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Background: Patients (pts) receiving FDA-approved chimeric antigen receptor T-cell (CAR-T) therapy or Bispecific antibody Teclistamab (Tec) are commonly managed in the inpatient setting given the common adverse events such as cytokine release syndrome (CRS) and immune cell-associated neurotoxicity syndrome ICANS. We have previously reported that hospital-based outpatient (HBO) management of pts receiving CAR-T is feasible and safe (Bansal et al, ASH2022). In 2023, HBO management at our institution began incorporating home health visits and management of grade 1 CRS in outpatient setting for select pts receiving standard of care (SOC) CAR-T. Here, we report outcomes of our updated practice. Methods: We retrospectively analyzed medical records and remote monitoring data of adult pts who received SOC CAR-T or Tec between 10/2020 and 7/2023 at Mayo Clinic, Rochester under an IRB approved protocol. Results: In 3/2023, pts deemed to be low risk for severe CRS (fever onset >= 3 days from infusion, CRP<100) received HBO management for grade 1 CRS, including outpatient administration of tocilizumab. If CRS improved or resolved, outpatient monitoring was continued. If CRS persisted within the observation period on HBO, pts were admitted. Recurrent CRS after the first episode were all managed inpatient. Nine pts met these criteria for HBO CRS management and their outcomes were compared to those who received initial inpatient (INPT) CRS management (INPT, n=17) during the same timeframe, as well as the outcome of 164 pts who had CRS management INPT prior to our practice change (Table 1). Two-third of the pts with initial management of CRS outpatient did not require hospitalization. Median time to hospitalization trended later than those managed inpatient at the onset of CRS. The duration of hospitalization was comparable for all pts admitted between initial HBO and INPT CRS management. However with fewer admissions in the initial CRS HBO group, the average hospitalization days (LOS) per patient treated for that group was lower compared to initial INPT CRS management. Data on additional pts will be presented at ASH. In 1/2023, pts on RPM with no ongoing CRS symptoms, no language barriers, and no compliance concerns received home health visits during weeks 3 and 4 post CAR-T infusion in place of clinic visits on HBO. Home health visit team communicated with HBO staff to review assessment and plan. Changes in HBO utilization will be presented. Finally, 24 pts received 223 Tec infusions on HBO. Median age was 66 years, 15 (61%) were males, 9 (38%) had high risk cytogenetics. The median prior lines of therapy was 5. Among these pts, 220/223 (99%) doses were performed on HBO and 204/220 (93%) infusions never required admission for management. Twenty pts enrolled in RPM (Figure 1). An average of 2 alerts were generated per patient during the 2 week period and median time from infusion to alert was 1.5 days. Majority of alerts were resolved over a phone call and only 13/114 (11%) alerts required a physician visit/hospital admission. Of the 16 Tec infusions resulting in admission, 4/16 (25%) required re-admission resulting in a total of 20 hospitalizations. Admissions mostly occurred during step-up dosing (18/20; 90%). Most common reason for first admission was fever (13/16, 85%) and median time to admission was 1 day from infusion. Median LOS was 1.5 days (range, 0-12). In terms of CRS, majority were Grade 1 (12/13, 93%) which were managed with steroids (dexamethasone/ prednisone) alone. One patient had CRS grade 4 event, in the setting of concurrent decompensation during dialysis, and was treated with steroids, tocilizumab, vasopressor, CRRT, thoracentesis, intubation and mechanical ventilation. The rate of second CRS event after management of first CRS with steroid (dexamethasone/ prednisone) was 15% (2/13). These second CRS episodes also resolved with steroid alone. Data on additional pts receiving Tec will be presented at ASH. Conclusion: Our data showed that additional advances in outpatient practice, including initial outpatient management of CRS and outpatient administration of Tec step up dosing are feasible, safe and reduce hospital resource utilization.

Introduction: Chronic myelomonocytic leukemia (CMML) is a myeloid neoplasm with limited therapeutic options and dismal outcomes. Truncating mutations in the epigenetic modifier ASXL1 are common and lead to a proliferative disease phenotype, resistance to epigenetic therapies, and higher rates of AML transformation. ASXL1-mutant CMML is characterized by widespread epigenetic remodeling and up-regulation of key leukemogenic driver genes (e.g. HOXA9 and its co-factor MEIS1). There is a genotype-specific activation of enhancers in ASXL1-mutant CMML that is associated with up-regulation of these leukemogenic driver genes. Here, we test the hypothesis that disrupting the oncogenic interactions at these genotype-specific enhancers can be exploited for therapeutic benefit. Methods: We identified activated enhancers specific to ASXL1-mutant CMML as previously described ( Binder et al. Nat Commun 2022;13(1):1434). To disrupt the E2542605 enhancer, we created unique mapped single guide RNAs (confirmed by BLAT). We generated a ribonucleoprotein complex using the Alt-R CRISPR-Cas9 system (IDT Technologies, Coralville IA). We combined the RNP along with Electroporation Enhancer to 3x10^5 cells of the monocytic cell line U937 in 20uL strip-wells provided by the SF Cell Line 4D-Nucleofector X Kit (Lonza, Basel, Switzerland). To deliver the RNP, U937 cells were electroporated via listed cell line specific protocol by the Amaxa 4D-Nucleofector (Lonza). Forty-eight hours post-electroporation, cells were split and sequenced for E2542605 genomic structure disruption. In parallel, RNA was harvested, converted to cDNA and qPCR for HOXA9 and MEIS1 expression was performed using PrimeTime qPCR FAM labeled probe assays (IDT). Gene expression was determined using delta-delta Ct method. For assessment of selective sensitivity of ASXL1 / enhancer interactions, we performed progenitor colony forming assays using primary bone marrow mononuclear cells from CMML patients with or without ASXL1 mutations and healthy normal controls (n=2 in each category), exposed to increasing concentrations of the dual p300/CBP and BET bromodomain inhibitor EP31670. Briefly, we plated cells in methocellulose fortified with recombinant human cytokines supporting hematopoietic growth in duplicate, in a range of EP31670 concentrations. After 10 days, visible hematopoietic colonies were quantified and characterized. IC 50 values were generated using non-linear regression log(EP31670) vs. normalized response. Results: We computationally identified candidate transcriptional regulators enriched at the activated enhancers specific to ASXL1-mutant CMML, including BRD4 (FDR<2.57x10 -370), CBP (FDR=2.56x10 -217), and p300 (FDR=6.36x10 -93). We selected the ASXL1-mutant-specific enhancer E2542605 (predicted to drive HOXA9 expression), given the up-regulation of HOXA9 in ASXL1-mutant CMML (log 2-fold change +2.05, FDR=0.006, n=14). We disrupted E2542605 using two different CRISPR guides, leading to a PCR trace detection of a 14bp deletion and a 26bp indel in the E2542605 enhancer region, respectively. Both enhancer disruptions led to a down-regulation of its putative target gene HOXA9: Mean relative fold-change 0.36 (p=0.001, n=3) and 0.65 (p=0.046, n=3), respectively ( Fig. 1a). We then used a pharmacologic approach (EP31670) to target the candidate transcriptional regulators involved in the oncogenic interaction at these ASXL1-mutant-specific enhancers. We observed selective sensitivity to growth of CMML colonies (particularly ASXL1-mutant colonies) compared to ASXL1-wild type cases and normal bone marrow controls ( Fig. 1b). Conclusions: In CMML patients, truncating ASXL1 mutations are associated with the activation of genotype-specific enhancers and the recruitment of an extended repertoire of transcriptional regulators including BRD4, CBP, and p300. In a model system, the disruption of an enhancer predicted to govern the expression of the leukemogenic driver HOXA9, led to a significant down-regulation of HOXA9 expression. Pharmacologically disrupting the oncogenic interaction at such enhancers with EP31670 in primary patient samples led to significant therapeutic effects at nanomolar drug concentrations in a genotype-specific manner. Oncogenic interactions at activated enhancers are viable therapeutic targets in ASXL1-mutant CMML and warrant further clinical investigation.

Background: Cytopenias are a common complication of and prolonged (beyond month 3 post CAR-T infusion), severe (grade 3 or higher) cytopenias can be difficult to manage. Stem cell boosts have been reported to restore hematopoiesis; however, stem cells would need to be available prior to CAR-T therapy for potential use post CAR-T. Most lymphoma patients and limited number of myeloma patients may have pre-collected stem cells in storage. Identifying patients at high risk for prolonged and severe cytopenia post CAR-T at the time of CAR-T evaluation (baseline), before leukapheresis, can help identify the patients for coordination of stem cell collection during CAR-T manufacturing and increase the likelihood that the collected stem cells would be used. In this study, we aim to identify clinical variables at the time of CAR-T evaluation, prior to leukapheresis, that are associated with severe cytopenias at month 3 post CAR-T infusion and identify patients who could be considered for pre-emptive stem cell collection prior to CAR-T therapy. Methods: We conducted a retrospective analysis of patients with multiple myeloma (MM) and non-Hodgkin lymphoma (NHL) who received CAR-T products at Mayo Clinic from 01/2016 to 06/2022. Patients with progressive disease in the first year post CAR-T were excluded from the analysis. Baseline (at CAR-T evaluation, prior to leukapheresis) variables were compared between those with and without severe cytopenia at month 3 post CAR-T. Severe cytopenias were defined as hemoglobin (Hg) < 8 g/dL, absolute neutrophil count (ANC) < 0.5 x 10 9/L, and/or platelet count (PLT) < 50 x 10 9/L. Statistically significant variables (p<0.05) by analysis were examined for statistical significance in multivariate analysis (MVA). Results: Among the 166 patients who received CAR-T (88 NHL, 78 MM) during the study period, 31 (18.67%) had a severe cytopenia at month . Twenty baseline variables were examined; HGB, PLT, ANC, and c-reactive protein (CRP) We devised a cytopenia risk score using 1 point each for Hg<10 or PLT<100k at baseline, with a range of 0 to 2. Demographics and clinical outcome by cytopenia risk score is shown in Table 1B. A higher percentage of patients with a score of 1 or 2 had a severe cytopenia at month 3 (Figure 1). In particular, there was a . In addition Conclusion: Baseline cytopenias before leukapheresis may identify patients with increased risk for severe cytopenias at month 3 post CAR-T. These patients can have continued slow hematopoietic recovery in the first year. Stem cell collection, if feasible, could be considered before CAR-T to alleviate post-CAR-T severe prolonged cytopenias.

Introduction: Clonal dendritic cell (DC) aggregates in chronic myelomonocytic leukemia (CMML) are seen in approximately 20-30% patients at diagnosis. Previously, these were thought to be comprised of CD123+ plasmacytoid DCs but our data has suggested that these are heterogenous and comprise of myeloid DCs, monocytes, and myeloid-derived suppressor cells. Furthermore, these aggregates uniformly express immune checkpoints such as indoleamine 2,3-dioxygenase-1 (IDO), associate with an IDO-specific systemic impact (increased trytophan catabolism), and expanded regulatory T cell population in CMML, suggesting a role in inducing immune tolerance. DC aggregates are also associated with increased risk of acute myeloid leukemia (AML) transformation and resistance to hypomethylating agents, highlighting that they are important for disease progression in CMML (Mangaonkar A et al. Blood Adv 2020). We performed this study to decipher the architecture of a CMML DC aggregate to understand the complex inter-cellular interactions, and assess their impact on the adaptive immune system. Methods: In this study, we used archival fresh-frozen paraffin-embedded (FFPE) bone marrow biopsy specimens obtained from CMML patients, and isolated monocytes (CD14+ magnetic bead sorting) and lymphocytes (CD14-ve fraction) from untreated CMML and age-matched normal control (NC) peripheral blood mononuclear cells (PBMCs). DCs were cultured from monocytes using a commercial protocol. Spatial architecture of the CMML BM microenvironment was interrogated through multiplex imaging of FFPE samples by co-detection by indexing (CODEX) using 30 markers (CCR6, CD107a, CD11c, CD20, CD21, CD31, CD3e, CD4, CD44, CD45, CD45RO CD56, CD68, CD8, E-Cadherin, FoxP3, HLA-DR, CD14, CD16, CD11b, CD33, CD15, CD66b, CD123, CD303, CD34, CD163 and IDO). Single-cell transcriptomic signatures were analyzed using the 10X single cell Fixed RNA profiling platform, and validated using bulk RNA seq (Illumina stranded mRNA prep) from isolated and cultured cells. Impact of DCs on lymphocytes was assessed via autologous mixed DC-T culture experiments. Results: BM FFPE samples from 5 CMML cases (3 with DC aggregates) were included for multiplex imaging via CODEX. Results confirm the significant interactions of CD8+ and CD4+ T cells with CD123+/HLA-DR+ DCs within a CMML DC aggregate (Fig. 1A). Upon quantitative assessment of cell-cell interactions, IDO+/CD8+T ( P=0.006), IDO+/MDSC ( P=0.005), and IDO+/macrophage ( P=0.001) interactions were significantly increased in CMML samples with versus without DC aggregates . Specific findings were validated using single-stain immunohistochemistry and multiplex immunoflourescence staining. Next, in order to assess transcriptomic signatures within BM at the single-cell level, we chose two cases; CMML (BM aspirate blast% 1, WBC 49.6 x 10 9/L, ASXL1/GATA2/SETBP1/SRSF2 mutations) and AML transformed from CMML (BM aspirate blast% 81, WBC 152 x 10 9/L, NPM1/DNMT3A/TET2 mutations). Approximately, 10,000 cells were obtained and analyzed with cell type annotation through human PBMC reference (Azimuth). Results show an expanded regulatory T cell population in AML compared to CMML (UMAP plot, Fig. 1B), suggestive of immune tolerance. In order to validate findings and perform functional experiments, we used sorted monocytes and cutured DCs from CMML and NC. DC phenotype was confirmed both through visual inspection and flow cytometry, and clonality was confirmed through Sanger sequencing (for previously identified mutations). Differential gene expression analysis through bulk RNAseq showed significant differences between CMML and NC lymphocytes with immunoinhibitory receptor, LILRB2 (log2fold change=7.05, adjusted P=0.0002) being one of the top five significantly upregulated genes, further confirming immune tolerance. Finally, mixed autologous DC-lymphocyte reaction (1:4 ratio) experiments demonstrated that DCs induce T cell tolerance in CMML (expansion of exhausted PD1/TIM3/LAG3+ CD8 T cells) when compared to NC. Conclusion: Clonal dendritic cell aggregates within the CMML bone marrow microenviroment interact with T cells and induce immune tolerance. This represents a novel mechanism of disease progression in CMML with potential therapeutic targets (IDO, LILRB2, and/or CD123).

Background: Relapsed DLBCL occurs in up to 40% of patients and has a poor prognosis. Current prognostic tools such as the international prognostic index (IPI) and newer forms (NCCN-IPI) only include baseline clinical features. PET/CT features have not yet been incorporated into prognostic risk models despite being essential for staging and response assessment. Deep learning computer algorithms have consistently demonstrated the ability to analyze imaging data and identify features that are not readily apparent to the human eye. Using a deep learning computer vision model that automatically extracted radiomic features from PET/CTs, we examined the association of changes between baseline PET and interim PET (PET2) radiomic features on survival outcomes and compared the prognostic performance with NCCN-IPI. Methods: Adult patients with newly diagnosed diffuse large B-cell lymphoma (DLBCL) between 2005 and 2015 and enrolled in the prospective MER cohort were included. Native DICOM images from FDG PET/CT scans at baseline and interim PET (PET2, after 2-3 cycles of chemotherapy) were preprocessed for regularity and then segmented using the nnU-Net architecture with an external lymphoma-specific model. Feature extraction and standard uptake value (SUV) characterization were accomplished with PyRadiomics and NiBabel. Our computational method included no manual segmentation correction. Individual radiomics features (n=115) and the % change above (Δ High) and below (Δ low) 50 th quartile from baseline to PET2 were evaluated for association with event free survival (EFS) and overall survival (OS) using a univariate Cox regression model and by Kaplan Meier analysis. EFS was defined as time from PET2 to first systemic relapse or death from any cause. OS was defined as time from PET2 to death from any cause. Additionally, Spearman and Pearson correlation matrices were used to guide feature selection while minimizing collinearity. We then assessed the association of the highest scoring radiomics features with EFS in a multivariate cox regression model. Results: A total of 506 patients had baseline and PET2 scans available for radiomic feature extraction. Median age at diagnosis was 61 years (range 18-90), 43% were females. NCCN-IPI composition and outcomes of our cohort was comparable to the previously published NCCN cohort, with patient distribution and 5-year OS as follows: Low (9%, 5-y OS 83%), Low-intermediate (38%, 5-y OS 49%), High-intermediate (41%, 5-y OS 31%), High (11%, 5-y OS 12%). At a median follow up of 81 months,there were 308 events, and272 patients had died.Several radiomics features were associated with EFS including change in tumor surface area (SA Δ) (HR: 1.75, 95% CI 1.36-2.24, p<0.005, median of 26,927 mm 2, Figure 1A) and change in total metabolic tumor volume (TMTV Δ) (HR: 1.64, 95% CI 1.27-2.10, p<0.005, median of 120,473 mm 3, Figure 1B). As a reference, NCCN-IPI univariate Cox regression analysis of EFS produced a Harrell's C-statistic (c) of 0.624. Single radiomics features of SA Δ and TMTV Δ individually produced unadjusted c-statistics of 0.616 and 0.614 respectively. Combinations of radiomics features (SA Δ, TMTV Δ and NCCN-IPI classification) demonstrated cumulative benefit (c=0.652). Conclusion: Automatic PET-CT radiomic feature extraction using deep learning models is feasible among patients with newly diagnosed DLBCL. The change in tumor SA and TMTV appear to be promising radiomic biomarkers. A low decline in either tumor SA or TMTV by PET2 is associated with higher risk of relapse and poor survival outcomes. As individual characteristics, these features are similar prognostic indicators of EFS as the NCCN-IPI. Further investigation into risk stratification when combining radiomics with clinical and genomic variables is warranted. Figure 1. Event free survival for DLBCL patients with A) a change in tumor surface area by PET2 less than 50% percentile (SA_Δ Low) and greater than 50 th percentile (SA_Δ High) and B) a change in TMTV by PET2 less than 50% percentile (TMTV_Δ Low) and greater than 50 th percentile (TMTV_Δ High).

Abstract The approach to patients with high-risk smoldering multiple myeloma (SMM) varies among clinicians; while some advocate early intervention, others reserve treatment at progression to multiple myeloma (MM). We aimed to describe the myeloma-defining events (MDEs) and clinical presentations leading to MM diagnosis among SMM patients seen at our institution. We included 406 patients diagnosed with SMM between 2013-2022, seen at Mayo Clinic, Rochester, MN. The 2018 Mayo 20/2/20 criteria were used for risk stratification. Median follow-up was 3.9 years. Among high-risk patients who did not receive treatment in the SMM phase (n=71), 51 progressed by last follow-up; the MDEs included: bone lesions(37%), anemia(35%), hypercalcemia(8%), and renal failure(6%); 24% met MM criteria based on marrow plasmacytosis (≥60%) and/or free light chain ratio (>100); 45% had clinically significant MDEs (hypercalcemia, renal insufficiency, and/or bone lesions). MM diagnosis was made based on surveillance labs/imaging(45%), testing obtained due to provider suspicion for progression(14%), bone pain(20%), and hospitalization/ED presentations due to MM complications/symptoms(4%). The presentation was undocumented in 14%. A high proportion (45%) of patients with high-risk SMM on active surveillance develop end-organ damage at progression. About a quarter of patients who progress to MM are not diagnosed based on routine interval surveillance testing.