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Analysis of AML genes in dysregulated molecular networks.

ABSTRACT: 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.

SUBMITTER: Lee E

PROVIDER: S-EPMC2745689 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature

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Analysis of AML genes in dysregulated molecular networks.

Lee Eunjung E Jung Hyunchul H Radivojac Predrag P Kim Jong-Won JW Lee Doheon D

BMC bioinformatics 20090917

<h4>Background</h4>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 invaluabl ...[more]

PMID: 19761572

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Project description:Down syndrome (DS), caused by an extra copy of chromosome 21, affects 1 in 750 live births and is characterised by cognitive impairment and a constellation of congenital defects. Currently, little is known about the molecular pathogenesis and no direct genotype-phenotype relationship has yet been confirmed. Since DS amniocytes are expected to have a distinct biological behaviour compared to normal amniocytes, we hypothesise that relative quantification of proteins produced from trisomy and euploid (chromosomally normal) amniocytes will reveal dysregulated molecular pathways. Chromosomally normal- and Trisomy 21-amniocytes were quantitatively analyzed by using Stable Isotope Labeling of Amino acids in Cell culture and tandem mass spectrometry. The most extensive proteome of amniocytes and amniotic fluid has been generated and differentially expressed proteins from amniocytes with Trisomy 21 revealed molecular pathways that seem to be most significantly affected by the presence of an extra copy of chromosome 21. Mass spectra were analyzed using Mascot (version 2.2, Matrix Science), executing a spectral search against a concatenated International Protein Index (IPI) human protein database (version 3.54 containing 39,925 entries) and a decoy database. Parameters included: trypsin enzyme specificity, SILAC double measurements of Lys6 and Arg8, 1 missed cleavage, minimum peptide length of 7 amino acids, minimum of 1 unique peptide, top 6 MS/MS peaks per 100 Da, peptide mass tolerance of 20 ppm for precursor ion and MS/MS tolerance of 0.5 Da. Oxidation of methionine and N-terminal protein acetylation for variable modifications and cysteine caramidomethylation for fixed modification. All entries were filtered using a false positive rate of 1% both at the peptide and protein levels, and false positives were removed. Quantification via normalised H/L ratios was based on minimum of 3 peptide ratio counts. Protein group entries with a normalised ratio significance B score of =< 0.05 or significance A score of =< 0.05 were retained for further analysis.

Dataset Information

Analysis of AML genes in dysregulated molecular networks.

Publications

Analysis of AML genes in dysregulated molecular networks.

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