Andy G X Zeng, Ilaria Iacobucci, Sayyam Shah, Amanda Mitchell, Gordon Wong, Suraj Bansal, David Chen, Qingsong Gao, Hyerin Kim, James A Kennedy, Andrea Arruda, Mark D Minden, Torsten Haferlach, Charles G Mullighan, John E Dick
{"title":"Single-cell Transcriptional Atlas of Human Hematopoiesis Reveals Genetic and Hierarchy-Based Determinants of Aberrant AML Differentiation.","authors":"Andy G X Zeng, Ilaria Iacobucci, Sayyam Shah, Amanda Mitchell, Gordon Wong, Suraj Bansal, David Chen, Qingsong Gao, Hyerin Kim, James A Kennedy, Andrea Arruda, Mark D Minden, Torsten Haferlach, Charles G Mullighan, John E Dick","doi":"10.1158/2643-3230.BCD-24-0342","DOIUrl":null,"url":null,"abstract":"<p><p>Therapeutic targeting of acute myeloid leukemia (AML) is hampered by intra- and inter-tumoral cell state heterogeneity. To develop a more precise understanding of AML cell states, we constructed a reference atlas of human hematopoiesis from 263,159 single-cell transcriptomes spanning 55 cellular states. Using this atlas, we mapped more than 1.2 million cells spanning 318 leukemia samples, revealing 12 recurrent patterns of aberrant differentiation in AML. Notably, this uncovered unexpected AML cell states resembling lymphoid and erythroid progenitors that were prognostic within the clinically heterogeneous context of normal karyotype AML, independent of genomic classifications. Systematic mapping of genotype-to-phenotype associations revealed specific differentiation landscapes associated with more than 45 genetic drivers. Importantly, distinct cellular hierarchies can arise from samples sharing the same genetic driver, potentially reflecting distinct cellular origins for disease-sustaining leukemia stem cells. Thus, precise mapping of malignant cell states provides insights into leukemogenesis and refines disease classification in acute leukemia.</p><p><strong>Significance: </strong>We present a single-cell reference atlas of human hematopoiesis and a computational tool for rapid mapping and classification of healthy and leukemic cells. Applied to AML, this has enabled single-cell analysis at the scale of hundreds of patient samples, revealing the full breadth of derailment of differentiation in AML. See related commentary by Berger and Penter, p. 280.</p>","PeriodicalId":29944,"journal":{"name":"Blood Cancer Discovery","volume":" ","pages":"307-324"},"PeriodicalIF":11.5000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12209776/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Blood Cancer Discovery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1158/2643-3230.BCD-24-0342","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEMATOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Therapeutic targeting of acute myeloid leukemia (AML) is hampered by intra- and inter-tumoral cell state heterogeneity. To develop a more precise understanding of AML cell states, we constructed a reference atlas of human hematopoiesis from 263,159 single-cell transcriptomes spanning 55 cellular states. Using this atlas, we mapped more than 1.2 million cells spanning 318 leukemia samples, revealing 12 recurrent patterns of aberrant differentiation in AML. Notably, this uncovered unexpected AML cell states resembling lymphoid and erythroid progenitors that were prognostic within the clinically heterogeneous context of normal karyotype AML, independent of genomic classifications. Systematic mapping of genotype-to-phenotype associations revealed specific differentiation landscapes associated with more than 45 genetic drivers. Importantly, distinct cellular hierarchies can arise from samples sharing the same genetic driver, potentially reflecting distinct cellular origins for disease-sustaining leukemia stem cells. Thus, precise mapping of malignant cell states provides insights into leukemogenesis and refines disease classification in acute leukemia.
Significance: We present a single-cell reference atlas of human hematopoiesis and a computational tool for rapid mapping and classification of healthy and leukemic cells. Applied to AML, this has enabled single-cell analysis at the scale of hundreds of patient samples, revealing the full breadth of derailment of differentiation in AML. See related commentary by Berger and Penter, p. 280.
期刊介绍:
The journal Blood Cancer Discovery publishes high-quality Research Articles and Briefs that focus on major advances in basic, translational, and clinical research of leukemia, lymphoma, myeloma, and associated diseases. The topics covered include molecular and cellular features of pathogenesis, therapy response and relapse, transcriptional circuits, stem cells, differentiation, microenvironment, metabolism, immunity, mutagenesis, and clonal evolution. These subjects are investigated in both animal disease models and high-dimensional clinical data landscapes.
The journal also welcomes submissions on new pharmacological, biological, and living cell therapies, as well as new diagnostic tools. They are interested in prognostic, diagnostic, and pharmacodynamic biomarkers, and computational and machine learning approaches to personalized medicine. The scope of submissions ranges from preclinical proof of concept to clinical trials and real-world evidence.
Blood Cancer Discovery serves as a forum for diverse ideas that shape future research directions in hematooncology. In addition to Research Articles and Briefs, the journal also publishes Reviews, Perspectives, and Commentaries on topics of broad interest in the field.