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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., (© 2024 American Society of Hematology. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.)

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 F 1 score of ≈0.94 when evaluated on 519 B-ALL samples and shows better results than existing methods on 4 different datasets., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)