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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Nature Portfolio
2021
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oai:doaj.org-article:b8f2ebaeb4ca47dbbfddf2abb90ffb182021-12-02T17:17:22ZA clinical transcriptome approach to patient stratification and therapy selection in acute myeloid leukemia10.1038/s41467-021-22625-y2041-1723https://doaj.org/article/b8f2ebaeb4ca47dbbfddf2abb90ffb182021-04-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-22625-yhttps://doaj.org/toc/2041-1723Several 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.T. Roderick DockingJeremy D. K. ParkerMartin JäderstenGerben DunsLinda ChangJihong JiangJessica A. PilsworthLucas A. SwansonSimon K. ChanReadman ChiuKa Ming NipSamantha MarAngela MoXuan WangSergio Martinez-HøyerRyan J. StubbinsKaren L. MungallAndrew J. MungallRichard A. MooreSteven J. M. Jonesİnanç BirolMarco A. MarraDonna HoggeAly KarsanNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-15 (2021) |
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Science Q 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 A clinical transcriptome approach to patient stratification and therapy selection in acute myeloid leukemia |
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. |
format |
article |
author |
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 |
author_facet |
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 |
author_sort |
T. Roderick Docking |
title |
A clinical transcriptome approach to patient stratification and therapy selection in acute myeloid leukemia |
title_short |
A clinical transcriptome approach to patient stratification and therapy selection in acute myeloid leukemia |
title_full |
A clinical transcriptome approach to patient stratification and therapy selection in acute myeloid leukemia |
title_fullStr |
A clinical transcriptome approach to patient stratification and therapy selection in acute myeloid leukemia |
title_full_unstemmed |
A clinical transcriptome approach to patient stratification and therapy selection in acute myeloid leukemia |
title_sort |
clinical transcriptome approach to patient stratification and therapy selection in acute myeloid leukemia |
publisher |
Nature Portfolio |
publishDate |
2021 |
url |
https://doaj.org/article/b8f2ebaeb4ca47dbbfddf2abb90ffb18 |
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