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

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

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...

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Auteurs principaux: 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
Format: article
Langue:EN
Publié: Nature Portfolio 2021
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Science
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Accès en ligne:https://doaj.org/article/b8f2ebaeb4ca47dbbfddf2abb90ffb18
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Résumé: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.

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