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Weighted gene co-expression network analysis identifies key hub genes and pathways in acute myeloid leukemia

Introduction: Acute myeloid leukemia (AML) is the most common type of leukemia in adults. However, there is a gap in understanding the molecular basis of the disease, partly because key genes associated with AML have not been extensively explored. In the current study, we aimed to identify genes tha...

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Autores principales: Wang, Xinfeng, Bajpai, Akhilesh K., Gu, Qingqing, Ashbrook, David G., Starlard-Davenport, Athena, Lu, Lu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10008864/
https://www.ncbi.nlm.nih.gov/pubmed/36923792
http://dx.doi.org/10.3389/fgene.2023.1009462
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author Wang, Xinfeng
Bajpai, Akhilesh K.
Gu, Qingqing
Ashbrook, David G.
Starlard-Davenport, Athena
Lu, Lu
author_facet Wang, Xinfeng
Bajpai, Akhilesh K.
Gu, Qingqing
Ashbrook, David G.
Starlard-Davenport, Athena
Lu, Lu
author_sort Wang, Xinfeng
collection PubMed
description Introduction: Acute myeloid leukemia (AML) is the most common type of leukemia in adults. However, there is a gap in understanding the molecular basis of the disease, partly because key genes associated with AML have not been extensively explored. In the current study, we aimed to identify genes that have strong association with AML based on a cross-species integrative approach. Methods: We used Weighted Gene Co-Expression Network Analysis (WGCNA) to identify co-expressed gene modules significantly correlated with human AML, and further selected the genes exhibiting a significant difference in expression between AML and healthy mouse. Protein-protein interactions, transcription factors, gene function, genetic regulation, and coding sequence variants were integrated to identify key hub genes in AML. Results: The cross-species approach identified a total of 412 genes associated with both human and mouse AML. Enrichment analysis confirmed an association of these genes with hematopoietic and immune-related functions, phenotypes, processes, and pathways. Further, the integrated analysis approach identified a set of important module genes including Nfe2, Trim27, Mef2c, Ets1, Tal1, Foxo1, and Gata1 in AML. Six of these genes (except ETS1) showed significant differential expression between human AML and healthy samples in an independent microarray dataset. All of these genes are known to be involved in immune/hematopoietic functions, and in transcriptional regulation. In addition, Nfe2, Trim27, Mef2c, and Ets1 harbor coding sequence variants, whereas Nfe2 and Trim27 are cis-regulated, making them attractive candidates for validation. Furthermore, subtype-specific analysis of the hub genes in human AML indicated high expression of NFE2 across all the subtypes (M0 through M7) and enriched expression of ETS1, LEF1, GATA1, and TAL1 in M6 and M7 subtypes. A significant correlation between methylation status and expression level was observed for most of these genes in AML patients. Conclusion: Findings from the current study highlight the importance of our cross-species approach in the identification of multiple key candidate genes in AML, which can be further studied to explore their detailed role in leukemia/AML.
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spelling pubmed-100088642023-03-14 Weighted gene co-expression network analysis identifies key hub genes and pathways in acute myeloid leukemia Wang, Xinfeng Bajpai, Akhilesh K. Gu, Qingqing Ashbrook, David G. Starlard-Davenport, Athena Lu, Lu Front Genet Genetics Introduction: Acute myeloid leukemia (AML) is the most common type of leukemia in adults. However, there is a gap in understanding the molecular basis of the disease, partly because key genes associated with AML have not been extensively explored. In the current study, we aimed to identify genes that have strong association with AML based on a cross-species integrative approach. Methods: We used Weighted Gene Co-Expression Network Analysis (WGCNA) to identify co-expressed gene modules significantly correlated with human AML, and further selected the genes exhibiting a significant difference in expression between AML and healthy mouse. Protein-protein interactions, transcription factors, gene function, genetic regulation, and coding sequence variants were integrated to identify key hub genes in AML. Results: The cross-species approach identified a total of 412 genes associated with both human and mouse AML. Enrichment analysis confirmed an association of these genes with hematopoietic and immune-related functions, phenotypes, processes, and pathways. Further, the integrated analysis approach identified a set of important module genes including Nfe2, Trim27, Mef2c, Ets1, Tal1, Foxo1, and Gata1 in AML. Six of these genes (except ETS1) showed significant differential expression between human AML and healthy samples in an independent microarray dataset. All of these genes are known to be involved in immune/hematopoietic functions, and in transcriptional regulation. In addition, Nfe2, Trim27, Mef2c, and Ets1 harbor coding sequence variants, whereas Nfe2 and Trim27 are cis-regulated, making them attractive candidates for validation. Furthermore, subtype-specific analysis of the hub genes in human AML indicated high expression of NFE2 across all the subtypes (M0 through M7) and enriched expression of ETS1, LEF1, GATA1, and TAL1 in M6 and M7 subtypes. A significant correlation between methylation status and expression level was observed for most of these genes in AML patients. Conclusion: Findings from the current study highlight the importance of our cross-species approach in the identification of multiple key candidate genes in AML, which can be further studied to explore their detailed role in leukemia/AML. Frontiers Media S.A. 2023-02-27 /pmc/articles/PMC10008864/ /pubmed/36923792 http://dx.doi.org/10.3389/fgene.2023.1009462 Text en Copyright © 2023 Wang, Bajpai, Gu, Ashbrook, Starlard-Davenport and Lu. 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 Genetics
Wang, Xinfeng
Bajpai, Akhilesh K.
Gu, Qingqing
Ashbrook, David G.
Starlard-Davenport, Athena
Lu, Lu
Weighted gene co-expression network analysis identifies key hub genes and pathways in acute myeloid leukemia
title Weighted gene co-expression network analysis identifies key hub genes and pathways in acute myeloid leukemia
title_full Weighted gene co-expression network analysis identifies key hub genes and pathways in acute myeloid leukemia
title_fullStr Weighted gene co-expression network analysis identifies key hub genes and pathways in acute myeloid leukemia
title_full_unstemmed Weighted gene co-expression network analysis identifies key hub genes and pathways in acute myeloid leukemia
title_short Weighted gene co-expression network analysis identifies key hub genes and pathways in acute myeloid leukemia
title_sort weighted gene co-expression network analysis identifies key hub genes and pathways in acute myeloid leukemia
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10008864/
https://www.ncbi.nlm.nih.gov/pubmed/36923792
http://dx.doi.org/10.3389/fgene.2023.1009462
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