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Clinical impact of the genomic landscape and leukemogenic trajectories in non-intensively treated elderly acute myeloid leukemia patients
To characterize the genomic landscape and leukemogenic pathways of older, newly diagnosed, non-intensively treated patients with AML and to study the clinical implications, comprehensive genetics analyses were performed including targeted DNA sequencing of 263 genes in 604 patients treated in a pros...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10624608/ https://www.ncbi.nlm.nih.gov/pubmed/37591941 http://dx.doi.org/10.1038/s41375-023-01999-6 |
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author | Jahn, Ekaterina Saadati, Maral Fenaux, Pierre Gobbi, Marco Roboz, Gail J. Bullinger, Lars Lutsik, Pavlo Riedel, Anna Plass, Christoph Jahn, Nikolaus Walter, Claudia Holzmann, Karlheinz Hao, Yong Naim, Sue Schreck, Nicholas Krzykalla, Julia Benner, Axel Keer, Harold N. Azab, Mohammad Döhner, Konstanze Döhner, Hartmut |
author_facet | Jahn, Ekaterina Saadati, Maral Fenaux, Pierre Gobbi, Marco Roboz, Gail J. Bullinger, Lars Lutsik, Pavlo Riedel, Anna Plass, Christoph Jahn, Nikolaus Walter, Claudia Holzmann, Karlheinz Hao, Yong Naim, Sue Schreck, Nicholas Krzykalla, Julia Benner, Axel Keer, Harold N. Azab, Mohammad Döhner, Konstanze Döhner, Hartmut |
author_sort | Jahn, Ekaterina |
collection | PubMed |
description | To characterize the genomic landscape and leukemogenic pathways of older, newly diagnosed, non-intensively treated patients with AML and to study the clinical implications, comprehensive genetics analyses were performed including targeted DNA sequencing of 263 genes in 604 patients treated in a prospective Phase III clinical trial. Leukemic trajectories were delineated using oncogenetic tree modeling and hierarchical clustering, and prognostic groups were derived from multivariable Cox regression models. Clonal hematopoiesis-related genes (ASXL1, TET2, SRSF2, DNMT3A) were most frequently mutated. The oncogenetic modeling algorithm produced a tree with five branches with ASXL1, DDX41, DNMT3A, TET2, and TP53 emanating from the root suggesting leukemia-initiating events which gave rise to further subbranches with distinct subclones. Unsupervised clustering mirrored the genetic groups identified by the tree model. Multivariable analysis identified FLT3 internal tandem duplications (ITD), SRSF2, and TP53 mutations as poor prognostic factors, while DDX41 mutations exerted an exceptionally favorable effect. Subsequent backwards elimination based on the Akaike information criterion delineated three genetic risk groups: DDX41 mutations (favorable-risk), DDX41(wildtype)/FLT3-ITD(neg)/TP53(wildtype) (intermediate-risk), and FLT3-ITD or TP53 mutations (high-risk). Our data identified distinct trajectories of leukemia development in older AML patients and provide a basis for a clinically meaningful genetic outcome stratification for patients receiving less intensive therapies. |
format | Online Article Text |
id | pubmed-10624608 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106246082023-11-05 Clinical impact of the genomic landscape and leukemogenic trajectories in non-intensively treated elderly acute myeloid leukemia patients Jahn, Ekaterina Saadati, Maral Fenaux, Pierre Gobbi, Marco Roboz, Gail J. Bullinger, Lars Lutsik, Pavlo Riedel, Anna Plass, Christoph Jahn, Nikolaus Walter, Claudia Holzmann, Karlheinz Hao, Yong Naim, Sue Schreck, Nicholas Krzykalla, Julia Benner, Axel Keer, Harold N. Azab, Mohammad Döhner, Konstanze Döhner, Hartmut Leukemia Article To characterize the genomic landscape and leukemogenic pathways of older, newly diagnosed, non-intensively treated patients with AML and to study the clinical implications, comprehensive genetics analyses were performed including targeted DNA sequencing of 263 genes in 604 patients treated in a prospective Phase III clinical trial. Leukemic trajectories were delineated using oncogenetic tree modeling and hierarchical clustering, and prognostic groups were derived from multivariable Cox regression models. Clonal hematopoiesis-related genes (ASXL1, TET2, SRSF2, DNMT3A) were most frequently mutated. The oncogenetic modeling algorithm produced a tree with five branches with ASXL1, DDX41, DNMT3A, TET2, and TP53 emanating from the root suggesting leukemia-initiating events which gave rise to further subbranches with distinct subclones. Unsupervised clustering mirrored the genetic groups identified by the tree model. Multivariable analysis identified FLT3 internal tandem duplications (ITD), SRSF2, and TP53 mutations as poor prognostic factors, while DDX41 mutations exerted an exceptionally favorable effect. Subsequent backwards elimination based on the Akaike information criterion delineated three genetic risk groups: DDX41 mutations (favorable-risk), DDX41(wildtype)/FLT3-ITD(neg)/TP53(wildtype) (intermediate-risk), and FLT3-ITD or TP53 mutations (high-risk). Our data identified distinct trajectories of leukemia development in older AML patients and provide a basis for a clinically meaningful genetic outcome stratification for patients receiving less intensive therapies. Nature Publishing Group UK 2023-08-17 2023 /pmc/articles/PMC10624608/ /pubmed/37591941 http://dx.doi.org/10.1038/s41375-023-01999-6 Text en © The Author(s) 2023, corrected publication 2023 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Jahn, Ekaterina Saadati, Maral Fenaux, Pierre Gobbi, Marco Roboz, Gail J. Bullinger, Lars Lutsik, Pavlo Riedel, Anna Plass, Christoph Jahn, Nikolaus Walter, Claudia Holzmann, Karlheinz Hao, Yong Naim, Sue Schreck, Nicholas Krzykalla, Julia Benner, Axel Keer, Harold N. Azab, Mohammad Döhner, Konstanze Döhner, Hartmut Clinical impact of the genomic landscape and leukemogenic trajectories in non-intensively treated elderly acute myeloid leukemia patients |
title | Clinical impact of the genomic landscape and leukemogenic trajectories in non-intensively treated elderly acute myeloid leukemia patients |
title_full | Clinical impact of the genomic landscape and leukemogenic trajectories in non-intensively treated elderly acute myeloid leukemia patients |
title_fullStr | Clinical impact of the genomic landscape and leukemogenic trajectories in non-intensively treated elderly acute myeloid leukemia patients |
title_full_unstemmed | Clinical impact of the genomic landscape and leukemogenic trajectories in non-intensively treated elderly acute myeloid leukemia patients |
title_short | Clinical impact of the genomic landscape and leukemogenic trajectories in non-intensively treated elderly acute myeloid leukemia patients |
title_sort | clinical impact of the genomic landscape and leukemogenic trajectories in non-intensively treated elderly acute myeloid leukemia patients |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10624608/ https://www.ncbi.nlm.nih.gov/pubmed/37591941 http://dx.doi.org/10.1038/s41375-023-01999-6 |
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