Nature Communications (Oct 2020)
Clonal evolution of acute myeloid leukemia revealed by high-throughput single-cell genomics
- Kiyomi Morita,
- Feng Wang,
- Katharina Jahn,
- Tianyuan Hu,
- Tomoyuki Tanaka,
- Yuya Sasaki,
- Jack Kuipers,
- Sanam Loghavi,
- Sa A. Wang,
- Yuanqing Yan,
- Ken Furudate,
- Jairo Matthews,
- Latasha Little,
- Curtis Gumbs,
- Jianhua Zhang,
- Xingzhi Song,
- Erika Thompson,
- Keyur P. Patel,
- Carlos E. Bueso-Ramos,
- Courtney D. DiNardo,
- Farhad Ravandi,
- Elias Jabbour,
- Michael Andreeff,
- Jorge Cortes,
- Kapil Bhalla,
- Guillermo Garcia-Manero,
- Hagop Kantarjian,
- Marina Konopleva,
- Daisuke Nakada,
- Nicholas Navin,
- Niko Beerenwinkel,
- P. Andrew Futreal,
- Koichi Takahashi
Affiliations
- Kiyomi Morita
- Department of Leukemia, The University of Texas MD Anderson Cancer Center
- Feng Wang
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center
- Katharina Jahn
- Department of Biosystems Science and Engineering, ETH Zurich
- Tianyuan Hu
- Department of Molecular and Human Genetics, Baylor College of Medicine
- Tomoyuki Tanaka
- Department of Leukemia, The University of Texas MD Anderson Cancer Center
- Yuya Sasaki
- Department of Leukemia, The University of Texas MD Anderson Cancer Center
- Jack Kuipers
- Department of Biosystems Science and Engineering, ETH Zurich
- Sanam Loghavi
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center
- Sa A. Wang
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center
- Yuanqing Yan
- Department of Neurosurgery, The University of Texas Health Science Center at Houston
- Ken Furudate
- Department of Leukemia, The University of Texas MD Anderson Cancer Center
- Jairo Matthews
- Department of Leukemia, The University of Texas MD Anderson Cancer Center
- Latasha Little
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center
- Curtis Gumbs
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center
- Jianhua Zhang
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center
- Xingzhi Song
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center
- Erika Thompson
- Department of Genetics, The University of Texas MD Anderson Cancer Center
- Keyur P. Patel
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center
- Carlos E. Bueso-Ramos
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center
- Courtney D. DiNardo
- Department of Leukemia, The University of Texas MD Anderson Cancer Center
- Farhad Ravandi
- Department of Leukemia, The University of Texas MD Anderson Cancer Center
- Elias Jabbour
- Department of Leukemia, The University of Texas MD Anderson Cancer Center
- Michael Andreeff
- Department of Leukemia, The University of Texas MD Anderson Cancer Center
- Jorge Cortes
- Department of Leukemia, The University of Texas MD Anderson Cancer Center
- Kapil Bhalla
- Department of Leukemia, The University of Texas MD Anderson Cancer Center
- Guillermo Garcia-Manero
- Department of Leukemia, The University of Texas MD Anderson Cancer Center
- Hagop Kantarjian
- Department of Leukemia, The University of Texas MD Anderson Cancer Center
- Marina Konopleva
- Department of Leukemia, The University of Texas MD Anderson Cancer Center
- Daisuke Nakada
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center
- Nicholas Navin
- Department of Genetics, The University of Texas MD Anderson Cancer Center
- Niko Beerenwinkel
- Department of Biosystems Science and Engineering, ETH Zurich
- P. Andrew Futreal
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center
- Koichi Takahashi
- Department of Leukemia, The University of Texas MD Anderson Cancer Center
- DOI
- https://doi.org/10.1038/s41467-020-19119-8
- Journal volume & issue
-
Vol. 11,
no. 1
pp. 1 – 17
Abstract
Understanding the evolutionary trajectory of cancer samples may enable understanding resistance to treatment. Here, the authors used single cell sequencing of a cohort of acute myeloid leukemia tumours and identify features of linear and branching evolution in tumours.
