| 1. |
- Grafström, Roland C, et al.
(författare)
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Toward the Replacement of Animal Experiments through the Bioinformatics-driven Analysis of 'Omics' Data from Human Cell Cultures
- 2015
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Ingår i: ATLA (Alternatives to Laboratory Animals). - : SAGE Publications. - 0261-1929 .- 2632-3559. ; 43:5, s. 325-332
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Tidskriftsartikel (refereegranskat)abstract
- This paper outlines the work for which Roland Grafström and Pekka Kohonen were awarded the 2014 Lush Science Prize. The research activities of the Grafström laboratory have, for many years, covered cancer biology studies, as well as the development and application of toxicity-predictive in vitro models to determine chemical safety. Through the integration of in silico analyses of diverse types of genomics data (transcriptomic and proteomic), their efforts have proved to fit well into the recently-developed Adverse Outcome Pathway paradigm. Genomics analysis within state-of-the-art cancer biology research and Toxicology in the 21st Century concepts share many technological tools. A key category within the Three Rs paradigm is the Replacement of animals in toxicity testing with alternative methods, such as bioinformatics-driven analyses of data obtained from human cell cultures exposed to diverse toxicants. This work was recently expanded within the pan-European SEURAT-1 project (Safety Evaluation Ultimately Replacing Animal Testing), to replace repeat-dose toxicity testing with data-rich analyses of sophisticated cell culture models. The aims and objectives of the SEURAT project have been to guide the application, analysis, interpretation and storage of 'omics' technology-derived data within the service-oriented sub-project, ToxBank. Particularly addressing the Lush Science Prize focus on the relevance of toxicity pathways, a 'data warehouse' that is under continuous expansion, coupled with the development of novel data storage and management methods for toxicology, serve to address data integration across multiple 'omics' technologies. The prize winners' guiding principles and concepts for modern knowledge management of toxicological data are summarised. The translation of basic discovery results ranged from chemical-testing and material-testing data, to information relevant to human health and environmental safety.
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| 2. |
- Kohonen, Pekka, et al.
(författare)
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Cancer Biology, Toxicology and Alternative Methods Development Go Hand-in-Hand
- 2014
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Ingår i: Basic & Clinical Pharmacology & Toxicology. - : Wiley. - 1742-7835 .- 1742-7843. ; 115:1, s. 50-58
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Forskningsöversikt (refereegranskat)abstract
- Toxicological research faces the challenge of integrating knowledge from diverse fields and novel technological developments generally in the biological and medical sciences. We discuss herein the fact that the multiple facets of cancer research, including discovery related to mechanisms, treatment and diagnosis, overlap many up and coming interest areas in toxicology, including the need for improved methods and analysis tools. Common to both disciplines, in vitro and in silico methods serve as alternative investigation routes to animal studies. Knowledge on cancer development helps in understanding the relevance of chemical toxicity studies in cell models, and many bioinformatics-based cancer biomarker discovery tools are also applicable to computational toxicology. Robotics-aided cell-based high throughput screening, microscale immunostaining techniques, and gene expression profiling analyses are common tools in cancer research, and when sequentially combined, form a tiered approach to structured safety evaluation of thousands of environmental agents, novel chemicals or engineered nanomaterials. Comprehensive tumour data collections in databases have been translated into clinically useful data, and this concept serves as template for computer-driven evaluation of toxicity data into meaningful results. Future “cancer research-inspired knowledge management” of toxicological data will aid the translation of basic discovery results and chemicals- and materials-testing data to information relevant to human health and environmental safety.
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| 3. |
- Lampa, Samuel, et al.
(författare)
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RDFIO : extending Semantic MediaWiki for interoperable biomedical data management
- 2017
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Ingår i: Journal of Biomedical Semantics. - : Springer Science and Business Media LLC. - 2041-1480. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Biological sciences are characterised not only by an increasing amount but also the extreme complexity of its data. This stresses the need for efficient ways of integrating these data in a coherent description of biological systems. In many cases, biological data needs organization before integration. This is not seldom a collaborative effort, and it is thus important that tools for data integration support a collaborative way of working. Wiki systems with support for structured semantic data authoring, such as Semantic MediaWiki, provide a powerful solution for collaborative editing of data combined with machine-readability, so that data can be handled in an automated fashion in any downstream analyses. Semantic MediaWiki lacks a built-in data import function though, which hinders efficient round-tripping of data between interoperable Semantic Web formats such as RDF and the internal wiki format.RESULTS: To solve this deficiency, the RDFIO suite of tools is presented, which supports importing of RDF data into Semantic MediaWiki, with metadata needed to export it again in the same RDF format, or ontology. Additionally, the new functionality enables mash-ups of automated data imports combined with manually created data presentations. The application of the suite of tools is demonstrated by importing drug discovery related data about rare diseases from Orphanet and acid dissociation constants from Wikidata. The RDFIO suite of tools is freely available for download via pharmb.io/project/rdfio .CONCLUSIONS: Through a set of biomedical demonstrators, it is demonstrated how the new functionality enables a number of usage scenarios where the interoperability of SMW and the wider Semantic Web is leveraged for biomedical data sets, to create an easy to use and flexible platform for exploring and working with biomedical data.
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| 4. |
- Ostling, Päivi, et al.
(författare)
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Systematic Analysis of MicroRNAs Targeting the Androgen Receptor in Prostate Cancer Cells.
- 2011
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Ingår i: Cancer Research. - 1538-7445. ; 71, s. 1956-1967
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Tidskriftsartikel (refereegranskat)abstract
- Androgen receptor (AR) is expressed in all stages of prostate cancer progression, including in castration-resistant tumors. Eliminating AR function continues to represent a focus of therapeutic investigation, but AR regulatory mechanisms remain poorly understood. To systematically characterize mechanisms involving microRNAs (miRNAs), we conducted a gain-of function screen of 1129 miRNA molecules in a panel of human prostate cancer cell lines and quantified changes in AR protein content using protein lysate microarrays. In this way, we defined 71 unique miRNAs that influenced the level of AR in human prostate cancer cells. RNA sequencing data revealed that the 3'UTR of AR (and other genes) is much longer than currently used in miRNA target prediction programs. Our own analyses predicted that most of the miRNA regulation of AR would target an extended 6 kb 3'UTR. 3'UTR-binding assays validated 13 miRNAs that are able to regulate this long AR 3'UTR (miR-135b, miR-185, miR-297, miR-299-3p, miR-34a, miR-34c, miR-371-3p, miR-421, miR-449a, miR-449b, miR-634, miR-654-5p, and miR-9). Fifteen AR downregulating miRNAs decreased androgen-induced proliferation of prostate cancer cells. In particular, analysis of clinical prostate cancers confirmed a negative correlation of miR-34a and miR-34c expression with AR levels. Our findings establish that miRNAs interacting with the long 3'UTR of the AR gene are important regulators of AR protein levels, with implications for developing new therapeutic strategies to inhibit AR function and androgen-dependent cell growth. Cancer Res; 71(5); 1-12. ©2011 AACR.
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| 5. |
- Vogt, Carmen, et al.
(författare)
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Proteomics Analysis Reveals Distinct Corona Composition on Magnetic Nanoparticles with Different Surface Coatings : Implications for Interactions with Primary Human Macrophages
- 2015
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 10:10
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Tidskriftsartikel (refereegranskat)abstract
- Superparamagnetic iron oxide nanoparticles (SPIONs) have emerged as promising contrast agents for magnetic resonance imaging. The influence of different surface coatings on the biocompatibility of SPIONs has been addressed, but the potential impact of the so-called corona of adsorbed proteins on the surface of SPIONs on their biological behavior is less well studied. Here, we determined the composition of the plasma protein corona on silica- coated versus dextran-coated SPIONs using mass spectrometry-based proteomics approaches. Notably, gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed distinct protein corona compositions for the two different SPIONs. Relaxivity of silica-coated SPIONs was modulated by the presence of a protein corona. Moreover, the viability of primary human monocyte-derived macrophages was influenced by the protein corona on silica-coated, but not dextran-coated SPIONs, and the protein corona promoted cellular uptake of silica-coated SPIONs, but did not affect internalization of dextran-coated SPIONs.
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