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.
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.
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.
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.
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.
Supplemental Digital Content is available in the text
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.
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.
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