Jevremović, Dragan

Abstract Measurable residual disease (MRD) assessment by flow cytometry (FC) plays an essential role in prognosis and therapy escalation of B-cell acute lymphoblastic leukemia (B-ALL). However, the high degree of expertise and manual analysis time required limits the availability of this assay. To overcome this limitation, we developed a data-enhancing artificial intelligence (AI) pipeline that accelerates and simplifies MRD analysis. Unaltered FC files from 171 B-ALL MRD-positive and 89 MRD-negative cases were processed through an AI pipeline trained with 31 expert-gated negative controls. Cluster-informed downsampling reduced FC files from 1.2 million to 155 884 cells per case, on average, (87% cellularity reduction), whereas preserving small MRD populations (median, 100% retention for MRD of <1%) and allowing for true percentage MRD estimates using a correction factor. A deep neural network cell classifier automatically identified normal hematopoietic subsets (macro-averaged F1 score of 0.86); and an AI measure of anomaly discriminated B-ALL from benign mononuclear (area under the curve [AUC] of 0.98) or B-lymphoid cells (AUC of 0.94). Manual analysis of AI-enhanced files was completed in only 1.01 minutes per case, on average (standard deviation of ±0.57); with 100% positive agreement with conventional analysis (for MRD of ≥0.01%), 100% negative agreement, and excellent quantitative correlation (R2 = 0.92). Our cloud-based AI-enhancement solution accelerates B-ALL MRD identification without compromising test performance and has the potential of facilitating B-ALL MRD analysis by more clinical laboratories.

Abstract Monoclonal antibodies targeting CD38 are a therapeutic mainstay in multiple myeloma (MM). Although they have contributed to improved outcomes, most patients still experience disease relapse, and little is known about tumor-intrinsic mechanisms of resistance to these drugs. Antigen escape has been implicated as a mechanism of tumor-cell evasion in immunotherapy. Yet, it is unknown whether MM cells can develop permanent resistance to anti-CD38 antibodies by acquiring genomic events leading to biallelic disruption of the CD38 gene locus. Here, we analyzed whole-genome and whole-exome sequencing data from patients 701 newly diagnosed MM, 67 patients at relapse with naivety to anti-CD38 antibodies, and 50 patients collected at relapse after anti-CD38 antibodies. We report a loss of CD38 in 10 of 50 patients (20%) after CD38 therapy, 3 of whom exhibited a loss of both copies. Two of these cases showed convergent evolution in which distinct subclones independently acquired similar advantageous variants. Functional studies on missense mutations involved in biallelic CD38 events revealed that 2 variants, L153H and C275Y, decreased binding affinity and antibody-dependent cellular cytotoxicity of the commercial antibodies daratumumab and isatuximab. However, a third mutation, R140G, conferred selective resistance to daratumumab, while retaining sensitivity to isatuximab. Clinically, patients with MM are often rechallenged with CD38 antibodies after disease progression and these data suggest that next-generation sequencing may play a role in subsequent treatment selection for a subset of patients.

e19531 Background: Effective treatment and elimination of clonal plasma cells (PC) in multiple myeloma (MM) are typically associated with recovery of polyclonal (normal) plasma cells (PPC). Studies suggest that robust PPC recovery is associated with better outcomes. However, it is unclear if this remains valid in the context of monoclonal antibodies, such as Daratumumab, that selectively target plasma cells, and in turn, may adversely impact PPC recovery. Methods: We identified patients with MM who underwent MRD testing using Euroflow method at 6-12 months after treatment initiation. Eight patients had disease progression prior to MRD testing and were excluded from further analysis. PPC was quantitated by the proportion of total events acquired during flow examination. Patients were considered MRD-negative if they had <1 clonal PCs in 10 5 cells, as detected in the marrow. We first examined the impact of initial therapy (Daratumumab vs. non-Daratumumab based regimens) and MRD status on PPC recovery. Subsequently, we analyzed impact of PPC recovery on patient outcomes in terms of progression-free survival (PFS) and overall survival (OS). Results: We identified 572 patients who had MRD testing by flow at a median of 9 months (range 6-12) after treatment initiation. The median age was 63 years, 58% were male. Daratumumab was part of initial therapy in 17% of patients; the most common induction therapies were PI-IMiD triplets (73%), and dara-PI-IMiD quads (15%). In our cohort, 74% of patients were MRD-negative. In our practice, only samples with no monotypic PCs identified on initial low-sensitivity flow proceed to MRD testing, hence, the proportion of MRD-negative patients appears higher in our study than previously reported. Median PPC was 0.02% and was similar between MRD-negative and -positive patients. We found the median PPC was significantly low in patients who received Daratumumab compared to the non-Daratumumab treated cohort (0.011% vs. 0.023%; p<0.01). There was a trend towards lower PFS and OS among the lowest PPC quartile group compared to the upper 3 quartiles, although this was not significant (p=0.07 for PFS and OS, Wilcoxon). This trend was more evident among patients who did not receive Daratumumab. Conclusions: Our study demonstrates negative impact of anti-CD38 therapy with Daratumumab on recovery of PPCs after initial treatment, consistent with the persistent hypogammaglobulinemia seen in clinical practice among these patients. However, unlike the observation with the non-Daratumumab treated cohort, the low proportion of PPCs does not significantly impact patient outcomes among patients who received Daratumumab.

Background: Flow cytometric detection of minimal residual disease (MRD) in chronic lymphocytic leukemia (CLL) is complex, time-consuming, and subject to inter-operator variability. Deep neural networks (DNNs) offer potential for standardization and efficiency improvement, but require rigorous validation and monitoring for safe clinical implementation. Methods: We evaluated a DNN-assisted human-in-the-loop approach for CLL MRD detection. Initial validation included method comparison against manual analysis (n = 240), precision studies, and analytical sensitivity verification. Post-implementation monitoring comprised four components: daily electronic quality control, input data drift detection, error analysis, and attribute acceptance sampling. Laboratory efficiency was assessed through a timing study of 161 cases analyzed by five technologists. Results: Method comparison demonstrated 97.5% concordance with manual analysis for qualitative classification (sensitivity 100%, specificity 95%) and excellent correlation for quantitative assessment (r = 0.99, Deming slope = 0.99). Precision studies confirmed high repeatability and within-laboratory precision across multiple operators. Analytical sensitivity was verified at 0.002% MRD. Post-implementation monitoring identified 2.97% of cases (26/874) with input data drift, primarily high-burden CLL and non-CLL neoplasms. Error analysis showed the DNN alone achieved 97% sensitivity compared to human-in-the-loop-reviewed results, with 13 missed cases (1.5%) showing atypical immunophenotypes. Attribute acceptance sampling confirmed 98.8% of reported negative cases were true negatives. The DNN-assisted workflow reduced average analysis time by 60.3% compared to manual analysis (4.2 ± 2.3 vs. 10.5 ± 5.8 min). Conclusions: The implementation of a DNN-assisted approach for CLL MRD detection in a clinical laboratory provides diagnostic performance equivalent to expert manual analysis while substantially reducing analysis time. Comprehensive performance monitoring ensures ongoing safety and effectiveness in routine clinical practice. This approach provides a model for responsible AI integration in clinical laboratories, balancing automation benefits with expert oversight.

Abstract Extramedullary disease (EMD) is associated with an inferior prognosis and lower response rates to conventional multiple myeloma (MM)–directed therapies compared to MM without EMD. A deeper understanding of the molecular landscape and underlying drivers of EMD is essential to identify potential targets for novel therapeutic strategies. To address this, we performed whole-exome sequencing on EMD tumor tissue from 18 unique patients and bone marrow aspirates (BMAs) from 20 patients at the time of EMD development. Notably, paired EMD and BMA samples were collected from 6 patients at the point of EMD diagnosis, allowing for direct comparison of molecular profiles. Our analysis revealed a near-universal presence of mutations within the MAPK pathway in EMD samples (94%), compared to BMAs (60%; odds ratio, 10.7; P = .02; q &lt; 0.1). Additionally, mutations in established driver genes (NRAS, KRAS, and BRAF) were common and frequently clonal, suggesting their central role in EMD pathogenesis. We also identified alterations in genes associated with cell adhesion and migration (ROBO1, ROBO2, and FAT1) and the SWI/SNF complex and epigenetic regulators (ARID1A, KMT2C, KMT2D, and EP300), although these were predominantly subclonal. Furthermore, we frequently detected biallelic alterations in the tumor suppressor genes MAX (22%), a binding partner for MYC, and CDKN2C (17%). Genomic complexity was significantly higher in EMD samples than BMAs, as evidenced by increased tumor mutational burden and the enrichment of 1q gain/amplifications. These findings underscore the distinct molecular profile of EMD compared to BMA and highlight the genomically complex and heterogeneous nature of extramedullary disease in MM.

Background/Objectives: DDX41, DEAD-box RNA helicase 41 gene located on chromosome 5q25.3, is one of the most mutated genes in patients with germline predisposition to myeloid neoplasms. Germline and somatic mutations often have different locations and patterns of mutation, with some hotspots displaying diversity based on ethnicity. We aimed to explore clinical outcomes in patients with various DDX41 hot-spot mutations. Methods: This was a retrospective study of patients at Mayo Clinic with DDX41 mutation identified through Next Generation Sequencing (NGS) between 2018 and 2024. We completed unadjusted comparisons using continuous or categorical variables, and survival rates were assessed using the Kaplan–Meier method and cox regression analysis. Results: Overall survival appears to be higher in those with p.M1| when compared to p.Asp140GlyFs*2 and p.Arg525His, with comparable survival between p.Arg525His and p.Asp140GlyFs*2. Among males with p.M1| who underwent bone marrow transplant, those who underwent bone marrow transplant appeared to have lower survival rates, although not statistically significant. Our study was limited by a small sample size, therefore limiting our ability to reach significance. Conclusions: Our findings suggest potential implications for clinical outcomes based on DDX41 mutation hot-spots.

Background/Objectives: Acute myeloid leukemia (AML) is a biologically heterogeneous malignancy with a variable prognosis. Despite many patients achieving complete remission, relapse remains common, underscoring the need for effective prognostic markers. Measurable residual disease (MRD) has emerged as a critical prognostic indicator, associated with higher relapse risk and shorter survival. This study reports on our initial experience of MRD detection by flow cytometry in 385 bone marrow samples from 126 AML patients. Methods: The flow cytometry MRD assay, validated according to stringent consensus recommendations, consists of a 3-tube, 10-color panel incorporating a broad spectrum of lineage differentiation markers. Analytical specificity, sensitivity, precision, and reproducibility were evaluated, demonstrating the assay’s robustness. Results: The results reveal distinct immunophenotypic aberrancies in all AML cases, with consistent identification of aberrant immunophenotypes in follow-up specimens. AML MRD was detected in 32 out of 126 patients (25%) and in 77 out of 385 analyses (20%), with a median aberrant blast percentage of 1.87% (range, 0.01–12). A change in immunophenotype was documented in 21% of the MRD-positive cases. MRD positivity detected in the first sample studied was associated with reduced overall survival (HR: 5.153; p < 0.0001). Conclusions: Our findings support the integration of flow cytometric MRD analysis into routine clinical practice to enhance risk stratification and treatment planning for AML patients, as currently recommended by professional guidelines.

nema

Introduction: Myeloma response to treatment can be biochemical, pathological, or radiological, with pathological assessments being invasive. Next-generation blood flow (PBF) for assessment of circulating tumor plasma cells (CTCs) has shown promising results as a prognostic in Multiple Myeloma (MM) patients. CTC detection via PBF has a potential to serve as non-invasive method for assessing pathological burden of disease and response to treatment. Comparing CTC responses to the International Myeloma Working Group (IMWG) criteria will further help to understand PBF's utility in predicting response to therapy. Patients and Methods: The study conducted is a retrospective observational study. We included patients with MM treated at Mayo Clinic from 01/01/2011 to 12/31/2019 with CTC records available at the time of best response (BR) to frontline therapy. The CTC values were expressed as the number of plasma cell events per 150,000 Peripheral Blood Mononuclear Cells (CD38, CD138, CD19, CD45, Kappa, Lambda). The CTC levels were compared across all response(IMWG Criteria) groups at BR, and at baseline. The CTC response was expressed as % CTC decrease at BR from baseline. Time-to-event analyses utilized the Kaplan Meier method and Cox-proportional hazards models, with comparisons made using the log-rank test. Results: We identified 621 patients with CTC data at the time of BR to frontline therapy. Of these, 148 (24%) had baseline CTC data from diagnosis. The median age at diagnosis was 62.3 (27.2-83.7). The median follow-up was 66.15 months; the distribution of patients by treatment class is as follows- Alkylator: 0.8%, PI(Proteasome Inhibitor)+Cyclophosphamide: 27.4%, IMid: 12.7%, PI+IMid(Immunomodulator): 55.9%, PI+IMid+antiCD38: 3.2%; 378 patients (78.8%) underwent an autologous transplant. BR to initial therapy was sCR/stringent Complete Response (10, 1.6%), CR (230, 36.9%), VGPR/Very Good Partial Response (224, 36.1%), PR (123, 19.8%), MR/Minimal Response (12, 1.9%), SD/Stable Disease (14, 2.3%), PD/Progressive Disease (8, 1.3%). In the study, 64 patients (10.31%) had detectable CTCs at their BR. The distribution of CTCs across the different response categories was as follows: none (0%) in sCR, 3 patients (1.3%) in CR, 18 patients (8%) in VGPR, 24 patients (19.5%) in PR, 8 patients (66.7%) in MR, 6 patients (42.9%) in SD, and 5 patients (62.5%) in PD. The median CTC counts and their interquartile ranges for these categories showed significant variability: CR had a median of 46 (IQR: 28.5, 923), VGPR had 39.5 (IQR: 15.5, 111.25), PR had 47 (IQR: 22.75, 82.5), MR had 55 (IQR: 28.5, 85), SD had 96.5 (IQR: 22.25, 218.75), and PD had 317 (IQR: 57, 415). This Analysis of Variance (ANOVA) for response-wise distribution of CTC was &lt;0.01. Response was dichotomized as PR and above for sCR, CR, VGPR, PR and less than PR for MR, SD and PD. Median Overall Survival(OS) for PR and above was 127.8 months (vs less than PR 56.7 months, p=0.01). Median OS for CTC+ at BR was 56.7 months (vs 134.8 for CTC negative, p=0.01). On multivariate analysis, presence of CTC at best response (Hazards Ratio = 2.9, n=1.1-2.9), RISS staging at diagnosis (Hazards Ratio = 2.35, n=1.5-3.05), less than PR (Hazards Ratio =1.8, 1.1-2.9) were independent predictors of inferior OS. In patients with data for CTC available at both baseline and at BR to frontline therapy (n=148), 110 had CTC detectable at diagnosis. Among patients in various response categories, a complete disappearance of CTCs was observed in sCR (n=3, 75.0%), CR (n=36, 69.2%), VGPR (n=38, 64.4%), and PR (n=14, 60.9%). CTC responses greater than 90% were noted in VGPR (n=3, 5.1%), PR (n=2, 8.7%), and SD (n=2, 40.0%). No CTC response was reported in sCR (1, 25.0%), CR (16, 30.8%), VGPR (2, 3.4% and 13, 22.0%), PR (3, 13.0% and both 2, 8.7%), SD (1, 20.0% and both 2, 40.0%), MR (1, 50.0%), and PD (1, 33.3% and 1, 50.0%, respectively). The median OS for those with a CTC response was 112.4 months vs 28.2 months for no response. (p=0.01). Conclusion: The presence of CTC at best response is an independent prognostic marker for inferior OS. Depth of response to frontline therapy correspond to a high rate of clearance of CTCs. Presence of CTC at best response provides independent prognostic value beyond the depth of response. A complete clearance of CTC at best response is associated with improved OS. CTC levels have not been corrected for WBC counts and may not be applicable in all settings.