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  • 1
    Language: English
    In: Electrophoresis, June 2013, Vol.34(11), pp.1649-56
    Description: Molecular profiling techniques have provided extensive sets of molecular features characterizing clinical phenotypes, but further extrapolation to mechanistic molecular models of disease pathophysiology faces major challenges. Here, we describe a computational procedure for delineating molecular disease models utilizing omics profiles, and exemplify the methodology on aspects of the cardiorenal syndrome describing the clinical association of declining kidney function and increased cardiovascular event rates. Individual molecular features as well as selected molecular processes were identified as linking cardiovascular and renal pathology as a combination of cross-organ mediators and common pathophysiology. The molecular characterization of the disease presents as a set of molecular processes together with their interactions, composing a molecular disease model of the cardiorenal syndrome. Integrating omics profiles describing aspects of cardiovascular disease and respective profiles for advanced chronic kidney disease on molecular interaction networks, computation of disease term-specific subgraphs, and complemented by subgraph segmentation allowed delineation of disease term-specific molecular models, at their intersection providing contributors to cardiorenal pathology. Building such molecular disease models allows in a generic way to integrate multi-omics sources for generating comprehensive sets of molecular processes, on such basis providing rationale for biomarker panel selection for further characterizing clinical phenotypes.
    Keywords: Cardio-Renal Syndrome -- Physiopathology ; Computational Biology -- Methods ; Heart -- Physiopathology ; Kidney -- Physiopathology
    ISSN: 01730835
    E-ISSN: 1522-2683
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  • 2
    In: ELECTROPHORESIS, June 2013, Vol.34(11), pp.NA-NA
    Description: Electrophoresis 2013, 34, 1649‐1656. DOI: 10.1002/elps.201200642 Proteomics (together with other Omics procedures) provides us with extendedmolecular feature sets characterizing clinical phenotypes; challenge is to traverse such molecular feature sets into molecular processes and pathways allowing an interpretation of the pathophysiological background of phenotypes, from there enabling effective biomarker and drug/target selection. Delineating suchmolecular diseasemodels, resting on Omics profile integration utilizing molecular interaction networks, has become feasible, as exemplarily shown for chronic kidney disease (left) and cardiovascular disease (right). The models encompass individual molecular processes (nodes of the models with their respectivemolecular feature subgraphs) and the functional dependence between such process nodes. Such molecular models allow improved analysis of specific clinical phenotypes, but also enable analysis of their mutual interaction, in the given case being the cardio‐renal syndrome at the interface of kidney and cardiovascular disease.
    Keywords: Biomarker ; Cross‐Omics ; Integration ; Process ; Systems Biology
    ISSN: 0173-0835
    E-ISSN: 1522-2683
    Source: John Wiley & Sons, Inc.
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  • 3
    In: Molecular BioSystems, 2012, Vol.8(12), pp.3197-3207
    Description: Systematic study of the effect of mycophenolate mofetil (MMF) on the molecular level in the context of other drugs and molecular disease profiles became possible due to the availability of large scale molecular profiles on both disease characterization and drug mode of action. Such analysis is of particular value in elucidating alternative drug use for addressing clinically unmet needs, and the concept of synthetic lethality provides an alternative tool for such repositioning strategies. Resting on consolidation of transcriptomics data and literature mining, a MMF molecular footprint became available including a set of 170 genes specifically affected by the drug. Analysis of this profile on a molecular pathway level reveals a set of 14 pathways as affected. Next to assignment of molecular pathways and associated diseases synergistic drug combinations are proposed by utilizing the synthetic lethal interaction network. Of particular interest is the combination of MMF with adenosine deaminase inhibitors, sulfasalazine, and other selected drugs interfering with calcium-based regulatory pathways and metabolism. Indeed analysis of drugs in clinical trials positively identifies combinations with MMF in the context of synthetic lethality and affected pathways, particularly in diseases such as multiple sclerosis, vasculitis, GVHD and lupus nephritis. Importantly, the synthetic lethal interaction of the drug mode of action is an interesting basis for rational repositioning strategies by suggesting combinations which exhibit a synergistic rather than a mere additive effect, as for example is evident for the combination of tacrolimus and MMF. Inherent is also the assessment of possible adverse effects of drug combinations.
    Keywords: Drug Interactions ; Drug Therapy, Combination ; Mycophenolic Acid -- Analogs & Derivatives;
    ISSN: 1742-206X
    E-ISSN: 1742-2051
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  • 4
    In: International Journal of Systems Biology and Biomedical Technologies (IJSBBT), 2012, Vol.1(1), pp.11-25
    Description: Omics profiling in translational clinical research has provided detailed molecular characterization of disease phenotypes. Integrating this molecular data space with clinical phenotype descriptors has triggered advancements regarding a systems view on disease, resulting in the concept of stratified medicine. The authors present a methodology for patient stratification by analyzing clinical and molecular information on a per-patient level represented as a data graph. This approach rests on linking patient specific clinical data and biomarker profiles with molecular functional units being derived by segmenting a human proteome interaction network. As a result patient strata are built holding sets of affected functional molecular units as common denominator. Annotation of such functional units on the level of associated diseases, biomarkers and drug targets allows reconciliation with respective clinical data for further improving the assignment of patients to specific strata. The authors finally discuss this approach in the light of adaptive clinical trials design and analysis.
    ISSN: 2160-9586
    E-ISSN: 21609594
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  • 5
    Language: English
    In: Immunome research, 03 November 2010, Vol.6 Suppl 2, pp.S7
    Description: The last years have seen a renaissance of the vaccine area, driven by clinical needs in infectious diseases but also chronic diseases such as cancer and autoimmune disorders. Equally important are technological improvements involving nano-scale delivery platforms as well as third generation adjuvants. In parallel immunoinformatics routines have reached essential maturity for supporting central aspects in vaccinology going beyond prediction of antigenic determinants. On this basis computational vaccinology has emerged as a discipline aimed at ab-initio rational vaccine design.Here we present a computational workflow for implementing computational vaccinology covering aspects from vaccine target identification to functional characterization and epitope selection supported by a Systems Biology assessment of central aspects in host-pathogen interaction. We exemplify the procedures for Epstein Barr Virus (EBV), a clinically relevant pathogen causing chronic infection and suspected of triggering malignancies and autoimmune disorders. We introduce pBone/pView as a computational workflow supporting design and execution of immunoinformatics workflow modules, additionally involving aspects of results visualization, knowledge sharing and re-use. Specific elements of the workflow involve identification of vaccine targets in the realm of a Systems Biology assessment of host-pathogen interaction for identifying functionally relevant targets, as well as various methodologies for delineating B- and T-cell epitopes with particular emphasis on broad coverage of viral isolates as well as MHC alleles.Applying the workflow on EBV specifically proposes sequences from the viral proteins LMP2, EBNA2 and BALF4 as vaccine targets holding specific B- and T-cell epitopes promising broad strain and allele coverage. Based on advancements in the experimental assessment of genomes, transcriptomes and proteomes for both, pathogen and (human) host, the fundaments for rational design of vaccines have been laid out. In parallel, immunoinformatics modules have been designed and successfully applied for supporting specific aspects in vaccine design. Joining these advancements, further complemented by novel vaccine formulation and delivery aspects, have paved the way for implementing computational vaccinology for rational vaccine design tackling presently unmet vaccine challenges.
    Keywords: Research;
    E-ISSN: 1745-7580
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  • 6
    In: Molecular BioSystems, 2011, Vol.7(1), pp.200-214
    Description: Chemotherapy of cancer experiences a number of shortcomings including development of drug resistance. This fact also holds true for neuroblastoma utilizing chemotherapeutics as vincristine. We performed a comparative analysis of molecular and cellular mechanisms associated with vincristine resistance utilizing cell line as well as human tissue data. Differential gene expression analysis revealed molecular features, processes and pathways afflicted with drug resistance mechanisms in general, and specifically with vincristine significantly involving actin associated features. However, specific mode of resistance as well as underlying genotype of parental, vincristine sensitive cells apparently exhibited significant heterogeneity. No consensus profile for vincristine resistance could be derived, but resistance-associated changes on the level of individual neuroblastoma cell lines as well as individual patient profiles became clearly evident. Based on these prerequisites we utilized the concept of synthetic lethality aimed at identifying hub proteins which when inhibited promise to induce cell death due to a synthetic lethal interaction with down-regulated, chemoresistance associated features. Our screening procedure identified synthetic lethal hub proteins afflicted with actin associated processes holding synthetic lethal interactions to down-regulated features individually found in all chemoresistant cell lines tested, therefore promising an improved therapeutic window. Verification of such synthetic lethal hub candidates in human neuroblastoma tissue expression profiles indicated the feasibility of this screening approach for addressing vincristine resistance in neuroblastoma.
    Keywords: Antineoplastic Agents -- Pharmacology ; Drug Resistance, Neoplasm -- Physiology ; Neoplasm Proteins -- Metabolism ; Neuroblastoma -- Metabolism ; Vincristine -- Pharmacology;
    ISSN: 1742-206X
    E-ISSN: 1742-2051
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  • 7
    Language: English
    In: Omics : a journal of integrative biology, March 2012, Vol.16(3), pp.105-12
    Description: The risk of developing cardiovascular diseases (CVD) is dramatically increased in patients with chronic kidney diseases (CKD). Mechanisms leading to this cardiorenal syndrome (CRS) are multifactorial, and combined analyses of both failing organs may provide routes toward developing strategies for early risk assessment, prognosis, and consequently effective therapy. In order to identify molecular mechanisms involved in the crosstalk between the diseased cardiovascular system and kidney, we analyzed tissue specific transcriptomics profiles on atherosclerosis and diabetic nephropathy together with gene sets associated with cardiovascular and chronic kidney diseases that derived from a literature mining approach. We focused on enriched molecular pathways and highlight molecular interactions found within as well as between affected pathways identified for the two organs. Analysis on the level of molecular pathways pointed out the role of PPAR signaling, coagulation, inflammation, and focal adhesion pathways in formation and progression of the CRS. The proteins apolipoprotein A1 (APOA1) and albumin (ALB) turned out to be of particular importance in the context of dyslipidemia, one of the major risk factors for the development of CVD. In summary, our analyses highlight mechanisms associated with dyslipidemia, hemodynamic regulation, and inflammation on the interface between the cardiovascular and the renal system.
    Keywords: Cardio-Renal Syndrome -- Metabolism ; Cardiovascular Diseases -- Metabolism
    ISSN: 15362310
    E-ISSN: 1557-8100
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  • 8
    Language: English
    In: Methods in molecular biology (Clifton, N.J.), 2014, Vol.1159, pp.109-33
    Description: The field of biomarker research has experienced a major boost in recent years, and the number of publications on biomarker studies evaluating given, but also proposing novel biomarker candidates is increasing rapidly for numerous clinically relevant disease areas. However, individual markers often lack sensitivity and specificity in the clinical context, resting essentially on the intra-individual phenotype variability hampering sensitivity, or on assessing more general processes downstream of the causative molecular events characterizing a disease term, in consequence impairing disease specificity. The trend to circumvent these shortcomings goes towards utilizing multimarker panels, thus combining the strength of individual markers to further enhance performance regarding both sensitivity and specificity. A way of identifying the optimal composition of individual markers in a panel approach is to pick each marker as representative for a specific pathophysiological (mechanistic) process relevant for the disease under investigation, hence resulting in a multimarker panel for covering the set of pathophysiological processes underlying the frequently multifactorial composition of a clinical phenotype.Here we outline a procedure of identifying such sets of disease-specific pathophysiological processes (units) delineated on the basis of disease-associated molecular feature lists derived from literature mining as well as aggregated, publicly available Omics profiling experiments. With such molecular units in hand, providing an improved reflection of a specific clinical phenotype, biomarker candidates can then be assigned to or novel candidates are to be selected from these units, subsequently resulting in a multimarker panel promising improved accuracy in disease diagnosis as well as prognosis.
    Keywords: Biological Ontologies ; Biomarkers -- Metabolism ; Data Mining -- Methods ; Literature Based Discovery -- Methods
    ISSN: 10643745
    E-ISSN: 1940-6029
    Source: MEDLINE/PubMed (U.S. National Library of Medicine)
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  • 9
    Language: English
    In: Methods in molecular biology (Clifton, N.J.), 2011, Vol.719, pp.379-97
    Description: Progress in experimental procedures has led to rapid availability of Omics profiles. Various open-access as well as commercial tools have been developed for storage, analysis, and interpretation of transcriptomics, proteomics, and metabolomics data. Generally, major analysis steps include data storage, retrieval, preprocessing, and normalization, followed by identification of differentially expressed features, functional annotation on the level of biological processes and molecular pathways, as well as interpretation of gene lists in the context of protein-protein interaction networks. In this chapter, we discuss a sequential transcriptomics data analysis workflow utilizing open-source tools, specifically exemplified on a gene expression dataset on familial hypercholesterolemia.
    Keywords: Data Interpretation, Statistical ; Computational Biology -- Methods
    E-ISSN: 1940-6029
    Source: MEDLINE/PubMed (U.S. National Library of Medicine)
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  • 10
    In: Transplantation, 2009, Vol.88(3S Suppl), pp.S14-S19
    Description: Ischemia reperfusion injury (IRI) is a choreographed process leading to delayed graft function (DGF) and reduced long-term patency of the transplanted organ. Early identification of recipients of grafts at risk would allow modification of the posttransplant management, and thereby potentially improve short- and long-term outcomes. The recently emerged “omics” technologies together with bioinformatics workup have allowed the integration and analysis of IRI-associated molecular profiles in the context of DGF. Such a systems biological approach promises qualitative information about interdependencies of complex processes such as IRI regulation, rather than offering descriptive tables of differentially regulated features on a transcriptome, proteome, or metabolome level leaking the functional, biological framework. In deceased-donor kidney transplantation as the primary causative factor resulting in IRI and DGF, a distinct signature and choreography of molecular events in the graft before harvesting seems to be associated with subsequent DGF. A systems biological assessment of these molecular changes suggests that processes along inflammation are of pivotal importance for the early stage of IRI. The causal proof of this association has been tested by a double-blinded, randomized, controlled trial of steroid or placebo infusion into deceased donors before the organs were harvested. Thorough systems biological analysis revealed a panel of biomarkers with excellent discrimination. In summary, integrated analysis of omics data has brought forward biomarker candidates and candidate panels that promise early assessment of IRI. However, the clinical utility of these markers still needs to be established in prospective trials in independent patient populations.
    Keywords: Kidney Transplantation -- Immunology ; Reperfusion Injury -- Immunology;
    ISSN: 0041-1337
    E-ISSN: 15346080
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