CD371-positive pediatric B-cell acute lymphoblastic leukemia: propensity to lineage switch and slow early response to treatment.

ABSTRACT: In the effort to improve immunophenotyping and minimal residual disease (MRD) assessment in acute lymphoblastic leukemia (ALL), the international Berlin-Frankfurt-Münster (iBFM) Flow Network introduced the myelomonocytic marker CD371 for a large prospective characterization with a long follow-up. In the present study, we aimed to investigate the clinical and biological features of CD371-positive (CD371pos) pediatric B-cell precursor ALL (BCP-ALL). From June 2014 to February 2017, 1812 pediatric patients with newly diagnosed BCP-ALLs enrolled in trial AIEOP-BFM ALL 2009 were evaluated as part of either a screening (n = 843, Italian centers) or validation cohort (n = 969, other iBFM centers). Laboratory assessment at diagnosis consisted of morphological, immunophenotypic, and genetic analysis. Response assessment relied on morphology, multiparametric flow cytometry (MFC), and polymerase chain reaction (PCR)-MRD. At diagnosis, 160 of 1812 (8.8%) BCP-ALLs were CD371pos. This correlated with older age, lower ETV6::RUNX1 frequency, immunophenotypic immaturity (all P < .001), and strong expression of CD34 and of CD45 (P < .05). During induction therapy, CD371pos BCP-ALLs showed a transient myelomonocytic switch (mm-SW: up to 65.4% of samples at day 15) and an inferior response to chemotherapy (slow early response, P < .001). However, the 5-year event-free survival was 88.3%. Among 420 patients from the validation cohort, 27 of 28 (96.4%) cases positive for DUX4-fusions were CD371pos. In conclusion, in the largest pediatric cohort, CD371 is the most sensitive marker of transient mm-SW, whose recognition is essential for proper MFC MRD assessment. CD371pos is associated to poor early treatment response, although a good outcome can be reached after MRD-based ALL-related therapies.

FCM marker importance for MRD assessment in T-cell acute lymphoblastic leukemia: An AIEOP-BFM-ALL-FLOW study group report.

T-lineage acute lymphoblastic leukemia (T-ALL) accounts for about 15% of pediatric and about 25% of adult ALL cases. Minimal/measurable residual disease (MRD) assessed by flow cytometry (FCM) is an important prognostic indicator for risk stratification. In order to assess the MRD a limited number of antibodies directed against the most discriminative antigens must be selected. We propose a pipeline for evaluating the influence of different markers for cell population classification in FCM data. We use linear support vector machine, fitted to each sample individually to avoid issues with patient and laboratory variations. The best separating hyperplane direction as well as the influence of omitting specific markers is considered. Ninety-one bone marrow samples of 43 pediatric T-ALL patients from five reference laboratories were analyzed by FCM regarding marker importance for blast cell identification using combinations of eight different markers. For all laboratories, CD48 and CD99 were among the top three markers with strongest contribution to the optimal hyperplane, measured by median separating hyperplane coefficient size for all samples per center and time point (diagnosis, Day 15, Day 33). Based on the available limited set tested (CD3, CD4, CD5, CD7, CD8, CD45, CD48, CD99), our findings prove that CD48 and CD99 are useful markers for MRD monitoring in T-ALL. The proposed pipeline can be applied for evaluation of other marker combinations in the future.

Genomic breakpoint-specific monitoring of measurable residual disease in pediatric non-standard-risk acute myeloid leukemia.

Pediatric acute myeloid leukemia (AML) is a highly heterogeneous disease making standardized measurable residual disease (MRD) assessment challenging. Currently, patient-specific DNA-based assays are only rarely applied for MRD assessment in pediatric AML. We tested whether quantification of genomic breakpoint-specific sequences via quantitative polymerase chain reaction (gDNA-PCR) provides a reliable means of MRD quantification in children with non-standardrisk AML and compared its results to those obtained with state-of-the-art ten-color flow cytometry (FCM). Breakpointspecific gDNA-PCR assays were established according to Euro-MRD consortium guidelines. FCM-MRD assessment was performed according to the European Leukemia Network guidelines with adaptations for pediatric AML. Of 77 consecutively recruited non-standard-risk pediatric AML cases, 49 (64%) carried a chromosomal translocation potentially suitable for MRD quantification. Genomic breakpoint analysis returned a specific DNA sequence in 100% (41/41) of the cases submitted for investigation. MRD levels were evaluated using gDNA-PCR in 243 follow-up samples from 36 patients, achieving a quantitative range of at least 10-4 in 231/243 (95%) of samples. Comparing gDNA-PCR with FCM-MRD data for 183 bone marrow follow-up samples at various therapy timepoints showed a high concordance of 90.2%, considering a cut-off of ≥0.1%. Both methodologies outperformed morphological assessment. We conclude that MRD monitoring by gDNA-PCR is feasible in pediatric AML with traceable genetic rearrangements and correlates well with FCM-MRD in the currently applied clinically relevant range, while being more sensitive below that. The methodology should be evaluated in larger cohorts to pave the way for clinical application.

Chemical Acetylation of Ligands and Two-Step Digestion Protocol for Reducing Codigestion in Affinity Purification-Mass Spectrometry.

We present an effective, fast, and user-friendly method to reduce codigestion of bead-bound ligands, such as antibodies or streptavidin, in affinity purification-mass spectrometry experiments. A short preincubation of beads with Sulfo-NHS-Acetate leads to chemical acetylation of lysine residues, making ligands insusceptible to Lys-C-mediated proteolysis. In contrast to similar approaches, our procedure offers the advantage of exclusively using nontoxic chemicals and employing mild chemical reaction conditions. After binding of bait proteins to Sulfo-NHS-Acetate treated beads, we employ a two-step digestion protocol with the sequential use of Lys-C protease for on-bead digestion followed by in-solution digestion of the released proteins with trypsin. The implementation of this protocol results in a strong reduction of contaminating ligand peptides, which allows significantly higher amounts of sample to be subjected to LC-MS analysis, improving sensitivity and quantitative accuracy.

Automated Flow Cytometric MRD Assessment in Childhood Acute B- Lymphoblastic Leukemia Using Supervised Machine Learning.

Minimal residual disease (MRD) as measured by multiparameter flow cytometry (FCM) is an independent and strong prognostic factor in B-cell acute lymphoblastic leukemia (B-ALL). However, reliable flow cytometric detection of MRD strongly depends on operator skills and expert knowledge. Hence, an objective, automated tool for reliable FCM-MRD quantification, able to overcome the technical diversity and analytical subjectivity, would be most helpful. We developed a supervised machine learning approach using a combination of multiple Gaussian Mixture Models (GMM) as a parametric density model. The approach was used for finding the weights of a linear combination of multiple GMMs to represent new, "unseen" samples by an interpolation of stored samples. The experimental data set contained FCM-MRD data of 337 bone marrow samples collected at day 15 of induction therapy in three different laboratories from pediatric patients with B-ALL for which accurate, expert-set gates existed. We compared MRD quantification by our proposed GMM approach to operator assessments, its performance on data from different laboratories, as well as to other state-of-the-art automated read-out methods. Our proposed GMM-combination approach proved superior over support vector machines, deep neural networks, and a single GMM approach in terms of precision and average F 1 -scores. A high correlation of expert operator-based and automated MRD assessment was achieved with reliable automated MRD quantification (F 1 -scores >0.5 in more than 95% of samples) in the clinically relevant range. Although best performance was found, if test and training samples were from the same system (i.e., flow cytometer and staining panel; lowest median F 1 -score 0.92), cross-system performance remained high with a median F 1 -score above 0.85 in all settings. In conclusion, our proposed automated approach could potentially be used to assess FCM-MRD in B-ALL in an objective and standardized manner across different laboratories. © 2019 International Society for Advancement of Cytometry.

Flow-cytometric minimal residual disease monitoring in blood predicts relapse risk in pediatric B-cell precursor acute lymphoblastic leukemia in trial AIEOP-BFM-ALL 2000.

BACKGROUND: Flow-cytometric monitoring of minimal residual disease (MRD) in bone marrow (BM) during induction of pediatric patients with acute lymphoblastic leukemia (ALL) is widely used for outcome prognostication and treatment stratification. Utilizing peripheral blood (PB) instead of BM might be favorable, but data on its usefulness are scarce. PROCEDURE: We investigated 1303 PB samples (days 0, 8, 15, 33, and 52) and 285 BMs (day 15) from 288 pediatric ALL patients treated in trial AIEOP-BFM ALL 2000. MRD was assessed by four-color flow cytometry and evaluated as relative, absolute, and kinetic result. RESULTS: In B-ALL only, PB measures from early time points correlated with relapse incidence (CIR). Best separation occurred at threshold <1 blast/µL at day 8 (5-year CIR 0.02 ± 0.02 vs 0.12 ± 0.03; P = 0.044). Patients with highest relapse risk were not distinguishable, but PB-MRD at days 33 and 52 correlated with prednisone response and postinduction BM-MRD by PCR (P < 0.001). Kinetic assessment did not convey any advantage. In multivariate analysis including day 15 BM-MRD, PB-MRD measures lost statistical power. CONCLUSIONS: In summary, PB-MRD in pediatric B-ALL correlates with outcome and risk parameters, but its prognostic significance is not strong enough to substitute for BM assessment in AIEOP-BFM trials. It might, however, be valuable in treatment environments not using multifaceted risk stratification with other MRD measures.

UMAP Based Anomaly Detection for Minimal Residual Disease Quantification within Acute Myeloid Leukemia.

Leukemia is the most frequent malignancy in children and adolescents, with acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) as the most common subtypes. Minimal residual disease (MRD) measured by flow cytometry (FCM) has proven to be a strong prognostic factor in ALL as well as in AML. Machine learning techniques have been emerging in the field of automated MRD quantification with the objective of superseding subjective and time-consuming manual analysis of FCM-MRD data. In contrast to ALL, where supervised multi-class classification methods have been successfully deployed for MRD detection, AML poses new challenges: AML is rarer (with fewer available training data) than ALL and much more heterogeneous in its immunophenotypic appearance, where one-class classification (anomaly detection) methods seem more suitable. In this work, a new semi-supervised approach based on the UMAP algorithm for MRD detection utilizing only labels of blast free FCM samples is presented. The method is tested on a newly gathered set of AML FCM samples and results are compared to state-of-the-art methods. We reach a median F1-score of 0.794, while providing a transparent classification pipeline with explainable results that facilitates inter-disciplinary work between medical and technical experts. This work shows that despite several issues yet to overcome, the merits of automated MRD quantification can be fully exploited also in AML.

Automated identification of cell populations in flow cytometry data with transformers.

Acute Lymphoblastic Leukemia (ALL) is the most frequent hematologic malignancy in children and adolescents. A strong prognostic factor in ALL is given by the Minimal Residual Disease (MRD), which is a measure for the number of leukemic cells persistent in a patient. Manual MRD assessment from Multiparameter Flow Cytometry (FCM) data after treatment is time-consuming and subjective. In this work, we present an automated method to compute the MRD value directly from FCM data. We present a novel neural network approach based on the transformer architecture that learns to directly identify blast cells in a sample. We train our method in a supervised manner and evaluate it on publicly available ALL FCM data from three different clinical centers. Our method reaches a median F1 score of ≈0.94 when evaluated on 519 B-ALL samples and shows better results than existing methods on 4 different datasets.

An Extensive Quality Control and Quality Assurance (QC/QA) Program Significantly Improves Inter-Laboratory Concordance Rates of Flow-Cytometric Minimal Residual Disease Assessment in Acute Lymphoblastic Leukemia: An I-BFM-FLOW-Network Report.

Monitoring of minimal residual disease (MRD) by flow cytometry (FCM) is a powerful prognostic tool for predicting outcomes in acute lymphoblastic leukemia (ALL). To apply FCM-MRD in large, collaborative trials, dedicated laboratory staff must be educated to concordantly high levels of expertise and their performance quality should be continuously monitored. We sought to install a unique and comprehensive training and quality control (QC) program involving a large number of reference laboratories within the international Berlin-Frankfurt-Münster (I-BFM) consortium, in order to complement the standardization of the methodology with an educational component and persistent quality control measures. Our QC and quality assurance (QA) program is based on four major cornerstones: (i) a twinning maturation program, (ii) obligatory participation in external QA programs (spiked sample send around, United Kingdom National External Quality Assessment Service (UK NEQAS)), (iii) regular participation in list-mode-data (LMD) file ring trials (FCM data file send arounds), and (iv) surveys of independent data derived from trial results. We demonstrate that the training of laboratories using experienced twinning partners, along with continuous educational feedback significantly improves the performance of laboratories in detecting and quantifying MRD in pediatric ALL patients. Overall, our extensive education and quality control program improved inter-laboratory concordance rates of FCM-MRD assessments and ultimately led to a very high conformity of risk estimates in independent patient cohorts.

Phospho-Profiling Linking Biology and Clinics in Pediatric Acute Myeloid Leukemia.

Aberrant activation of key signaling-molecules is a hallmark of acute myeloid leukemia (AML) and may have prognostic and therapeutic implications. AML summarizes several disease entities with a variety of genetic subtypes. A comprehensive model spanning from signal activation patterns in major genetic subtypes of pediatric AML (pedAML) to outcome prediction and pre-clinical response to signaling inhibitors has not yet been provided. We established a high-throughput flow-cytometry based method to assess activation of hallmark phospho-proteins (phospho-flow) in 166 bone-marrow derived pedAML samples under basal and cytokine stimulated conditions. We correlated levels of activated phospho-proteins at diagnosis with relapse incidence in intermediate (IR) and high risk (HR) subtypes. In parallel, we screened a set of signaling inhibitors for their efficacy against primary AML blasts in a flow-cytometry based ex vivo cytotoxicity assay and validated the results in a murine xenograft model. Certain phospho-signal patterns differ between genetic subtypes of pedAML. Some are consistently seen through all AML subtypes such as pSTAT5. In IR/HR subtypes high levels of GM-CSF stimulated pSTAT5 and low levels of unstimulated pJNK correlated with increased relapse risk overall. Combination of GM-CSF/pSTAT5high and basal/pJNKlow separated three risk groups among IR/HR subtypes. Out of 10 tested signaling inhibitors, midostaurin most effectively affected AML blasts and simultaneously blocked phosphorylation of multiple proteins, including STAT5. In a mouse xenograft model of KMT2A-rearranged pedAML, midostaurin significantly prolonged disease latency. Our study demonstrates the applicability of phospho-flow for relapse-risk assessment in pedAML, whereas functional phenotype-driven ex vivo testing of signaling inhibitors may allow individualized therapy.

Flow-Cytometric Monitoring of Minimal Residual Disease in Pediatric Patients With Acute Myeloid Leukemia: Recent Advances and Future Strategies.

Minimal residual disease (MRD) by multiparametric flow cytometry (MFC) has been recently shown as a strong and independent prognostic marker of relapse in pediatric AML (pedAML) when measured at specific time points during Induction and/or Consolidation therapy. Hence, MFC-MRD has the potential to refine the current strategies of pedAML risk stratification, traditionally based on the cytogenetic and molecular genetic aberrations at diagnosis. Consequently, it may guide the modulation of therapy intensity and clinical decision making. However, the use of non-standardized protocols, including different staining panels, analysis, and gating strategies, may hamper a broad implementation of MFC-MRD monitoring in clinical routine. Besides, the thresholds of MRD positivity still need to be validated in large, prospective and multi-center clinical studies, as well as optimal time points of MRD assessment during therapy, to better discriminate patients with different prognosis. In the present review, we summarize the most relevant findings on MFC-MRD testing in pedAML. We examine the clinical significance of MFC-MRD and the recent advances in its standardization, including innovative approaches with an automated analysis of MFC-MRD data. We also touch upon other technologies for MRD assessment in AML, such as quantitative genomic breakpoint PCR, current challenges and future strategies to enable full incorporation of MFC-MRD into clinical practice.

B cells sustain inflammation and predict response to immune checkpoint blockade in human melanoma.

Tumor associated inflammation predicts response to immune checkpoint blockade in human melanoma. Current theories on regulation of inflammation center on anti-tumor T cell responses. Here we show that tumor associated B cells are vital to melanoma associated inflammation. Human B cells express pro- and anti-inflammatory factors and differentiate into plasmablast-like cells when exposed to autologous melanoma secretomes in vitro. This plasmablast-like phenotype can be reconciled in human melanomas where plasmablast-like cells also express T cell-recruiting chemokines CCL3, CCL4, CCL5. Depletion of B cells in melanoma patients by anti-CD20 immunotherapy decreases tumor associated inflammation and CD8+ T cell numbers. Plasmablast-like cells also increase PD-1+ T cell activation through anti-PD-1 blockade in vitro and their frequency in pretherapy melanomas predicts response and survival to immune checkpoint blockade. Tumor associated B cells therefore orchestrate and sustain melanoma inflammation and may represent a predictor for survival and response to immune checkpoint blockade therapy.