Cancer causes 13% of human deaths worldwide, 90% of which involve metastasis. The reactivation of embryonic processes in epithelial cancers—and the epithelial-mesenchymal transition (EMT) in particular—results in increased cell motility and invasiveness, and is a known mechanism for initiating metastasis. The reverse process, the mesenchymal-epithelial transition (MET), is implicated in the process of cells colonising pre-metastatic niches. Understanding the relationships between EMT, MET and metastasis is therefore highly relevant to cancer research and treatment. Key challenges include deciphering the large, uncharted space of gene function, mapping the complex signalling networks involved and understanding how the EMT and MET programmes function in vivo within specific environments and disease contexts. Inference and analysis of small-scale networks from human tumour tissue samples, scored for protein expression, provides insight into pleiotropy, complex interactions and context-specific behaviour. Small sets of proteins (10–50, representative of key biological processes) are scored using quantitative antibody-based technologies (e.g. immunofluorescence) to give static expression values. A novel inference algorithm specifically for these data, Gabi, is presented, which produces signed, directed networks. On synthetic data, inferred networks often recapitulate the information flow between proteins in ground truth connectivity. Directionality predictions are highly accurate (90% correct) if the input network structure is itself accurate. The Gabi algorithm was applied to study multiple carcinomas (renal, breast, ovarian), providing novel insights into the relationships between EMT players and fundamental processes dysregulated in cancers (e.g. apoptosis, proliferation). Survival analysis on these cohorts shows further evidence for association of EMT with poor outcome. A patent-pending method is presented for stratifying response to sunitinib in metastatic renal cancer patients. The method is based on a proportional hazards model with predictive features selected automatically using regularisation (Bayesian information criterion). The final algorithm includes N-cadherin expression, a determinant of mesenchymal properties, and shows significant predictive power (p = 7.6x10-7, log-rank test). A separate method stratifies response to tamoxifen in estrogen-receptor positive, node-negative breast cancer patients using a cross-validated support vector machine (SVM). The algorithm was predictive on blind-test data (p = 4.92 x 10-6, log-rank test). Methods developed have been made available within a web application (TMA Navigator) and an R package (rTMA). TMA Navigator produces visual data summaries, networks and survival analysis for uploaded tissue microarray (TMA) scores. rTMA expands on TMA Navigator capabilities for advanced workflows within a programming environment.

About one in eight women in the United States will develop breast cancer over the course of her lifetime. Moreover, patient-to-patient variability in disease progression continues to complicate clinical decisions in diagnosis and treatment for breast cancer patients. Early detection of tumors is a key factor influencing patient survival, and advancements in diagnostic and imaging techniques has allowed clinicians to spot smaller sized lesions. There has also been an increase in premature treatments of non-malignant lesions because there is no clear way to predict whether these lesions will become invasive over time. Patient variability due to genetic polymorphisms has been investigated, but studies on variability at the level of cellular activity have been extremely limited. An individual’s biochemical milieu of cytokines, growth factors, and other stimuli contain a myriad of cues that pre-condition cells and induce patient variability in response to tumor progression or treatment. Circulating white blood cells called monocytes respond to these cues and enter tissues to differentiate into monocyte-derived macrophages (MDMs) and osteoclasts that produce cysteine cathepsins, powerful extracellular matrix proteases. Cathepsins have been mechanistically linked to accelerated tumor growth and metastasis. This study aims to elucidate the variability in disease progression among patients by examining the variability of protease production from tissue-remodeling macrophages and osteoclasts. Since most extracellular cues initiate multiple signaling cascades that are interconnected and dynamic, this current study uses a systems biology approach known as cue-signal-response (CSR) paradigm to capture this complexity comprehensively. The novel and significant finding of this study is that we have identified and predicted donor-to-donor variability in disease modifying cysteine cathepsin activities in macrophages and osteoclasts. This study applied this novel finding to the context of tumor invasion and showed that variability in tumor associated macrophage cathepsin activity and their inhibitor cystatin C level mediates variability in cancer cell invasion. These findings help to provide a minimally invasive way to identify individuals with particularly high remodeling capabilities. This could be used to give insight into the risk for tumor invasion and develop a personalized therapeutic regime to maximize efficacy and chance of disease free survival.

Ce travail de recherche vise à évaluer les enjeux éthiques posés par le recours au diagnostic anténatal dans le cadre des maladies génétiques à révélation tardive.Notre première étude a été d’analyser les décisions prises en réunions de Centres Pluridisciplinaires de Diagnostic Prénatal (CPDPN) et, à travers des situations réelles et singulières, relever les éléments de discussion et plus particulièrement ceux pouvant influencer la décision. Nous avons, ensuite réalisé deux enquêtes par questionnaires qui ont permis: 1) D’explorer le point de vue des personnes directement concernées par une telle pathologie (porteurs du gène responsable - malades ou asymptomatiques -, conjoints et/ou parents d’une personne porteuse du gène) ; 2) D’étudier la position des professionnels de la parentalité, travaillant en lien avec un CPDPN, et qui sont décideurs de la recevabilité ou non d’une demande de diagnostic anténatal dans ce contexte.Ce travail a ainsi contribué à faire émerger des questionnements pertinents sur le plan éthique et une réflexion sur de possibles évolutions législatives et sociétales dans ce domaine. / This research carries out with the aim of evaluating the ethical challenges faced by the use of antenatal diagnosis in late-onset genetic diseases.In a first study, we analysed the decisions of Multidisciplinary Centres for Prenatal Diagnosis (MCPD) and, through real and specific situations, we identified the elements for discussion and more particularly the ones that could influence the decision-making process. Then, we conducted two questionnaire surveys that allowed to: 1) Explore the viewpoints of people directly affected by this type of pathology (responsible gene carriers - ill or asymptomatic individuals -, partners and/or parents of gene carriers); 2) Examinate the opinions of professionals, working in association with a CPDPN and who are decision-makers of the acceptability or not for an antenatal diagnosis request in this context.This work has therefore brought out questions on ethics, and views on the potential legal and social developments in this area.

The purposes of this study are: a) to understand the treatments compliance behavior of the patient with chronic disease at the behavioral level, particularly, the relationship between treatments compliance behavior and normative beliefs; b) develop a behavioral model of patient's treatments compliance behavior that could be used for predicting, combating, treating, tracking and controlling the treatments compliance behavior of the patients with chronic disease. Seventy-two patients from senior daycare centers in the Dallas area, who suffer or had suffered from at least, one chronic disease, participated in the study. Data gathering was conducted using paper-based questionnaire. The most significant finding of this study is the relationship between normative beliefs and the treatments compliance behavior of the patient with chronic disease. Normative beliefs were found to have significant impact on the treatments compliance intent and behavior of the patients with chronic disease. Another important finding showed that side-effects of prescribed treatments have little or no influence on the treatments compliance behavior of the patient with chronic disease. A relationship between the effectiveness of medicine, particularly, predictive medicine, and treatments compliance behavior was established. The design of the study was intended to provide coverages for a set of constructs that may be the interacting units in the environment of any chronic disease treatments decision. It depicts relational, information communications links between the constructs. The Imhonde model of treatments compliance behavior was designed to include cultural norms and other beliefs that are significant for real-time human ailments decisions behaviors. It is recommended that further studies may include the use of a larger population of participants from diverse cultures and localities in multiple states and countries, with the object of finding the differences that culture and local environments may have on the normative leaning for treatments compliance behavioral decisions in chronic disease cases.