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

As more clinically-relevant genomic features of myeloid malignancies are revealed, it has become clear that targeted clinical genetic testing is inadequate for risk stratification. Here, we develop and validate a clinical transcriptome-based assay for stratification of acute myeloid leukemia (AML)....

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Autores principales: Docking, T. Roderick, Parker, Jeremy D. K., Jädersten, Martin, Duns, Gerben, Chang, Linda, Jiang, Jihong, Pilsworth, Jessica A., Swanson, Lucas A., Chan, Simon K., Chiu, Readman, Nip, Ka Ming, Mar, Samantha, Mo, Angela, Wang, Xuan, Martinez-Høyer, Sergio, Stubbins, Ryan J., Mungall, Karen L., Mungall, Andrew J., Moore, Richard A., Jones, Steven J. M., Birol, İnanç, Marra, Marco A., Hogge, Donna, Karsan, Aly
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8087683/
https://www.ncbi.nlm.nih.gov/pubmed/33931648
http://dx.doi.org/10.1038/s41467-021-22625-y
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author Docking, T. Roderick
Parker, Jeremy D. K.
Jädersten, Martin
Duns, Gerben
Chang, Linda
Jiang, Jihong
Pilsworth, Jessica A.
Swanson, Lucas A.
Chan, Simon K.
Chiu, Readman
Nip, Ka Ming
Mar, Samantha
Mo, Angela
Wang, Xuan
Martinez-Høyer, Sergio
Stubbins, Ryan J.
Mungall, Karen L.
Mungall, Andrew J.
Moore, Richard A.
Jones, Steven J. M.
Birol, İnanç
Marra, Marco A.
Hogge, Donna
Karsan, Aly
author_facet Docking, T. Roderick
Parker, Jeremy D. K.
Jädersten, Martin
Duns, Gerben
Chang, Linda
Jiang, Jihong
Pilsworth, Jessica A.
Swanson, Lucas A.
Chan, Simon K.
Chiu, Readman
Nip, Ka Ming
Mar, Samantha
Mo, Angela
Wang, Xuan
Martinez-Høyer, Sergio
Stubbins, Ryan J.
Mungall, Karen L.
Mungall, Andrew J.
Moore, Richard A.
Jones, Steven J. M.
Birol, İnanç
Marra, Marco A.
Hogge, Donna
Karsan, Aly
author_sort Docking, T. Roderick
collection PubMed
description As more clinically-relevant genomic features of myeloid malignancies are revealed, it has become clear that targeted clinical genetic testing is inadequate for risk stratification. Here, we develop and validate a clinical transcriptome-based assay for stratification of acute myeloid leukemia (AML). Comparison of ribonucleic acid sequencing (RNA-Seq) to whole genome and exome sequencing reveals that a standalone RNA-Seq assay offers the greatest diagnostic return, enabling identification of expressed gene fusions, single nucleotide and short insertion/deletion variants, and whole-transcriptome expression information. Expression data from 154 AML patients are used to develop a novel AML prognostic score, which is strongly associated with patient outcomes across 620 patients from three independent cohorts, and 42 patients from a prospective cohort. When combined with molecular risk guidelines, the risk score allows for the re-stratification of 22.1 to 25.3% of AML patients from three independent cohorts into correct risk groups. Within the adverse-risk subgroup, we identify a subset of patients characterized by dysregulated integrin signaling and RUNX1 or TP53 mutation. We show that these patients may benefit from therapy with inhibitors of focal adhesion kinase, encoded by PTK2, demonstrating additional utility of transcriptome-based testing for therapy selection in myeloid malignancy.
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spelling pubmed-80876832021-05-11 A clinical transcriptome approach to patient stratification and therapy selection in acute myeloid leukemia Docking, T. Roderick Parker, Jeremy D. K. Jädersten, Martin Duns, Gerben Chang, Linda Jiang, Jihong Pilsworth, Jessica A. Swanson, Lucas A. Chan, Simon K. Chiu, Readman Nip, Ka Ming Mar, Samantha Mo, Angela Wang, Xuan Martinez-Høyer, Sergio Stubbins, Ryan J. Mungall, Karen L. Mungall, Andrew J. Moore, Richard A. Jones, Steven J. M. Birol, İnanç Marra, Marco A. Hogge, Donna Karsan, Aly Nat Commun Article As more clinically-relevant genomic features of myeloid malignancies are revealed, it has become clear that targeted clinical genetic testing is inadequate for risk stratification. Here, we develop and validate a clinical transcriptome-based assay for stratification of acute myeloid leukemia (AML). Comparison of ribonucleic acid sequencing (RNA-Seq) to whole genome and exome sequencing reveals that a standalone RNA-Seq assay offers the greatest diagnostic return, enabling identification of expressed gene fusions, single nucleotide and short insertion/deletion variants, and whole-transcriptome expression information. Expression data from 154 AML patients are used to develop a novel AML prognostic score, which is strongly associated with patient outcomes across 620 patients from three independent cohorts, and 42 patients from a prospective cohort. When combined with molecular risk guidelines, the risk score allows for the re-stratification of 22.1 to 25.3% of AML patients from three independent cohorts into correct risk groups. Within the adverse-risk subgroup, we identify a subset of patients characterized by dysregulated integrin signaling and RUNX1 or TP53 mutation. We show that these patients may benefit from therapy with inhibitors of focal adhesion kinase, encoded by PTK2, demonstrating additional utility of transcriptome-based testing for therapy selection in myeloid malignancy. Nature Publishing Group UK 2021-04-30 /pmc/articles/PMC8087683/ /pubmed/33931648 http://dx.doi.org/10.1038/s41467-021-22625-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Docking, T. Roderick
Parker, Jeremy D. K.
Jädersten, Martin
Duns, Gerben
Chang, Linda
Jiang, Jihong
Pilsworth, Jessica A.
Swanson, Lucas A.
Chan, Simon K.
Chiu, Readman
Nip, Ka Ming
Mar, Samantha
Mo, Angela
Wang, Xuan
Martinez-Høyer, Sergio
Stubbins, Ryan J.
Mungall, Karen L.
Mungall, Andrew J.
Moore, Richard A.
Jones, Steven J. M.
Birol, İnanç
Marra, Marco A.
Hogge, Donna
Karsan, Aly
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
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_short 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
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8087683/
https://www.ncbi.nlm.nih.gov/pubmed/33931648
http://dx.doi.org/10.1038/s41467-021-22625-y
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