Walking pathways with positive feedback loops reveal DNA methylation biomarkers of colorectal cancer.

BACKGROUND: The search for molecular biomarkers of early-onset colorectal cancer (CRC) is an important but still quite challenging and unsolved task. Detection of CpG methylation in human DNA obtained from blood or stool has been proposed as a promising approach to a noninvasive early diagnosis of CRC. Thousands of abnormally methylated CpG positions in CRC genomes are often located in non-coding parts of genes. Novel bioinformatic methods are thus urgently needed for multi-omics data analysis to reveal causative biomarkers with a potential driver role in early stages of cancer. METHODS: We have developed a method for finding potential causal relationships between epigenetic changes (DNA methylations) in gene regulatory regions that affect transcription factor binding sites (TFBS) and gene expression changes. This method also considers the topology of the involved signal transduction pathways and searches for positive feedback loops that may cause the carcinogenic aberrations in gene expression. We call this method "Walking pathways", since it searches for potential rewiring mechanisms in cancer pathways due to dynamic changes in the DNA methylation status of important gene regulatory regions ("epigenomic walking"). RESULTS: In this paper, we analysed an extensive collection of full genome gene-expression data (RNA-seq) and DNA methylation data of genomic CpG islands (using Illumina methylation arrays) generated from a sample of tumor and normal gut epithelial tissues of 300 patients with colorectal cancer (at different stages of the disease) (data generated in the EU-supported SysCol project). Identification of potential epigenetic biomarkers of DNA methylation was performed using the fully automatic multi-omics analysis web service "My Genome Enhancer" (MGE) (my-genome-enhancer.com). MGE uses the database on gene regulation TRANSFAC®, the signal transduction pathways database TRANSPATH®, and software that employs AI (artificial intelligence) methods for the analysis of cancer-specific enhancers. CONCLUSIONS: The identified biomarkers underwent experimental testing on an independent set of blood samples from patients with colorectal cancer. As a result, using advanced methods of statistics and machine learning, a minimum set of 6 biomarkers was selected, which together achieve the best cancer detection potential. The markers include hypermethylated positions in regulatory regions of the following genes: CALCA, ENO1, MYC, PDX1, TCF7, ZNF43.

Glial responses during epileptogenesis in Mus musculus point to potential therapeutic targets.

The Mesio-Temporal Lobe Epilepsy syndrome is the most common form of intractable epilepsy. It is characterized by recurrence of focal seizures and is often associated with hippocampal sclerosis and drug resistance. We aimed to characterize the molecular changes occurring during the initial stages of epileptogenesis in search of new therapeutic targets for Mesio-Temporal Lobe Epilepsy. We used a mouse model obtained by intra-hippocampal microinjection of kainate and performed hippocampal whole genome expression analysis at 6h, 12h and 24h post-injection, followed by multilevel bioinformatics analysis. We report significant changes in immune and inflammatory responses, neuronal network reorganization processes and glial functions, predominantly initiated during status epilepticus at 12h and persistent after the end of status epilepticus at 24h post-kainate. Upstream regulator analysis highlighted Cyba, Cybb and Vim as central regulators of multiple overexpressed genes implicated in glial responses at 24h. In silico microRNA analysis indicated that miR-9, miR-19b, miR-129, and miR-223 may regulate the expression of glial-associated genes at 24h. Our data support the hypothesis that glial-mediated inflammatory response holds a key role during epileptogenesis, and that microglial cells may participate in the initial process of epileptogenesis through increased ROS production via the NOX complex.

Multi-omics "upstream analysis" of regulatory genomic regions helps identifying targets against methotrexate resistance of colon cancer.

We present an "upstream analysis" strategy for causal analysis of multiple "-omics" data. It analyzes promoters using the TRANSFAC database, combines it with an analysis of the upstream signal transduction pathways and identifies master regulators as potential drug targets for a pathological process. We applied this approach to a complex multi-omics data set that contains transcriptomics, proteomics and epigenomics data. We identified the following potential drug targets against induced resistance of cancer cells towards chemotherapy by methotrexate (MTX): TGFalpha, IGFBP7, alpha9-integrin, and the following chemical compounds: zardaverine and divalproex as well as human metabolites such as nicotinamide N-oxide.

Pathways of aging: comparative analysis of gene signatures in replicative senescence and stress induced premature senescence.

BACKGROUND: In culturing normal diploid cells, senescence may either happen naturally, in the form of replicative senescence, or it may be a consequence of external challenges such as oxidative stress. Here we present a comparative analysis aimed at reconstruction of molecular cascades specific for replicative (RS) and stressinduced senescence (SIPS) in human fibroblasts. RESULTS: An involvement of caspase-3/keratin-18 pathway and serine/threonine kinase Aurora A/ MDM2 pathway was shared between RS and SIPS. Moreover, stromelysin/MMP3 and N-acetylglucosaminyltransferase enzyme MGAT1, which initiates the synthesis of hybrid and complex Nglycans, were identified as key orchestrating components in RS and SIPS, respectively. In RS only, Aurora-B driven cell cycle signaling was deregulated in concert with the suppression of anabolic branches of the fatty acids and estrogen metabolism. In SIPS, Aurora-B signaling is deprioritized, and the synthetic branches of cholesterol metabolism are upregulated, rather than downregulated. Moreover, in SIPS, proteasome/ubiquitin ligase pathways of protein degradation dominate the regulatory landscape. This picture indicates that SIPS proceeds in cells that are actively fighting stress which facilitates premature senescence while failing to completely activate the orderly program of RS. The promoters of genes differentially expressed in either RS or SIPS are unusually enriched by the binding sites for homeobox family proteins, with particular emphasis on HMX1, IRX2, HDX and HOXC13. Additionally, we identified Iroquois Homeobox 2 (IRX2) as a master regulator for the secretion of SPP1-encoded osteopontin, a stromal driver for tumor growth that is overexpressed by both RS and SIPS fibroblasts. The latter supports the hypothesis that senescence-specific de-repression of SPP1 aids in SIPS-dependent stromal activation. CONCLUSIONS: Reanalysis of previously published experimental data is cost-effective approach for extraction of additional insignts into the functioning of biological systems.

MatrixCatch--a novel tool for the recognition of composite regulatory elements in promoters.

BACKGROUND: Accurate recognition of regulatory elements in promoters is an essential prerequisite for understanding the mechanisms of gene regulation at the level of transcription. Composite regulatory elements represent a particular type of such transcriptional regulatory elements consisting of pairs of individual DNA motifs. In contrast to the present approach, most available recognition techniques are based purely on statistical evaluation of the occurrence of single motifs. Such methods are limited in application, since the accuracy of recognition is greatly dependent on the size and quality of the sequence dataset. Methods that exploit available knowledge and have broad applicability are evidently needed. RESULTS: We developed a novel method to identify composite regulatory elements in promoters using a library of known examples. In depth investigation of regularities encoded in known composite elements allowed us to introduce a new characteristic measure and to improve the specificity compared with other methods. Tests on an established benchmark and real genomic data show that our method outperforms other available methods based either on known examples or statistical evaluations. In addition to better recognition, a practical advantage of this method is first the ability to detect a high number of different types of composite elements, and second direct biological interpretation of the identified results. The program is available at http://gnaweb.helmholtz-hzi.de/cgi-bin/MCatch/MatrixCatch.pl and includes an option to extend the provided library by user supplied data. CONCLUSIONS: The novel algorithm for the identification of composite regulatory elements presented in this paper was proved to be superior to existing methods. Its application to tissue specific promoters identified several highly specific composite elements with relevance to their biological function. This approach together with other methods will further advance the understanding of transcriptional regulation of genes.

Building a knowledge base for systems pathology.

Translating the exponentially growing amount of omics data into knowledge usable for a personalized medicine approach poses a formidable challenge. In this article-taking diabetes as a use case-we present strategies for developing data repositories into computer-accessible knowledge sources that can be used for a systemic view on the molecular causes of diseases, thus laying the foundation for systems pathology.

Identification of dominant signaling pathways from proteomics expression data.

The availability of the results of high-throughput analyses coming from 'omic' technologies has been one of the major driving forces of pathway biology. Analytical pathway biology strives to design a 'pathway search engine', where the input is the 'omic' data and the output is the list of activated or dominant pathways in a given sample. Here we describe the first attempt to design and validate such a pathway search engine using as input expression proteomics data. The engine represents a specific workflow in computational tools developed originally for mRNA analysis (BMC Bioinformatics 2006, 7 (Suppl 2), S13). Using our own datasets as well as data from recent proteomics literature we demonstrate that different dominant pathways (EGF, TGF(beta), stress, and Fas pathways) can be correctly identified even from limited datasets. Pathway search engines can find application in a variety of proteomics-related fields, from fundamental molecular biology to search for novel types of disease biomarkers.

Integrating pathway data for systems pathology.

The HumanPSD database on the complete proteomes of human, mouse and rat has been integrated with the databases TRANSFAC on gene regulation and TRANSPATH on signal transduction to provide a comprehensive systems biological platform for these organisms. As a next step, integration with PathoDB and PathoSign on pathologically relevant mutations is planned together with an extension beyond the limits of the individual cell, towards intercellular networks, by integrating the database EndoNet on hormonal networks as well. The overall aim is to come up with a platform that is suitable to provide knowledge for systems pathology, i. e. a system-wide modeling of pathological states and their development.

Integrative content-driven concepts for bioinformatics "beyond the cell".

Bioinformatics has delivered great contributions to genome and genomics research, without which the world-wide success of this and other global ('omics') approaches would not have been possible. More recently, it has developed further towards the analysis of different kinds of networks thus laying the foundation for comprehensive description, analysis and manipulation of whole living systems in modern "systems biology". The next step which is necessary for developing a systems biology that deals with systemic phenomena is to expand the existing and develop new methodologies that are appropriate to characterize intercellular processes and interactions without omitting the causal underlying molecular mechanisms. Modelling the processes on the different levels of complexity involved requires a comprehensive integration of information on gene regulatory events, signal transduction pathways, protein interaction and metabolic networks as well as cellular functions in the respective tissues / organs.

Beyond microarrays: find key transcription factors controlling signal transduction pathways.

BACKGROUND: Massive gene expression changes in different cellular states measured by microarrays, in fact, reflect just an "echo" of real molecular processes in the cells. Transcription factors constitute a class of the regulatory molecules that typically require posttranscriptional modifications or ligand binding in order to exert their function. Therefore, such important functional changes of transcription factors are not directly visible in the microarray experiments. RESULTS: We developed a novel approach to find key transcription factors that may explain concerted expression changes of specific components of the signal transduction network. The approach aims at revealing evidence of positive feedback loops in the signal transduction circuits through activation of pathway-specific transcription factors. We demonstrate that promoters of genes encoding components of many known signal transduction pathways are enriched by binding sites of those transcription factors that are endpoints of the considered pathways. Application of the approach to the microarray gene expression data on TNF-alpha stimulated primary human endothelial cells helped to reveal novel key transcription factors potentially involved in the regulation of the signal transduction pathways of the cells. CONCLUSION: We developed a novel computational approach for revealing key transcription factors by knowledge-based analysis of gene expression data with the help of databases on gene regulatory networks (TRANSFAC and TRANSPATH. The corresponding software and databases are available at http://www.gene-regulation.com.

Aberrant intestinal expression and allelic variants of mucin genes associated with inflammatory bowel disease.

Loss of intestinal mucosa integrity is an important factor in the pathogenesis of inflammatory bowel disease (IBD). The aim of this study was to characterize expression changes and allelic variants of genes related to intestinal epithelial barrier function in this disease. Therefore, ileal and colonic mucosal biopsies from nonaffected regions of patients with ulcerative colitis (UC) and Crohn's disease (CD), as well as non-IBD probands, were subjected to Affymetrix DNA-microarray analysis. Real-time reverse transcription polymerase chain reaction was used for verification in larger IBD sample numbers. Disturbed mRNA expression was identified for several mucin genes in both disease groups and tissues. A significant downregulation in the colon was obtained for MUC2 in CD and MUC12 in CD and UC. Expression analysis of all dysregulated mucins in a broad human tissue panel revealed dominant epithelial tissue-specific transcription. In silico analysis of the regulatory regions of these mucins indicated nuclear factor kappaB (NFkappaB) binding sites in each promoter. Furthermore, NFkappaB was overrepresented in mucin promoters and a component of a specific combination of transcription factors (composite module). In vivo stimulation experiments in the adenocarcinoma cell line LS174T showed inducible mucin expression by the cytokines tumor necrosis factor-alpha and transforming growth factor-beta, which could be blocked by NFkappaB signaling inhibitors. Allelic discrimination screening obtained statistically significant associations for the MUC2-V116M (P = 0.003) polymorphism with CD and for MUC4-A585S (P = 0.025), as well as MUC13-R502S (P = 0.0003) with UC. These data suggest that the disturbed expression of mucin genes and the connection to the NFkappaB pathway may influence the integrity of the intestine and therefore contribute to the pathophysiology of IBD.

TRANSPATH: an information resource for storing and visualizing signaling pathways and their pathological aberrations.

TRANSPATH is a database about signal transduction events. It provides information about signaling molecules, their reactions and the pathways these reactions constitute. The representation of signaling molecules is organized in a number of orthogonal hierarchies reflecting the classification of the molecules, their species-specific or generic features, and their post-translational modifications. Reactions are similarly hierarchically organized in a three-layer architecture, differentiating between reactions that are evidenced by individual publications, generalizations of these reactions to construct species-independent 'reference pathways' and the 'semantic projections' of these pathways. A number of search and browse options allow easy access to the database contents, which can be visualized with the tool PathwayBuildertrade mark. The module PathoSign adds data about pathologically relevant mutations in signaling components, including their genotypes and phenotypes. TRANSPATH and PathoSign can be used as encyclopaedia, in the educational process, for vizualization and modeling of signal transduction networks and for the analysis of gene expression data. TRANSPATH Public 6.0 is freely accessible for users from non-profit organizations under http://www.gene-regulation.com/pub/databases.html.

TRANSPATH--a high quality database focused on signal transduction.

TRANSPATH can either be used as an encyclopedia, for both specific and general information on signal transduction, or can serve as a network analyser. Therefore, three modules have been created: the first one is the data, which have been manually extracted, mostly from the primary literature; the second is PathwayBuilder, which provides several different types of network visualization and hence faciliates understanding; the third is ArrayAnalyzer, which is particularly suited to gene expression array interpretation, and is able to identify key molecules within signalling networks (potential drug targets). These key molecules could be responsible for the coordinated regulation of downstream events. Manual data extraction focuses on direct reactions between signalling molecules and the experimental evidence for them, including species of genes/proteins used in individual experiments, experimental systems, materials and methods. This combination of materials and methods is used in TRANSPATH to assign a quality value to each experimentally proven reaction, which reflects the probability that this reaction would happen under physiological conditions. Another important feature in TRANSPATH is the inclusion of transcription factor-gene relations, which are transferred from TRANSFAC, a database focused on transcription regulation and transcription factors. Since interactions between molecules are mainly direct, this allows a complete and stepwise pathway reconstruction from ligands to regulated genes. More information is available at www.biobase.de/pages/products/databases.html.

Consistent re-modeling of signaling pathways and its implementation in the TRANSPATH database.

The data model of the signaling pathways database TRANSPATH has been re-engineered to a three-layer model comprising experimental evidences and summarized pathway information, both in a mechanistically detailed manner, and a "semantic" projection for the abstract overview. Each molecule is described in the context of a certain reaction in the multidimensional space of posttranslational modification, molecular family relationships, and the biological species of its origin. The new model makes the data better suitable for reconstructing signaling pathways and networks and mapping expression data, for instance from microarray experiments, onto regulatory networks.

Composition-sensitive analysis of the human genome for regulatory signals.

Known transcription regulatory signals which generally act as transcription factor binding sites (TFs) differ significantly in their base composition. Therefore, their occurrence in a genome largely depends on the local base composition. In an attempt to initiate an all human genome analysis for the occurrence of potential TFs, we systematically analyzed the GC-content of distinct functional regions (e. g., upstream and downstream gene regions, exons, long and short introns, repetitive elements) and correlated the frequencies of potential binding sites of a representative set of TFs in these regions. For these analyses, we used the pattern collection of the TRANSFAC database on transcriptional regulation, the information about functionally relevant combinations of them from the database TRANSCompel, and our new resource, TRANSGenomeTM, which provides an overall annotation of the human genome with emphasis on its regulatory characteristics. We show that the occurrence of sequence patterns with regulatory potential may be supported by, but cannot be fully explained by either the GC content of a whole chromosome or its putative promoter regions, nor by the information content of the patterns. Several patterns, HNF-3, NFAT, and GC box, show a clear overrepresentation in all promoter groups as well as in all chromosomes. Other patterns, like E2F and CRE-BP1, are underrepresented in all promoter groups as well as in all chromosomes in comparison with random sequences. Simultaneously, both patterns are over-represented in promoters in comparison with repetitive elements. We define several structural characteristics of the proximal promoters that differentiate them from other functional genomic regions. Two well-known promoter elements, GC- and TATA-boxes, are statistically enriched in promoters in comparison with random sequences, repetitive elements and exons. Altogether, our findings provide insights into the macroheterogeneity amongst the individual chromosomes, into the microheterogeneity among different functional regions of individual chromosomes, contribute to further understanding of structural organization of gene regulatory regions, and give first hints on the development of regulatory features during evolution.

TRANSCompel: a database on composite regulatory elements in eukaryotic genes.

Originating from COMPEL, the TRANSCompel database emphasizes the key role of specific interactions between transcription factors binding to their target sites providing specific features of gene regulation in a particular cellular content. Composite regulatory elements contain two closely situated binding sites for distinct transcription factors and represent minimal functional units providing combinatorial transcriptional regulation. Both specific factor--DNA and factor--factor interactions contribute to the function of composite elements (CEs). Information about the structure of known CEs and specific gene regulation achieved through such CEs appears to be extremely useful for promoter prediction, for gene function prediction and for applied gene engineering as well. Each database entry corresponds to an individual CE within a particular gene and contains information about two binding sites, two corresponding transcription factors and experiments confirming cooperative action between transcription factors. The COMPEL database, equipped with the search and browse tools, is available at http://www.gene-regulation.com/pub/databases.html#transcompel. Moreover, we have developed the program CATCH for searching potential CEs in DNA sequences. It is freely available as CompelPatternSearch at http://compel.bionet.nsc.ru/FunSite/CompelPatternSearch.html.