Mumme Hope L, Huang Chenbin, Ohlstrom Denis, Bakhtiari Mojtaba, Raikar Sunil S, DeRyckere Deborah, Qayed Muna, Castellino Sharon M, Wechsler Daniel S, Porter Christopher C, Graham Douglas K, Bhasin Swati S, Bhasin Manoj
Department of Biomedical Informatics, Emory University, 101 Woodruff Circle, Atlanta, GA, 30322, USA.
Coulter Department of Biomedical Engineering, Georgia Institute of Technology, 313 Ferst Dr NW, Atlanta, GA, 30332, USA.
Nat Commun. 2025 May 2;16(1):4114. doi: 10.1038/s41467-025-59362-5.
Single-cell transcriptome profiling enables unparalleled characterization of the heterogeneous microenvironment of pediatric leukemias. To facilitate comparative analyses and generate pediatric leukemia signatures, we collect, process, and annotate single-cell data comprising over 540,000 cells from 159 different pediatric acute leukemia (myeloid, lymphoid, mixed phenotype lineages) and healthy bone marrow (BM) samples, profiled in our lab and curated from publicly available studies. The analysis identifies a leukemia-enriched signature of nine genes with over-expression in leukemic blast compared to healthy BM cells. This signature is also consistently over-expressed in leukemia samples compared to normal BM in bulk RNA-seq datasets (over 2000 samples). Outcome-based analysis on diagnosis samples using measurable residual disease (MRD) status depicts a significant association of oncogene-induced senescence and g-protein activation pathways with MRD positivity. MRD positivity across pediatric leukemias is also correlated with significant depletion of CD8+ and CD4+ naïve T-cells and M1-macrophages at diagnosis. To enable easy access to this comprehensive pediatric leukemia single-cell atlas, we develop the Pediatric Single-cell Cancer Atlas (PedSCAtlas, https://bhasinlab.bmi.emory.edu/PediatricSCAtlas/ ). The atlas allows for quick exploration of single-cell data based on genes, cell type composition, and clinical outcomes to understand the cellular landscape of pediatric leukemias.
单细胞转录组分析能够对儿童白血病的异质性微环境进行无与伦比的表征。为了便于进行比较分析并生成儿童白血病特征，我们收集、处理并注释了来自159个不同儿童急性白血病（髓系、淋巴系、混合表型谱系）和健康骨髓（BM）样本的超过540,000个细胞的单细胞数据，这些数据在我们实验室进行了分析，并从公开可用的研究中整理而来。分析确定了一个由九个基因组成的白血病富集特征，与健康BM细胞相比，白血病母细胞中这些基因过度表达。在批量RNA测序数据集（超过2000个样本）中，与正常BM相比，该特征在白血病样本中也始终过度表达。使用可测量残留疾病（MRD）状态对诊断样本进行基于结果的分析表明，癌基因诱导的衰老和G蛋白激活途径与MRD阳性之间存在显著关联。儿童白血病中的MRD阳性也与诊断时CD8 +和CD4 +初始T细胞以及M1巨噬细胞的显著耗竭相关。为了便于轻松访问这个全面的儿童白血病单细胞图谱，我们开发了儿童单细胞癌症图谱（PedSCAtlas，https://bhasinlab.bmi.emory.edu/PediatricSCAtlas/ ）。该图谱允许基于基因、细胞类型组成和临床结果快速探索单细胞数据，以了解儿童白血病的细胞景观。
