DS-PACK: Tool assembly for the end-to-end support of controlled access human data sharing.

The EU General Data Protection Regulation (GDPR) requirements have prompted a shift from centralised controlled access genome-phenome archives to federated models for sharing sensitive human data. In a data-sharing federation, a central node facilitates data discovery; meanwhile, distributed nodes are responsible for handling data access requests, concluding agreements with data users and providing secure access to the data. Research institutions that want to become part of such federations often lack the resources to set up the required controlled access processes. The DS-PACK tool assembly is a reusable, open-source middleware solution that semi-automates controlled access processes end-to-end, from data submission to access. Data protection principles are engraved into all components of the DS-PACK assembly. DS-PACK centralises access control management and distributes access control enforcement with support for data access via cloud-based applications. DS-PACK is in production use at the ELIXIR Luxembourg data hosting platform, combined with an operational model including legal facilitation and data stewardship.

Getting your DUCs in a row - standardising the representation of Digital Use Conditions.

Improving patient care and advancing scientific discovery requires responsible sharing of research data, healthcare records, biosamples, and biomedical resources that must also respect applicable use conditions. Defining a standard to structure and manage these use conditions is a complex and challenging task. This is exemplified by a near unlimited range of asset types, a high variability of applicable conditions, and differing applications at the individual or collective level. Furthermore, the specifics and granularity required are likely to vary depending on the ultimate contexts of use. All these factors confound alignment of institutional missions, funding objectives, regulatory and technical requirements to facilitate effective sharing. The presented work highlights the complexity and diversity of the problem, reviews the current state of the art, and emphasises the need for a flexible and adaptable approach. We propose Digital Use Conditions (DUC) as a framework that addresses these needs by leveraging existing standards, striking a balance between expressiveness versus ambiguity, and considering the breadth of applicable information with their context of use.

The Translational Data Catalog - discoverable biomedical datasets.

The discoverability of datasets resulting from the diverse range of translational and biomedical projects remains sporadic. It is especially difficult for datasets emerging from pre-competitive projects, often due to the legal constraints of data-sharing agreements, and the different priorities of the private and public sectors. The Translational Data Catalog is a single discovery point for the projects and datasets produced by a number of major research programmes funded by the European Commission. Funded by and rooted in a number of these European private-public partnership projects, the Data Catalog is built on FAIR-enabling community standards, and its mission is to ensure that datasets are findable and accessible by machines. Here we present its creation, content, value and adoption, as well as the next steps for sustainability within the ELIXIR ecosystem.

The Data Use Ontology to streamline responsible access to human biomedical datasets.

Human biomedical datasets that are critical for research and clinical studies to benefit human health also often contain sensitive or potentially identifying information of individual participants. Thus, care must be taken when they are processed and made available to comply with ethical and regulatory frameworks and informed consent data conditions. To enable and streamline data access for these biomedical datasets, the Global Alliance for Genomics and Health (GA4GH) Data Use and Researcher Identities (DURI) work stream developed and approved the Data Use Ontology (DUO) standard. DUO is a hierarchical vocabulary of human and machine-readable data use terms that consistently and unambiguously represents a dataset's allowable data uses. DUO has been implemented by major international stakeholders such as the Broad and Sanger Institutes and is currently used in annotation of over 200,000 datasets worldwide. Using DUO in data management and access facilitates researchers' discovery and access of relevant datasets. DUO annotations increase the FAIRness of datasets and support data linkages using common data use profiles when integrating the data for secondary analyses. DUO is implemented in the Web Ontology Language (OWL) and, to increase community awareness and engagement, hosted in an open, centralized GitHub repository. DUO, together with the GA4GH Passport standard, offers a new, efficient, and streamlined data authorization and access framework that has enabled increased sharing of biomedical datasets worldwide.

GA4GH Passport standard for digital identity and access permissions.

The Global Alliance for Genomics and Health (GA4GH) supports international standards that enable a federated data sharing model for the research community while respecting data security, ethical and regulatory frameworks, and data authorization and access processes for sensitive data. The GA4GH Passport standard (Passport) defines a machine-readable digital identity that conveys roles and data access permissions (called "visas") for individual users. Visas are issued by data stewards, including data access committees (DACs) working with public databases, the entities responsible for the quality, integrity, and access arrangements for the datasets in the management of human biomedical data. Passports streamline management of data access rights across data systems by using visas that present a data user's digital identity and permissions across organizations, tools, environments, and services. We describe real-world implementations of the GA4GH Passport standard in use cases from ELIXIR Europe, National Institutes of Health, and the Autism Sharing Initiative. These implementations demonstrate that the Passport standard has provided transparent mechanisms for establishing permissions and authorizing data access across platforms.

Soloxolone methyl, as a 18ßH-glycyrrhetinic acid derivate, may result in endoplasmic reticulum stress to induce apoptosis in breast cancer cells.

Being one of the leading causes of cancer death among women, various chemotherapeutic agents isolated from natural compounds are used in breast cancer treatment and consequently studies to develop new drugs still continue. There are several studies on 18ßH-glycyrrhetinic acid, a secondary metabolite which is found in Glycyrrhiza glabra (liquorice roots), as a potential anticancer agent. In this study, the cytotoxic and apoptotic effects of Soloxolone methyl compound, a semisynthetic derivative of 18ßH-glycyrrhetinic acid were investigated on breast cancer cells (MCF-7, MDA-MBA-231). Soloxolone methyl is found to be cytotoxic on both MCF-7 and MDA-MBA-231 breast cancer cells by inducing apoptosis. Especially in MDA-MB-231 cells apoptosis is detected to be triggered by ER stress. The antigrowth effects of Soloxolone methyl were determined using MTT and ATP assays. To identify the mode of cell death (apoptosis/necrosis), fluorescent staining (Hoechst 33342 and Propidium iodide) and caspase-cleaved cytokeratin 18 (M30-antigen) analyses were used. In addition, apoptosis was investigated on gene and protein levels by PCR and Western Blotting. Soloxolone methyl decreased cell viability on cells in a dose and time-dependent manner and induced apoptosis markers. An increase on apoptotic proteins related to endoplasmic reticulum stress (IRE1-α, Bip, CHOP) was also determined in MDA-MB-231 cells. Moreover, an increase of apoptotic gene expressions was determined in both cells treated with Soloxolone methyl. Advance analyses should be performed to elucidate the potential of Soloxolone methyl as an anticancer agent in breast cancer treatment.

Mixed ligand complexes of Co(II), Ni(II) and Cu(II) with quercetin and diimine ligands: synthesis, characterization, anti-cancer and anti-oxidant activity.

In this work, mixed ligand complexes of Co(II) Ni(II) and Cu(II) were synthesized using quercetin and diimine (1,10-phenanthroline or 2,2'-bipyiridine) ligands. The obtained Ni(II) and Co(II) complexes are new and the Cu(II) complexes are synthesized by different method from the literature. The characterization of complexes was performed by elemental analysis, thermogravimetric analysis, ESI-MS, UV-visible and infrared spectral analyses, magnetic susceptibility and molar conductivity measurements. It was found that quercetin, diimine and metal(II) ion form 1:1:1 complexes. Resulting data supported octahedral geometry for Ni(II) and Co(II) complexes and square pyramidal geometry for Cu(II) complexes. The proposed compositions are [Co(queH-1)Cl(phen)(H2O)]∙2H2O (1, queH = quercetin, phen = 1,10-phenanthroline), [Ni(queH-1)Cl(phen)(H2O)]∙2H2O (2), [Cu(queH-1)Cl(phen)]∙2.5H2O (3) and [Cu(queH-1)Cl(bpy)]∙2H2O (4, bpy = 2,2'-bipyiridine). Antioxidant capacity and total phenolic content of complexes measured by Folin-Ciocalteu and ABTS methods. Anti-cancer effect of these compounds were tested against different cancer cells (A549, PC-3, HeLa and MCF-7). Apoptosis identified by the fluorescence imaging, caspase cleaved cytokeratin-18 and flow cytometry analysis (annexin V, caspase 3/7, mitochondria membrane potential and oxidative stress). As a result, Cu(II) complexes are more effective than the other compounds and Complex 3 is a promising anti-cancer compound against breast cancer MCF-7 and MDA-MB-231 cells (IC50 values are 2.4 and 5.4 µM for 48 h, respectively). Flow cytometry analysis exhibited that Complex 3 caused apoptosis in MCF-7 cells. These results support that Complex 3 has anticancer activity and can be a potential anticancer agent especially in breast cancer.

DAISY: A Data Information System for accountability under the General Data Protection Regulation.

BACKGROUND: The new European legislation on data protection, namely, the General Data Protection Regulation (GDPR), has introduced comprehensive requirements for the documentation about the processing of personal data as well as informing the data subjects of its use. GDPR's accountability principle requires institutions, projects, and data hubs to document their data processings and demonstrate compliance with the GDPR. In response to this requirement, we see the emergence of commercial data-mapping tools, and institutions creating GDPR data register with such tools. One shortcoming of this approach is the genericity of tools, and their process-based model not capturing the project-based, collaborative nature of data processing in biomedical research. FINDINGS: We have developed a software tool to allow research institutions to comply with the GDPR accountability requirement and map the sometimes very complex data flows in biomedical research. By analysing the transparency and record-keeping obligations of each GDPR principle, we observe that our tool effectively meets the accountability requirement. CONCLUSIONS: The GDPR is bringing data protection to center stage in research data management, necessitating dedicated tools, personnel, and processes. Our tool, DAISY, is tailored specifically for biomedical research and can help institutions in tackling the documentation challenge brought about by the GDPR. DAISY is made available as a free and open source tool on Github. DAISY is actively being used at the Luxembourg Centre for Systems Biomedicine and the ELIXIR-Luxembourg data hub.

Palladium(ii) and platinum(ii) saccharinate complexes with bis(diphenylphosphino)methane/ethane: synthesis, S-phase arrest and ROS-mediated apoptosis in human colon cancer cells.

New neutral [M(sac)2(diphos)] and cationic [M(diphos)2](sac)2 complexes, where M = PdII or PtII, sac = saccharinate, and diphos = 1,1-bis(diphenylphosphino)methane (dppm) or 1,2-bis(diphenylphosphino)ethane (dppe), were synthesized and structurally characterized. The anticancer activity of the complexes was investigated against MCF-7 (breast), A549 (lung), HCT116 (colon), DU145 (prostate) cancer and BEAS-2B (normal bronchial epithelial) cells. Neutral Pt-dppm (2) and Pd-dppe complexes (5) did not show any biological activity. The cationic Pd-dppe (7) complex displayed antiproliferative activity, while the rest of the complexes exhibited potent cytotoxicity compared with cisplatin. The active Pd(ii)/Pt(ii) complexes were then included in further studies including interaction with DNA/HSA, nuclease activity, cellular uptake and lipophilicity. The potent complexes induced the apoptotic cell death as probed through annexin V positivity and caspase activation. Mechanistic studies on HCT116 cells showed that the complexes cause cell cycle arrest at the DNA synthesis (S) phase and excessive generation of reactive oxygen species (ROS), damaging to both mitochondria and DNA.

A promising natural product, pristimerin, results in cytotoxicity against breast cancer stem cells in vitro and xenografts in vivo through apoptosis and an incomplete autopaghy in breast cancer.

Several natural products have been suggested as effective agents for the treatment of cancer. Given the important role of CSCs (Cancer Stem Cells) in cancer, which is a trendy hypothesis, it is worth investigating the effects of pristimerin on CSCs as well as on the other malignant cells (MCF-7 and MDA-MB-231) of breast cancer. The anti-growth activity of pristimerin against MCF-7 and MCF-7s (cancer stem cell enriched population) cells was investigated by real time viability monitorization (xCELLigence System®) and ATP assay, respectively. Mode of cell death was evaluated using electron and fluorescence microscopies, western blotting (autophagy, apoptosis and ER-stress related markers) and flow cytometry (annexin-V staining, caspase 3/7 activity, BCL-2 and PI3K expressions). Pristimerin showed an anti-growth effect on cancer cells and cancer stem cells with IC50 values ranging at 0.38-1.75µM. It inhibited sphere formation at relatively lower doses (<1.56µM). Apoptosis was induced in MCF-7 and MCF-7s cells. In addition, extensive cytoplasmic vacuolation was observed, implying an incompleted autophagy as evidenced by the increase of autophagy-related proteins (p62 and LC3-II) with an unfolded protein response (UPR). Pristimerin inhibited the growth of MCF-7 and MDA-MB-231-originated xenografts in NOD.CB17-Prkdcscid/J mice. In mice, apoptosis was further confirmed by cleavage of PARP, activation of caspase 3 and/or 7 and TUNEL staining. Taken together, pristimerin shows cytotoxic activity on breast cancer both in vitro and in vivo. It seems to represent a robust promising agent for the treatment of breast cancer. Pristimerin's itself or synthetic novel derivatives should be taken into consideration for novel potent anticancer agent(s).

Data capture in bioinformatics: requirements and experiences with Pedro.

BACKGROUND: The systematic capture of appropriately annotated experimental data is a prerequisite for most bioinformatics analyses. Data capture is required not only for submission of data to public repositories, but also to underpin integrated analysis, archiving, and sharing - both within laboratories and in collaborative projects. The widespread requirement to capture data means that data capture and annotation are taking place at many sites, but the small scale of the literature on tools, techniques and experiences suggests that there is work to be done to identify good practice and reduce duplication of effort. RESULTS: This paper reports on experience gained in the deployment of the Pedro data capture tool in a range of representative bioinformatics applications. The paper makes explicit the requirements that have recurred when capturing data in different contexts, indicates how these requirements are addressed in Pedro, and describes case studies that illustrate where the requirements have arisen in practice. CONCLUSION: Data capture is a fundamental activity for bioinformatics; all biological data resources build on some form of data capture activity, and many require a blend of import, analysis and annotation. Recurring requirements in data capture suggest that model-driven architectures can be used to construct data capture infrastructures that can be rapidly configured to meet the needs of individual use cases. We have described how one such model-driven infrastructure, namely Pedro, has been deployed in representative case studies, and discussed the extent to which the model-driven approach has been effective in practice.