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

Title: A clinical transcriptome approach to patient stratification and therapy selection in acute myeloid leukemia
Authors: 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
Source: Nature Communications, Vol 12, Iss 1, Pp 1-15 (2021)
Publisher Information: Nature Portfolio, 2021.
Publication Year: 2021
Collection: LCC:Science
Subject Terms: Science
Description: 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.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2041-1723
Relation: https://doaj.org/toc/2041-1723
DOI: 10.1038/s41467-021-22625-y
Access URL: https://doaj.org/article/b8f2ebaeb4ca47dbbfddf2abb90ffb18
Accession Number: edsdoj.b8f2ebaeb4ca47dbbfddf2abb90ffb18
Database: Directory of Open Access Journals