儿童急性髓系白血病（AML）是一种侵袭性血癌，预后不良，复发率高。当前识别免疫治疗靶点的挑战来自于患者特异性母细胞免疫表型及其在疾病进展过程中的变化。为了克服这个问题，我们提出了一种新的计算研究工具来快速识别恶性细胞。我们生成了 21 名儿童 AML 患者的单细胞流式细胞术图谱，并在诊断、缓解和复发时提供了匹配的样本。我们将分类器与自动编码器结合起来进行异常检测，并以 90% 的准确率对恶性爆炸进行分类。此外，我们的方法在单细胞水平上为原始细胞分配一个发育阶段，改进了当前基于显性表型分化的分类方法。我们观察到诊断和复发之间主要的免疫表型和发育阶段的变化。与具有其他分子特征的患者相比，具有 KMT2A 重排的患者在复发时其原始细胞免疫表型发生了更深刻的变化。我们的方法以公正的方式提供了对 AML 母细胞的免疫表型组成的新见解，并有助于确定可能改善个性化 AML 治疗的免疫治疗靶点。© 2024 Driessen 等人。

Pediatric acute myeloid leukemia (AML) is an aggressive blood cancer with a poor prognosis and high relapse rate. Current challenges in the identification of immunotherapy targets arise from patient-specific blast immunophenotypes and their change during disease progression. To overcome this, we present a new computational research tool to rapidly identify malignant cells. We generated single-cell flow cytometry profiles of 21 pediatric AML patients with matched samples at diagnosis, remission, and relapse. We coupled a classifier to an autoencoder for anomaly detection and classified malignant blasts with 90% accuracy. Moreover, our method assigns a developmental stage to blasts at the single-cell level, improving current classification approaches based on differentiation of the dominant phenotype. We observed major immunophenotype and developmental stage alterations between diagnosis and relapse. Patients with KMT2A rearrangement had more profound changes in their blast immunophenotypes at relapse compared to patients with other molecular features. Our method provides new insights into the immunophenotypic composition of AML blasts in an unbiased fashion and can help to define immunotherapy targets that might improve personalized AML treatment.© 2024 Driessen et al.