Mining single-cell transcriptomic data reveals distinct T-cell population in pediatric B-ALL and AML at diagnosis

Immunotherapy represents a promising strategy to improve outcomes in pediatric leukemia; however, its efficacy remains considerably lower in acute myeloid leukemia (AML) compared with B-cell acute lymphoblastic leukemia (B-ALL). To characterize T-cell subsets in AML and B-ALL, we took advantage of existing data sets and performed an integrated single-cell RNA sequencing (scRNA-seq) analysis of T cells from pediatric patients with B-ALL (n=89) and AML (n=26), and healthy donors (n=9), mostly from bone marrow at diagnosis. In total, 47,610 T cells were analyzed, revealing 17 transcriptionally distinct subsets. Comparative analysis identified T-cell subsets distinguishing B-ALL from AML, such as proliferative, naïve CD4, and progenitor exhausted, and naïve or resting CD4 regulatory T cells. We identified a rare T-cell subset expressing hemoglobin genes, which was enriched in B-ALL and characterized by upregulation of heme metabolism and chronic hypoxia-associated pathways, and its abundance was associated with better outcomes. Collectively, our findings delineate the transcriptional and functional heterogeneity of T cells in pediatric B-ALL and AML and provide insights that may inform future T-cell-based immunotherapeutic strategies.

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Publication Details

Journal
Blood Advances
Published
2026-04-14
DOI
https://doi.org/10.1182/bloodadvances.2025019565
Primary Topic
Acute Lymphoblastic Leukemia research
Type
article
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article

Mining single-cell transcriptomic data reveals distinct T-cell population in pediatric B-ALL and AML at diagnosis

Stephen M Gottschalk, Liqing Tian
Blood Advances
Acute Lymphoblastic Leukemia research
article

Mining single-cell transcriptomic data reveals distinct T-cell population in pediatric B-ALL and AML at diagnosis

Stephen M Gottschalk, Liqing Tian
article en

Abstract

Immunotherapy represents a promising strategy to improve outcomes in pediatric leukemia; however, its efficacy remains considerably lower in acute myeloid leukemia (AML) compared with B-cell acute lymphoblastic leukemia (B-ALL). To characterize T-cell subsets in AML and B-ALL, we took advantage of existing data sets and performed an integrated single-cell RNA sequencing (scRNA-seq) analysis of T cells from pediatric patients with B-ALL (n=89) and AML (n=26), and healthy donors (n=9), mostly from bone marrow at diagnosis. In total, 47,610 T cells were analyzed, revealing 17 transcriptionally distinct subsets. Comparative analysis identified T-cell subsets distinguishing B-ALL from AML, such as proliferative, naïve CD4, and progenitor exhausted, and naïve or resting CD4 regulatory T cells. We identified a rare T-cell subset expressing hemoglobin genes, which was enriched in B-ALL and characterized by upregulation of heme metabolism and chronic hypoxia-associated pathways, and its abundance was associated with better outcomes. Collectively, our findings delineate the transcriptional and functional heterogeneity of T cells in pediatric B-ALL and AML and provide insights that may inform future T-cell-based immunotherapeutic strategies.

Blood Advances
St. Jude Children's Research Hospital (US)
Good health and well-being
Openalex Percentile: Top 15%
Acute Lymphoblastic Leukemia research
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Mining single-cell transcriptomic data reveals distinct T-cell population in pediatric B-ALL and AML at diagnosis — Stephen M Gottschalk, Liqing Tian · Blood Advances (2026) | TGRS Research Map | TGRS