TFCheckpoint database update, a cross-referencing system for transcription factors from human, mouse and rat.

Prior knowledge about DNA-binding transcription factors (dbTFs), transcription co-regulators (coTFs) and general transcriptional factors (GTFs) is crucial for the study and understanding of the regulation of transcription. This is reflected by the many publications and database resources describing knowledge about TFs. We previously launched the TFCheckpoint database, an integrated resource focused on human, mouse and rat dbTFs, providing users access to a comprehensive overview of these proteins.

Expanding the coverage of regulons from high-confidence prior knowledge for accurate estimation of transcription factor activities.

Gene regulation plays a critical role in the cellular processes that underlie human health and disease. The regulatory relationship between transcription factors (TFs), key regulators of gene expression, and their target genes, the so called TF regulons, can be coupled with computational algorithms to estimate the activity of TFs. However, to interpret these findings accurately, regulons of high reliability and coverage are needed.

Characterisation of Colorectal Cancer Cell Lines through Proteomic Profiling of Their Extracellular Vesicles.

Colorectal cancer (CRC) is one of the most prevalent cancers, driven by several factors including deregulations in intracellular signalling pathways. Small extracellular vesicles (sEVs) are nanosized protein-packaged particles released from cells, which are present in liquid biopsies. Here, we characterised the proteome landscape of sEVs and their cells of origin in three CRC cell lines HCT116, HT29 and SW620 to explore molecular traits that could be exploited as cancer biomarker candidates and how intracellular signalling can be assessed by sEV analysis instead of directly obtaining the cell of origin itself.

ExTRI: Extraction of transcription regulation interactions from literature.

The regulation of gene transcription by transcription factors is a fundamental biological process, yet the relations between transcription factors (TF) and their target genes (TG) are still only sparsely covered in databases. Text-mining tools can offer broad and complementary solutions to help locate and extract mentions of these biological relationships in articles. We have generated ExTRI, a knowledge graph of TF-TG relationships, by applying a high recall text-mining pipeline to MedLine abstracts identifying over 100,000 candidate sentences with TF-TG relations.

The gene regulation knowledge commons: the action area of GREEKC.

As computational modeling becomes more essential to analyze and understand biological regulatory mechanisms, governance of the many databases and knowledge bases that support this domain is crucial to guarantee reliability and interoperability of resources. To address this, the COST Action Gene Regulation Ensemble Effort for the Knowledge Commons (GREEKC, CA15205, www.greekc.

Formalization of gene regulation knowledge using ontologies and gene ontology causal activity models.

Gene regulation computational research requires handling and integrating large amounts of heterogeneous data. The Gene Ontology has demonstrated that ontologies play a fundamental role in biological data interoperability and integration. Ontologies help to express data and knowledge in a machine processable way, which enables complex querying and advanced exploitation of distributed data.

A GO catalogue of human DNA-binding transcription factors.

To control gene transcription, DNA-binding transcription factors recognise specific sequence motifs in gene regulatory regions. A complete and reliable GO annotation of all DNA-binding transcription factors is key to investigating the delicate balance of gene regulation in response to environmental and developmental stimuli. The need for such information is demonstrated by the many lists of transcription factors that have been produced over the past decade.

Gene Ontology representation for transcription factor functions.

Transcription plays a central role in defining the identity and functionalities of cells, as well as in their responses to changes in the cellular environment. The Gene Ontology (GO) provides a rigorously defined set of concepts that describe the functions of gene products. A GO annotation is a statement about the function of a particular gene product, represented as an association between a gene product and the biological concept a GO term defines.

Author Correction: High-throughput screening reveals higher synergistic effect of MEK inhibitor combinations in colon cancer spheroids.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Strategies to Enhance Logic Modeling-Based Cell Line-Specific Drug Synergy Prediction.

Discrete dynamical modeling shows promise in prioritizing drug combinations for screening efforts by reducing the experimental workload inherent to the vast numbers of possible drug combinations. We have investigated approaches to predict combination responses across different cancer cell lines using logic models generated from one generic prior-knowledge network representing 144 nodes covering major cancer signaling pathways. Cell-line specific models were configured to agree with baseline activity data from each unperturbed cell line.

High-throughput screening reveals higher synergistic effect of MEK inhibitor combinations in colon cancer spheroids.

Drug combinations have been proposed to combat drug resistance, but putative treatments are challenged by low bench-to-bed translational efficiency. To explore the effect of cell culture format and readout methods on identification of synergistic drug combinations in vitro, we studied response to 21 clinically relevant drug combinations in standard planar (2D) layouts and physiologically more relevant spheroid (3D) cultures of HCT-116, HT-29 and SW-620 cells. By assessing changes in viability, confluency and spheroid size, we were able to identify readout- and culture format-independent synergies, as well as synergies specific to either culture format or readout method.

The Minimum Information about a Molecular Interaction CAusal STatement (MI2CAST).

Motivation: A large variety of molecular interactions occurs between biomolecular components in cells. When a molecular interaction results in a regulatory effect, exerted by one component onto a downstream component, a so-called 'causal interaction' takes place. Causal interactions constitute the building blocks in our understanding of larger regulatory networks in cells.

Silencing trust: confidence and familiarity in re-engineering knowledge infrastructures.

In this paper, we tell the story of efforts currently underway, on diverse fronts, to build digital knowledge repositories ('knowledge-bases') to support research in the life sciences. If successful, knowledge bases will be part of a new knowledge infrastructure-capable of facilitating ever-more comprehensive, computational models of biological systems. Such an infrastructure would, however, represent a sea-change in the technological management and manipulation of complex data, inducing a generational shift in how questions are asked and answered and results published and circulated.

A high-throughput drug combination screen of targeted small molecule inhibitors in cancer cell lines.

While there is a high interest in drug combinations in cancer therapy, openly accessible datasets for drug combination responses are sparse. Here we present a dataset comprising 171 pairwise combinations of 19 individual drugs targeting signal transduction mechanisms across eight cancer cell lines, where the effect of each drug and drug combination is reported as cell viability assessed by metabolic activity. Drugs are chosen by their capacity to specifically interfere with well-known signal transduction mechanisms.

CImbinator: a web-based tool for drug synergy analysis in small- and large-scale datasets.

Motivation: Drug synergies are sought to identify combinations of drugs particularly beneficial. User-friendly software solutions that can assist analysis of large-scale datasets are required.

Results: CImbinator is a web-service that can aid in batch-wise and in-depth analyzes of data from small-scale and large-scale drug combination screens.

Gene regulation knowledge commons: community action takes care of DNA binding transcription factors.

A large gap remains between the amount of knowledge in scientific literature and the fraction that gets curated into standardized databases, despite many curation initiatives. Yet the availability of comprehensive knowledge in databases is crucial for exploiting existing background knowledge, both for designing follow-up experiments and for interpreting new experimental data. Structured resources also underpin the computational integration and modeling of regulatory pathways, which further aids our understanding of regulatory dynamics.

Discovery of Drug Synergies in Gastric Cancer Cells Predicted by Logical Modeling.

Discovery of efficient anti-cancer drug combinations is a major challenge, since experimental testing of all possible combinations is clearly impossible. Recent efforts to computationally predict drug combination responses retain this experimental search space, as model definitions typically rely on extensive drug perturbation data. We developed a dynamical model representing a cell fate decision network in the AGS gastric cancer cell line, relying on background knowledge extracted from literature and databases.

The gastrin and cholecystokinin receptors mediated signaling network: a scaffold for data analysis and new hypotheses on regulatory mechanisms.

Background: The gastrointestinal peptide hormones cholecystokinin and gastrin exert their biological functions via cholecystokinin receptors CCK1R and CCK2R respectively. Gastrin, a central regulator of gastric acid secretion, is involved in growth and differentiation of gastric and colonic mucosa, and there is evidence that it is pro-carcinogenic. Cholecystokinin is implicated in digestion, appetite control and body weight regulation, and may play a role in several digestive disorders.

Finding gene regulatory network candidates using the gene expression knowledge base.

Background: Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of 'omics' data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats.

Salt-inducible kinase 1 (SIK1) is induced by gastrin and inhibits migration of gastric adenocarcinoma cells.

Salt-inducible kinase 1 (SIK1/Snf1lk) belongs to the AMP-activated protein kinase (AMPK) family of kinases, all of which play major roles in regulating metabolism and cell growth. Recent studies have shown that reduced levels of SIK1 are associated with poor outcome in cancers, and that this involves an invasive cellular phenotype with increased metastatic potential. However, the molecular mechanism(s) regulated by SIK1 in cancer cells is not well explored.

NR4A2 is regulated by gastrin and influences cellular responses of gastric adenocarcinoma cells.

The peptide hormone gastrin is known to play a role in differentiation, growth and apoptosis of cells in the gastric mucosa. In this study we demonstrate that gastrin induces Nuclear Receptor 4A2 (NR4A2) expression in the adenocarcinoma cell lines AR42J and AGS-GR, which both possess the gastrin/CCK2 receptor. In vivo, NR4A2 is strongly expressed in the gastrin responsive neuroendocrine ECL cells in normal mucosa, whereas gastric adenocarcinoma tissue reveals a more diffuse and variable expression in tumor cells.

Gene Ontology annotation of sequence-specific DNA binding transcription factors: setting the stage for a large-scale curation effort.

Transcription factors control which information in a genome becomes transcribed to produce RNAs that function in the biological systems of cells and organisms. Reliable and comprehensive information about transcription factors is invaluable for large-scale network-based studies. However, existing transcription factor knowledge bases are still lacking in well-documented functional information.

Platelet-activating factor induces proliferation in differentiated keratinocytes.

Increased levels of platelet-activating factor (PAF; 1-O-alkyl-2-acetyl-sn-glycero-3-phosphocholine) are found in several inflammatory dermatoses, but PAF's exact role in epidermis is uncertain. In order to better understand the physiological consequences of excess PAF production in epidermis, we examined the gene regulatory effects of PAF short-term stimulation in differentiated HaCaT keratinocytes by transcriptional profiling. Even though PAF induces COX2 expression, we found that PAF regulates only few genes associated with inflammation in differentiated keratinocytes.

TFcheckpoint: a curated compendium of specific DNA-binding RNA polymerase II transcription factors.

Summary: Gene regulatory network assembly and analysis requires high-quality knowledge sources that cover functional aspects of the various components of the gene regulatory machinery. A multiplicity of resources exists with information about mammalian transcription factors (TFs); yet, only few of these provide sufficiently accurate classifications of the functional roles of individual TFs, or standardized evidence that would justify the information on which these functional classifications are based. We compiled the list of all putative TFs from nine different resources, ignored factors such as general TFs, mediator complexes and chromatin modifiers, and for the remaining factors checked the available literature for references that support their function as a true sequence-specific DNA-binding RNA polymerase II TF (DbTF).

The duration of gastrin treatment affects global gene expression and molecular responses involved in ER stress and anti-apoptosis.

Background: How cells decipher the duration of an external signal into different transcriptional outcomes is poorly understood. The hormone gastrin can promote a variety of cellular responses including proliferation, differentiation, migration and anti-apoptosis. While gastrin in normal concentrations has important physiological functions in the gastrointestine, prolonged high levels of gastrin (hypergastrinemia) is related to pathophysiological processes.