Cargando…

Analysis of AML genes in dysregulated molecular networks

BACKGROUND: Identifying disease causing genes and understanding their molecular mechanisms are essential to developing effective therapeutics. Thus, several computational methods have been proposed to prioritize candidate disease genes by integrating different data types, including sequence informat...

Descripción completa

Detalles Bibliográficos
Autores principales: Lee, Eunjung, Jung, Hyunchul, Radivojac, Predrag, Kim, Jong-Won, Lee, Doheon
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2745689/
https://www.ncbi.nlm.nih.gov/pubmed/19761572
http://dx.doi.org/10.1186/1471-2105-10-S9-S2
_version_ 1782171987003572224
author Lee, Eunjung
Jung, Hyunchul
Radivojac, Predrag
Kim, Jong-Won
Lee, Doheon
author_facet Lee, Eunjung
Jung, Hyunchul
Radivojac, Predrag
Kim, Jong-Won
Lee, Doheon
author_sort Lee, Eunjung
collection PubMed
description BACKGROUND: Identifying disease causing genes and understanding their molecular mechanisms are essential to developing effective therapeutics. Thus, several computational methods have been proposed to prioritize candidate disease genes by integrating different data types, including sequence information, biomedical literature, and pathway information. Recently, molecular interaction networks have been incorporated to predict disease genes, but most of those methods do not utilize invaluable disease-specific information available in mRNA expression profiles of patient samples. RESULTS: Through the integration of protein-protein interaction networks and gene expression profiles of acute myeloid leukemia (AML) patients, we identified subnetworks of interacting proteins dysregulated in AML and characterized known mutation genes causally implicated to AML embedded in the subnetworks. The analysis shows that the set of extracted subnetworks is a reservoir rich in AML genes reflecting key leukemogenic processes such as myeloid differentiation. CONCLUSION: We showed that the integrative approach both utilizing gene expression profiles and molecular networks could identify AML causing genes most of which were not detectable with gene expression analysis alone due to the minor changes in mRNA level.
format Text
id pubmed-2745689
institution National Center for Biotechnology Information
language English
publishDate 2009
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-27456892009-09-18 Analysis of AML genes in dysregulated molecular networks Lee, Eunjung Jung, Hyunchul Radivojac, Predrag Kim, Jong-Won Lee, Doheon BMC Bioinformatics Proceedings BACKGROUND: Identifying disease causing genes and understanding their molecular mechanisms are essential to developing effective therapeutics. Thus, several computational methods have been proposed to prioritize candidate disease genes by integrating different data types, including sequence information, biomedical literature, and pathway information. Recently, molecular interaction networks have been incorporated to predict disease genes, but most of those methods do not utilize invaluable disease-specific information available in mRNA expression profiles of patient samples. RESULTS: Through the integration of protein-protein interaction networks and gene expression profiles of acute myeloid leukemia (AML) patients, we identified subnetworks of interacting proteins dysregulated in AML and characterized known mutation genes causally implicated to AML embedded in the subnetworks. The analysis shows that the set of extracted subnetworks is a reservoir rich in AML genes reflecting key leukemogenic processes such as myeloid differentiation. CONCLUSION: We showed that the integrative approach both utilizing gene expression profiles and molecular networks could identify AML causing genes most of which were not detectable with gene expression analysis alone due to the minor changes in mRNA level. BioMed Central 2009-09-17 /pmc/articles/PMC2745689/ /pubmed/19761572 http://dx.doi.org/10.1186/1471-2105-10-S9-S2 Text en Copyright © 2009 Lee et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Proceedings
Lee, Eunjung
Jung, Hyunchul
Radivojac, Predrag
Kim, Jong-Won
Lee, Doheon
Analysis of AML genes in dysregulated molecular networks
title Analysis of AML genes in dysregulated molecular networks
title_full Analysis of AML genes in dysregulated molecular networks
title_fullStr Analysis of AML genes in dysregulated molecular networks
title_full_unstemmed Analysis of AML genes in dysregulated molecular networks
title_short Analysis of AML genes in dysregulated molecular networks
title_sort analysis of aml genes in dysregulated molecular networks
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2745689/
https://www.ncbi.nlm.nih.gov/pubmed/19761572
http://dx.doi.org/10.1186/1471-2105-10-S9-S2
work_keys_str_mv AT leeeunjung analysisofamlgenesindysregulatedmolecularnetworks
AT junghyunchul analysisofamlgenesindysregulatedmolecularnetworks
AT radivojacpredrag analysisofamlgenesindysregulatedmolecularnetworks
AT kimjongwon analysisofamlgenesindysregulatedmolecularnetworks
AT leedoheon analysisofamlgenesindysregulatedmolecularnetworks