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Abstract BACKGROUND Early disease progression within 24 months following chemoimmunotherapy (CIT) is an established adverse prognostic factor for overall survival (OS) in patients (pts) with indolent non-Hodgkin lymphomas. Initially reported in pts with follicular lymphoma, progression of disease (PD) within 24 months in pts with CLL treated with CIT (occurring in ~1-out-of-4 pts) is also associated with inferior OS. The prognostic utility of early event status in pts with CLL treated with targeted therapies is unknown. Recently, we reported worse than expected outcomes with BCL2 inhibitor (BCL2i) treatments in an international cohort of pts with covalent BTK inhibitor (BTKi)-resistant, CIT-naïve CLL. We hypothesize that early disease progression on first-line (1L) targeted agent treatment will identify additional pts with high-risk disease beyond conventional prognostics in the current era. METHODS We identified pts in the Mayo Clinic CLL Database with the following 1L treatments a) BTKi (+/- anti-CD20 monoclonal antibody [CD20mAb]); b) BCL2i + CD20mAb; c) BTKi + BCL2i +/- CD20mAb. PD was defined by a) new or progressive lymphadenopathy or splenomegaly; and/or b) ≥ 50% increase from nadir absolute lymphocyte count (ALC) with persistent (>2 months), and otherwise unexplained ALC ≥ 10x109/L; and/or c) Richter transformation. Logistic regression model evaluated association between clinical factors and POD36 status. OS in pts with PD within 36 months of 1L start (POD36) was evaluated and compared to those without early PD (non-POD36) with analyses: a) starting from time of PD (POD36) and starting from 3 years after 1L initiation (non-POD36); and b) Kaplan-Meier landmark analysis amongst pts alive 3 years post 1L initiation. Cox regression analyses compared a) OS from POD36 by groups and b) OS from 1L treatment with POD36 as a time-dependent covariate. RESULTS A total of 787 pts with CLL initiated 1L targeted therapy (n=538 [68%] BTKi +/- CD20mAb; n=151 [19%] BCL2i + CD20mAb; n=98 [13%] BTKi + BCL2i +/- CD20mAb. The median age at 1L start was 67 years (range 26-92 years), and 67% of pts were male. Among pts with complete CLL-IPI data (n=519), 44% and 15% had high- and very high-risk CLL-IPI risk scores, respectively. Specific pre-1L treatment disease characteristics included TP53 disruption (del17p or TP53 mutation) in 120/639 (19%), del11q in 103/634 (16%), unmutated IGHV in 406/591 (69%), complex karyotype (≥3 clonal structural or numerical abnormalities on karyotype) in 70/273 (26%), and positive CD49d expression in 229/449 (46%). The median pre-treatment beta-2-microglobulin level was 3.3 mcg/mL (range 1.2-24.4 mcg/mL). The median follow-up from 1L start was 50 months (95% CI 46-54 months). 496 pts met criteria for defining POD36 status; 72 (15%) had PD, and 424 did not. TP53 disruption (OR 2.9; 95% CI 1.5-5.7, P=0.001) was associated with POD36 on univariate analysis; complex karyotype, unmutated IGHV status, elevated serum lactate dehydrogenase level, age, sex, and inclusion of CD20mAb were not associated with POD36 status. Median OS from the time of determination of POD36 status was not reached. OS was significantly shorter after POD36 compared to non-POD36 pts (HR 3.5; 95%CI 2.1-6.0, P<0.0001), with 4-year OS estimates of 65% and 88%, respectively. When assessed by landmark analysis at the 3-year timepoint following 1L start (n=50 POD36), OS was also shorter in pts with POD36 compared to non-POD36 pts (HR 3.5; 95%CI 1.8-6.8, P=0.0002). In the overall cohort (n=787), when evaluating OS from 1L treatment with POD36 as a time-dependent covariate, POD36 status was associated with an increased risk of death (HR 4.3; 95% CI 2.6-7.1, P<0.0001) on univariable analysis; and remained an independent marker of shorter OS in multivariable analyses after adjusting for age, sex, TP53 disruption status, and IGHV status (HR 4.2; 95% CI 2.1-8.4, P<0.0001). CONCLUSIONMost pts achieved durable CLL disease control with 1L targeted treatments, and early PD occurs much less frequently than previously reported with CIT. However, among pts who receive 1L targeted therapies for CLL, PD within 36 months is associated with a ~4-fold higher risk of death. These results, if validated in larger data sets, will provide a practical measure for identifying a high-risk subgroup of pts in need of novel treatment strategies in future trials.

Abstract Introduction: Pirtobrutinib, a highly selective non-covalent BTK inhibitor, demonstrated encouraging efficacy in Richter transformation (RT) of chronic lymphocytic leukemia (CLL) in the BRUIN trial (Wierda et al, Lancet Haematology, 2024). However, a control arm was not included in this phase 1/2 trial, and how pirtobrutinib compares to usual care is unknown. To address this gap of knowledge, we sought to compare efficacy outcomes in BRUIN to that in a control cohort consisting of RT patients treated with usual care at Mayo Clinic. Methods: The study was approved by the Mayo Clinic IRB. Patient-level data from BRUIN (n=79; investigator-assessed) were obtained from the study sponsor. Patients with histologically confirmed RT (large B-cell lymphoma) who received at least one line of therapy (n=230) were identified from the Mayo Clinic CLL Database. Multivariable logistic regression was employed to calculate propensity scores for baseline covariates (ie, age at RT treatment line, number of prior lines of CLL treatment [truncated at 3], number of prior lines of RT treatment [truncated at 3], and LDH). For each Mayo patient, propensity scores for each line of RT therapy were calculated, and the line with the highest propensity score was chosen as the index RT treatment line. Using the inverse probability treatment weighting (IPTW) methodology, individual weights were computed, and standardized mean differences (SMDs) were examined for each of the unadjusted and weighted baseline covariates to ensure that balance was obtained between BRUIN cases and Mayo controls. Overall survival (OS; the primary endpoint) and progression-free survival (PFS) were analyzed using unweighted and weighted Cox proportional hazards models. Unweighted and weighted overall response rates (ORRs) and complete response (CR) rates were analyzed using logistic regression. Results: The final analysis dataset contained 79 BRUIN cases (median age 67 [range 26-95], 66% male) and 204 Mayo controls (median age 69 [range 30-89], 74% male). The BRUIN cohort had more patients with ECOG PS ≥1 (61% vs 40%, p=0.001) and elevated LDH (81% vs 63%, p=0.003) than the Mayo cohort. The proportion of patients with TP53 aberration was not statistically different in both cohorts (57% vs. 44%, p=0.15). The index line of RT treatment in the Mayo cohort included chemoimmunotherapy (n=167, 80%) and novel agent-based therapy (eg, cBTKi, venetoclax, PI3Ki, immune checkpoint inhibitor, etc; n=42, 20%). Median lines of prior CLL therapy were 2 (IQR 1-4) vs 1 (IQR 0-3) in the BRUIN and Mayo cohorts, respectively; median lines of prior RT therapy were 2 (IQR 1-2) vs 0 (IQR 0-2). The SMDs of the weighted baseline factors met pre-determined criteria (-0.25≤SMD≤0.25), indicating that balance between the two cohorts was achieved. The median follow-up was 18.3 months (range 0.7-32.9) in the BRUIN cohort and 122.8 months (range 0-280.2) in the Mayo cohort. The unweighted median OS was 12.5 months (95% CI 7.0-20.6) in the BRUIN cohort and 5.7 months (95% CI 3.9-10.7) in the Mayo cohort. The unweighted HR was 0.76 (95% CI 0.54-1.07, p=0.12). After IPTW, the weighted HR was 0.63 (95% CI 0.50-0.78, p<0.001), significantly favoring the BRUIN cohort. The unweighted median PFS was 3.6 months (95% CI 2.8-5.1) in the BRUIN cohort and 3.1 months (95% CI 2.5-4.3) in the Mayo cohort. The unweighted HR was 0.98 (95%CI 0.72-1.34, p=0.92). After IPTW, the weighted HR was 0.78 (95% CI 0.64-0.95, p=0.01), again favoring the BRUIN cohort. Response was evaluable/available in 69 patients in BRUIN and 182 patients in Mayo cohort. The unweighted ORR was 58% vs 53% in BRUIN and Mayo cohorts, respectively (OR=0.83, 95% CI 0.47-1.45, p=0.51), and the CR rate was 16% vs 36% (OR=2.94, 95% CI 1.43-5.88, p=0.003). After IPTW, the weighted OR was 0.65 (95% CI 0.45-0.93, p=0.02) for ORR, favoring the BRUIN cohort, and 1.89 (95%CI 1.23-2.86, p=0.02) for CR rate, favoring the Mayo cohort. Conclusions: This individual patient-level IPTW-based analysis demonstrated that single agent pirtobrutinib is associated with improved OS, PFS, and ORR compared to usual care in patients with RT. These results support the choice of pirtobrutinib over traditional therapies for RT. Although these results are encouraging, the durability of response to pirtobrutinib remains suboptimal. Ongoing trials and other future research will evaluate the efficacy of pirtobrutinib in combination with other treatments in this setting.

Abstract Introduction: A subset of patients with chronic lymphocytic leukemia (CLL) experiences disease progression from CLL to Richter transformation (RT), characterized by the occurrence of a high-grade lymphoma. The outcomes of patients with RT are typically dismal and identifying better therapeutic strategies remains critically important for these patients. To discern the biologic underpinnings driving this transformation, we studied immune changes and genetic evolution in samples from CLL patients who developed RT. Methods: We identified 18 patients with CLL who developed RT; and performed single cell (sc) RNA-sequencing(seq) on sorted B and T cells from peripheral blood mononuclear cells (PBMCs) at the time of RT (n=18) and at the earlier time of CLL diagnosis (n=11). The median time between the CLL sample and the one closest to RT was 4.3 years (range, 0.2-7.3); and patients received a median of 1 CLL directed treatment (range, 0 – 7). A total of 749,906 cells and 36,601 genes were captured during scRNAseq and 720,580 cells and 21,892 genes were retained for downstream analysis, respectively. Analysis was performed using the immunopipe (https://github.com/pwwang/immunopipe) that wraps around Seurat (v5.1.0) and identified enriched pathways using Enrichr service. The sc-T cell receptor (TCR)-repertoire(R)-seq data was analyzed and visualized using scplotter (). The whole exome sequencing (WES) analysis with tumor B-cells from same patients of CLL & RT stages were done using the Agilent sureselect Human all exon v5 + UTR capture kit. Reads from paired end sequencing were processed with the sarek pipeline. Results: Analysis of 720,580 cells from 11 CLL and 18 RT samples showed 16 distinct cell types- 3 B and 13 T cell subtypes. We observed an increasing trend of CD8 TEM [mean 0.548 vs. 0.384, p = 0.12 (Wilcoxon test)] but a decreasing trend of CD4 TCM (mean 0.236 vs. 0.337, p = 0.08) and B-memory (mean 0.0085 vs. 0.0195, p = 0.51) subsets in RT compared to their CLL stage. When comparing transcriptional changes, we found that among the top 18 highly variable genes, the expression of FP236383.3 (lncRNA) and TCL1A was significantly higher (p<0.0001) in the B cell subsets of patients with RT vs. CLL stage. Additionally, in T cell subsets—primarily dnT, γδT, and CD8/CD4 naïve cells—the expression of FP236383.3, NKG7, GNLY, and CCL5 was significantly higher (p<0.0001), while the expression of LDHB, GZMK, and IL32 was significantly lower (p<0.0001) in RT vs. CLL stage samples. Comparison of specific gene set enrichment analysis showed significantly increased expression of GZMB in gdT (p<0.001) and decreased expression of GZMA, GZMK, TIGIT and TCF7 in dnT and CD8 Naïve cells (p<0.001) for RT vs. CLL stage. The top 10 differentially expressed pathways in RT included oxidative phosphorylation, allograft rejection, IFN-α/-γ responses, TNF-α signaling via NF-κβ, complement, Myc targets V1, mTORC1, hypoxia, and p53 signaling across various B and T cell subsets compared to the CLL stage. Initial analysis of TCR-R data showed that patients with RT stage have lower number of unique clones (p<0.5) and reduced clonal diversity (p<0.5), and a higher number of large and hyperexpanded clones compared to their CLL stage. Additionally, WES data indicated that the most frequently mutated gene is TP53 in tumor B cells of both CLL and RT stages. However, a higher percentage of RT-stage samples carry mutations in MGA, ATM, and IRF2BP2 genes compared to their CLL-stage. WES data also showed a trend toward differing frequencies of copy number amplification at 19q12 (p=0.10) and 4q13.1 (p=0.52) between RT and CLL stages. Conclusions: The main findings of our study are as follows:The transcriptional landscape showed significant changes in multiple genes and pathway enrichment related to cell growth, differentiation and immune response in RT vs. CLL stage.A decreased fraction of CD4 TCM cells and reduced TCR clonal diversity were observed in samples at the RT stage and may indicate a poor prognosis for the patients at this stage. WES data of tumor B cells also indicated possible genetic alterations in the RT vs. CLL stage. Data from in-depth analyses on understanding of the dynamics of T cell response and additional experiments on these patients are expected to provide valuable insights into tumor genetic heterogeneity, transcriptional and immune regulation in blood-based immune subsets.

Abstract Background: The synergistic mechanisms of BCL-2 inhibitors and CD20-directed antibodies in the treatment of chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) often lead to deep and durable responses. Although the use of venetoclax-obinutuzumab (Ven-O) in the frontline setting (1L) for CLL/SLL has led to a paradigm shift in the disease management, there are limited data on its efficacy in the relapsed/refractory (R/R) setting. In this study, we evaluated the efficacy and safety of Ven-O in both 1L and R/R CLL among patients treated outside the context of clinical trials at our institution. Methods We used the Mayo Clinic CLL Database to identify patients with CLL who were treated with Ven-O, both in 1L and R/R settings. Patients seen at Mayo Clinic Rochester between 2017 and 2025 were included. Overall survival (OS) was calculated from date of Ven-O initiation until last known alive date. Event-free survival (EFS) was calculated from date of Ven-O initiation until the next line of treatment or last known alive date. Kaplan-Meier methods estimated EFS and OS rates at 1, 3, and 5 years. Cox proportional hazards models were used to explore the association between baseline factors and EFS and OS; results are reported as hazard ratios (HR) and 95% confidence intervals (95%CI). Finally, we compared the OS to the age- and sex-matched general population of the state of Minnesota. Results A total of 154 patients (91 1L, 63 R/R) were included in the study. The median age was 68 years (69 1L, 68 R/R), and 68% were male (64% 1L, 73% R/R). Overall, TP53 disruptions (either del17p by FISH or TP53 mutation) were noted in 22 (15%) patients (9% 1L, 23% R/R). CLL FISH findings demonstrated del11q in 24 (19%) patients (19% 1L, 18% R/R), del13q in 46 (36%) patients (36% 1L, 36% R/R), and trisomy 12 in 21 (16%) patients (16% 1L, 18% R/R). IGHV genes were unmutated in 95 (68%) patients (60% 1L, 80% R/R). The CLL-IPI risk score was high in 54 (51%) patients (51% 1L, 53% R/R) and very-high in 18 (17%) patients (8% 1L, 34% R/R). A total of 121 (89%) patients completed planned treatment (1 year of venetoclax in 73 [90%] 1L and 2 years of venetoclax in 48 [87%] R/R). Median follow-up for the entire cohort was 1.8 years (2.2 1L, 1.5 R/R). Neither median EFS nor OS was reached for the overall cohort or within the 1L and R/R subgroups. The 1, 3, and 5-year EFS estimates for the overall cohort were 91% (86-96%), 85% (78-92%), and 67% (51-89%), respectively; corresponding EFS values for the 1L subgroup were 95% (91-100%), 89% (82-98%), and 67% (47-95%), respectively; and for the R/R subgroup were 85% (76-95%), 77% (65-92%), and 77% (65-92%), respectively. The 1, 3, and 5-year OS estimates were 98% (95-100%), 95% (91-99%), and 88% (76%-100%), respectively; corresponding OS values for the 1L subgroup were 99% (96-100%), 97% (94-100%), and 97% (94-100%) and for the R/R subgroup were 96% (91-100%), 91% (82-100%), and 61% (27-100%), respectively. Univariable analyses showed that TP53 disruption was associated with shorter EFS (HR 3.8, 95%CI 1.4-10.2, p=0.01), although IGHV mutation status was not associated with shorter EFS. A higher level of serum beta-2 microglobulin (HR 1.27, 95%CI 1.01-1.59, p=0.04) and R/R status (HR 4.9, 95%CI 0.9-25.8, p=0.06) were associated with a shorter OS. Interestingly, TP53 mutation status and IGHV mutation status were not associated with inferior OS. There was no difference in the observed and expected OS for both the 1L (p-0.23) and R/R (p=0.14) Ven-O treated cohorts compared to the age- and sex-matched general population of the state of Minnesota. Conclusions Our study shows that Ven-O is a well-tolerated regimen with demonstration of durable treatment responses both in the 1L and R/R groups, when used outside the context of a clinical trial. To the best of our knowledge, these data for the first time demonstrate no difference in OS of patients treated with Ven-O compared to age- and sex-matched general population, in both the 1L and R/R settings.

Abstract Background: B-cell maturation antigen (BCMA)-targeted T cell engagers (TCEs) have emerged as a highly potent immunotherapy for relapsed/refractory multiple myeloma (MM). However, both primary and acquired resistance significantly limit the durability of responses. Antigen escape and development of dysfunctional T cell responses are a significant driver of relapse post-therapy. Here, we preclinically interrogate if continual versus intermittent/response-adapted dosing differently affects development of resistance, the translatability to clinical resistance mechanisms, and how tumor-intrinsic or microenvironmental factors shape the development of resistance to BCMA-TCEs. Methods: We utilized a syngeneic transplantable Vk*MYC MM model which permits clonal tracking through unique immunoglobulin rearrangements. Two cohorts of tumor-bearing mice were treated with a murine surrogate BCMA-TCE using distinct strategies: (1) continuous weekly dosing until disease progression, and (2) an “ intermittent/response-adapted” strategy, where treatment was paused after initial response and resumed upon detection of M-spike. At time of relapse on therapy, RNA-seq was performed on isolated tumor cells to investigate mutations in- or loss of Tnfrsf17/BCMA. Single-cell RNA sequencing (scRNA-seq) was also performed on 189,025 cells isolated from bone marrow and extramedullary sites. Results: Both continuous and intermittent treatment regimens resulted in similar overall survival. BCMA-TCE treatment induced a distinctive pattern of disease progression, with para- and extra-medullary dissemination observed in 31% (17/54) of treated mice—regardless of treatment schedule. Given this treatment-induced dissemination hasn't been historically observed in our model, we further profiled BCMA expression and infiltrating immune cells to understand relapse mechanisms at these sites. Furthermore, we noted lower BCMA expression in tumors from continuously treated mice compared to untreated or stop-and-go cohorts. Importantly, reduced BCMA expression occurred without loss of plasma cell identity indicating that lineage switching may not be occurring as observed in other hematological malignancies treated similarly (Ruella, 2023, Nat Rev Drug Discov); malignant cells retained high expression of canonical plasma cell markers Irf4, Prdm1, Xbp1, Sdc1. We identified three mechanisms of acquired resistance:Genomic BCMA loss: Complete and irreversible loss of BCMA due to retrotransposition of IAP particles into the first intron of Tnfrsf17, disrupting transcription of downstream exons. This represented a genomic mechanism of antigen escape occurring with continual and prolonged TCE dosing, disrupting transcription and eliminating surface BCMA.Transient BCMA downregulation: Transient downregulation of BCMA expression associated with rapid disease relapse under continuous treatment. Tumors exhibited low BCMA levels and widespread dissemination in paramedullary sites. However, re-transplantation into naïve hosts led to restoration of BCMA expression and re-sensitization to TCE, indicating antigen loss was not permanent.Resistance without antigen loss: In the intermittent dosing regimen, several cases achieved complete remission after two doses, relapsed after treatment pause, and were not controlled after subsequent retreatment. Despite preserved BCMA expression and absence of BCMA mutations or deletions, tumors were refractory to retreatment, suggesting a tumor extrinsic mechanism of resistance. scRNA-seq analysis of the tumor microenvironment is ongoing and the role of uniquely identified immune infiltrates, like NK-like lymphocytes and distinct macrophages, in shaping the cell responses is under consideration. Conclusion: Resistance to BCMA-TCE therapy in the Vk*MYC model of MM arises through multiple mechanisms including genomic antigen loss and transient antigen downregulation. Continuous therapy drives selective pressure leading to target loss via genomic or epigenetic routes, while intermittent dosing preserves antigen but permits resistance to TCE, potentially through immune escape mediated by microenvironmental changes. These insights underscore the translatability of the Vk*MYC model for evaluating rational combination therapies to mitigate these resistance mechanisms. All procedures performed on animals were in accordance with regulations and established guidelines and were reviewed and approved by an IACUC or through an ethical review process.

Abstract Introduction: Despite remarkable advances in treatment, patients with multiple myeloma (MM) continue to suffer relapse. Therefore, the development of novel therapeutic strategies is required. The SWI/SNF chromatin remodeling complex, especially its core ATPase subunits SMARCA2/4, is essential for super-enhancer function and MM cell survival. Furthermore, NSD2, which is overexpressed in t(4;14)-positive MM, has been reported to interact with SMARCA2/4, suggesting differential sensitivity to SMARCA2/4 inhibition. While ATPase inhibitors and PROTAC degraders targeting SMARCA2/4 have demonstrated promising preclinical efficacy in MM and other malignancies, their broader therapeutic relevance remains to be clarified. Methods: To support the clinical development of mSWI/SNF antagonists for MM, we first performed PRISM-based profiling of the anti-proliferative effects of both an mSWI/SNF ATPase PROTAC degrader and a catalytic inhibitor across a panel of 888 cancer cell lines from diverse lineages. Lineage enrichment analysis identified plasma cell myeloma as one of the most sensitive malignancies, with the PROTAC degrader demonstrating particularly potent effects. These were followed by in-depth studies in 35 human myeloma cell lines (HMCLs) using FHD-286 (SMARCA2/4 ATPase inhibitor), AU-24118 (CRBN-based degrader), and AU-15330 (VHL-based degrader). Cell viability was assessed after 5-day treatment by flow cytometry with Annexin V and Live/Dead staining. Additional assays were performed in hCRBN-engineered murine plasmacytoma cell lines and Vk*MYChCRBN MM mouse models. Chromatin profiling employed CUT&Tag with SMARCA2/4 and IKZF1/3 antibodies. Results: FHD-286 and AU-24118 showed potent anti-myeloma activity across most cell lines (median IC₅₀: 4.5 nM and 5.9 nM, respectively). HMCLs with t(4;14), as compared to those without, were more sensitive to FHD-286 (p= 0.0064), with a similar trend for AU-24118 (p=0.09). AU-24118 log2 IC₅₀ values correlated with those of FHD-286 (r=0.62, p=0.0002) and with pomalidomide (r=0.61, p=0.0002), suggesting a shared biology. Indeed, CUT&Tag analysis for SMARCA2/4 and the pomalidomide targets IKZF1/3 showed these factors co-localized at most sites throughout the genome in MM.1S cells, including at DUSP22/IRF4, POU2AF1, and IgH super-enhancers. Treatment with AU-15330, depleted SMARCA2/4 off chromatin at >80% of sites within 8 hours (FDR <0.01), and somewhat surprisingly also depleted IKZF1/3 off chromatin at 70% of bound regions, indicating IKZF1/3 function is dependent upon SWI/SNF. Resultantly, combination studies of SWI/SNF targeting agents and pomalidomide showed a lack of synergy and in some cases antagonism, highlighting the importance of careful evaluation when considering combination with pomalidomide. We and others have demonstrated that murine cells are IMiDs resistant due to species-specific differences in CRBN. Using three distinct mouse plasmacytoma cell lines (+/-hCRBN), hCRBN-expressing cells showed a 100-fold greater sensitivity to AU-24118 compared hCRBN- cell lines. In vivo safety testing of AU-24118 using hCRBN transgenic mice exhibited early mortality within 7 days at doses ≥1.875 mpk and within 3 days at doses ≥7.5 mpk, accompanied by rapid body weight loss. In contrast, a preliminary efficacy study using de novo Vk*MYChCRBN mice, AU-24118 administered at 1 mpk three times per week was well tolerated and led to approximately 40% reduction in serum M-protein within 2 weeks (p<0.05), with no notable weight loss, demonstrating a therapeutic window. Conclusions: Broad PRISM profiling confirms lineage-specific vulnerability of MM to SWI/SNF inhibition, with in vitro and in vivo validation supporting selective efficacy in high-risk t(4;14)-positive subtypes. FHD-286, AU-15330, and AU-24118 demonstrated strong in vitro activity, particularly in t(4;14)-positive HMCLs. This activity was due, in part, to chromatin compaction and decommissioning of lineage and oncogenic enhancers as well as eviction of IKZF1/3 off chromatin. AU-24118 showed high selectivity, with picomolar range IC₅₀ in sensitive HMCLs. Due to species-specific CRBN differences, accurate toxicity evaluation of AU-24118 requires hCRBN-expressing models, and preliminary data indicate in vivo efficacy in the highly predictive Vk*MYChCRBN model. These findings support the potential of SMARCA2/4 targeting agents, especially AU-24118, as promising therapies for MM, particularly in high-risk t(4;14)-positive cases.

Abstract Background: Flow cytometry (FC) is widely utilized for the identification of measurable residual disease (MRD) in multiple myeloma (MM), 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 currently 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 MM MRD using the 2-tube Euroflow Consortium Panel (Cytognos). Raw FC files corresponding to 150 MRD-positive bone marrow samples (MRD < 5%, median = 0.0022%), and 39 MRD-negative samples were processed through our CCADDAS (Clustering and Classification of All events, Dimensionality reduction, Downsampling and Aberrancy Scaling) pipeline, deployed on a custom clinical-grade cloud environment (Biolegend). Automated processing steps included elimination of acquisition errors (FlowCut), state-of-the-art clustering (PARC), cluster-informed and density-based downsampling with preservation of low-event subsets, dimensionality reduction (UMAP), and cluster-based anomaly detection compared to negative controls (29 bone marrow aspirates). 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 2.3, Beckman Coulter), and %MRD estimates were compared to reported results based on traditional expert analysis of original FC files. Results: Cluster-informed downsampling reduced the number of cells to be manually analyzed from 4.1 million to 196,761 cells per tube, on average (95% cellularity reduction); resulting in a smaller FC data file (from 203.2 MB to 20.5 MB; 90% data reduction). Importantly, low-level MRD events were adequately preserved after downsampling (median 88% and 77% retention, for 0.01-0.001% MRD and < 0.001% MRD, respectively). 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. In 96% of positive cases, MRD was rapidly identified as immunoglobulin light chain-restricted plasma cells on a single pre-calculated UMAP plot (tube 2), after dual coloring for kappa and lambda. On the remainder 4% of positive cases, MRD was easily segregated from benign plasma cells using the AI-generated “aberrancy scale” parameter or other strategies. The use of AI-enhanced files reduced manual analysis time from 15.05 minutes (SD = 6.84) to 1.29 minutes (SD = 0.90) per case, on average (p < 0.0001) (91% reduction of manual analysis time). MM MRD was detected in all positive cases above limit of detection for our assay (≥0.0002%), with excellent quantitative correlation with conventional analysis on original FC files (linear regression slope = 0.9841, P < 0.0001). Conclusion: We introduce a largely unsupervised AI pipeline that transforms raw MM MRD FC data from the Euroflow Consortium panel into a markedly smaller, AI-annotated and software-agnostic FC file, including comparison to normal controls. This CCADDAS pipeline simplifies and accelerates detection of MM MRD in clinical diagnostics, reducing the number of cells analyzed by 95% and manual analysis time by 91%, without impacting test performance. Moreover, CCADDAS can be utilized for any laboratory-developed MM 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 MM MRD FC analysis by more clinical laboratories.

Abstract Introduction High disease burden has been associated with reduced efficacy and resistance to BCMA CAR-T therapy in relapsed/refractory multiple myeloma (van de Donk, Blood Cancer Discov, 2021; Martin, J Clin Oncol, 2023). While CAR-T cells can still induce remissions in these patients, outcomes are often worse compared to those with a lower tumor load. In addition to tumor debulking, novel strategies are needed to improve responses and durability of CAR-T cells in these patients. We previously demonstrated that immunomodulatory drugs (IMiDs) improve in vivo responses to T cell engagers (TCE) in high tumor burden setting by boosting T cell activation (Meermeier, Blood Cancer Discov, 2021; Meermeier, Blood, in press). IMiDs have also been shown to promote CAR-T cell antitumor activity in moderate to low tumor burden conditions (E:T ratios ≥1:1) (Yan, J Transl Med, 2024; Wang, Clin Cancer Res, 2018). We hypothesized that combining CAR-T with an IMiD may improve CAR-T function in high tumor burden setting. Methods We generated murine anti-BCMA.CD28 CAR-T cells by transducing Con-A stimulated T lymphocytes extracted from hCRBN+ mice, expanded with IL-7 and IL-15 to express a memory phenotype. We then tested CAR-T, or untransduced T cells, ability to kill in vitro IMiD resistant, hCRBN-, Vk*MYC myeloma cells in low (E:T 1:1) and high (E:T 1:≥5) tumor burden, with and without pomalidomide (POM) and IL-2. Tumor killing and T cell phenotype were assessed by flow cytometry at 24-72 hours. This controlled system allowed us to focus on putative CAR-T cell intrinsic impact of IMiDs. Results In low tumor burden setting, CAR-T effectively killed tumor at all timepoints, with or without POM; addition of POM increased T cell number, confirming that IMiDs support CAR-T expansion. Unexpectedly, in high tumor burden (E:T 1:≥5), adding POM diminished CAR-T mediated killing over time and hindered CAR-T expansion. Moreover, combination with POM decreased granzyme B, while increased expression of exhaustion marker TOX, ultimately leading to CAR-T apoptosis. This phenotype was further intensified by increasing concentrations of IL-2 in the co-culture, resulting in increased expression of CAR-T expressing LAG-3, TIM-3, and TIGIT, suggesting that CAR-T cells may be overactivated by POM and IL-2. Our manufacturing protocol preferentially expands memory CAR-T cells, favored for their durability, proliferative capacity, and considered to rapidly expand upon encounter with antigen. We reasoned that CAR-T are already sufficiently activated by CAR/CD3z stimulation, especially with a CD28 co-stimulatory domain (versus 4-1BB), known promote rapid, effector memory expansion upon activation (Kawalekar, Immunity, 2016). Activation is intensified by high tumor burden where antigen is highly abundant. We hypothesize under intense, sustained antigen exposure in high tumor burden, the addition of POM paradoxically triggers activation induced cell death (AICD). Conclusion Although it is well accepted that POM can boost T cell function and proliferation, we demonstrate that in high tumor burden, POM drives memory CAR-T to increase exhaustion markers and apoptotic cell death by overactivation, further exacerbated by exogenous IL-2. Interestingly, we have shown opposite effects of preclinically combining POM with TCE therapy in high tumor burden, based on dosing schedule. Concomitant administration transiently boosted T cell activation improving response rates but rapidly led to T cell exhaustion (Meermeier, Blood Cancer Discov, 2021). In contrast, IMiD pretreatment in the context of step-up dosing TCE administration improved T cell fitness and longevity (Meermeier, Blood, in press).The effect of IMiDs on T cells transcriptional program is likely to differ depending on differentiation stage and mode of T cell activation. Memory cells have more sensitive TCR signaling (Kumar, Immunity, 2011) and can be hyperactivated, leading to AICD. Thus, timing of IMiD administration, when tumor burden is low, may be a critical consideration as different T cell subsets require different levels of activation. Conversely, TCE provide only initial activation via TCR signaling, therefore POM may help in providing necessary co-stimulation in this setting. Future studies will evaluate different co-stimulatory domains and test in vivo effects of POM on CAR-T expansion and persistence, particularly as CAR-T cells diminish over time as tumor burden increases.

Abstract Overview: The emergence of effective immune therapies for multiple myeloma has highlighted the importance of understanding the roles of less abundant components within the tumor microenvironment. Single-cell analyses provide snapshots of the functional relationships of individual cells at precise moments in time, as well as insight into the overall cellular composition. By integrating single-cell datasets from multiple studies, we improve our ability to identify trends within rare cell populations, such as macrophages, and explore their clinical implications. We investigate human data here because our prior research of murine models indicated that macrophages expressing C1q, particularly those co-expressing Fcgr4, tend to correlate positively with increased tumor burden. Methods: We combined 56 human bone marrow samples – primarily collected at baseline, post-induction, or post-ASCT – with three publicly available data sets: GSE210079 (post CAR-T bone marrow microenvironment); GSE223060 (single-cell analysis of the MMRF cohort); and GSE271107 (disease progression from healthy donors and MGUS to SMM and NDMM). These data sets were integrated using Seurat to generate robust cellular clusters from over 300,000 cells across 117 samples. We validated our single-cell findings with bulk Affymetrix, whole bone marrow gene expression data (collected at baseline and post-baseline) from the Total Therapy clinical trials (GSE136324). Results: A distinct cluster of C1QA/B/C-expressing macrophages was consistently identified in all single-cell cohorts. These cells co-express FCER1G, CSF1R, and CD68 (markers also expressed in murine C1Q macrophages) and typically cluster adjacent to FCGR3A-expressing monocytes. Within the disease progression cohort, C1Q macrophages were found in all phases of progression: healthy donors, MGUS, SMM, and NDMM. However, C1Q macrophages in progressive disease (SMM and NDMM) have distinct expression features including lower levels of MRC1 and higher levels of APOBEC3A and ISG15 – genes linked to inflammatory responses. Among 11 post-induction samples submitted to lenalidomide maintenance, five with shorter responses displayed elevated expression of APOBEC3A and ISG15 in C1Q-expressing macrophages compared to six samples with longer responses. In a cohort of 22 samples 100 days post-ASCT, seven poor responders showed both an increased frequency of C1Q macrophages and elevated APOBEC3A expression compared to good responders. The MMRF cohort indicated that higher baseline frequencies of C1Q macrophages often preceded rapid disease progression (e.g. MMRF_1720, MMRF_1641). Anecdotal evidence from the CAR-T therapy cohort suggests that expansion of C1Q macrophages could serve as an early warning for tumor recurrence; sample 16 showed retention and expansion of C1Q macrophages 28 days post-CAR-T, that was subsequently followed by increased tumor cell counts at 3 months post-therapy. Analysis of bulk, whole bone marrow gene expression revealed that elevated levels of C1Q genes correlated with poorer outcomes, particularly in post-baseline samples. Multivariate Cox survival analysis revealed that high C1Q expression independently predicted inferior overall survival in post-baseline samples after adjusting for age, ISS stage, high levels of tumor-associated markers (SDC1, JCHAIN, DERL3), and high-risk UAMS7 subtypes (MF, MS, PR). Moreover, post-baseline GEP70 risk scores (from matched bone marrow aspirates) positively correlated with elevated C1Q expression in whole bone marrow samples. Conclusion: Both single-cell and bulk analyses indicate that the persistence of immunosuppressive C1Q macrophages following therapy is associated with inferior clinical outcomes. Although the precise mechanisms are yet to be fully understood, the close proximity of similar macrophages to tumor cells–as observed in other cancers–likely also occurs in myeloma and reflects the crucial relationship between tumor cells and macrophages within the bone marrow. While C1Q macrophages are typically rare in individual samples, analysis of combined cohorts is building evidence of their crucial role in immune cross-talk and therapeutic resistance mechanisms.

Abstract Pancreatic ductal adenocarcinoma (PDAC) remains among the most aggressive cancers, due to its limited therapeutic options and poor prognosis. Even with the adoption of total neoadjuvant therapy (TNT) and potentially curative surgical resection, PDAC relapse rates remain unacceptably high. Current systems for evaluating tumor response are valuable but limited, as they fail to capture the ecological complexity and broader architecture of the tumor microenvironment (TME). This results in uncertainty regarding the prognosis and recurrence risk of patients. To address this and to capture the complexity of the PDAC TME, we developed the Tumor Landscape Analysis (TLA). Using digitized H&E slides from 203 PDAC patients who received TNT and surgical resection at our institution, we applied a machine-learning pipeline to segment tumor and stromal compartments. We then quantified the TME architecture using ecological frameworks to assess the disease in multiple scales: individual patches, whole-slide landscapes, and aggregated patient-level summaries. Our analysis revealed that higher-order spatial features are independently prognostic of disease-free survival (DFS). Two statistical models showed different but complementary spatial characteristics that predict disease risk. In the first model, patients with more irregular cancer patch shapes and lower variability in stromal shape had significantly better DFS, with high-risk patients relapsing in a median of 7.2 months compared to 11.6 months in the low-risk group (HR=1.82, p=0.0003). In the second model, smaller stromal patch areas combined with greater tumor-stroma edge density identified patients at elevated risk, with high-risk individuals showing a median DFS of 8.0 months versus 15.7 months in low-risk patients (HR=1.73, p=0.0007). Importantly, these associations persisted even after adjustment for the T and N stage, showing that spatial features provide unique information beyond traditional pathology measures. These models help visualize PDAC as a comprehensive ecosystem that carries clinical significance. By quantifying tumor conformation and configuration, our models reveal prognostic information not available through CAP grading, percent tumor burden, or routine cell counts. This study suggests that tumor-stroma interactions and their spatial organizations are potentially biologically important for recurrence. We present a new, ecologically inspired approach to digital pathology for PDAC that not only improves our ability to predict recurrence and survival in PDAC but also sheds light on cancer as a complex, evolving ecosystem. Citation Format: Merih D. Toruner, Luis H. Cisneros, Miranda Lin, Andrea Maraone, Carlo Maley, Paul Dizona, Qian Shi, Martin E. Fernandez-Zapico, Ryan M. Carr. Ecological landscape analysis of the tumor microenvironment predicts recurrence risk in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Cancer Evolution: The Dynamics of Progression and Persistence; 2025 Dec 4-6; Albuquerque, NM. Philadelphia (PA): AACR; Cancer Res 2025;85(23_Suppl):Abstract nr B027.