No description available.

No description available.

No description available.

No description available.

No description available.

No description available.

No / It is known that cells within the inflammatory background in classical Hodgkin lymphoma (cHL) provide signals essential for the continual survival of the neoplastic Hodgkin and Reed-Sternberg (HRS) cells. However, the mechanisms underlying the recruitment of this inflammatory infiltrate into the involved lymph nodes are less well understood. In this study, we show in vitro that HRS cells secrete lymphotoxin-α (LTα) which acts on endothelial cells to upregulate the expression of adhesion molecules that are important for T cell recruitment. LTα also enhances the expression of hyaluronan which preferentially contributes to the recruitment of CD4+ CD45RA+ naïve T cells under in vitro defined flow conditions. Enhanced expression of LTα in HRS cells and tissue stroma; and hyaluronan on endothelial cells are readily detected in involved lymph nodes from cHL patients. Our study also shows that although NF-κB and AP-1 are involved, the cyclooxygenase (COX) pathway is the dominant regulator of LTα production in HRS cells. Using pharmacological inhibitors, our data suggest that activity of COX1, but not of COX2, directly regulates the expression of nuclear c-Fos in HRS cells. Our findings suggest that HRS cell-derived LTα is an important mediator that contributes to T cell recruitment into lesional lymph nodes in cHL.

No / Ethylmethanesulphonate (EMS), benzidine (BZD) and benzo[a]pyrene (B[a]P) were assayed for ability to induce mutation at the hprt locus of wild-type L5178Y mouse lymphoma cells. EMS was assayed in the absence of metabolic activation, B[a]P in the presence of metabolic activation (S-9 mix) and BZD both in the absence and presence of S-9. Treatment with EMS minus S-9 and B[a]P plus S-9, especially when the S-9 content of the incubation was 2% (v/v), produced strong dose-related increases in mutant frequency. BZD failed to induce mutation at the hprt locus, either in the absence or presence of S-9.

Machine learning can provide insight and support for a variety of decisions. In some areas of medicine, decision-support models are capable of assisting healthcare practitioners in making accurate diagnoses. In this work we explored the application of these techniques to distinguish between two diseases in veterinary medicine; inflammatory bowel disease (IBD) and alimentary lymphoma (ALA). Both disorders are common gastrointestinal (GI) diseases in humans and animals that share very similar clinical and pathological outcomes. Because of these similarities, distinguishing between these two diseases can sometimes be challenging. In order to identify patterns that may help with this differentiation, we retrospectively mined medical records from dogs and cats with histopathologically diagnosed GI diseases. Since the pathology report is the key conveyer of this information in the medical records, our first study focused on its information structure. Other groups have had a similar interest. In 2008, to help insure consistent reporting, the World Small Animal Veterinary Association (WSAVA) GI International Standardization Group proposed standards for recording histopathological findings (HF) from GI biopsy samples. In our work, we extend WSAVA efforts and propose an information model (composed of information structure and terminology mapped to the Systematized Nomenclature of Medicine - Clinical Terms) to be used when recording histopathological diagnoses (HDX, one or more HF from one or more tissues). Next, our aim was to identify free-text HF not currently expressed in the WSAVA format that may provide evidence for distinguishing between IBD and ALA in cats. As part of this work, we hypothesized that WSAVA-based structured reports would have higher classification accuracy of GI disorders in comparison to use of unstructured free-text format. We trained machine learning models in 60 structured, and independently, 60 unstructured reports. Results show that unstructured information-based models using two machine learning algorithms achieved higher accuracy in predicting the diagnosis when compared to the structured information-based models, and some novel free-text features were identified for possible inclusion in the WSAVA-reports. In our third study, we tested the use of machine learning algorithms to differentiate between IBD and ALA using complete blood count and serum chemistry data. Three models (using naïve Bayes, neural networks, and C4.5 decision trees) were trained and tested on laboratory results for 40 Normal, 40 IBD, and 40 ALA cats. Diagnostic models achieved classification sensitivity ranging between 63% and 71% with naïve Bayes and neural networks being superior. These models can provide another non-invasive diagnostic tool to assist with differentiating between IBD and ALA, and between diseased and non-diseased cats. We believe that relying on our information model for histopathological reporting can lead to a more complete, consistent, and computable knowledgebase in which machine learning algorithms can more efficiently identify these and other disease patterns. / Ph. D. / Computational models play an important role in supporting the decision making process. In some areas of medicine, decision-support models assist healthcare practitioners to make accurate diagnoses. In this work, we explored the application of computational techniques to distinguish between two diseases; inflammatory bowel disease (IBD) and alimentary lymphoma (ALA). These are common gastrointestinal (GI) diseases in humans and animals that share very similar laboratory findings. Because of these similarities, distinguishing between these two diseases can sometimes be challenging. In order to identify patterns that may help with this differentiation, we mined medical records from dogs and cats diagnosed with GI diseases. Since the pathology report is a key source of information for the diagnosis of these two diseases, in our first study we focused on its information structure. Others with similar interest have also examined reports of this type. In 2008, a group proposed standards for recording histopathological findings (HF) from GI biopsy samples. In our work, we extend the group’s efforts and propose an information model (composed of information structure and terminology) to be used when recording histopathological diagnoses (HDX, one or more HF from one or more tissues). Next, our aim was to identify free-text HF not currently expressed in the standardization group’s format that may provide evidence for distinguishing between IBD and ALA in cats. We trained computational models in 60 structured, and independently, 60 unstructured reports. Results show that unstructured information-based models using two computational models achieved higher accuracy in predicting the diagnosis when compared to the structured information-based models. As a result, novel free text features, which improved the performance of the structured reports, were identified. In our third study, we tested the use of computational models to differentiate between IBD and ALA using routine laboratory results. Three models were trained and tested on laboratory results from 40 Normal, 40 IBD, and 40 ALA cats. Diagnostic models achieved classification sensitivity ranging between 63% and 71%. These models can provide another noninvasive diagnostic tool to assist with differentiating between IBD and ALA, and between diseased and non-diseased cats. We believe that relying on our information model for histopathological reporting can lead to a more complete, consistent, and computable knowledgebase for the identification of these two diseases.

Les anticorps monoclonaux (AcM) ont été utilisés pour traiter des cancers dès le début des années 1980, en particulier lors du travail pionnier de l’équipe de Ronald Levy dans le traitement des lymphomes. Ces traitements ont pendant longtemps été considérés comme une sérothérapie passive à effet immédiat et à court terme. Cependant, au cours de ces dernières années, le concept d’un effet « vaccinal » des anticorps à usage thérapeutique en oncologie a peu à peu vu le jour du fait de réponses cliniques à long terme observées chez certains patients et de différentes études précliniques. En 2010, notre équipe a démontré que des souris immunocompétentes injectées avec les cellules tumorales EL4-huCD20 et traitées avec un AcM anti-huCD20 générait une réponse immunitaire anti-tumorale à long-terme par le biais de mécanismes dépendants de la région constante de l’anticorps et de lymphocytes T CD4+. Mon travail de thèse a donc porté sur l’analyse des mécanismes cellulaires et moléculaires par lesquels le traitement par un AcM anti-CD20 génère une immunité cellulaire adaptative anti-tumorale. J’ai ainsi pu montrer que le traitement des souris avec l’AcM anti-CD20 conduit à une expansion de lymphocytes Th1 producteurs d’IFN-γ, à l’apparition de lymphocytes T CD4+ effecteurs mémoires spécifiques des cellules tumorales CD20+, et au blocage de l’expansion de lymphocytes Tregs induite par les cellules tumorales. Le rôle central dans la protection anti-tumorale et la genèse d’une réponse adaptative anti-tumorale joué par l’axe IL-12/IFN-γ et leurs principales sources cellulaires, cellules dendritiques (DCs) et cellules NK, a été démontré par des expériences de neutralisation de ces cytokines, qui provoque une importante diminution du nombre de Th1 spléniques, de déplétion des cellules NK, ainsi que par des analyses phénotypiques qui ont permis d’identifier des DCs activées par le traitement - comme le montre l’expression accrue des molécules de classe II du CMH et de co-stimulation CD80 et CD86 - comme une importante source cellulaire de l’IL-12. Enfin, nous avons pu montrer qu’un variant de l’IL-2, liant préférentiellement le récepteur de l’IL-2By et faiblement le récepteur de l’IL-2aBy exprimé majoritairement par les Tregs, permettait l’obtention d’une protection anti-tumorale accrue d’animaux porteurs de tumeurs et traités par l’AcM anti-CD20. En conclusion, nous avons démontré qu’un contexte immunitaire pro-tumoral façonné par la présence d’une tumeur en développement peut être inversé par le traitement par un anticorps anti-tumoral, aboutissant à un contexte anti-tumoral. Qu’une telle réponse immunitaire adaptative cellulaire puisse être observée chez des patients atteints de lymphomes, traités par un anticorps anti-CD20, reste encore à être déterminé. / Monoclonal antibodies have been used to treat cancers since the early 1980s, in particular with the pioneer work of Ronald Levy for the treatment of lymphomas. Those treatments have been considered for a long time as a passive serotherapy with immediate and short term actions. Yet, recently, the idea of a vaccine effect of therapeutic antibodies in oncology have appeared, after preclinical studies and clinic observations suggesting a long term immune response in patients. In 2010, our team demonstrated that immunocompetent mice injected with EL4-huCD20 tumor cells and treated with anti-huCD20 monoclonal antibody generated a long term anti-tumor immune response linked with mechanisms dependent on constant part of antibodies and CD4+ T cells. My PhD work was based on the analysis of cellular and molecular mechanisms by which the treatment by an anti-CD20 mAb generates a cellar adaptive anti-tumor immunity. I could show that the treatment of mice with anti-CD20 antibody lead to the expansion of Th1 lymphocytes IFN-γ producers, to the apparition of effector memory CD4+ T cells specific for CD20 antigen, and to the blockade of the expansion of Treg cells induced by tumor cells. The key role of an adaptive anti-tumor immune response played by IL-12/IFN- γ and their main cellular sources, dendritic cells and NK cells, in the anti-tumor protection and genesis, has been demonstrated by experiments of cytokine neutralization, provoking an important decrease of splenic Th1 number, by NK depletion and by phenotypic analysis that allowed the identification of DCs activated by the treatment – as it is shown by the increased expression of MHC-II and CD80 and CD86 costimulation molecules, - as an important cellular source of IL-12. Finally, we could show that a variant of IL-2, binding preferentially IL-2By with a lower affinity for the IL-2aBy receptor mainly expressed by Tregs, could induce an increased anti-tumor protection of tumor-bearing animals treated with anti-CD20 mAb. In conclusion, we have demonstrated that a pro-tumor immune contexture affected by a growing tumor can be modified by an anti-tumor antibody leading to an anti-tumor contexture. That such cellular adaptive immune response could be observed in lymphoma patients treated with anti-CD20 still need to be determined.