cancer or autoimmunity were enrolled in the Dyna-RISC study. Whole blood samples were collected at baseline (BL), on day 1 of cycle 2 (C2D1), on day 1 of last cycle (CLD1), and 6 months after completion of therapy (6mo). Age- and gender-matched healthy individuals provided blood for baseline comparison. Samples were stained fresh with a pre-mixed lyophilized cocktail containing 30 metal-tagged monoclonal antibodies (Maxpar Direct Immune Profile Assay), fixed and cryopreserved. Samples were barcoded and acquired in batches on the Helios CyTOF (cytometry by time-of-flight) system. Cytometry data was analyzed using OMIQ. Differential abundance analysis was performed using relative frequencies of cell subsets (% of parent) using a false-discovery rate of 0.05 to account for multiple comparisons. Results: Between 11/2020 and 06/2021, 15 lymphoma pts were enrolled. Median age was 62 years (range 43-86), 5 pts (33%) were female. Five pts had follicular lymphoma (FL), 3 had diffuse large B-cell lymphoma (DLBCL),1 had primary mediastinal B-cell lymphoma (PBML), 1 had classic Hodgking lymphoma (cHL), 1 had mantle cell lymphoma (MCL), 1 had plasmablastic lymphoma (PBL), 1 had splenic marginal zone lymphoma (SpMZL), 1 had ALK- anaplastic large cell lymphoma (ALCL), 1 had subcutaneous panniculitis-like T-cell lymphoma (SPTCL). Four pts received bendamustine plus rituximab (BR) and 7 pts received R-CHOP. In total, more than 30 million cellular events were acquired, resulting in over 18 million analyzable live single-cell events after expert manual gating. A total of 27 cell subsets were identified within 9 major immune cell compartments. At baseline, lymphoma pts showed significant reduction (p<0.05) of CD4+ naïve T cells (median 1.37%, range 0.33%-9.01%) compared to controls (median 9.28%, range 3.44-21.3%). Concurrently, lymphoma patients at baseline had significant elevation (p<0.05) of intermediate monocytes (median 2.1%, range 0.64%-5.73%) compared to controls (median 0.8%, range 0.2%-2.73%). Naïve cytotoxic T cells were significantly increased (p<0.05) in lymphoma pts at the 6mo timepoint (median 2.08%, range 0.7%-7.46%) compared to baseline (median 0.23%, range 0.03%-4.79%). A sub-group analysis restricted to patients who received either BR or R-CHOP with 6mo timepoint samples available (n=10), showed a significant reduction (p<0.05) in the frequency of CD4+ central memory T cells in the BR group (median 0.76%, range 0.06%-1.02%) compared to the R-CHOP group (median 3.3%, range 2.19%-5.0%). Additional results describing the details of the immune profile dynamics at intermediate timepoints (C2D1, CLD1) will be presented at the conference. Conclusion: Our results suggest that lymphoma patients have an unfavorable immune profile (high intermediate monocytes combined with low naïve CD4+ T cells) at the time of diagnosis, compared to matched healthy individuals. Their immune profile is reshaped after treatment with increase in naïve cytotoxic T cells 6 months after therapy. Bendamustine-based treatment seems to particularly affect T cell recovery post-therapy, leading to a reduction in CD4+ central memory T cells, compared to patients treated with R-CHOP. These findings highlight the importance of studying baseline and treatment-mediated immune changes in lymphoma pts. This characterization is of special interest in the context of therapies that rely on the fitness of immune cells to mediate an effect, such as chimeric antigen receptor (CAR) T cell therapy and bispecific T cell engagers (BiTEs).

Introduction As part of the Multiple Myeloma Research Foundation (MMRF) MyDRUG umbrella clinical trial, we compared immune cell transcriptomic and proteomic signatures of multiple myeloma bone marrow samples from patients assessed by single-cell RNA sequencing (scRNA-seq) and mass cytometry (CyTOF). The goal of our study is to evaluate the effects of cobimetinib on the immune repertoire over the treatment course at single-cell resolution. Methods Bone marrow samples were collected from patients prior to therapy with cobimetinib (baseline/BL), after 2 cycles of cobimetinib therapy (EOC2), after 2 cycles of combination cobimetinib with IPd (EOC4) and at the end of treatment or at disease progression (EOT). All samples were processed into CD138+ myeloma cell and CD138- “immune cell” fractions for single-cell analysis. In this study, the CD138- “immune cell” fractions were transcriptionally profiled by single-cell RNA-sequencing (scRNA) at up to four time points. Results Transcriptome profiles of approximately 50,000 cells were analyzed across 22 samples from 9 patients with tumor MAPK Pathway mutations including: BRAF (p.K483Q, p.V600E, n=2); KRAS (p.Q61H, p.G12V, p.G12R, n=3); NRAS (p.Q61H, p.Q61R, p.Q61K, n=4). A subset of paired samples were subject to CyTOF with two immune related panels to supplement the single-cell transcriptomic findings. Focusing on one immune panel, 4 samples were profiled at baseline and end of cycle 2 while two samples were profiled only at baseline capturing over 600,000 cells spanning both timepoints. Our immune focused CyTOF panel contained 41 markers including T and NK cell markers (CD4,CD8A,CD3, GZMB, CD56), Myeloid lineage markers (CD14), B/Plasma markers (CD19, CD20, SLAMF7, CD38) among others. The largest populations captured by CyTOF included 260,000 neutrophils, 139,000 monocytes, 130,000 CD4/CD8 T cells, 43,000 NK cells, 40,000 dendritic cells and 22,000 B/plasmablasts/myeloma cells. Exhaustion markers, including LAG3 and TIGIT, are increased in CD8 and CD4 T cells after MEK inhibition, while PD1 is downregulated. PD-L1 is upregulated in both T cell compartments (CD4/CD8), monocytes and in residual myeloma cells profiled by both CyTOF and scRNA-seq. Both the IFNG and STAT1 pathways are concurrently upregulated post MEK inhibition in transcriptionally distinct CD8 T cell subsets profiled by scRNA-seq, suggesting a mechanism influencing PD-L1 expression. Conclusions These data indicate IFNG pathway activation by CD8+ T cells post MEK inhibition promotes PD-L1 expression on residual myeloma cells, suggesting the PD-L1 and IFNG signaling axes is activated in relapsed refractory myeloma patients after MEKi treatment. Here we present immunophenotypic and transcriptional profiling of longitudinal samples pre/post-MEK inhibition with multiple myeloma patients which can inform precision guided treatment options.

Background Clinical biomarkers are essential for optimizing CAR T-cell therapy in multiple myeloma (MM). Clinicians can anticipate patient responses by evaluating predictive biomarkers, particularly earlier during treatment, tailoring treatments to enhance efficacy and survival outcomes. Ferritin, a general inflammation marker, appears to be a promising predictor of clinical outcome in MM patients receiving therapy with CAR T-cells. Our goal was to evaluate this and other biomarkers in this patient population. Methods We retrospectively analyzed MM-patients treated with idecabtagene vicleucel (ide-cel) and ciltacabtagene autoleucel (cilta-cel) at Mayo Clinic Arizona between September/2019 and November/2023. We evaluated the demographic characteristics, pre-infusion bone marrow samples, adverse events, mortality, and clinical response after CAR T-cell therapy infusion, and clinical laboratory data were interpreted using reference limits established by Mayo Clinic laboratories. Statistical calculations using parametric tests were performed, and survival curves were estimated using the Kaplan-Meier analysis and compared statistically using the log-rank test and Pearson's correlation. Results Forty patients with MM received CAR T cells, and 23 and 17 patients received cilta-cel and Ide-cel, respectively. The median age was 64 years [IQR 40-80], and 62.5% were male. All patients received inpatient CAR T-cell infusions; the median vein-to-vein was 54 days (IQR: 39-109), and the median length of hospital stay was ten days (IQR: 7-25). Cytokine release syndrome (CRS) was observed in 90% of patients (3% grade ≥3), while immune effector cell-associated neurotoxicity syndrome (ICANS) was observed in 23% of patients (3% grade ≥3). At day 90, the overall response rate (ORR) was 87.5%, with 21 patients (52.5%) having a complete response (CR), 9 (22.5%) with a very good partial response (VGPR), 5 (12.5%) had a partial response (PR), 1 (2.5%) had stable disease (SD), and 4 (10%) had progressive disease (PD). 35 patients was evaluated for minimal residual assessment (MRD) using flow cytometry cut-off 10-5. Of the total population eligible (PR, VGPR, and CR) for MRD evaluation, 97% were MRD negative. The median progression-free survival (PFS) was 13.5 months on ide-cel and has not been reached on cilta-cel. The mortality rate was 23.5% Ide-cel vs 8.6% with cilta-cel. In terms of PFS, we did not find any association with age, disease risk, number of previous lines of therapy, time from last treatment to CAR T-cell infusion, absolute lymphocyte counts at leukapheresis, % of plasma cells in bone marrow pre-infusion, vein-to-vein time, use of tocilizumab, or steroids for CRS/ICANS management. However, univariate analyses showed that a ferritin level <337 mcg/L at baseline pre-CAR T-cell infusion strongly correlated independently with improved PFS (median non-reached) compared with patients with ferritin levels >337 mcg/L that had a PFS of 13.50 months HR 0.2 (95% CI 0.07 - 0.83); p=0.0245. In addition, ferritin levels <337 mcg/L pre-infusion correlated with improved overall survival (OS) (median non-reached) compared with 22.23 months in patients with higher ferritin levels HR 0.2 (95% CI 0.02 - 0.53), p=0.0069. Conclusions In conclusion, our analysis shows that ferritin levels pre-CAR T-cell infusion are independent predictive biomarkers of PFS and OS in MM-patients regardless of the CAR T-cell product received. Our cohort of MM-patients treated with the two FDA-approved CAR T-cell products showed the expected PFS, OS, and adverse events. Moreover, our results showed no significant association between clinical response and age, risk stratification, number of previous therapy lines, or other evaluated factors with disease progression. Future prospective studies will help to validate these findings and explore the mechanisms associated with high ferritin levels and their potential implications in the heightened immune-activation state in patients that express high ferritin levels and their correlation with CAR T-cell efficacy.

Background: Chronic lymphocytic leukemia (CLL) is one of the most common leukemias in the United States (US), with an estimated incidence of 20,700 cases in 2024. Population-based studies conducted in Olmsted County (OC), Minnesota, reported an increase in CLL incidence over a 55-year period (1935 through 1989), which was attributed to increased detection of early-stage cases in individuals over age 50. In an updated study from 2000 to 2010 in OC, we reported no further increase in the incidence of CLL using the 2008 International Workshop on CLL (IWCLL 2008) guidelines. Additionally, when we compared the 1996 National Cancer Institute Working Group (NCI-WG 96) criteria with the IWCLL 2008 guidelines incorporating the monoclonal B-cell lymphocytosis designation, we found that the use of the IWCLL 2008 guidelines reduced the overt CLL incidence, modified the distribution of Rai Stages at diagnosis, and shortened the median time to first treatment (TTFT). Over the last two decades, 5-year survival for CLL has increased due to new therapies and improved supportive care. Herein we provide updated data on the incidence, prevalence, and natural progression of CLL in OC and studied similar features in an expanded 6-county region around Mayo Clinic, Rochester. Methods: We utilized the Rochester Epidemiology Project (REP), a population-based medical records linkage system, to identify CLL cases from 2000 to 2020 using International Classification of Diseases codes. We included individuals residing in OC and the expanded 7-county region (REP-7, including OC), for which data became available starting in 2010. CLL cases were included if they met the IWCLL 2008 criteria. All CLL diagnoses were confirmed by manual review of medical records and data on CLL-related factors were collected, including treatment status, prior history of other cancers, and overall survival (OS). Age- and sex-specific incidence rates were derived from REP census data and adjusted to the 2020 US white population. OS analyses were conducted using the Kaplan-Meier method. TTFT was calculated with death as a competing risk. Cox regression was used to evaluate the effect of decade on TTFT and OS among patients in OC. Results: From 2010-2020, 242 patients were diagnosed with CLL in REP-7, and between 2000-2020, 174 patients were diagnosed in OC. Among the 242 CLL patients in REP-7, the median age at diagnosis was 71 years (range 30-96),158 (65%) were male, 236 (99%) were white, and 74 (31%) had a history of other cancer, with non-melanoma skin cancer being the most common. After age and sex adjustment to the 2020 US white population, the CLL incidence in REP-7 and OC from 2010 to 2020 was 7.8 and 8.1 per 100,000 individuals, respectively. In OC, the age- and sex-adjusted CLL incidence from 2000 to 2020 was 7.5 per 100,000 individuals, showing no significant trend changes over time. Among the 242 patients diagnosed with CLL in REP-7 between 2010 and 2020, 102 received treatment with a median TTFT of 9.8 years. In OC from 2000 to 2020, 79 out of 174 patients received treatment with a median TTFT of 9.4 years. When comparing across two decades in OC, the median TTFT was 12.8 years for the period from 2000 to 2009, decreasing to 5.9 years between 2010 and 2020, but was not significantly different after accounting for age and sex. The median OS for patients diagnosed with CLL in REP-7 from 2010 to 2020 was 11 years. The median OS for patients in OC between 2000 to 2020 was 12.6 years. When comparing across decades in OC, the median OS was 8.9 years for the period from 2000 to 2009, increasing to 13.6 years for those diagnosed between 2010 and 2020, but this trend was not significantly different after accounting for age and sex. Prevalence data for REP-7 and OC were analyzed as of 01/01/2020. Additionally, prevalence data for OC were available for 01/01/2010. In REP-7, the prevalence of CLL was 97 per 100,000 individuals on 01/01/2020. In OC, the CLL prevalence was 86 per 100,000 individuals on 01/01/2010, and 100 per 100,000 individuals on 01/01/2020. Conclusions: We observed no substantial increase in the incidence rates of CLL in REP-7 from 2010 to 2020, nor in the 20 years of available data from OC. However, the prevalence of CLL in OC increased by 16% from 2010 to 2020. Additionally, evidence indicated a longer OS among newly diagnosed CLL cases in OC compared to previous decades, suggesting a potential impact of improved therapeutic approaches on OS.