Background: Breast cancer is a complex disease, both phenotypically and etiologically. Accordingly, the responses to various treatments in the adjuvant setting among individuals vary considerably. There is a demand for tools that can distinguish patients who may benefit or may suffer from particular systemic treatments. We hypothesized that combination of data on genetic biomarkers with data from traditional clinical and pathophysiological (clinicopathologic) factors using traditional Cox model or Support Vector Machine (SVM) method, a new machine learning method, may provide a better tool for prediction of benefits to chemotherapy for the treatment of early breast cancer than using either biomarker or clinicopathologic data alone. Methods: This project included 531 patients from NCIC-CTG MA.5 trial who had data on both clinicopathologic factors, such as age, tumor size, ER status, type of surgery, tumor grade and lymph node involvement, and biomarkers assayed on tissue microarrays (TMAs), including HER2, p53, CA9, MEP21, clusterin, pAKT, COX2 and TOP2A. The Cox model and SVM methods were used to develop prognostic indices for relapse-free or overall survival with either data from TMAs and clinicopathologic assessments alone or their combination. The prognostic indices developed were then examined for their value as predictive classifiers for benefits from CEF treatment. The power of the predictive classifiers derived was evaluated and compared using the bootstrap approach. Results: None of the prognostic indices developed were found to have significant predictive value, although the prognostic index developed using SVM method based on only biomarkers yielded a marginal significant p-value (p=0.0527) for the interaction between classifier and treatment. In accordance with results published previously, the interaction between the classifier developed based on HER2 or TOP2A and treatment was significant (p=0.02 and 0.04 respectively). Comparisons based on the bootstrap approach indicate classifiers developed based on SVM performed better than those based on the Cox model method. Conclusions: Combination of data using biomarkers and clinical-pathological factors, and using either the traditional COX model method or the new machine learning method was not shown to perform better than two single previously known biomarkers in prediction of response to CEF treatment for early breast cancer. / Thesis (Master, Community Health & Epidemiology) -- Queen's University, 2010-04-27 10:16:11.811

Circulating tumor cells (CTCs) represent a systemic phase of the localised cancer disease. They can be distinguished and enriched from the peripheral blood and so from the surrounding leukocytes by either physical properties (e.g., density and size) or biological properties (e.g., expression of epithelial proteins such as EpCAM or cytokeratins) and are usually further characterized by immunostaining or RT-PCR assays. Selecting patients with the risk of disease relaps at the time of diagnosis is crucial for clinicians in deciding who should, and who should not, receive adjuvant chemotherapy. We know that CTCs are strong prognostic factor in patients with metastatic as well as localized breast cancer (BC). It is also known that the prognostic power of circulating tumor cells in women with BC is independent from the standard prognostic indicators. Testing of CTCs known recently as "liquid biopsy" could be informative not only as predictor of the disease relapse, but also as the predictor of therapy effectiveness. The clinical use of CTCs must be strictly encouraged by clinical trials results. Monitoring of CTCs in time could zoom in the mechanism of therapy resistance and/or may provide the identification of new druggable targets. The purpose of my work was therefore to assess the CTCs positivity rate...

La néphropathie à BK virus (BKV) est l'une des complications les plus fréquentes de la transplantation rénale. La prise en charge consiste en la réduction préemptive de l'immunosuppression basée sur le suivi de la charge virale, mais cette stratégie n’est pas complètement efficace et augmente le risque de rejet. Dans un premier volet, nous avons évalué la mesure de la charge virale par PCR quantitative en temps réel, permettant de mettre en évidence des facteurs de variabilité comme le polymorphisme du BKV et de valider la technique utilisée pour le suivi de notre cohorte. L’intérêt des anticorps neutralisants (AcNs) anti-BKV en tant que marqueur prédictif de la réplication BKV a ensuite été évalué dans une cohorte de 168 transplantés rénaux. Nous avons montré i) que le virus responsable de l’infection provenait du donneur ; ii) que les AcNs jouent un rôle dans la prévention de la réactivation et le contrôle de la réplication virale et iii) qu’un seuil d’AcNs de 4 log10 permettait de stratifier le risque de réplication BKV. Ce travail ouvre la voie à un suivi personnalisé en fonction du risque de réplication BKV et à de nouvelles approches immunothérapeutiques. / BK virus (BKV)-associated nephropathy is one of the major causes of graft dysfunction and loss in kidney transplant recipients. Since no BKV-specific antiviral therapies are available, management relies on preemptive immunosuppression reduction based on viral load monitoring. However, this strategy does not fully eliminate the risk of nephropathy and can increase the risk of graft rejection. In this work, we evaluated viral load measurement by quantitative real-time PCR in an interlaboratory comparison. Variability factors such as BKV polymorphism or pre-PCR steps have been highlighted and the method used for monitoring our cohort has been validated. The role of anti-BKV neutralizing antibodies (NAbs) as a predictive marker of BKV replication has been investigated in a cohort of 168 kidney transplant recipients. We showed that i) viral infection is caused by the donor strain; ii) NAbs play an essential role in viral replication prevention and control and iii) a NAbs cutoff of 4 log10 allows to stratify BKV replication risk. This work paves the way for personalized monitoring according to BKV replication risk and for new preventive or therapeutic strategies.

No description available.

La dystrophie musculaire de Duchenne (DMD) touche un garçon sur 3500, contraint à l'usage du fauteuil roulant à l'âge de 10 ans, et entraîne le décès à une vingtaine d'années. Cette maladie demeure incurable, et les pistes thérapeutiques envisagées nécessitent d'être validées en amont, dans les modèles murins, puis au stade pré-clinique, dans les modèles canins.L'un d'eux, le chien GRMD (Golden Retriever Muscular Dystrophy), est le plus largement utilisé, et présente l'intérêt de partager, avec le patient qu'il modélise, de nombreuses similitudes génotypiques et phénotypiques. Les différentes fonctions touchées doivent donc pouvoir faire l'objet de mesures objectives et quantitatives, à l'aide d'outils dédiés. Par ailleurs, une problématique inhérente à l'utilisation de ce modèle est sa grande variabilité sur le plan phénotypique.L'objectif du travail mené ici a été de développer des outils d'évaluation du chien GRMD, afin de mieux connaître et maîtriser cette hétérogénéité clinique.La mesure de force de flexion du tarse a permis de démontrer que la force tétanique maximale pouvait être utilisée comme indice d'évaluation à différents stades de la maladie, sans que le déficit de force musculaire puisse être relié à l'atteinte motrice globale. De plus, la relaxation s'est avérée altérée chez les chiens GRMD, en corrélation avec leur atteinte motrice.La locomotion, évaluée par accélérométrie tri-dimensionnelle, a pu montrer des altérations multiples, mesurées par différentes variables. Certaines variables sont altérées de manière précoce, tandis que d'autres anomalies s'installent durant les premiers mois, traduisant l'aggravation de la fonction locomotrice.La dysfonction respiratoire, évaluée par spirométrie en respiration de Tidal, et cinématique diaphragmatique sur images radioscopiques, a également pu être objectivée par différents indices. Une moindre mobilité diaphragmatique, une rétraction caudale du diaphragme, et un effondrement du débit expiratoire en fin d'expiration, s'installent au cours des premiers mois.Afin de contrôler l'hétérogénéité clinique ainsi mesurée, une recherche de marqueurs prédictifs de l'évolution clinique a été menée. Différents indices histologiques et cliniques ont été évalués sur leur valeur pronostique à un stade précoce. La fréquence des cycles locomoteurs à 2 mois et le défaut de relaxation à 4 mois se sont avérés prédictifs de formes accélérées.Enfin, les différents outils mis en place ont été évalués dans le cadre du suivi d'animaux au cours d'un essai thérapeutique, qui a, de plus, permis de disposer d'une population de référence sous traitement immunosuppresseur. Une amélioration fonctionnelle des animaux traités a pu être démontrée par nombre des indices mesurés.Ces résultats démontrent que les outils développés sont utilisables au cours d'essais pré-cliniques, et permettent, malgré l'hétérogénéité clinique qu'ils mesurent, de démontrer un bénéfice fonctionnel. Plus largement, ces données permettent d'optimiser l'utilisation pré-clinique du modèle GRMD. / Duchenne Muscular Dystrophy (DMD) affects one boy over 3500 at birth. The affected individuals are wheelchair-bound at about 10 years, and death occurs in the early twenties. DMD remains incurable, and therapeutic strategies need to be validated in murine models, and, subsequently, at the preclinical stage, in canine models.Among the existing canine models, the GRMD (Golden Retriever Muscular Dystrophy) dog is the most widely used. The strong genotypic and phenotypic similarities it shares with DMD patients make this model of great interest. The many affected functions must therefore be reliably measured using dedicated tools, providing objective and quantitative evaluation. Moreover, the wide phenotypic heterogeneity peculiar to this model may compromise its use in preclinical studies.The aim of the present work was to develop evaluation tools for the GRMD dog, in order to better know and handle this clinical variability.The measurement of the contraction force generated by tarsal flexion has shown that the maximal tetanic force could be used as an evaluation index, at different stages of the disease. However, no correlation with the global motor impairment could be found. Conversely, the relaxation has shown to be altered in GRMD dogs, and correlated with the motor impairment.The locomotion was evaluated using three-dimensional accelerometry. This method allowed the measurement of several variables, some of which being early impaired, and some others being altered in a more progressive fashion, reflecting the degradation of the locomotor function.The respiratory impairment has been evaluated by diaphragmatic kinematics using radioscopic acquisitions and by Tidal-breathing spirometry. The diaphragm was shown to be less mobile, and to be caudally displaced. The end-expiration flows were decreased. These abnormalities progressed during the first months.In order to better handle the clinical heterogeneity, some markers able to predict the clinical evolution were looked for. The prognostic value of many histological and clinical indexes at an early stage has been evaluated. The stride frequency at the age of 2 months, as well as the relaxation impairment at the age of 4 months succeeded in predicting severe accelerated forms.Finally, the developed tools have been tested in the context of a clinical follow-up during a therapeutic trial. This trial also aimed to provide a reference-group of GRMD dogs treated with immunosuppressive drugs. Several indexes have demonstrated a clinical improvement of the treated animals.These results show that the developed tools are useable during preclinical trials and allow to quantitatively highlight a functional improvement, despite the clinical heterogeneity. More widely, these data will lead to an optimization of the preclinical use of GRMD dogs.