Despite tremendous progress in the understanding of breast cancer (BC), gaps remain in our knowledge of the molecular basis underlying the aggressiveness of BC and BC disparities. Nuclear respiratory factor 1 (NRF1) is a transcription factor (TF) known to control breast cancer cell cycle progression. DNA response elements bound by NRF1 positively correlate with the progression of malignant breast cancer. Mechanistic aspects by which NRF1 contributes to susceptibility to different breast tumor subtypes are still not fully understood. Therefore, the primary objective of this dissertation was to decipher mechanisms by which NRF1 coordinates changes in the transcriptional and chromatin landscape affecting development and progression of invasive breast cancer. Our hypothesis was that NRF1 reprogramming the transcription of tumor initiating gene(s) and tumor suppressor gene(s) contribute in the development and progression of invasive breast cancer. To test this hypothesis, we proposed three specific aims: (a) Decipher regulatory landscape of NRF1 networks in breast cancer. (b) Determine the role of NRF1 gene networks in different subtypes of breast cancer. (c) Determine differential NRF1 gene network sensitivity contributing to breast cancer disparities. Our approach to test these aims consisted of a systematic integration of ChIP DNA-seq, RNA-Seq, NRF1 protein-DNA motif binding, signal pathway analysis, and Bayesian machine learning. We uncovered a novel oncogenic role for NRF1. This discovery strongly supported the supposition that NRF1 overexpression is sufficient to derive breast tumorigenesis. We also observed new roles for NRF1 in the acquisition of breast tumor initiating cells, regulation of epithelial to mesenchymal transition (EMT), and invasiveness of BC stem cells. Furthermore, through the use of Bayesian network structure learning we found that the NRF1 motif was enriched in 14 associated with HER2 amplified breast cancer. Three genes—GSK3B, E2F3, and PIK3CA—were able to predict HER2 breast tumor status with 96% to100% confidence. The findings of this study also showed the roles of NRF1 sensitivity to development of lobular A, Her2+, and TNBC in different racial/ethnic groups of breast cancer patients. In summary, our study revealed for the first time the role of NRF1 in the pathogenesis of invasive BC and BC disparities.

Intracellular sterol redistribution is an important step in the lipid homeostasis of organisms, a process directly linked to the organizational arrangement in the plasma membrane (PM) of cells. Previous studies in the budding yeast Saccharomyces cerevisiae have demonstrated that the ARV1 (ACAT-related enzyme-2 required for viability 1) protein is a major regulator of sterol transport from the endoplasmic reticulum to the plasma membrane, contributing to the structural organization of the PM, rendering it resistant to anti-fungal compounds as well as maintaining ER integrity. This study assessed the significance of ARV1 in the plant pathogenic fungus Cryphonectria parasitica (Cparv1) and investigated its role in the pathogenesis and virulence of the fungus. C. parasitica is the causative agent of Chestnut blight, which has wreaked havoc on the American chestnut species. Genomic analysis revealed that the Cparv1 gene is very closely linked to another gene that putatively encodes a cyanamide hydratase (Cpcah). An initial gene deletion event resulted in the elimination of both genes and a highly deformed phenotype in C. parasitica that was fully recoverable by complementation. PCR-based expression analysis determined that the lack of Cparv1 was responsible for the debilitated phenotype of the double mutant, with no transcript detectable from Cpcah. Subsequent complementation of the Cparv1 gene was also observed to restore the wildtype phenotype. Mass spectrometry-based (MS) results indicated a decrease in sterol content of the DCparv1 mutant strain compared to wildtype EP155 thus confirming a role for Cparv1 in sterol homeostasis. It has been shown that infection of C. parasitica with virulence-attenuating hypoviruses altered intracellular lipid content and protein secretion. Ultrastructure studies conducted on the Cparv1 strain showed disrupted organelle integrity and the presence of cytoplasmic double membrane stretches. Decreased sterol content in C. parasitica infected with CHV1-EP713 was observed similar to DCparv1 suggesting a connection between the hypovirus-infected phenotype and Cparv1. Furthermore, a non-targeted metabolomic study on all three strains identified 324 metabolites. Through the subsequent pathway analysis, we have investigated the pleiotropic effects in the C. parasitica strains and established a mechanistic linkage between this the activity of the ARV-1 protein and the hypovirus-infected phenotype.

This is a case study of the political situation in Sweden where a present and growing far-right has generated an outcome of political fragmentation. The process between this probable cause and outcome will be investigated to find the best possible explanation for how an isolated party could generate the outcome of political fragmentation despite their denied political participation with the other parties. The process will be analyzed through mainstream parties’ political discourse about the far-right and how they give expression for their strategies to deal with their presence. This will be done through an abductive discourse-pathway analysis, wherein mainstream parties’ dynamics towards the far-right and how it has changed over time will be analyzed. The result from the analysis showed that there are three possible outcomes when dealing with the far-right: political fragmentation, political unity and political polarization. The conclusion is that political fragmentation occurs when mainstream parties are pulled in different directions regarding what strategies to use when they ought to deal with a growing far-right presence.

Le réseau des MAPK est composé de pathways de signalisation fermement entrecroisés impliqués dans le cancer. Toutefois, les mécanismes précis qui sous-tendent son influence sur l'équilibre entre la prolifération et la mort cellulaire demeurent insaisissablesDes données publiques ont été intégrés dans une carte de réactions détaillée, représentant l'influence du réseau des MAPKs sur la décision du destin cellulaire. Cette carte a ensuite été utilisée pour des analyses informatiques spécifiquesTout d'abord, les dynamiques du réseau des MAPKs dans les cancers de la vessie ont été analysés.Un modèle Booléen a été construit, représentant la réponse du réseau aux inputs d'intérêt.Les résultats de simulations systématiques ont été trouvés globalement cohérents avec des données publiques, et ont permis de déchiffrer les principaux événements qui sous-tendent les différents comportements observés dans le cancerEnsuite, la carte a été exploitée pour réanalyser des données publiques d'expression de gènes, avec l'objectif d'identifier les principaux acteurs de la transduction des signaux prolifératifs, dans des types cellulaires spécifiques.Des analyses du réseaux et des calculs statistiques ont conduit à l'identification de régions dérégulées dans le réseau des MAPKs, et à la délinéation de points d'intervention optimales dans cinq stades du cancer de la vessie et dans quatre sous-types de lymphome TL'ensemble de ces résultats a conduit à la formulation de nouvelles hypothèses concernant le fonctionnement du réseau des MAPKs dans différents états pathologiques, et à la sélection de composants cibles qui pourraient être envisagées pour le développement de nouveaux traitements / MAPK network consists of tightly interconnected signalling pathways. Although several studies established the involvement of this network in cancer deregulations, the precise mechanisms underlying its influence on the balance between cell proliferation and death remain elusive.Public data were integrated into a detailed reaction map, accounting for the influence of MAPK network on cell fate decision. This map was then used for computational analyses addressing specific cancer-related questions.First, the dynamics of MAPK network in bladder cancers were analysed. A Boolean model was built, accounting for the response of the network to selected inputs. The results of systematic simulations were found globally coherent with published data. Based on in silico experiments, the main events underlying different observed cancer cell behaviours were then deciphered.Next, the MAPK reaction map was exploited to reanalyse public high-throughput gene expression data. The goal was to identify key actors for the transduction of proliferative signals, in specific cell types. Network analyses and statistical computations led to the identification of deregulated MAPK network regions, and to the delineation of optimal intervention points aimed at blocking the proliferative signals transduced from such regions. This approach was used to study five different tumour stages and four different subtypes of T-cell lymphoma.Altogether, these results led to the formulation of novel hypotheses concerning the functioning of MAPK network in different pathological conditions, and to the selection of target components that might be considered for the development of novel treatments.

No description available.

Acute lymphoblastic leukemia is a hematological malignancy that gains a proliferative advantage and originates in the bone marrow. One of the more common genetic alterations in ALL is KMT2A-rearrangement which constitutes 80% of the cases of ALL in infants. Patients carrying the KMT2A rearrangement have a poor prognosis and will eventually develop drug resistance. This project aimed to find new therapeutic targets which would help in the development of novel drugs. We designed a model which uses gene expression data, to infer expressions of oncogenes and the genes which could be associated with immune pathways. The data was extracted and transformed by removing the batch effects and identifying the biotypes of these genes for more focused research. Here we utilized exome RNA-seq,  hence it was necessary to reduce the high dimensionality of the data. The dimensionality reduction was performed using Monte Carlo Feature Selection. After the feature selection, a list of highly significant genes was obtained. These genes were used in a machine learning model, R.ROSETTA, which produces rule-based results centered on rough sets theory. The rules were visualized using VisuNet, an interactive tool that creates networks from the rules. Among others, we identified levels of expressions of genes such as JAK3, TOX3, and DMRTA1 and their relations to other genes  using the machine learning model. These significant genes were also used to do pathway analysis using pathfindR which allowed us to infer the oncogenic pathways. The pathway analysis helped us deduce pathways such as immunodeficiency and other signaling pathways that could be potential drugs

No description available.

No description available.

No description available.

L’anémie falciforme est une maladie monogénique causée par une mutation dans le locus de la β-globine. Malgré le fait que l’anémie falciforme soit une maladie monogénique, cette maladie présente une grande hétérogénéité clinique. On présume que des facteurs environnementaux et génétiques contribuent à cette hétérogénéité. Il a été observé qu’un haut taux d’hémoglobine fœtale (HbF) diminuait la sévérité et la mortalité des patients atteints de l’anémie falciforme. Le but de mon projet était d’identifier des variations génétiques modifiant la sévérité clinique de l’anémie falciforme. Dans un premier temps, nous avons effectué la cartographie-fine de trois régions précédemment associées avec le taux d’hémoglobine fœtale. Nous avons ensuite effectué des études d’association pan-génomiques avec deux complications cliniques de l’anémie falciforme ainsi qu’avec le taux d’hémoglobine fœtale. Hormis les régions déjà identifiées comme étant associées au taux d’hémoglobine fœtale, aucun locus n’a atteint le niveau significatif de la puce de génotypage. Pour identifier des groupes de gènes modérément associés au taux d’hémoglobine fœtale qui seraient impliqués dans de mêmes voies biologiques, nous avons effectué une étude des processus biologiques. Finalement, nous avons effectué l’analyse de 19 exomes de patients Jamaïcains ayant des complications cliniques mineures de l’anémie falciforme. Compte tenu de la taille des cohortes de réplication disponibles, nous n’avons pas les moyens de valider statistiquement les variations identifiées par notre étude. Cependant, nos résultats fournissent de bons gènes candidats pour des études fonctionnelles et pour les réplications futures. Nos résultats suggèrent aussi que le β-hydroxybutyrate en concentration endogène pourraient influencer le taux d’hémoglobine fœtale. De plus, nous montrons que la cartographie-fine des régions associées par des études pan-génomiques peut identifier des signaux d’association additionnels et augmenter la variation héritable expliquée par cette région. / Sickle cell disease is a monogenic disease caused by a mutation in the β-globin locus. Although it is a monogenic disease, it shows a high clinical heterogeneity. Environmental and genetic factors are thought to play a role in this heterogeneity. It has been observed that a high fetal hemoglobin (HbF) levels correlates with a diminution of the severity and mortality of patients with sickle cell disease. The goal of my project was to identify genetic modifiers of the clinical severity of sickle cell disease. First, I performed the fine-mapping of three regions previously associated with HbF levels. Second, I performed genome-wide association studies with two clinical complications of sickle cell disease as well as with HbF levels. Since no new loci reached array-wide significance for HbF levels, I performed a pathway analysis to identify additional HbF loci of smaller effect size that might implicate shared biological processes. Finally, I performed the analysis of 19 whole exomes from Jamaican sickle cell disease patients with very mild complications. In conclusion, given the sample size of the replication cohorts available, we do not currently have the means to statistically validate the association signals. However, these results provide good candidate genes for functional studies and for future replication. Our results also suggest that β-hydroxybutyrate in endogenous levels could influence HbF levels. Furthermore, we show that fine-mapping the loci associated in genome-wide association studies can identify additional signals and increase the explained heritable variation.