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Decoupling Lineage-Associated Genes in Acute Myeloid Leukemia Reveals Inflammatory and Metabolic Signatures Associated With Outcomes
Acute myeloid leukemia (AML) is a heterogeneous disease with variable responses to therapy. Cytogenetic and genomic features are used to classify AML patients into prognostic and treatment groups. However, these molecular characteristics harbor significant patient-to-patient variability and do not f...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8372368/ https://www.ncbi.nlm.nih.gov/pubmed/34422660 http://dx.doi.org/10.3389/fonc.2021.705627 |
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author | Abbas, Hussein A. Mohanty, Vakul Wang, Ruiping Huang, Yuefan Liang, Shaoheng Wang, Feng Zhang, Jianhua Qiu, Yihua Hu, Chenyue W. Qutub, Amina A. Dail, Monique Bolen, Christopher R. Daver, Naval Konopleva, Marina Futreal, Andrew Chen, Ken Wang, Linghua Kornblau, Steven M. |
author_facet | Abbas, Hussein A. Mohanty, Vakul Wang, Ruiping Huang, Yuefan Liang, Shaoheng Wang, Feng Zhang, Jianhua Qiu, Yihua Hu, Chenyue W. Qutub, Amina A. Dail, Monique Bolen, Christopher R. Daver, Naval Konopleva, Marina Futreal, Andrew Chen, Ken Wang, Linghua Kornblau, Steven M. |
author_sort | Abbas, Hussein A. |
collection | PubMed |
description | Acute myeloid leukemia (AML) is a heterogeneous disease with variable responses to therapy. Cytogenetic and genomic features are used to classify AML patients into prognostic and treatment groups. However, these molecular characteristics harbor significant patient-to-patient variability and do not fully account for AML heterogeneity. RNA-based classifications have also been applied in AML as an alternative approach, but transcriptomic grouping is strongly associated with AML morphologic lineages. We used a training cohort of newly diagnosed AML patients and conducted unsupervised RNA-based classification after excluding lineage-associated genes. We identified three AML patient groups that have distinct biological pathways associated with outcomes. Enrichment of inflammatory pathways and downregulation of HOX pathways were associated with improved outcomes, and this was validated in 2 independent cohorts. We also identified a group of AML patients who harbored high metabolic and mTOR pathway activity, and this was associated with worse clinical outcomes. Using a comprehensive reverse phase protein array, we identified higher mTOR protein expression in the highly metabolic group. We also identified a positive correlation between degree of resistance to venetoclax and mTOR activation in myeloid and lymphoid cell lines. Our approach of integrating RNA, protein, and genomic data uncovered lineage-independent AML patient groups that share biologic mechanisms and can inform outcomes independent of commonly used clinical and demographic variables; these groups could be used to guide therapeutic strategies. |
format | Online Article Text |
id | pubmed-8372368 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-83723682021-08-19 Decoupling Lineage-Associated Genes in Acute Myeloid Leukemia Reveals Inflammatory and Metabolic Signatures Associated With Outcomes Abbas, Hussein A. Mohanty, Vakul Wang, Ruiping Huang, Yuefan Liang, Shaoheng Wang, Feng Zhang, Jianhua Qiu, Yihua Hu, Chenyue W. Qutub, Amina A. Dail, Monique Bolen, Christopher R. Daver, Naval Konopleva, Marina Futreal, Andrew Chen, Ken Wang, Linghua Kornblau, Steven M. Front Oncol Oncology Acute myeloid leukemia (AML) is a heterogeneous disease with variable responses to therapy. Cytogenetic and genomic features are used to classify AML patients into prognostic and treatment groups. However, these molecular characteristics harbor significant patient-to-patient variability and do not fully account for AML heterogeneity. RNA-based classifications have also been applied in AML as an alternative approach, but transcriptomic grouping is strongly associated with AML morphologic lineages. We used a training cohort of newly diagnosed AML patients and conducted unsupervised RNA-based classification after excluding lineage-associated genes. We identified three AML patient groups that have distinct biological pathways associated with outcomes. Enrichment of inflammatory pathways and downregulation of HOX pathways were associated with improved outcomes, and this was validated in 2 independent cohorts. We also identified a group of AML patients who harbored high metabolic and mTOR pathway activity, and this was associated with worse clinical outcomes. Using a comprehensive reverse phase protein array, we identified higher mTOR protein expression in the highly metabolic group. We also identified a positive correlation between degree of resistance to venetoclax and mTOR activation in myeloid and lymphoid cell lines. Our approach of integrating RNA, protein, and genomic data uncovered lineage-independent AML patient groups that share biologic mechanisms and can inform outcomes independent of commonly used clinical and demographic variables; these groups could be used to guide therapeutic strategies. Frontiers Media S.A. 2021-08-04 /pmc/articles/PMC8372368/ /pubmed/34422660 http://dx.doi.org/10.3389/fonc.2021.705627 Text en Copyright © 2021 Abbas, Mohanty, Wang, Huang, Liang, Wang, Zhang, Qiu, Hu, Qutub, Dail, Bolen, Daver, Konopleva, Futreal, Chen, Wang and Kornblau https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Abbas, Hussein A. Mohanty, Vakul Wang, Ruiping Huang, Yuefan Liang, Shaoheng Wang, Feng Zhang, Jianhua Qiu, Yihua Hu, Chenyue W. Qutub, Amina A. Dail, Monique Bolen, Christopher R. Daver, Naval Konopleva, Marina Futreal, Andrew Chen, Ken Wang, Linghua Kornblau, Steven M. Decoupling Lineage-Associated Genes in Acute Myeloid Leukemia Reveals Inflammatory and Metabolic Signatures Associated With Outcomes |
title | Decoupling Lineage-Associated Genes in Acute Myeloid Leukemia Reveals Inflammatory and Metabolic Signatures Associated With Outcomes |
title_full | Decoupling Lineage-Associated Genes in Acute Myeloid Leukemia Reveals Inflammatory and Metabolic Signatures Associated With Outcomes |
title_fullStr | Decoupling Lineage-Associated Genes in Acute Myeloid Leukemia Reveals Inflammatory and Metabolic Signatures Associated With Outcomes |
title_full_unstemmed | Decoupling Lineage-Associated Genes in Acute Myeloid Leukemia Reveals Inflammatory and Metabolic Signatures Associated With Outcomes |
title_short | Decoupling Lineage-Associated Genes in Acute Myeloid Leukemia Reveals Inflammatory and Metabolic Signatures Associated With Outcomes |
title_sort | decoupling lineage-associated genes in acute myeloid leukemia reveals inflammatory and metabolic signatures associated with outcomes |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8372368/ https://www.ncbi.nlm.nih.gov/pubmed/34422660 http://dx.doi.org/10.3389/fonc.2021.705627 |
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