Nature Communications (Apr 2021)

A clinical transcriptome approach to patient stratification and therapy selection in acute myeloid leukemia

  • T. Roderick Docking,
  • Jeremy D. K. Parker,
  • Martin Jädersten,
  • Gerben Duns,
  • Linda Chang,
  • Jihong Jiang,
  • Jessica A. Pilsworth,
  • Lucas A. Swanson,
  • Simon K. Chan,
  • Readman Chiu,
  • Ka Ming Nip,
  • Samantha Mar,
  • Angela Mo,
  • Xuan Wang,
  • Sergio Martinez-Høyer,
  • Ryan J. Stubbins,
  • Karen L. Mungall,
  • Andrew J. Mungall,
  • Richard A. Moore,
  • Steven J. M. Jones,
  • İnanç Birol,
  • Marco A. Marra,
  • Donna Hogge,
  • Aly Karsan

DOI
https://doi.org/10.1038/s41467-021-22625-y
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 15

Abstract

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Several genomic features have been found for acute myeloid leukaemia (AML) but targeted clinical genetic testing fails to predict prognosis. Here, the authors generate an AML prognostic score from RNA-seq data of patients, which successfully stratifies AML patients and which may provide guidance for therapeutic strategies.