bioRxivCancer Biology
Clonally resolved single-cell multi-omics identifies routes of cellular differentiation in acute myeloid leukemia
S. Beneyto-Calabuig, A. K. Ludwig, J.-A. Kniffka, C. Szu-Tu, C. Rohde, M. Antes, A. Waclawiczek, P. Pervan, M. Janssen, J. J. M. Landry, V. Benes, A. Jauch, M. Brough, M. Bauer, B. Besenbeck, J. Felden, S. Baeumer, M. Hundemer, T. Sauer, C. Pabst, C. Wickenhauser, L. Angenendt, C. Schliemann, A. Trumpp, S. Haas, , L. Velten
Abstract
Inter-patient variability and the similarity of healthy and leukemic stem cells have impeded the characterization of leukemic stem cells (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. While residual healthy cells dominated the dormant stem cell compartment, active leukemic stem cells resembled their healthy counterpart and retained erythroid capacity. By contrast, downstream myeloid progenitors were highly aberrant and constituted the disease-defining compartment: Their gene expression and differentiation state determined both chemotherapy response and the leukemias ability to differentiate to transcriptomically normal monocytes. Finally, we demonstrated the potential of CloneTracer to identify surface markers mis-regulated specifically in leukemic cells by intra-patient comparisons. Taken together, CloneTracer revealed a differentiation landscape that mimics its healthy counterpart and determines biology and therapy response in AML.
- organism: human
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: trajectory inference
- research focus: differential expression
- approach: deep learning
- approach: statistical model
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