No description available.

Suicidal behavior represents the most severe, yet inherently preventable, outcome of psychiatric disease. Despite tremendous efforts to improve the awareness and treatment of psychiatric illness, suicidal behavior rates have been on the rise. The greatest challenge to confronting this crisis is the effective identification and treatment of those at risk for suicide. This challenge has been difficult to address due, in part, to the lack of a clear biological basis for suicidal behavior. Toward addressing this knowledge gap, evidence has been identified of a significant heritable component to suicidal behavior. Subsequent genetic research efforts have focused on the examination of common sites of genetic variation within candidate genes and throughout the genome. These efforts have identified many potentially important risk loci, but the majority of the risk expected to arise from genetic variation remains unexplained by current data. The primary objective of this dissertation was to examine the contribution of largely unexplored rare and potentially damaging genetic variation within suicidal behavior. To do this, targeted next-generation sequencing approaches were employed within a cohort of individuals diagnosed with bipolar disorder, a group particularly enriched for suicidal behavior. Sequence data was generated that examined essentially all protein-coding regions of the human genome (“exome”), with expanded sequencing around and within candidate genes hypothesized to play a role in suicidal behavior risk. The secondary objective of this dissertation focused on the assessment of rare variation within bipolar disorder through sequenced pedigrees and followup in a large collaborative bipolar disorder versus normal control sequencing dataset. These objectives were addressed through the thoughtful application of diverse and complimentary methods. These methods were selected to investigate individual variants, genes, and biological pathways. This approach offered examinations of the potential impact of rare genetic variation within focused regions and across complex biological process pathways that could be disrupted through damaging variation in many different genes. The presented efforts represent the largest examinations of rare functional variation with suicidal behavior and bipolar disorder performed, to date. No individual variant or gene survived correction for multiple testing for either phenotype. These results are consistent with other initial sequencing efforts in complex psychiatric phenotypes, offering conclusions that larger samples will likely be required to identify significant associations for single variants and genes. Within pathway analyses, however, we identified a significant enrichment of rare damaging variation that segregated within bipolar disorder pedigrees in genes that have been implicated in de novo studies of autism. This finding was further replicated within three large case/control sequencing samples, providing support to emerging evidence of a potential overlap of risk loci for autism and bipolar disorder. Many additional results approached significance that bear further consideration. These results offer potential candidate genes and pathways that could be utilized in future sequencing efforts for suicidal behavior and bipolar disorder. In addition, highly valuable resources in the form of datasets strongly enriched for novel rare loci were produced that can significantly contribute to ongoing efforts to investigate bipolar disorder and suicidal behavior. These data can be used in combination with other emerging datasets to generate more powerful meta- and mega-analyses to confidently identify risk loci for both phenotypes.

This work helps to determine the extent of immune system involvement in the adaptive response to subacute ruminal acidosis (SARA) in three parts. The first (Chapter 2) uses non-lactating cows to study specific changes in inflammatory protein expression in which SARA is created. The second (Chapter 3), uses the same model as Chapter 2. However, in this case, lactating cows are used to help establish the time course for adaptation to acidosis. The third part (Chapter 4) delineates the genomic changes that occur in the rumen epithelium when a therapeutic intervention is introduced using exogenous supplemental butyrate. In the first experiment, the expression of the extracellular matrix (ECM) proteins type IV collagen and laminin β1 decreased, and the monocarboxylate transporter MCT1, increased during the acidotic challenge. Nuclear factor of activated T-cells, NFATc2, and tumour necrosis factor alpha (TNF-α) decreased while interleukin-1 beta (IL-1β) increased during the experimental treatment period. Chapter 3 measured lipopolysaccharide (LPS) and its carrier, LPS binding protein, LBP, which were found to be elevated due to SARA. Moreover, NFATc2 was reduced during this period. Exogenous butyrate resulted in increased plasma LBP, plasma beta hydroxyl butyrate (BHBA), and ruminal butyrate. Milk parameters (total protein and fat) were unaffected by treatment, as were rumen LPS, acetate, valerate, isovalerate, and isobutyrate. Moreover, exogenous butyrate increased gene transcription of genes involved in non-specific host defences (NHSD) such as mucin, and remodelling (RM), such as matrix metallopeptidase 16 (MMP16), and decreased the transcription of genes of the immune response (IR), such as nuclear factor kappa B2 (NFκB2). Together, these three experiments have demonstrated that although wound healing is mediated by the immune system in more severe models of epithelial damage, our model of SARA did not involve full-thickness, penetrating lesions and hence did not involve the systemic immune system to such a degree than was previously thought. In addition, we were able to demonstrate that the addition of butyrate to this model of grain-induced acidosis was beneficial, as it decreased the local inflammatory response and helped the epithelium adapt to its harsher environment. / Agriculture and Agri-Food Canada, the National Sciences and Engineering Council of Canada (NSERC), the Ontario Ministry of Agriculture, Food and Rural Affairs (OMAFRA), the Canadian Dairy Commission (CDC), and the Dairy Farmers of Ontario (DFO).

abstract: Given the process of tumorigenesis, biological signaling pathways have become of interest in the field of oncology. Many of the regulatory mechanisms that are altered in cancer are directly related to signal transduction and cellular communication. Thus, identifying signaling pathways that have become deregulated may provide useful information to better understanding altered regulatory mechanisms within cancer. Many methods that have been created to measure the distinct activity of signaling pathways have relied strictly upon transcription profiles. With advancements in comparative genomic hybridization techniques, copy number data has become extremely useful in providing valuable information pertaining to the genomic landscape of cancer. The purpose of this thesis is to develop a methodology that incorporates both gene expression and copy number data to identify signaling pathways that have become deregulated in cancer. The central idea is that copy number data may significantly assist in identifying signaling pathway deregulation by justifying the aberrant activity being measured in gene expression profiles. This method was then applied to four different subtypes of breast cancer resulting in the identification of signaling pathways associated with distinct functionalities for each of the breast cancer subtypes. / Dissertation/Thesis / M.S. Computer Science 2011

No description available.

Résumé : L’adénocarcinome colorectal est parmi les plus importants cancers au Canada en terme de mortalité et morbidité. Cependant, nous n’en connaissons encore que peu, entres autres sur les voies cellulaires importantes et les protéines présentant un potentiel comme biomarqueur. Cette étude fut divisée en deux sous-projets. Sous-projet A. Il n’y a présentement aucun biomarqueur permettant de prédire la réponse à la radiothérapie comme modalité de traitement pour le cancer colorectal. Le but de ce sous-projet était de mettre au point les méthodes permettant d’effectuer une étude prospective ou rétrospective par spectrométrie de masse sur la réponse à la radiothérapie en utilisant des échantillons de tissu de patient. Des échantillons de tissu de souris et de tissu humains anonymisés ont été utilisés pour évaluer la faisabilité d’une telle étude. Différentes techniques d’extraction protéique ont été évaluées. Les extraits totaux et fractionnements subcellulaires de tissu frais ont permis une analyse appropriée des protéines cellulaires. Il en était de même pour l’extraction totale de tissus fixés. Cependant, les protéines extraites suite à microdissection au laser de tissu fixé étaient inadéquates et en nombre insuffisant. Sous-projet B. Afin d’investiguer l’importance de fonctions, voies ou protéines dans différents types de cancer colorectaux, neuf lignées cellulaires de cancer colorectal et de côlon normal ont été fractionnées en quatre compartiments subcellulaires et analysées par spectrométrie de masse. Aucun groupe de recherche n’avait analysé jusqu’à présent plus de cinq lignées et plus d’un compartiment subcellulaire à la fois. Les résultats montraient que certaines voies canoniques et fonctions cellulaires étaient de haute importance dans plusieurs des lignées analysées, dont la voie de signalisation par eIF2. De plus, les régulateurs de transcription TP53, MYC et TGFB1, pouvant être responsables des caractéristiques cellulaires observées, ont été identifiés. En conclusion, ce projet nous a permis d’améliorer nos connaissances sur les caractéristiques moléculaires d’importance dans le cancer colorectal et de mettre au point des techniques qui pourraient permettre la découverte de nouveaux biomarqueurs. / Abstract : Colorectal adenocarcinoma is one of the most important cancers in Canada in terms of mortality and morbidity. However, we still know very little on its molecular features. This study was divided into two sub-projects. Sub-project A. At this time, no biomarker has the capacity of predicting a patient’s response to radiotherapy, which is a commonly used treatment of colorectal cancer. The goal of this section was to develop the methods to conduct a prospective or retrospective mass spectrometry study on the patient response to radiotherapy, through the use of human tissues. Mouse tissues and tissues of an anonymous patient were obtained in order to evaluate the feasibility of such a study. Different protein extraction techniques were evaluated. Total lysates and subcellular fractionations of fresh tissues allowed for a successful analysis of the samples. The same was true of total lysates of fixed tissues. However, proteins extracted from cells isolated through laser capture microdissection were insufficient in numbers and their types were inconsistent with the expected results. Sub-project B. In order to study the importance of proteins and cellular functions or pathways in different types of colorectal cancers. nine cell lines originating from colorectal carcinoma and from normal colon were fractionated according to four subcellular compartments and analysed through mass spectrometry. Until now, no research group had analysed, in a single study more than 5 cell lines as well as more than one subcellular compartment at once. Some cellular functions and canonical pathways were shown to be of high importance in many of the studied cell lines, such as the signalling through eIF2 pathway. Furthermore, the transcription regulators TP53, MYC and TGFB1were identified as potentially responsible for the observed proteomic characteristics. In conclusion, this study allowed for a better understanding of important molecular caracteristics of colorectal cancer and allowed for the optimization of techniques that may serve in the discovery of new biomarkers relative to the use of radiotherapy as a treatment.

A typical gene expression data set consists of measurements of a large number of gene expressions, on a relatively small number of subjects, classified according to two or more outcomes, for example cancer or non-cancer. The identification of associations between gene expressions and outcome is a huge multiple testing problem. Early approaches to this problem involved the application of thousands of univariate tests with corrections for multiplicity. Over the past decade, numerous studies have demonstrated that analyzing gene expression data structured into predefined gene sets can produce benefits in terms of statistical power and robustness when compared to alternative approaches. This thesis presents the results of research on gene set analysis. In particular, it examines the properties of some existing methods for the analysis of gene sets. It introduces novel Bayesian methods for gene set analysis. A distinguishing feature of these methods is that the model is specified conditionally on the expression data, whereas other methods of gene set analysis and IGA generally make inferences conditionally on the outcome. Computer simulation is used to compare three common established methods for gene set analysis. In this simulation study a new procedure for the simulation of gene expression data is introduced. The simulation studies are used to identify situations in which the established methods perform poorly. The Bayesian approaches developed in this thesis apply reversible jump Markov chain Monte Carlo (RJMCMC) techniques to model gene expression effects on phenotype. The reversible jump step in the modelling procedure allows for posterior probabilities for activeness of gene set to be produced. These mixture models reverse the generally accepted conditionality and model outcome given gene expression, which is a more intuitive assumption when modelling the pathway to phenotype. It is demonstrated that the two models proposed may be superior to the established methods studied. There is considerable scope for further development of this line of research, which is appealing in terms of the use of mixture model priors that reflect the belief that a relatively small number of genes, restricted to a small number of gene sets, are associated with the outcome.

No description available.

One of the pressing needs in the field of disease biomarker discovery is new technologies that could allow high performance protein analysis in different types of clinical material, such as blood and solid tissues. This thesis includes four approaches that address important limitations of current technologies, thus enabling highly sensitive, specific and parallel protein measurements. Paper I describes a method for sensitive singleplex protein detection in complex biological samples, namely solid phase proximity ligation assay (SP-PLA). SP-PLA exhibited improved sensitivity compared to conventional sandwich immunoassays. We applied SP-PLA to validate the potential of GDF-15 as a biomarker for cardiovascular disease.   Paper II describes ProteinSeq, a multiplexed immunoassay based on the principle of SP-PLA, for parallel detection of 36 proteins using next-generation sequencing as readout. ProteinSeq exhibited improved sensitivity compared to multiplexed sandwich immunoassays, and the potential to achieve even higher levels of multiplexing while preserving a high sensitivity and specificity. We applied ProteinSeq to analyze 36 proteins, including one internal control, in 5 μl of plasma samples in a cohort of patients with cardiovascular disease and healthy controls. Paper III describes PLA-DTM, a strategy for recording all possible interactions between sets of proteins in clinical samples. Individual proteins and their interactions are first encoded to dual barcoded DNA by PLA, and the barcodes are interrogated by a method named dual tag microarray (DTM). We applied the method for studying interactions among protein members of the NFκB signaling pathway. Paper IV describes a novel probing strategy for analyzing individual biomolecules in solution or in situ. The technique employs a new class of probes for unfolding proximity ligation assays - uPLA probes. The probes are designed so that each probe set is sufficient in forming and replicating circular DNA reporter, without interactions among themselves when incubated with the sample. The uPLA probing strategy provides ease in the design of multiple probe sets in parallelized assays while enhancing the specificity of detection. We used the uPLA probes to detect various targets, including synthetic DNA and cancer-related transcripts in situ.

<p><a>Prostate cancer is the second leading cause of cancer death among men in the United States. The androgen receptor (AR) antagonist enzalutamide is an FDA-approved drug for treatment of patients with late-stage prostate cancer and is currently under clinical study for early-stage prostate cancer treatment.</a> After a short positive response period to enzalutamide, tumors will develop drug resistance. In these studies, we uncovered that NOTCH signaling and DNA methylation are a deregulated in enzalutamide-resistant cells. <i>NOTCH2</i> and<i> c-MYC </i><a>gene expression<i> </i>positively correlated with <i>AR </i>expression in samples from patients with hormone refractory disease in which AR expression levels correspond to those typically observed in enzalutamide-resistance</a>. The expression of Notch signaling components was upregulated in enzalutamide-resistant cells suggesting the activation of the pathway. Inhibition of this pathway <i>in vitro</i> and <i>in vivo</i> promoted an increase in the sensitivity to enzalutamide with an impact on AR expression. On the other hand, DNMT activity and DNMT3B expression were upregulated in resistant lines. Enzalutamide induced the expression of DNMT3A and DNMT3B in prostate cancer cells with a potential role for p53 and pRB in this process. The overexpression of DNMT3B3, a DNMT3B variant, promoted an enzalutamide-resistant phenotype in C4-2 cells. DNA methylation inhibition, using low-concentration decitabine, and <i>DNMT3B</i> knockdown induced a re-sensitization of resistant prostate cancer cells and tumors to enzalutamide. Decitabine treatment in enzalutamide-resistant induced a decrease in the expression of AR-V7 and changes in genes from the apoptosis, DNA repair and mRNA splicing pathways. Decitabine plus enzalutamide treatment of 22RV1 xenografts induced a decrease in tumor weight, KI-67 and AR-V7 expression and an increase in Cleaved-Caspase3 levels. All the above suggest that Notch signaling and DNA methylation pathways are deregulated after enzalutamide resistance onset, and targeting these pathways restores the sensitivity to enzalutamide.<b><u></u></b></p>