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Systematic analysis of hematopoietic gene expression profiles for prognostic prediction in acute myeloid leukemia
Acute myeloid leukemia (AML) is a hematopoietic disorder initiated by the leukemogenic transformation of myeloid cells into leukemia stem cells (LSCs). Preexisting gene expression programs in LSCs can be used to assess their transcriptional similarity to hematopoietic cell types. While this relation...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4657053/ https://www.ncbi.nlm.nih.gov/pubmed/26598031 http://dx.doi.org/10.1038/srep16987 |
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author | Varn, Frederick S. Andrews, Erik H. Cheng, Chao |
author_facet | Varn, Frederick S. Andrews, Erik H. Cheng, Chao |
author_sort | Varn, Frederick S. |
collection | PubMed |
description | Acute myeloid leukemia (AML) is a hematopoietic disorder initiated by the leukemogenic transformation of myeloid cells into leukemia stem cells (LSCs). Preexisting gene expression programs in LSCs can be used to assess their transcriptional similarity to hematopoietic cell types. While this relationship has previously been examined on a small scale, an analysis that systematically investigates this relationship throughout the hematopoietic hierarchy has yet to be implemented. We developed an integrative approach to assess the similarity between AML patient tumor profiles and a collection of 232 murine hematopoietic gene expression profiles compiled by the Immunological Genome Project. The resulting lineage similarity scores (LSS) were correlated with patient survival to assess the relationship between hematopoietic similarity and patient prognosis. This analysis demonstrated that patient tumor similarity to immature hematopoietic cell types correlated with poor survival. As a proof of concept, we highlighted one cell type identified by our analysis, the short-term reconstituting stem cell, whose LSSs were significantly correlated with patient prognosis across multiple datasets, and showed distinct patterns in patients stratified by traditional clinical variables. Finally, we validated our use of murine profiles by demonstrating similar results when applying our method to human profiles. |
format | Online Article Text |
id | pubmed-4657053 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-46570532015-11-30 Systematic analysis of hematopoietic gene expression profiles for prognostic prediction in acute myeloid leukemia Varn, Frederick S. Andrews, Erik H. Cheng, Chao Sci Rep Article Acute myeloid leukemia (AML) is a hematopoietic disorder initiated by the leukemogenic transformation of myeloid cells into leukemia stem cells (LSCs). Preexisting gene expression programs in LSCs can be used to assess their transcriptional similarity to hematopoietic cell types. While this relationship has previously been examined on a small scale, an analysis that systematically investigates this relationship throughout the hematopoietic hierarchy has yet to be implemented. We developed an integrative approach to assess the similarity between AML patient tumor profiles and a collection of 232 murine hematopoietic gene expression profiles compiled by the Immunological Genome Project. The resulting lineage similarity scores (LSS) were correlated with patient survival to assess the relationship between hematopoietic similarity and patient prognosis. This analysis demonstrated that patient tumor similarity to immature hematopoietic cell types correlated with poor survival. As a proof of concept, we highlighted one cell type identified by our analysis, the short-term reconstituting stem cell, whose LSSs were significantly correlated with patient prognosis across multiple datasets, and showed distinct patterns in patients stratified by traditional clinical variables. Finally, we validated our use of murine profiles by demonstrating similar results when applying our method to human profiles. Nature Publishing Group 2015-11-24 /pmc/articles/PMC4657053/ /pubmed/26598031 http://dx.doi.org/10.1038/srep16987 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Varn, Frederick S. Andrews, Erik H. Cheng, Chao Systematic analysis of hematopoietic gene expression profiles for prognostic prediction in acute myeloid leukemia |
title | Systematic analysis of hematopoietic gene expression profiles for prognostic prediction
in acute myeloid leukemia |
title_full | Systematic analysis of hematopoietic gene expression profiles for prognostic prediction
in acute myeloid leukemia |
title_fullStr | Systematic analysis of hematopoietic gene expression profiles for prognostic prediction
in acute myeloid leukemia |
title_full_unstemmed | Systematic analysis of hematopoietic gene expression profiles for prognostic prediction
in acute myeloid leukemia |
title_short | Systematic analysis of hematopoietic gene expression profiles for prognostic prediction
in acute myeloid leukemia |
title_sort | systematic analysis of hematopoietic gene expression profiles for prognostic prediction
in acute myeloid leukemia |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4657053/ https://www.ncbi.nlm.nih.gov/pubmed/26598031 http://dx.doi.org/10.1038/srep16987 |
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