Comprehensive Genomic Characterization of Long Non-coding RNAs across Human Cancers.

The discovery of long non-coding RNA (lncRNA) has dramatically altered our understanding of cancer. Here, we describe a comprehensive analysis of lncRNA alterations at transcriptional, genomic, and epigenetic levels in 5,037 human tumor specimens across 13 cancer types from The Cancer Genome Atlas. Our results suggest that the expression and dysregulation of lncRNAs are highly cancer type specific compared with protein-coding genes. Using the integrative data generated by this analysis, we present a clinically guided small interfering RNA screening strategy and a co-expression analysis approach to identify cancer driver lncRNAs and predict their functions. This provides a resource for investigating lncRNAs in cancer and lays the groundwork for the development of new diagnostics and treatments.

Mercury analysis in hair: comparability and quality assessment within the transnational COPHES/DEMOCOPHES project

Human biomonitoring (HBM) is an effective tool for assessing actual exposure to chemicals that takes into account all routes of intake. Although hair analysis is considered to be an optimal biomarker for assessing mercury exposure, the lack of harmonization as regards sampling and analytical procedures has often limited the comparison of data at national and international level. The European-funded projects COPHES and DEMOCOPHES developed and tested a harmonized European approach to Human Biomonitoring in response to the European Environment and Health Action Plan. Herein we describe the quality assurance program (QAP) for assessing mercury levels in hair samples from more than 1800 mother-child pairs recruited in 17 European countries. To ensure the comparability of the results, standard operating procedures (SOPs) for sampling and for mercury analysis were drafted and distributed to participating laboratories. Training sessions were organized for field workers and four external quality-assessment exercises (ICI/EQUAS), followed by the corresponding web conferences, were organized between March 2011 and February 2012. ICI/EQUAS used native hair samples at two mercury concentration ranges (0.20-0.71 and 0.80-1.63) per exercise. The results revealed relative standard deviations of 7.87-13.55% and 4.04-11.31% for the low and high mercury concentration ranges, respectively. A total of 16 out of 18 participating laboratories the QAP requirements and were allowed to analyze samples from the DEMOCOPHES pilot study. Web conferences after each ICI/EQUAS revealed this to be a new and effective tool for improving analytical performance and increasing capacity building. The procedure developed and tested in COPHES/DEMOCOPHES would be optimal for application on a global scale as regards implementation of the Minamata Convention on Mercury.

Genome-wide enrichment analysis between endometriosis and obesity-related traits reveals novel susceptibility loci.

Endometriosis is a chronic inflammatory condition in women that results in pelvic pain and subfertility, and has been associated with decreased body mass index (BMI). Genetic variants contributing to the heritable component have started to emerge from genome-wide association studies (GWAS), although the majority remain unknown. Unexpectedly, we observed an intergenic locus on 7p15.2 that was genome-wide significantly associated with both endometriosis and fat distribution (waist-to-hip ratio adjusted for BMI; WHRadjBMI) in an independent meta-GWAS of European ancestry individuals. This led us to investigate the potential overlap in genetic variants underlying the aetiology of endometriosis, WHRadjBMI and BMI using GWAS data. Our analyses demonstrated significant enrichment of common variants between fat distribution and endometriosis (P = 3.7 × 10(-3)), which was stronger when we restricted the investigation to more severe (Stage B) cases (P = 4.5 × 10(-4)). However, no genetic enrichment was observed between endometriosis and BMI (P = 0.79). In addition to 7p15.2, we identify four more variants with statistically significant evidence of involvement in both endometriosis and WHRadjBMI (in/near KIFAP3, CAB39L, WNT4, GRB14); two of these, KIFAP3 and CAB39L, are novel associations for both traits. KIFAP3, WNT4 and 7p15.2 are associated with the WNT signalling pathway; formal pathway analysis confirmed a statistically significant (P = 6.41 × 10(-4)) overrepresentation of shared associations in developmental processes/WNT signalling between the two traits. Our results demonstrate an example of potential biological pleiotropy that was hitherto unknown, and represent an opportunity for functional follow-up of loci and further cross-phenotype comparisons to assess how fat distribution and endometriosis pathogenesis research fields can inform each other.

Functional impact of genetic variation on gene expression

Numerous links between genetic variants and phenotypes are known and genome-wide association studies dramatically increased the number of genetic variants associated with traits during the last decade. However, how changes in the DNA perturb the molecular mechanisms and impact on the phenotype of an organism remains elusive. Studies suggest that many traitassociated variants are in the non-coding region of the genome and probably act through regulation of gene expression. During my thesis I investigated how genetic variants affect gene expression through gene regulatory mechanisms. The first chapter was a collaborative project with a pharmaceutical company, where we investigated genome-wide copy number variation (CNVs) among Cynomolgus monkeys (Macaca fascicularis) used in pharmaceutical studies, and associated them to changes in gene expression. We found substantial copy number variation and identified CNVs linked to tissue-specific expression changes of proximal genes. The second and third chapters focus on genetic variation in humans and its effects on gene regulatory mechanisms and gene expression. The second chapter studies two human trios, where the allelic effects of genetic variation on genome-wide gene expression, protein-DNA binding and chromatin modifications were investigated. We found abundant allele specific activity across all measured molecular phenotypes and show extended coordinated behavior among them. In the third chapter, we investigated the impact of genetic variation on these phenotypes in 47 unrelated individuals. We found that chromatin phenotypes are organized into local variable modules, often linked to genetic variation and gene expression. Our results suggest that chromatin variation emerges as a result of perturbations of cis-regulatory elements by genetic variants, leading to gene expression changes. The work of this thesis provides novel insights into how genetic variation impacts gene expression by perturbing regulatory mechanisms. -- De nombreux liens entre variations génétiques et phénotypes sont connus. Les études d'association pangénomique ont considérablement permis d'augmenter le nombre de variations génétiques associées à des phénotypes au cours de la dernière décennie. Cependant, comprendre comment ces changements perturbent les mécanismes moléculaires et affectent le phénotype d'un organisme nous échappe encore. Des études suggèrent que de nombreuses variations, associées à des phénotypes, sont situées dans les régions non codantes du génome et sont susceptibles d'agir en modifiant la régulation d'expression des gènes. Au cours de ma thèse, j'ai étudié comment les variations génétiques affectent les niveaux d'expression des gènes en perturbant les mécanismes de régulation de leur expression. Le travail présenté dans le premier chapitre est un projet en collaboration avec une société pharmaceutique. Nous avons étudié les variations en nombre de copies (CNV) présentes chez le macaque crabier (Macaca fascicularis) qui est utilisé dans les études pharmaceutiques, et nous les avons associées avec des changements d'expression des gènes. Nous avons découvert qu'il existe une variabilité substantielle du nombre de copies et nous avons identifié des CNVs liées aux changements d'expression des gènes situés dans leur voisinage. Ces associations sont présentes ou absentes de manière spécifique dans certains tissus. Les deuxième et troisième chapitres se concentrent sur les variations génétiques dans les populations humaines et leurs effets sur les mécanismes de régulation des gènes et leur expression. Le premier se penche sur deux trios humains, père, mère, enfant, au sein duquel nous avons étudié les effets alléliques des variations génétiques sur l'expression des gènes, les liaisons protéine-ADN et les modifications de la chromatine. Nous avons découvert que l'activité spécifique des allèles est abondante abonde dans tous ces phénotypes moléculaires et nous avons démontré que ces derniers ont un comportement coordonné entre eux. Dans le second, nous avons examiné l'impact des variations génétiques de ces phénotypes moléculaires chez 47 individus, sans lien de parenté. Nous avons observé que les phénotypes de la chromatine sont organisés en modules locaux, qui sont liés aux variations génétiques et à l'expression des gènes. Nos résultats suggèrent que la variabilité de la chromatine est due à des variations génétiques qui perturbent des éléments cis-régulateurs, et peut conduire à des changements dans l'expression des gènes. Le travail présenté dans cette thèse fournit de nouvelles pistes pour comprendre l'impact des différentes variations génétiques sur l'expression des gènes à travers les mécanismes de régulation.

Characterisation of anatomical properties of the human basal ganglia using magnetic resonance imaging

The detailed in-vivo characterization of subcortical brain structures is essential not only to understand the basic organizational principles of the healthy brain but also for the study of the involvement of the basal ganglia in brain disorders. The particular tissue properties of basal ganglia - most importantly their high iron content, strongly affect the contrast of magnetic resonance imaging (MRI) images, hampering the accurate automated assessment of these regions. This technical challenge explains the substantial controversy in the literature about the magnitude, directionality and neurobiological interpretation of basal ganglia structural changes estimated from MRI and computational anatomy techniques. My scientific project addresses the pertinent need for accurate automated delineation of basal ganglia using two complementary strategies: ? Empirical testing of the utility of novel imaging protocols to provide superior contrast in the basal ganglia and to quantify brain tissue properties; ? Improvement of the algorithms for the reliable automated detection of basal ganglia and thalamus Previous research demonstrated that MRI protocols based on magnetization transfer (MT) saturation maps provide optimal grey-white matter contrast in subcortical structures compared with the widely used Tl-weighted (Tlw) images (Helms et al., 2009). Under the assumption of a direct impact of brain tissue properties on MR contrast my first study addressed the question of the mechanisms underlying the regional specificities effect of the basal ganglia. I used established whole-brain voxel-based methods to test for grey matter volume differences between MT and Tlw imaging protocols with an emphasis on subcortical structures. I applied a regression model to explain the observed grey matter differences from the regionally specific impact of brain tissue properties on the MR contrast. The results of my first project prompted further methodological developments to create adequate priors for the basal ganglia and thalamus allowing optimal automated delineation of these structures in a probabilistic tissue classification framework. I established a standardized workflow for manual labelling of the basal ganglia, thalamus and cerebellar dentate to create new tissue probability maps from quantitative MR maps featuring optimal grey-white matter contrast in subcortical areas. The validation step of the new tissue priors included a comparison of the classification performance with the existing probability maps. In my third project I continued investigating the factors impacting automated brain tissue classification that result in interpretational shortcomings when using Tlw MRI data in the framework of computational anatomy. While the intensity in Tlw images is predominantly

Suitability of human and mammalian cells of different origin for the assessment of genotoxicity of metal and polymeric engineered nanoparticles.

Nanogenotoxicity is a crucial endpoint in safety testing of nanomaterials as it addresses potential mutagenicity, which has implications for risks of both genetic disease and carcinogenesis. Within the NanoTEST project, we investigated the genotoxic potential of well-characterised nanoparticles (NPs): titanium dioxide (TiO2) NPs of nominal size 20 nm, iron oxide (8 nm) both uncoated (U-Fe3O4) and oleic acid coated (OC-Fe3O4), rhodamine-labelled amorphous silica 25 (Fl-25 SiO2) and 50 nm (Fl-50 SiO) and polylactic glycolic acid polyethylene oxide polymeric NPs - as well as Endorem® as a negative control for detection of strand breaks and oxidised DNA lesions with the alkaline comet assay. Using primary cells and cell lines derived from blood (human lymphocytes and lymphoblastoid TK6 cells), vascular/central nervous system (human endothelial human cerebral endothelial cells), liver (rat hepatocytes and Kupffer cells), kidney (monkey Cos-1 and human HEK293 cells), lung (human bronchial 16HBE14o cells) and placenta (human BeWo b30), we were interested in which in vitro cell model is sufficient to detect positive (genotoxic) and negative (non-genotoxic) responses. All in vitro studies were harmonized, i.e. NPs from the same batch, and identical dispersion protocols (for TiO2 NPs, two dispersions were used), exposure time, concentration range, culture conditions and time-courses were used. The results from the statistical evaluation show that OC-Fe3O4 and TiO2 NPs are genotoxic in the experimental conditions used. When all NPs were included in the analysis, no differences were seen among cell lines - demonstrating the usefulness of the assay in all cells to identify genotoxic and non-genotoxic NPs. The TK6 cells, human lymphocytes, BeWo b30 and kidney cells seem to be the most reliable for detecting a dose-response.