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Clonally resolved single-cell multi-omics identifies routes of cellular differentiation in acute myeloid leukemia

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Item Type:Article
Title:Clonally resolved single-cell multi-omics identifies routes of cellular differentiation in acute myeloid leukemia
Creators Name:Beneyto-Calabuig, S. and Merbach, A.K. and Kniffka, J.A. and Antes, M. and Szu-Tu, C. and Rohde, C. and Waclawiczek, A. and Stelmach, P. and Gräßle, S. and Pervan, P. and Janssen, M. and Landry, J.J.M. and Benes, V. and Jauch, A. and Brough, M. and Bauer, M. and Besenbeck, B. and Felden, J. and Bäumer, S. and Hundemer, M. and Sauer, T. and Pabst, C. and Wickenhauser, C. and Angenendt, L. and Schliemann, C. and Trumpp, A. and Haas, S. and Scherer, M. and Raffel, S. and Müller-Tidow, C. and Velten, L.
Abstract:Inter-patient variability and the similarity of healthy and leukemic stem cells (LSCs) have impeded the characterization of LSCs in acute myeloid leukemia (AML) and their differentiation landscape. Here, we introduce CloneTracer, a novel method that adds clonal resolution to single-cell RNA-seq datasets. Applied to samples from 19 AML patients, CloneTracer revealed routes of leukemic differentiation. Although residual healthy and preleukemic cells dominated the dormant stem cell compartment, active LSCs resembled their healthy counterpart and retained erythroid capacity. By contrast, downstream myeloid progenitors constituted a highly aberrant, disease-defining compartment: their gene expression and differentiation state affected both the chemotherapy response and leukemia's ability to differentiate into transcriptomically normal monocytes. Finally, we demonstrated the potential of CloneTracer to identify surface markers misregulated specifically in leukemic cells. Taken together, CloneTracer reveals a differentiation landscape that mimics its healthy counterpart and may determine biology and therapy response in AML.
Keywords:Acute Myeloid Leukemia, Leukemic Stem Cells, Cancer Stem Cells, Hematopoietic Stem Cells, Cellular Differentiation, AML, LSC, CSC, HSC, Single-Cell RNA-Seq, Computational Biology, Single-Cell Genomics, Single-Cell Transcriptomics, Computational Method
Source:Cell Stem Cell
ISSN:1934-5909
Publisher:Cell Press
Volume:30
Number:5
Page Range:706-721
Date:4 May 2023
Official Publication:https://doi.org/10.1016/j.stem.2023.04.001
PubMed:View item in PubMed

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