Sensing the (digital) pulse. Future steps for improving the secondary use of data for research in Switzerland.

Introduction: Ensuring that the health data infrastructure and governance permits an efficient secondary use of data for research is a policy priority for many countries. Switzerland is no exception and many initiatives have been launched to improve its health data landscape. The country now stands at an important crossroad, debating the right way forward. We aimed to explore which specific elements of data governance can facilitate - from ethico-legal and socio-cultural perspectives - the sharing and reuse of data for research purposes in Switzerland. Methods: A modified Delphi methodology was used to collect and structure input from a panel of experts via successive rounds of mediated interaction on the topic of health data governance in Switzerland. Results: First, we suggested techniques to facilitate data sharing practices, especially when data are shared between researchers or from healthcare institutions to researchers. Second, we identified ways to improve the interaction between data protection law and the reuse of data for research, and the ways of implementing informed consent in this context. Third, we put forth ideas on policy changes, such as the steps necessary to improve coordination between different actors of the data landscape and to win the defensive and risk-adverse attitudes widespread when it comes to health data. Conclusions: After having engaged with these topics, we highlighted the importance of focusing on non-technical aspects to improve the data-readiness of a country (e.g., attitudes of stakeholders involved) and of having a pro-active debate between the different institutional actors, ethico-legal experts and society at large.

Defining new criteria for selection of cell-based intestinal models using publicly available databases.

BACKGROUND: The criteria for choosing relevant cell lines among a vast panel of available intestinal-derived lines exhibiting a wide range of functional properties are still ill-defined. The objective of this study was, therefore, to establish objective criteria for choosing relevant cell lines to assess their appropriateness as tumor models as well as for drug absorption studies. RESULTS: We made use of publicly available expression signatures and cell based functional assays to delineate differences between various intestinal colon carcinoma cell lines and normal intestinal epithelium. We have compared a panel of intestinal cell lines with patient-derived normal and tumor epithelium and classified them according to traits relating to oncogenic pathway activity, epithelial-mesenchymal transition (EMT) and stemness, migratory properties, proliferative activity, transporter expression profiles and chemosensitivity. For example, SW480 represent an EMT-high, migratory phenotype and scored highest in terms of signatures associated to worse overall survival and higher risk of recurrence based on patient derived databases. On the other hand, differentiated HT29 and T84 cells showed gene expression patterns closest to tumor bulk derived cells. Regarding drug absorption, we confirmed that differentiated Caco-2 cells are the model of choice for active uptake studies in the small intestine. Regarding chemosensitivity we were unable to confirm a recently proposed association of chemo-resistance with EMT traits. However, a novel signature was identified through mining of NCI60 GI50 values that allowed to rank the panel of intestinal cell lines according to their drug responsiveness to commonly used chemotherapeutics. CONCLUSIONS: This study presents a straightforward strategy to exploit publicly available gene expression data to guide the choice of cell-based models. While this approach does not overcome the major limitations of such models, introducing a rank order of selected features may allow selecting model cell lines that are more adapted and pertinent to the addressed biological question.

ACGT: advancing clinico-genomic trials on cancer - four years of experience.

The challenges regarding seamless integration of distributed, heterogeneous and multilevel data arising in the context of contemporary, post-genomic clinical trials cannot be effectively addressed with current methodologies. An urgent need exists to access data in a uniform manner, to share information among different clinical and research centers, and to store data in secure repositories assuring the privacy of patients. Advancing Clinico-Genomic Trials (ACGT) was a European Commission funded Integrated Project that aimed at providing tools and methods to enhance the efficiency of clinical trials in the -omics era. The project, now completed after four years of work, involved the development of both a set of methodological approaches as well as tools and services and its testing in the context of real-world clinico-genomic scenarios. This paper describes the main experiences using the ACGT platform and its tools within one such scenario and highlights the very promising results obtained.

SwissPKcdw - A clinical data warehouse for the optimization of pediatric dosing regimens.

Clinical trials have been performed mainly in adults and accordingly the necessary information is lacking for pediatric patients, especially regarding dosage recommendation for approved drugs. This gap in information could be filled with results from pharmacokinetic (PK) modeling, based on data collected in daily clinical routine. In order to make this data accessible and usable for research, the Swiss Pharmacokinetics Clinical Data Warehouse (SwissPKcdw ) project has been set up, including a clinical data warehouse (CDW) and the regulatory framework for data transfer and use within. Embedded into the secure BioMedIT network, the CDW can connect to various data providers and researchers in order to collaborate on the data securely. Due to its modularity, partially containerized deployment and open-source software, each of the components can be extended, modified, and re-used for similar projects that require integrated data management, data analysis, and web tools in a secure scientific data and information technology (IT) environment. Here, we describe a collaborative and interprofessional effort to implement the aforementioned infrastructure between several partners from medical health care and academia. Furthermore, we describe a real-world use case where blood samples from pediatric patients were analyzed for the presence of genetic polymorphisms and the results were aggregated and further analyzed together with the health-related patient data in the SwissPKcdw .

SPHN - The BioMedIT Network: A Secure IT Platform for Research with Sensitive Human Data.

The BioMedIT project is funded by the Swiss government as an integral part of the Swiss Personalized Health Network (SPHN), aiming to provide researchers with access to a secure, powerful and versatile IT infrastructure for doing data-driven research on sensitive biomedical data while ensuring data privacy protection. The BioMedIT network gives researchers the ability to securely transfer, store, manage and process sensitive research data. The underlying BioMedIT nodes provide compute and storage capacity that can be used locally or through a federated environment. The network operates under a common Information Security Policy using state-of-the-art security techniques. It utilizes cloud computing, virtualization, compute accelerators (GPUs), big data storage as well as federation technologies to lower computational boundaries for researchers and to guarantee that sensitive data can be processed in a secure and lawful way. Building on existing expertise and research infrastructure at the partnering Swiss institutions, the BioMedIT network establishes a competitive Swiss private-cloud - a secure national infrastructure resource that can be used by researchers of Swiss universities, hospitals and other research institutions.

MADAP, a flexible clustering tool for the interpretation of one-dimensional genome annotation data.

A recurring task in the analysis of mass genome annotation data from high-throughput technologies is the identification of peaks or clusters in a noisy signal profile. Examples of such applications are the definition of promoters on the basis of transcription start site profiles, the mapping of transcription factor binding sites based on ChIP-chip data and the identification of quantitative trait loci (QTL) from whole genome SNP profiles. Input to such an analysis is a set of genome coordinates associated with counts or intensities. The output consists of a discrete number of peaks with respective volumes, extensions and center positions. We have developed for this purpose a flexible one-dimensional clustering tool, called MADAP, which we make available as a web server and as standalone program. A set of parameters enables the user to customize the procedure to a specific problem. The web server, which returns results in textual and graphical form, is useful for small to medium-scale applications, as well as for evaluation and parameter tuning in view of large-scale applications, requiring a local installation. The program written in C++ can be freely downloaded from ftp://ftp.epd.unil.ch/pub/software/unix/madap. The MADAP web server can be accessed at http://www.isrec.isb-sib.ch/madap/.

Workflows for intelligent monitoring using proxy services.

Grid technologies have proven to be very successful in the area of eScience, and in particular in healthcare applications. But while the applicability of workflow enacting tools for biomedical research has long since been proven, the practical adoption into regular clinical research has some additional challenges in grid context. In this paper, we investigate the case of data monitoring, and how to seamlessly implement the step between a one-time proof-of-concept workflow and high-performance on-line monitoring of data streams, as exemplified by the case of long-running clinical trials. We will present an approach based on proxy services that allows executing single-run workflows repeatedly with little overhead.

Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures.

INTRODUCTION: Breast cancer subtyping and prognosis have been studied extensively by gene expression profiling, resulting in disparate signatures with little overlap in their constituent genes. Although a previous study demonstrated a prognostic concordance among gene expression signatures, it was limited to only one dataset and did not fully elucidate how the different genes were related to one another nor did it examine the contribution of well-known biological processes of breast cancer tumorigenesis to their prognostic performance. METHOD: To address the above issues and to further validate these initial findings, we performed the largest meta-analysis of publicly available breast cancer gene expression and clinical data, which are comprised of 2,833 breast tumors. Gene coexpression modules of three key biological processes in breast cancer (namely, proliferation, estrogen receptor [ER], and HER2 signaling) were used to dissect the role of constituent genes of nine prognostic signatures. RESULTS: Using a meta-analytical approach, we consolidated the signatures associated with ER signaling, ERBB2 amplification, and proliferation. Previously published expression-based nomenclature of breast cancer 'intrinsic' subtypes can be mapped to the three modules, namely, the ER-/HER2- (basal-like), the HER2+ (HER2-like), and the low- and high-proliferation ER+/HER2- subtypes (luminal A and B). We showed that all nine prognostic signatures exhibited a similar prognostic performance in the entire dataset. Their prognostic abilities are due mostly to the detection of proliferation activity. Although ER- status (basal-like) and ERBB2+ expression status correspond to bad outcome, they seem to act through elevated expression of proliferation genes and thus contain only indirect information about prognosis. Clinical variables measuring the extent of tumor progression, such as tumor size and nodal status, still add independent prognostic information to proliferation genes. CONCLUSION: This meta-analysis unifies various results of previous gene expression studies in breast cancer. It reveals connections between traditional prognostic factors, expression-based subtyping, and prognostic signatures, highlighting the important role of proliferation in breast cancer prognosis.

Exhaustive search for epistatic effects on the human methylome.

Studies assessing the existence and magnitude of epistatic effects on complex human traits provide inconclusive results. The study of such effects is complicated by considerable increase in computational burden, model complexity, and model uncertainty, which in concert decrease model stability. An additional source introducing significant uncertainty with regard to the detection of robust epistasis is the biological distance between the genetic variation and the trait under study. Here we studied CpG methylation, a genetically complex molecular trait that is particularly close to genomic variation, and performed an exhaustive search for two-locus epistatic effects on the CpG-methylation signal in two cohorts of healthy young subjects. We detected robust epistatic effects for a small number of CpGs (N = 404). Our results indicate that epistatic effects explain only a minor part of variation in DNA-CpG methylation. Interestingly, these CpGs were more likely to be associated with gene-expression of nearby genes, as also shown by their overrepresentation in DNase I hypersensitivity sites and underrepresentation in CpG islands. Finally, gene ontology analysis showed a significant enrichment of these CpGs in pathways related to HPV-infection and cancer.

The FAIR Guiding Principles for scientific data management and stewardship.

There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders-representing academia, industry, funding agencies, and scholarly publishers-have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.

Making sense of big data in health research: Towards an EU action plan.

Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health and healthcare for all Europeans.

Changes in the transcriptional profile of transporters in the intestine along the anterior-posterior and crypt-villus axes.

BACKGROUND: The purpose of this work was to characterize the expression of drug and nutrient carriers along the anterior-posterior and crypt-villus axes of the intestinal epithelium and to study the validity of utilizing whole gut tissue rather than purified epithelial cells to examine regional variations in gene expression. RESULTS: We have characterized the mRNA expression profiles of 76 % of all currently known transporters along the anterior-posterior axis of the gut. This is the first study to describe the expression profiles of the majority of all known transporters in the intestine. The expression profiles of transporters, as defined according to the Gene Ontology consortium, were measured in whole tissue of the murine duodenum, jejunum, ileum and colon using high-density microarrays. For nine transporters (Abca1, Abcc1, Abcc3, Abcg8, Slc10a2, Slc28a2, Slc2a1, Slc34a2 and Slc5a8), the mRNA profiles were further measured by RT-PCR in laser micro-dissected crypt and villus epithelial cells corresponding to the aforementioned intestinal regions. With respect to differentially regulated transporters, the colon had a distinct expression profile from small intestinal segments. The majority (59 % for p cutoff < or = 0.05) of transporter mRNA levels were constant across the intestinal sections studied. For the transporter subclass "carrier activity", which contains the majority of known carriers for biologically active compounds, a significant change (p < or = 0.05) along the anterior-posterior axis was observed. CONCLUSION: All nine transporters examined in laser-dissected material demonstrated good replication of the region-specific profiles revealed by microarray. Furthermore, we suggest that the distribution characteristics of Slc5a8 along the intestinal tract render it a suitable candidate carrier for monocarboxylate drugs in the posterior portion of the intestine. Our findings also predict that there is a significant difference in the absorption of carrier-mediated compounds in the different intestinal segments. The most pronounced differences can be expected between the adjoining segments ileum and colon, but the differences between the other adjoining segments are not negligible. Finally, for the examined genes, profiles measured in whole intestinal tissue extracts are representative of epithelial cell-only gene expression.

Comparative transcriptomics in East African cichlids reveals sex- and species-specific expression and new candidates for sex differentiation in fishes.

Males and females of the same species differ largely in gene expression, which accounts for most of the morphological and physiological differences and sex-specific phenotypes. Here, we analyzed sex-specific gene expression in the brain and the gonads of cichlid fishes from Lake Tanganyika belonging to four different lineages, so-called tribes (Eretmodini, Ectodini, Haplochromini, and Lamprologini), using the outgroup Nile tilapia (Oreochromis niloticus) as reference. The comparison between male and female brains revealed few differences between the sexes, consistent in all investigated species. The gonads, on the other hand, showed a large fraction of differentially expressed transcripts with the majority of them showing the same direction of expression in all four species. All here-studied cichlids, especially the three investigated mouth-breeding species, showed a trend toward more male- than female biased transcripts. Transcripts, which were female-biased in expression in all four species, were overrepresented on linkage group (LG)1 in the reference genome and common male-biased transcripts showed accumulation on LG23, the presumable sex chromosomes of the Nile tilapia. Sex-specific transcripts contained candidate genes for sex determination and differentiation in fishes,especially members of the transforming growth factor-b-superfamily and the Wnt-pathway and also prominent members of the sox-, dm-domain-, and high mobility group-box families. We further confirmed our previous finding on species/lineage-specific gene expression shifts in the sex steroid pathway, including synthesizing enzymes as the aromatase cyp19a1 and estrogen and androgen receptors.

FOXQ1, a novel target of the Wnt pathway and a new marker for activation of Wnt signaling in solid tumors.

BACKGROUND: The forkhead box transcription factor FOXQ1 has been shown to be upregulated in colorectal cancer (CRC) and metastatic breast cancer and involved in tumor development, epithelial-mesenchymal transition and chemoresistance. Yet, its transcriptional regulation is still unknown. METHODS: FOXQ1 mRNA and protein expression were analysed in a panel of CRC cell lines, and laser micro-dissected human biopsy samples by qRT-PCR, microarray GeneChip® U133 Plus 2.0 and western blots. FOXQ1 regulation was assayed by chromatin immunoprecipitation and luciferase reporter assays. RESULTS: FOXQ1 was robustly induced in CRC compared to other tumors, but had no predictive value with regards to grade, metastasis and survival in CRC. Prototype-based gene coexpression and gene set enrichment analysis showed a significant association between FOXQ1 and the Wnt pathway in tumors and cancer cell lines from different tissues. In vitro experiments confirmed, on a molecular level, FOXQ1 as a direct Wnt target. Analysis of known Wnt targets identified FOXQ1 as the most suitable marker for canonical Wnt activation across a wide panel of cell lines derived from different tissues. CONCLUSIONS: Our data show that FOXQ1 is one of the most over-expressed genes in CRC and a direct target of the canonical Wnt pathway. It is a potential new marker for detection of early CRC and Wnt activation in tumors of different origins.

EuroDia: a beta-cell gene expression resource.

Type 2 diabetes mellitus (T2DM) is a major disease affecting nearly 280 million people worldwide. Whilst the pathophysiological mechanisms leading to disease are poorly understood, dysfunction of the insulin-producing pancreatic beta-cells is key event for disease development. Monitoring the gene expression profiles of pancreatic beta-cells under several genetic or chemical perturbations has shed light on genes and pathways involved in T2DM. The EuroDia database has been established to build a unique collection of gene expression measurements performed on beta-cells of three organisms, namely human, mouse and rat. The Gene Expression Data Analysis Interface (GEDAI) has been developed to support this database. The quality of each dataset is assessed by a series of quality control procedures to detect putative hybridization outliers. The system integrates a web interface to several standard analysis functions from R/Bioconductor to identify differentially expressed genes and pathways. It also allows the combination of multiple experiments performed on different array platforms of the same technology. The design of this system enables each user to rapidly design a custom analysis pipeline and thus produce their own list of genes and pathways. Raw and normalized data can be downloaded for each experiment. The flexible engine of this database (GEDAI) is currently used to handle gene expression data from several laboratory-run projects dealing with different organisms and platforms. Database URL: http://eurodia.vital-it.ch.

CYR61 and alphaVbeta5 integrin cooperate to promote invasion and metastasis of tumors growing in preirradiated stroma.

Radiotherapy is widely used to treat human cancer. Patients locally recurring after radiotherapy, however, have increased risk of metastatic progression and poor prognosis. The clinical management of postradiation recurrences remains an unresolved issue. Tumors growing in preirradiated tissues have an increased fraction of hypoxic cells and are more metastatic, a condition known as tumor bed effect. The transcription factor hypoxia inducible factor (HIF)-1 promotes invasion and metastasis of hypoxic tumors, but its role in the tumor bed effect has not been reported. Here, we show that tumor cells derived from SCCVII and HCT116 tumors growing in a preirradiated bed, or selected in vitro through repeated cycles of severe hypoxia, retain invasive and metastatic capacities when returned to normoxia. HIF activity, although facilitating metastatic spreading of tumors growing in a preirradiated bed, is not essential. Through gene expression profiling and gain- and loss-of-function experiments, we identified the matricellular protein CYR61 and alphaVbeta5 integrin as proteins cooperating to mediate these effects. The anti-alphaV integrin monoclonal antibody 17E6 and the small molecular alphaVbeta3/alphaVbeta5 integrin inhibitor EMD121974 suppressed invasion and metastasis induced by CYR61 and attenuated metastasis of tumors growing within a preirradiated field. These results represent a conceptual advance to the understanding of the tumor bed effect and identify CYR61 and alphaVbeta5 integrin as proteins that cooperate to mediate metastasis. They also identify alphaV integrin inhibition as a potential therapeutic approach for preventing metastasis in patients at risk for postradiation recurrences.

Mutant huntingtin's effects on striatal gene expression in mice recapitulate changes observed in human Huntington's disease brain and do not differ with mutant huntingtin length or wild-type huntingtin dosage.

To test the hypotheses that mutant huntingtin protein length and wild-type huntingtin dosage have important effects on disease-related transcriptional dysfunction, we compared the changes in mRNA in seven genetic mouse models of Huntington's disease (HD) and postmortem human HD caudate. Transgenic models expressing short N-terminal fragments of mutant huntingtin (R6/1 and R6/2 mice) exhibited the most rapid effects on gene expression, consistent with previous studies. Although changes in the brains of knock-in and full-length transgenic models of HD took longer to appear, 15- and 22-month CHL2(Q150/Q150), 18-month Hdh(Q92/Q92) and 2-year-old YAC128 animals also exhibited significant HD-like mRNA signatures. Whereas it was expected that the expression of full-length huntingtin transprotein might result in unique gene expression changes compared with those caused by the expression of an N-terminal huntingtin fragment, no discernable differences between full-length and fragment models were detected. In addition, very high correlations between the signatures of mice expressing normal levels of wild-type huntingtin and mice in which the wild-type protein is absent suggest a limited effect of the wild-type protein to change basal gene expression or to influence the qualitative disease-related effect of mutant huntingtin. The combined analysis of mouse and human HD transcriptomes provides important temporal and mechanistic insights into the process by which mutant huntingtin kills striatal neurons. In addition, the discovery that several available lines of HD mice faithfully recapitulate the gene expression signature of the human disorder provides a novel aspect of validation with respect to their use in preclinical therapeutic trials.

Regional and cellular gene expression changes in human Huntington's disease brain.

Huntington's disease (HD) pathology is well understood at a histological level but a comprehensive molecular analysis of the effect of the disease in the human brain has not previously been available. To elucidate the molecular phenotype of HD on a genome-wide scale, we compared mRNA profiles from 44 human HD brains with those from 36 unaffected controls using microarray analysis. Four brain regions were analyzed: caudate nucleus, cerebellum, prefrontal association cortex [Brodmann's area 9 (BA9)] and motor cortex [Brodmann's area 4 (BA4)]. The greatest number and magnitude of differentially expressed mRNAs were detected in the caudate nucleus, followed by motor cortex, then cerebellum. Thus, the molecular phenotype of HD generally parallels established neuropathology. Surprisingly, no mRNA changes were detected in prefrontal association cortex, thereby revealing subtleties of pathology not previously disclosed by histological methods. To establish that the observed changes were not simply the result of cell loss, we examined mRNA levels in laser-capture microdissected neurons from Grade 1 HD caudate compared to control. These analyses confirmed changes in expression seen in tissue homogenates; we thus conclude that mRNA changes are not attributable to cell loss alone. These data from bona fide HD brains comprise an important reference for hypotheses related to HD and other neurodegenerative diseases.