MGMT methylation analysis of glioblastoma on the Infinium methylation BeadChip identifies two distinct CpG regions associated with gene silencing and outcome, yielding a prediction model for comparisons across datasets, tumor grades, and CIMP-status.

The methylation status of the O(6)-methylguanine-DNA methyltransferase (MGMT) gene is an important predictive biomarker for benefit from alkylating agent therapy in glioblastoma. Recent studies in anaplastic glioma suggest a prognostic value for MGMT methylation. Investigation of pathogenetic and epigenetic features of this intriguingly distinct behavior requires accurate MGMT classification to assess high throughput molecular databases. Promoter methylation-mediated gene silencing is strongly dependent on the location of the methylated CpGs, complicating classification. Using the HumanMethylation450 (HM-450K) BeadChip interrogating 176 CpGs annotated for the MGMT gene, with 14 located in the promoter, two distinct regions in the CpG island of the promoter were identified with high importance for gene silencing and outcome prediction. A logistic regression model (MGMT-STP27) comprising probes cg1243587 and cg12981137 provided good classification properties and prognostic value (kappa = 0.85; log-rank p < 0.001) using a training-set of 63 glioblastomas from homogenously treated patients, for whom MGMT methylation was previously shown to be predictive for outcome based on classification by methylation-specific PCR. MGMT-STP27 was successfully validated in an independent cohort of chemo-radiotherapy-treated glioblastoma patients (n = 50; kappa = 0.88; outcome, log-rank p < 0.001). Lower prevalence of MGMT methylation among CpG island methylator phenotype (CIMP) positive tumors was found in glioblastomas from The Cancer Genome Atlas than in low grade and anaplastic glioma cohorts, while in CIMP-negative gliomas MGMT was classified as methylated in approximately 50 % regardless of tumor grade. The proposed MGMT-STP27 prediction model allows mining of datasets derived on the HM-450K or HM-27K BeadChip to explore effects of distinct epigenetic context of MGMT methylation suspected to modulate treatment resistance in different tumor types.

Concordance among digital gene expression, microarrays, and qPCR when measuring differential expression of microRNAs.

Profiling microRNA (miRNA) expression is of widespread interest given the critical role of miRNAs in many cellular functions. Profiling can be achieved via hybridization-based (microarrays), sequencing-based, or amplification-based (quantitative reverse transcription-PCR, qPCR) technologies. Among these, microarrays face the significant challenge of accurately distinguishing between mature and immature miRNA forms, and different vendors have developed different methods to meet this challenge. Here we measure differential miRNA expression using the Affymetrix, Agilent, and Illumina microarray platforms, as well as qPCR (Applied Biosystems) and ultra high-throughput sequencing (Illumina). We show that the differential expression measurements are more divergent when the three types of microarrays are compared than when the Agilent microarray, qPCR, and sequencing technology measurements are compared, which exhibit a good overall concordance.

Rapid and sensitive hormonal profiling of complex plant samples by liquid chromatography coupled to electrospray ionization tandem mass spectrometry

Background Plant hormones play a pivotal role in several physiological processes during a plant's life cycle, from germination to senescence, and the determination of endogenous concentrations of hormones is essential to elucidate the role of a particular hormone in any physiological process. Availability of a sensitive and rapid method to quantify multiple classes of hormones simultaneously will greatly facilitate the investigation of signaling networks in controlling specific developmental pathways and physiological responses. Due to the presence of hormones at very low concentrations in plant tissues (10-9 M to 10-6 M) and their different chemistries, the development of a high-throughput and comprehensive method for the determination of hormones is challenging. Results The present work reports a rapid, specific and sensitive method using ultrahigh-performance liquid chromatography coupled to electrospray ionization tandem spectrometry (UPLC/ESI-MS/MS) to analyze quantitatively the major hormones found in plant tissues within six minutes, including auxins, cytokinins, gibberellins, abscisic acid, 1-amino-cyclopropane-1-carboxyic acid (the ethylene precursor), jasmonic acid and salicylic acid. Sample preparation, extraction procedures and UPLC-MS/MS conditions were optimized for the determination of all plant hormones and are summarized in a schematic extraction diagram for the analysis of small amounts of plant material without time-consuming additional steps such as purification, sample drying or re-suspension. Conclusions This new method is applicable to the analysis of dynamic changes in endogenous concentrations of hormones to study plant developmental processes or plant responses to biotic and abiotic stresses in complex tissues. An example is shown in which a hormone profiling is obtained from leaves of plants exposed to salt stress in the aromatic plant, Rosmarinus officinalis.

Pseudogenes in the ENCODE regions: consensus annotation, analysis of transcription, and evolution.

Arising from either retrotransposition or genomic duplication of functional genes, pseudogenes are "genomic fossils" valuable for exploring the dynamics and evolution of genes and genomes. Pseudogene identification is an important problem in computational genomics, and is also critical for obtaining an accurate picture of a genome's structure and function. However, no consensus computational scheme for defining and detecting pseudogenes has been developed thus far. As part of the ENCyclopedia Of DNA Elements (ENCODE) project, we have compared several distinct pseudogene annotation strategies and found that different approaches and parameters often resulted in rather distinct sets of pseudogenes. We subsequently developed a consensus approach for annotating pseudogenes (derived from protein coding genes) in the ENCODE regions, resulting in 201 pseudogenes, two-thirds of which originated from retrotransposition. A survey of orthologs for these pseudogenes in 28 vertebrate genomes showed that a significant fraction ( approximately 80%) of the processed pseudogenes are primate-specific sequences, highlighting the increasing retrotransposition activity in primates. Analysis of sequence conservation and variation also demonstrated that most pseudogenes evolve neutrally, and processed pseudogenes appear to have lost their coding potential immediately or soon after their emergence. In order to explore the functional implication of pseudogene prevalence, we have extensively examined the transcriptional activity of the ENCODE pseudogenes. We performed systematic series of pseudogene-specific RACE analyses. These, together with complementary evidence derived from tiling microarrays and high throughput sequencing, demonstrated that at least a fifth of the 201 pseudogenes are transcribed in one or more cell lines or tissues.

Applications of MALDI-TOF mass spectrometry in clinical diagnostic microbiology.

Until recently, microbial identification in clinical diagnostic laboratories has mainly relied on conventional phenotypic and gene sequencing identification techniques. The development of matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) devices has revolutionized the routine identification of microorganisms in clinical microbiology laboratories by introducing an easy, rapid, high throughput, low-cost, and efficient identification technique. This technology has been adapted to the constraint of clinical diagnostic laboratories and has the potential to replace and/or complement conventional identification techniques for both bacterial and fungal strains. Using standardized procedures, the resolution of MALDI-TOF MS allows accurate identification at the species level of most Gram-positive and Gram-negative bacterial strains with the exception of a few difficult strains that require more attention and further development of the method. Similarly, the routine identification by MALDI-TOF MS of yeast isolates is reliable and much quicker than conventional techniques. Recent studies have shown that MALDI-TOF MS has also the potential to accurately identify filamentous fungi and dermatophytes, providing that specific standardized procedures are established for these microorganisms. Moreover, MALDI-TOF MS has been used successfully for microbial typing and identification at the subspecies level, demonstrating that this technology is a potential efficient tool for epidemiological studies and for taxonomical classification.

Comparative modular analysis of gene expression in vertebrate development

The focus of my PhD research was the concept of modularity. In the last 15 years, modularity has become a classic term in different fields of biology. On the conceptual level, a module is a set of interacting elements that remain mostly independent from the elements outside of the module. I used modular analysis techniques to study gene expression evolution in vertebrates. In particular, I identified ``natural'' modules of gene expression in mouse and human, and I showed that expression of organ-specific and system-specific genes tends to be conserved between such distance vertebrates as mammals and fishes. Also with a modular approach, I studied patterns of developmental constraints on transcriptome evolution. I showed that none of the two commonly accepted models of the evolution of embryonic development (``evo-devo'') are exclusively valid. In particular, I found that the conservation of the sequences of regulatory regions is highest during mid-development of zebrafish, and thus it supports the ``hourglass model''. In contrast, events of gene duplication and new gene introduction are most rare in early development, which supports the ``early conservation model''. In addition to the biological insights on transcriptome evolution, I have also discussed in detail the advantages of modular approaches in large-scale data analysis. Moreover, I re-analyzed several studies (published in high-ranking journals), and showed that their conclusions do not hold out under a detailed analysis. This demonstrates that complex analysis of high-throughput data requires a co-operation between biologists, bioinformaticians, and statisticians.

Unexpected Role for Connexin37 in Circulating FVIII and Coagulation

The gap junction protein connexin37 (Cx37) plays an important role in cell-cell communication in the vasculature. Cx37 is expressed in endothelial cells, platelets and megakaryocytes. We have recently shown that Cx37 limits thrombus propensity by permitting intercellular signaling between aggregating platelets. Here, we have performed high throughput phage display to identify potential binding partners for the regulatory intracellular C-terminus of Cx37 (Cx37CT). We retrieved 2 consensus binding motifs for Cx37CT: WHK...[K,R]XP... and FH-K...[K,R]XXP.... Sequence alignment against the NCBI protein database indicated 66% homology of one the selected peptides with FVIII B-domain. We performed cross-linking reactions using BS3 and confirmed that an 11-mer peptide of the FVIII B-domain sequence linked to recombinant Cx37CT. In vitro binding of this peptide to Cx37CT was also confirmed by surface plasmon resonance. The dissociation constant of FVIII B-domain peptides to Cx37CT was ~20 uM. Other peptide sequences, designed upstream or downstream of the FVIII B-domain sequence, showed very low or no affinity for Cx37CT. Finally, in vivo studies revealed that thrombin generation in platelet-poor plasma from Cx37-/- mice (endogenous thrombin potential: 634±11 nM min, mean±SEM) was increased compared to Cx37+/+ mice (427±12, P<0.001). Moreover, partial activated thromboplastin time (aPTT) was shorter in Cx37-/- (39.7±1.5 s) than in Cx37+/+ mice (45.9±1.8, P=0.03), whereas prothrombin time was comparable. The shorter aPTT in Cx37-/- mice correlated with higher circulating FVIII activity (46.0±0.7 vs. 53.5±2.7 s for Cx37+/+, P=0.03). Overall, our data show for the first time a functional interaction between FVIII and Cx37. This interaction may be relevant for the control of FVIII secretion and, thereby, in the regulation of levels of FVIII circulating in blood. In addition, these results may open new perspectives to improve the efficiency of recombinant FVIII manufacturing.

Small-molecule inhibitor of USP7/HAUSP ubiquitin protease stabilizes and activates p53 in cells.

Deregulation of the ubiquitin/proteasome system has been implicated in the pathogenesis of many human diseases, including cancer. Ubiquitin-specific proteases (USP) are cysteine proteases involved in the deubiquitination of protein substrates. Functional connections between USP7 and essential viral proteins and oncogenic pathways, such as the p53/Mdm2 and phosphatidylinositol 3-kinase/protein kinase B networks, strongly suggest that the targeting of USP7 with small-molecule inhibitors may be useful for the treatment of cancers and viral diseases. Using high-throughput screening, we have discovered HBX 41,108, a small-molecule compound that inhibits USP7 deubiquitinating activity with an IC(50) in the submicromolar range. Kinetics data indicate an uncompetitive reversible inhibition mechanism. HBX 41,108 was shown to affect USP7-mediated p53 deubiquitination in vitro and in cells. As RNA interference-mediated USP7 silencing in cancer cells, HBX 41,108 treatment stabilized p53, activated the transcription of a p53 target gene without inducing genotoxic stress, and inhibited cancer cell growth. Finally, HBX 41,108 induced p53-dependent apoptosis as shown in p53 wild-type and null isogenic cancer cell lines. We thus report the identification of the first lead-like inhibitor against USP7, providing a structural basis for the development of new anticancer drugs.

Improving the prediction of the functional impact of cancer mutations by baseline tolerance transformation

High-throughput prioritization of cancer-causing mutations (drivers) is a key challenge of cancer genome projects, due to the number of somatic variants detected in tumors. One important step in this task is to assess the functional impact of tumor somatic mutations. A number of computational methods have been employed for that purpose, although most were originally developed to distinguish disease-related nonsynonymous single nucleotide variants (nsSNVs) from polymorphisms. Our new method, transformed Functional Impact score for Cancer (transFIC), improves the assessment of the functional impact of tumor nsSNVs by taking into account the baseline tolerance of genes to functional variants.

Practical considerations for improving the productivity of mass spectrometry-based proteomics.

Mass spectrometry (MS) is currently the most sensitive and selective analytical technique for routine peptide and protein structure analysis. Top-down proteomics is based on tandem mass spectrometry (MS/ MS) of intact proteins, where multiply charged precursor ions are fragmented in the gas phase, typically by electron transfer or electron capture dissociation, to yield sequence-specific fragment ions. This approach is primarily used for the study of protein isoforms, including localization of post-translational modifications and identification of splice variants. Bottom-up proteomics is utilized for routine high-throughput protein identification and quantitation from complex biological samples. The proteins are first enzymatically digested into small (usually less than ca. 3 kDa) peptides, these are identified by MS or MS/MS, usually employing collisional activation techniques. To overcome the limitations of these approaches while combining their benefits, middle-down proteomics has recently emerged. Here, the proteins are digested into long (3-15 kDa) peptides via restricted proteolysis followed by the MS/MS analysis of the obtained digest. With advancements of high-resolution MS and allied techniques, routine implementation of the middle-down approach has been made possible. Herein, we present the liquid chromatography (LC)-MS/MS-based experimental design of our middle-down proteomic workflow coupled with post-LC supercharging.

Networking of differentially expressed genes in human cancer cells resistant to methotrexate

BACKGROUND: The need for an integrated view of data obtained from high-throughput technologies gave rise to network analyses. These are especially useful to rationalize how external perturbations propagate through the expression of genes. To address this issue in the case of drug resistance, we constructed biological association networks of genes differentially expressed in cell lines resistant to methotrexate (MTX). METHODS: Seven cell lines representative of different types of cancer, including colon cancer (HT29 and Caco2), breast cancer (MCF-7 and MDA-MB-468), pancreatic cancer (MIA PaCa-2), erythroblastic leukemia (K562) and osteosarcoma (Saos-2), were used. The differential expression pattern between sensitive and MTX-resistant cells was determined by whole human genome microarrays and analyzed with the GeneSpring GX software package. Genes deregulated in common between the different cancer cell lines served to generate biological association networks using the Pathway Architect software. RESULTS: Dikkopf homolog-1 (DKK1) is a highly interconnected node in the network generated with genes in common between the two colon cancer cell lines, and functional validations of this target using small interfering RNAs (siRNAs) showed a chemosensitization toward MTX. Members of the UDP-glucuronosyltransferase 1A (UGT1A) family formed a network of genes differentially expressed in the two breast cancer cell lines. siRNA treatment against UGT1A also showed an increase in MTX sensitivity. Eukaryotic translation elongation factor 1 alpha 1 (EEF1A1) was overexpressed among the pancreatic cancer, leukemia and osteosarcoma cell lines, and siRNA treatment against EEF1A1 produced a chemosensitization toward MTX. CONCLUSIONS: Biological association networks identified DKK1, UGT1As and EEF1A1 as important gene nodes in MTX-resistance. Treatments using siRNA technology against these three genes showed chemosensitization toward MTX.

Quantify this! Report on a round table discussion on quantitative mass spectrometry in proteomics.

Following the success of the first round table in 2001, the Swiss Proteomic Society has organized two additional specific events during its last two meetings: a proteomic application exercise in 2002 and a round table in 2003. Such events have as their main objective to bring together, around a challenging topic in mass spectrometry, two groups of specialists, those who develop and commercialize mass spectrometry equipment and software, and expert MS users for peptidomics and proteomics studies. The first round table (Geneva, 2001) entitled "Challenges in Mass Spectrometry" was supported by brief oral presentations that stressed critical questions in the field of MS development or applications (Stöcklin and Binz, Proteomics 2002, 2, 825-827). Topics such as (i) direct analysis of complex biological samples, (ii) status and perspectives for MS investigations of noncovalent peptide-ligant interactions; (iii) is it more appropriate to have complementary instruments rather than a universal equipment, (iv) standardization and improvement of the MS signals for protein identification, (v) what would be the new generation of equipment and finally (vi) how to keep hardware and software adapted to MS up-to-date and accessible to all. For the SPS'02 meeting (Lausanne, 2002), a full session alternative event "Proteomic Application Exercise" was proposed. Two different samples were prepared and sent to the different participants: 100 micro g of snake venom (a complex mixture of peptides and proteins) and 10-20 micro g of almost pure recombinant polypeptide derived from the shrimp Penaeus vannamei carrying an heterogeneous post-translational modification (PTM). Among the 15 participants that received the samples blind, eight returned results and most of them were asked to present their results emphasizing the strategy, the manpower and the instrumentation used during the congress (Binz et. al., Proteomics 2003, 3, 1562-1566). It appeared that for the snake venom extract, the quality of the results was not particularly dependant on the strategy used, as all approaches allowed Lication of identification of a certain number of protein families. The genus of the snake was identified in most cases, but the species was ambiguous. Surprisingly, the precise identification of the recombinant almost pure polypeptides appeared to be much more complicated than expected as only one group reported the full sequence. Finally the SPS'03 meeting reported here included a round table on the difficult and challenging task of "Quantification by Mass Spectrometry", a discussion sustained by four selected oral presentations on the use of stable isotopes, electrospray ionization versus matrix-assisted laser desorption/ionization approaches to quantify peptides and proteins in biological fluids, the handling of differential two-dimensional liquid chromatography tandem mass spectrometry data resulting from high throughput experiments, and the quantitative analysis of PTMs. During these three events at the SPS meetings, the impressive quality and quantity of exchanges between the developers and providers of mass spectrometry equipment and software, expert users and the audience, were a key element for the success of these fruitful events and will have definitively paved the way for future round tables and challenging exercises at SPS meetings.

Computational and statistical analysis of copy number variants in normal and cancer genomes

AbstractAlthough the genomes from any two human individuals are more than 99.99% identical at the sequence level, some structural variation can be observed. Differences between genomes include single nucleotide polymorphism (SNP), inversion and copy number changes (gain or loss of DNA). The latter can range from submicroscopic events (CNVs, at least 1kb in size) to complete chromosomal aneuploidies. Small copy number variations have often no (lethal) consequences to the cell, but a few were associated to disease susceptibility and phenotypic variations. Larger re-arrangements (i.e. complete chromosome gain) are frequently associated with more severe consequences on health such as genomic disorders and cancer. High-throughput technologies like DNA microarrays enable the detection of CNVs in a genome-wide fashion. Since the initial catalogue of CNVs in the human genome in 2006, there has been tremendous interest in CNVs both in the context of population and medical genetics. Understanding CNV patterns within and between human populations is essential to elucidate their possible contribution to disease. But genome analysis is a challenging task; the technology evolves rapidly creating needs for novel, efficient and robust analytical tools which need to be compared with existing ones. Also, while the link between CNV and disease has been established, the relative CNV contribution is not fully understood and the predisposition to disease from CNVs of the general population has not been yet investigated.During my PhD thesis, I worked on several aspects related to CNVs. As l will report in chapter 3, ! was interested in computational methods to detect CNVs from the general population. I had access to the CoLaus dataset, a population-based study with more than 6,000 participants from the Lausanne area. All these individuals were analysed on SNP arrays and extensive clinical information were available. My work explored existing CNV detection methods and I developed a variety of metrics to compare their performance. Since these methods were not producing entirely satisfactory results, I implemented my own method which outperformed two existing methods. I also devised strategies to combine CNVs from different individuals into CNV regions.I was also interested in the clinical impact of CNVs in common disease (chapter 4). Through an international collaboration led by the Centre Hospitalier Universitaire Vaudois (CHUV) and the Imperial College London I was involved as a main data analyst in the investigation of a rare deletion at chromosome 16p11 detected in obese patients. Specifically, we compared 8,456 obese patients and 11,856 individuals from the general population and we found that the deletion was accounting for 0.7% of the morbid obesity cases and was absent in healthy non- obese controls. This highlights the importance of rare variants with strong impact and provides new insights in the design of clinical studies to identify the missing heritability in common disease.Furthermore, I was interested in the detection of somatic copy number alterations (SCNA) and their consequences in cancer (chapter 5). This project was a collaboration initiated by the Ludwig Institute for Cancer Research and involved other groups from the Swiss Institute of Bioinformatics, the CHUV and Universities of Lausanne and Geneva. The focus of my work was to identify genes with altered expression levels within somatic copy number alterations (SCNA) in seven metastatic melanoma ceil lines, using CGH and SNP arrays, RNA-seq, and karyotyping. Very few SCNA genes were shared by even two melanoma samples making it difficult to draw any conclusions at the individual gene level. To overcome this limitation, I used a network-guided analysis to determine whether any pathways, defined by amplified or deleted genes, were common among the samples. Six of the melanoma samples were potentially altered in four pathways and five samples harboured copy-number and expression changes in components of six pathways. In total, this approach identified 28 pathways. Validation with two external, large melanoma datasets confirmed all but three of the detected pathways and demonstrated the utility of network-guided approaches for both large and small datasets analysis.RésuméBien que le génome de deux individus soit similaire à plus de 99.99%, des différences de structure peuvent être observées. Ces différences incluent les polymorphismes simples de nucléotides, les inversions et les changements en nombre de copies (gain ou perte d'ADN). Ces derniers varient de petits événements dits sous-microscopiques (moins de 1kb en taille), appelés CNVs (copy number variants) jusqu'à des événements plus large pouvant affecter des chromosomes entiers. Les petites variations sont généralement sans conséquence pour la cellule, toutefois certaines ont été impliquées dans la prédisposition à certaines maladies, et à des variations phénotypiques dans la population générale. Les réarrangements plus grands (par exemple, une copie additionnelle d'un chromosome appelée communément trisomie) ont des répercutions plus grave pour la santé, comme par exemple dans certains syndromes génomiques et dans le cancer. Les technologies à haut-débit telle les puces à ADN permettent la détection de CNVs à l'échelle du génome humain. La cartographie en 2006 des CNV du génome humain, a suscité un fort intérêt en génétique des populations et en génétique médicale. La détection de différences au sein et entre plusieurs populations est un élément clef pour élucider la contribution possible des CNVs dans les maladies. Toutefois l'analyse du génome reste une tâche difficile, la technologie évolue très rapidement créant de nouveaux besoins pour le développement d'outils, l'amélioration des précédents, et la comparaison des différentes méthodes. De plus, si le lien entre CNV et maladie a été établit, leur contribution précise n'est pas encore comprise. De même que les études sur la prédisposition aux maladies par des CNVs détectés dans la population générale n'ont pas encore été réalisées.Pendant mon doctorat, je me suis concentré sur trois axes principaux ayant attrait aux CNV. Dans le chapitre 3, je détaille mes travaux sur les méthodes d'analyses des puces à ADN. J'ai eu accès aux données du projet CoLaus, une étude de la population de Lausanne. Dans cette étude, le génome de plus de 6000 individus a été analysé avec des puces SNP et de nombreuses informations cliniques ont été récoltées. Pendant mes travaux, j'ai utilisé et comparé plusieurs méthodes de détection des CNVs. Les résultats n'étant pas complètement satisfaisant, j'ai implémenté ma propre méthode qui donne de meilleures performances que deux des trois autres méthodes utilisées. Je me suis aussi intéressé aux stratégies pour combiner les CNVs de différents individus en régions.Je me suis aussi intéressé à l'impact clinique des CNVs dans le cas des maladies génétiques communes (chapitre 4). Ce projet fut possible grâce à une étroite collaboration avec le Centre Hospitalier Universitaire Vaudois (CHUV) et l'Impérial College à Londres. Dans ce projet, j'ai été l'un des analystes principaux et j'ai travaillé sur l'impact clinique d'une délétion rare du chromosome 16p11 présente chez des patients atteints d'obésité. Dans cette collaboration multidisciplinaire, nous avons comparés 8'456 patients atteint d'obésité et 11 '856 individus de la population générale. Nous avons trouvés que la délétion était impliquée dans 0.7% des cas d'obésité morbide et était absente chez les contrôles sains (non-atteint d'obésité). Notre étude illustre l'importance des CNVs rares qui peuvent avoir un impact clinique très important. De plus, ceci permet d'envisager une alternative aux études d'associations pour améliorer notre compréhension de l'étiologie des maladies génétiques communes.Egalement, j'ai travaillé sur la détection d'altérations somatiques en nombres de copies (SCNA) et de leurs conséquences pour le cancer (chapitre 5). Ce projet fut une collaboration initiée par l'Institut Ludwig de Recherche contre le Cancer et impliquant l'Institut Suisse de Bioinformatique, le CHUV et les Universités de Lausanne et Genève. Je me suis concentré sur l'identification de gènes affectés par des SCNAs et avec une sur- ou sous-expression dans des lignées cellulaires dérivées de mélanomes métastatiques. Les données utilisées ont été générées par des puces ADN (CGH et SNP) et du séquençage à haut débit du transcriptome. Mes recherches ont montrées que peu de gènes sont récurrents entre les mélanomes, ce qui rend difficile l'interprétation des résultats. Pour contourner ces limitations, j'ai utilisé une analyse de réseaux pour définir si des réseaux de signalisations enrichis en gènes amplifiés ou perdus, étaient communs aux différents échantillons. En fait, parmi les 28 réseaux détectés, quatre réseaux sont potentiellement dérégulés chez six mélanomes, et six réseaux supplémentaires sont affectés chez cinq mélanomes. La validation de ces résultats avec deux larges jeux de données publiques, a confirmée tous ces réseaux sauf trois. Ceci démontre l'utilité de cette approche pour l'analyse de petits et de larges jeux de données.Résumé grand publicL'avènement de la biologie moléculaire, en particulier ces dix dernières années, a révolutionné la recherche en génétique médicale. Grâce à la disponibilité du génome humain de référence dès 2001, de nouvelles technologies telles que les puces à ADN sont apparues et ont permis d'étudier le génome dans son ensemble avec une résolution dite sous-microscopique jusque-là impossible par les techniques traditionnelles de cytogénétique. Un des exemples les plus importants est l'étude des variations structurales du génome, en particulier l'étude du nombre de copies des gènes. Il était établi dès 1959 avec l'identification de la trisomie 21 par le professeur Jérôme Lejeune que le gain d'un chromosome supplémentaire était à l'origine de syndrome génétique avec des répercussions graves pour la santé du patient. Ces observations ont également été réalisées en oncologie sur les cellules cancéreuses qui accumulent fréquemment des aberrations en nombre de copies (telles que la perte ou le gain d'un ou plusieurs chromosomes). Dès 2004, plusieurs groupes de recherches ont répertorié des changements en nombre de copies dans des individus provenant de la population générale (c'est-à-dire sans symptômes cliniques visibles). En 2006, le Dr. Richard Redon a établi la première carte de variation en nombre de copies dans la population générale. Ces découvertes ont démontrées que les variations dans le génome était fréquentes et que la plupart d'entre elles étaient bénignes, c'est-à-dire sans conséquence clinique pour la santé de l'individu. Ceci a suscité un très grand intérêt pour comprendre les variations naturelles entre individus mais aussi pour mieux appréhender la prédisposition génétique à certaines maladies.Lors de ma thèse, j'ai développé de nouveaux outils informatiques pour l'analyse de puces à ADN dans le but de cartographier ces variations à l'échelle génomique. J'ai utilisé ces outils pour établir les variations dans la population suisse et je me suis consacré par la suite à l'étude de facteurs pouvant expliquer la prédisposition aux maladies telles que l'obésité. Cette étude en collaboration avec le Centre Hospitalier Universitaire Vaudois a permis l'identification d'une délétion sur le chromosome 16 expliquant 0.7% des cas d'obésité morbide. Cette étude a plusieurs répercussions. Tout d'abord elle permet d'effectuer le diagnostique chez les enfants à naître afin de déterminer leur prédisposition à l'obésité. Ensuite ce locus implique une vingtaine de gènes. Ceci permet de formuler de nouvelles hypothèses de travail et d'orienter la recherche afin d'améliorer notre compréhension de la maladie et l'espoir de découvrir un nouveau traitement Enfin notre étude fournit une alternative aux études d'association génétique qui n'ont eu jusqu'à présent qu'un succès mitigé.Dans la dernière partie de ma thèse, je me suis intéressé à l'analyse des aberrations en nombre de copies dans le cancer. Mon choix s'est porté sur l'étude de mélanomes, impliqués dans le cancer de la peau. Le mélanome est une tumeur très agressive, elle est responsable de 80% des décès des cancers de la peau et est souvent résistante aux traitements utilisés en oncologie (chimiothérapie, radiothérapie). Dans le cadre d'une collaboration entre l'Institut Ludwig de Recherche contre le Cancer, l'Institut Suisse de Bioinformatique, le CHUV et les universités de Lausanne et Genève, nous avons séquencés l'exome (les gènes) et le transcriptome (l'expression des gènes) de sept mélanomes métastatiques, effectués des analyses du nombre de copies par des puces à ADN et des caryotypes. Mes travaux ont permis le développement de nouvelles méthodes d'analyses adaptées au cancer, d'établir la liste des réseaux de signalisation cellulaire affectés de façon récurrente chez le mélanome et d'identifier deux cibles thérapeutiques potentielles jusqu'alors ignorées dans les cancers de la peau.

Comparison of five commercial serological tests for the detection of anti-Chlamydia trachomatis antibodies.

Screening for Chlamydia trachomatis-specific antibodies is valuable in investigating recurrent miscarriage, tubal infertility and extrauterine pregnancy. We compared here the performance of immunofluorescence (IF) to four other commercial tests in detecting IgG antibodies directed against C. trachomatis: two enzyme-linked immunosorbent assays (ELISAs) using the major outer membrane protein (MOMP) as the antigen, commercialised respectively by Medac and R-Biopharm (RB), one ELISA using the chlamydial heat shock protein 60 (cHSP60) as the antigen (Medac), as well as a new automated epifluorescence immunoassay (InoDiag). A total of 405 patients with (n = 251) and without (n = 154) miscarriages were tested by all five tests. The prevalence of C. trachomatis-specific IgG antibodies as determined by the IF, cHSP60-Medac, MOMP-Medac, MOMP-RB and InoDiag was 14.3, 23.2, 14.3, 11.9 and 26.2%, respectively. InoDiag exhibited the highest sensitivity, whereas MOMP-RB showed the best specificity. Cross-reactivity was observed with C. pneumoniae using IF, MOMP-RB and InoDiag, and Parachlamydia acanthamoebae using the cHSP60 ELISA test. No cross-reactivity was observed between C. trachomatis and the other Chlamydiales (Neochlamydia hartmannellae, Waddlia chondrophila and Simkania negevensis). Given its high sensitivity, the new automated epifluorescence immunoassay from InoDiag represents an interesting alternative. The MOMP-based ELISA of R-Biopharm should be preferred for large serological studies, given the high throughput of ELISA and its excellent specificity.

EADock : design of a new molecular docking algorithm and some of its applications

3 Summary 3. 1 English The pharmaceutical industry has been facing several challenges during the last years, and the optimization of their drug discovery pipeline is believed to be the only viable solution. High-throughput techniques do participate actively to this optimization, especially when complemented by computational approaches aiming at rationalizing the enormous amount of information that they can produce. In siiico techniques, such as virtual screening or rational drug design, are now routinely used to guide drug discovery. Both heavily rely on the prediction of the molecular interaction (docking) occurring between drug-like molecules and a therapeutically relevant target. Several softwares are available to this end, but despite the very promising picture drawn in most benchmarks, they still hold several hidden weaknesses. As pointed out in several recent reviews, the docking problem is far from being solved, and there is now a need for methods able to identify binding modes with a high accuracy, which is essential to reliably compute the binding free energy of the ligand. This quantity is directly linked to its affinity and can be related to its biological activity. Accurate docking algorithms are thus critical for both the discovery and the rational optimization of new drugs. In this thesis, a new docking software aiming at this goal is presented, EADock. It uses a hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with .the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 R around the center of mass of the ligand position in the crystal structure, and conversely to other benchmarks, our algorithms was fed with optimized ligand positions up to 10 A root mean square deviation 2MSD) from the crystal structure. This validation illustrates the efficiency of our sampling heuristic, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best-ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures in this benchmark could be explained by the presence of crystal contacts in the experimental structure. EADock has been used to understand molecular interactions involved in the regulation of the Na,K ATPase, and in the activation of the nuclear hormone peroxisome proliferatoractivated receptors a (PPARa). It also helped to understand the action of common pollutants (phthalates) on PPARy, and the impact of biotransformations of the anticancer drug Imatinib (Gleevec®) on its binding mode to the Bcr-Abl tyrosine kinase. Finally, a fragment-based rational drug design approach using EADock was developed, and led to the successful design of new peptidic ligands for the a5ß1 integrin, and for the human PPARa. In both cases, the designed peptides presented activities comparable to that of well-established ligands such as the anticancer drug Cilengitide and Wy14,643, respectively. 3.2 French Les récentes difficultés de l'industrie pharmaceutique ne semblent pouvoir se résoudre que par l'optimisation de leur processus de développement de médicaments. Cette dernière implique de plus en plus. de techniques dites "haut-débit", particulièrement efficaces lorsqu'elles sont couplées aux outils informatiques permettant de gérer la masse de données produite. Désormais, les approches in silico telles que le criblage virtuel ou la conception rationnelle de nouvelles molécules sont utilisées couramment. Toutes deux reposent sur la capacité à prédire les détails de l'interaction moléculaire entre une molécule ressemblant à un principe actif (PA) et une protéine cible ayant un intérêt thérapeutique. Les comparatifs de logiciels s'attaquant à cette prédiction sont flatteurs, mais plusieurs problèmes subsistent. La littérature récente tend à remettre en cause leur fiabilité, affirmant l'émergence .d'un besoin pour des approches plus précises du mode d'interaction. Cette précision est essentielle au calcul de l'énergie libre de liaison, qui est directement liée à l'affinité du PA potentiel pour la protéine cible, et indirectement liée à son activité biologique. Une prédiction précise est d'une importance toute particulière pour la découverte et l'optimisation de nouvelles molécules actives. Cette thèse présente un nouveau logiciel, EADock, mettant en avant une telle précision. Cet algorithme évolutionnaire hybride utilise deux pressions de sélections, combinées à une gestion de la diversité sophistiquée. EADock repose sur CHARMM pour les calculs d'énergie et la gestion des coordonnées atomiques. Sa validation a été effectuée sur 37 complexes protéine-ligand cristallisés, incluant 11 protéines différentes. L'espace de recherche a été étendu à une sphère de 151 de rayon autour du centre de masse du ligand cristallisé, et contrairement aux comparatifs habituels, l'algorithme est parti de solutions optimisées présentant un RMSD jusqu'à 10 R par rapport à la structure cristalline. Cette validation a permis de mettre en évidence l'efficacité de notre heuristique de recherche car des modes d'interactions présentant un RMSD inférieur à 2 R par rapport à la structure cristalline ont été classés premier pour 68% des complexes. Lorsque les cinq meilleures solutions sont prises en compte, le taux de succès grimpe à 78%, et 92% lorsque la totalité de la dernière génération est prise en compte. La plupart des erreurs de prédiction sont imputables à la présence de contacts cristallins. Depuis, EADock a été utilisé pour comprendre les mécanismes moléculaires impliqués dans la régulation de la Na,K ATPase et dans l'activation du peroxisome proliferatoractivated receptor a (PPARa). Il a également permis de décrire l'interaction de polluants couramment rencontrés sur PPARy, ainsi que l'influence de la métabolisation de l'Imatinib (PA anticancéreux) sur la fixation à la kinase Bcr-Abl. Une approche basée sur la prédiction des interactions de fragments moléculaires avec protéine cible est également proposée. Elle a permis la découverte de nouveaux ligands peptidiques de PPARa et de l'intégrine a5ß1. Dans les deux cas, l'activité de ces nouveaux peptides est comparable à celles de ligands bien établis, comme le Wy14,643 pour le premier, et le Cilengitide (PA anticancéreux) pour la seconde.