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- Akan, Pelin, et al.
(författare)
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Comprehensive analysis of the genome transcriptome and proteome landscapes of three tumor cell lines
- 2012
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Ingår i: Genome Medicine. - : Springer Science and Business Media LLC. - 1756-994X. ; 4, s. 86-
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Tidskriftsartikel (refereegranskat)abstract
- We here present a comparative genome, transcriptome and functional network analysis of three human cancer cell lines (A431, U251MG and U2OS), and investigate their relation to protein expression. Gene copy numbers significantly influenced corresponding transcript levels; their effect on protein levels was less pronounced. We focused on genes with altered mRNA and/or protein levels to identify those active in tumor maintenance. We provide comprehensive information for the three genomes and demonstrate the advantage of integrative analysis for identifying tumor-related genes amidst numerous background mutations by relating genomic variation to expression/protein abundance data and use gene networks to reveal implicated pathways.
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| 2. |
- Alfirevic, Ana, et al.
(författare)
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In silico analysis of HLA associations with drug-induced liver injury : use of a HLA-genotyped DNA archive from healthy volunteers
- 2012
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Ingår i: Genome Medicine. - : BioMed Central. - 1756-994X. ; 4:6
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Drug-induced liver injury (DILI) is one of the most common adverse reactions leading to product withdrawal post-marketing. Recently, genome-wide association studies have identified a number of human leukocyte antigen (HLA) alleles associated with DILI; however, the cellular and chemical mechanisms are not fully understood.METHODS: To study these mechanisms, we established an HLA-typed cell archive from 400 healthy volunteers. In addition, we utilized HLA genotype data from more than four million individuals from publicly accessible repositories such as the Allele Frequency Net Database, Major Histocompatibility Complex Database and Immune Epitope Database to study the HLA alleles associated with DILI. We utilized novel in silico strategies to examine HLA haplotype relationships among the alleles associated with DILI by using bioinformatics tools such as NetMHCpan, PyPop, GraphViz, PHYLIP and TreeView.RESULTS: We demonstrated that many of the alleles that have been associated with liver injury induced by structurally diverse drugs (flucloxacillin, co-amoxiclav, ximelagatran, lapatinib, lumiracoxib) reside on common HLA haplotypes, which were present in populations of diverse ethnicity.CONCLUSIONS: Our bioinformatic analysis indicates that there may be a connection between the different HLA alleles associated with DILI caused by therapeutically and structurally different drugs, possibly through peptide binding of one of the HLA alleles that defines the causal haplotype. Further functional work, together with next-generation sequencing techniques, will be needed to define the causal alleles associated with DILI.
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| 5. |
- Denkert, Carsten, et al.
(författare)
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Metabolomics of human breast cancer : new approaches for tumor typing and biomarker discovery
- 2012
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Ingår i: Genome Medicine. - London, United Kingdom : BioMed Central (BMC). - 1756-994X. ; 4:4
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Forskningsöversikt (refereegranskat)abstract
- Breast cancer is the most common cancer in women worldwide, and the development of new technologies for better understanding of the molecular changes involved in breast cancer progression is essential. Metabolic changes precede overt phenotypic changes, because cellular regulation ultimately affects the use of small-molecule substrates for cell division, growth or environmental changes such as hypoxia. Differences in metabolism between normal cells and cancer cells have been identified. Because small alterations in enzyme concentrations or activities can cause large changes in overall metabolite levels, the metabolome can be regarded as the amplified output of a biological system. The metabolome coverage in human breast cancer tissues can be maximized by combining different technologies for metabolic profiling. Researchers are investigating alterations in the steady state concentrations of metabolites that reflect amplified changes in genetic control of metabolism. Metabolomic results can be used to classify breast cancer on the basis of tumor biology, to identify new prognostic and predictive markers and to discover new targets for future therapeutic interventions. Here, we examine recent results, including those from the European FP7 project METAcancer consortium, that show that integrated metabolomic analyses can provide information on the stage, subtype and grade of breast tumors and give mechanistic insights. We predict an intensified use of metabolomic screens in clinical and preclinical studies focusing on the onset and progression of tumor development.
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| 7. |
- Feuk, Lars
(författare)
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Inversion variants in the human genome : role in disease and genome architecture
- 2010
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Ingår i: Genome Medicine. - : Springer Science and Business Media LLC. - 1756-994X. ; 2:2
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Tidskriftsartikel (refereegranskat)abstract
- Significant advances have been made over the past 5 years in mapping and characterizing structural variation in the human genome. Despite this progress, our understanding of inversion variants is still very restricted. While unbalanced variants such as copy number variations can be mapped using array-based approaches, strategies for characterization of inversion variants have been limited and underdeveloped. Traditional cytogenetic approaches have long been able to identify microscopic inversion events, but discovery of submicroscopic events has remained elusive and largely ignored. With the advent of paired-end sequencing approaches, it is now possible to map inversions across the human genome. Based on the paired-end sequencing studies published to date, it is now feasible to make a first map of inversions across the human genome and to use this map to explore the characteristics and distribution of this form of variation. The current map of inversions indicates that many remain to be identified, especially in the smaller size ranges. This review provides an overview of the current knowledge about human inversions and their contribution to human phenotypes. Further characterization of inversions should be considered as an important step towards a deeper understanding of human variation and genome dynamics.
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| 8. |
- Gustafsson, Mika, et al.
(författare)
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Integrated genomic and prospective clinical studies show the importance of modular pleiotropy for disease susceptibility, diagnosis and treatment
- 2014
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Ingår i: Genome Medicine. - : BioMed Central. - 1756-994X. ; 6:17
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Tidskriftsartikel (refereegranskat)abstract
- Background: Translational research typically aims to identify and functionally validate individual, disease-specific genes. However, reaching this aim is complicated by the involvement of thousands of genes in common diseases, and that many of those genes are pleiotropic, that is, shared by several diseases. Methods: We integrated genomic meta-analyses with prospective clinical studies to systematically investigate the pathogenic, diagnostic and therapeutic roles of pleiotropic genes. In a novel approach, we first used pathway analysis of all published genome-wide association studies (GWAS) to find a cell type common to many diseases. Results: The analysis showed over-representation of the T helper cell differentiation pathway, which is expressed in T cells. This led us to focus on expression profiling of CD4(+) T cells from highly diverse inflammatory and malignant diseases. We found that pleiotropic genes were highly interconnected and formed a pleiotropic module, which was enriched for inflammatory, metabolic and proliferative pathways. The general relevance of this module was supported by highly significant enrichment of genetic variants identified by all GWAS and cancer studies, as well as known diagnostic and therapeutic targets. Prospective clinical studies of multiple sclerosis and allergy showed the importance of both pleiotropic and disease specific modules for clinical stratification. Conclusions: In summary, this translational genomics study identified a pleiotropic module, which has key pathogenic, diagnostic and therapeutic roles.
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| 9. |
- Gustafsson, Mika, et al.
(författare)
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Modules, networks and systems medicine for understanding disease and aiding diagnosis
- 2014
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Ingår i: Genome Medicine. - : BioMed Central. - 1756-994X. ; 6:82
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Forskningsöversikt (refereegranskat)abstract
- Many common diseases, such as asthma, diabetes or obesity, involve altered interactions between thousands of genes. High-throughput techniques (omics) allow identification of such genes and their products, but functional understanding is a formidable challenge. Network-based analyses of omics data have identified modules of disease-associated genes that have been used to obtain both a systems level and a molecular understanding of disease mechanisms. For example, in allergy a module was used to find a novel candidate gene that was validated by functional and clinical studies. Such analyses play important roles in systems medicine. This is an emerging discipline that aims to gain a translational understanding of the complex mechanisms underlying common diseases. In this review, we will explain and provide examples of how network-based analyses of omics data, in combination with functional and clinical studies, are aiding our understanding of disease, as well as helping to prioritize diagnostic markers or therapeutic candidate genes. Such analyses involve significant problems and limitations, which will be discussed. We also highlight the steps needed for clinical implementation.
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