La réponse immunitaire est régulée spatialement et temporellement. Les cellules immunitaires font partie d’une plus grande communauté de populations cellulaires interconnectées qui coordonnent leurs actions par la signalisation intercellulaire. Suivant une blessure hépatique, la distribution et la composition du compartiment immunitaire évoluent rapidement au fil du temps. Par conséquent, l’information sur la position des cellules immunitaires dans le tissu hépatique est essentielle à la bonne compréhension de leurs fonctions dans la santé et la maladie. Cependant, l’organisation spatiale des cellules immunitaires en réponse à une atteinte hépatique aiguë, ainsi que les conséquences fonctionnelles de leur distribution topographique spécifique, restent mal comprises. Les macrophages hépatiques sont des cellules effectrices clés pendant l’homéostasie et en réponse à des blessures, et sont impliqués dans la pathogenèse de plusieurs maladies du foie. L’hétérogénéité et plasticité des macrophages dans le foie a été exposée avec l’émergence du séquençage de l’ARN, la cytométrie en flux et la cytométrie de masse. Ces techniques ont sensiblement contribué à la compréhension de l’origine, et fonctions des macrophages dans le foie. Cependant, ces technologies impliquent la destruction du tissu pour la préparation de suspension cellulaires ce qui entraîne une perte d’information spatiale et de contexte tissulaire. Par conséquent, la caractérisation spatiale et temporelle des macrophages dans le tissu hépatique pendant l’homéostasie tissulaire, et en réponse à une blessure, fournit une nouvelle information sur la façon dont les macrophages se rapportent aux cellules voisines et leur comportement pendant les réponses immunitaires. Dans la première partie de cette étude, nous avons conçu une stratégie pour le phénotypage spatial des cellules immunitaires hépatiques dans des échantillons de tissus. Cette stratégie combine techniques d'imagerie et l’alignement numérique des images pour surmonter les limitations actuelles du nombre de marqueurs pouvant être visualisés simultanément. En outre, nous avons généré des protocoles pour la quantification automatisée des cellules d’intérêt dans des sections de tissus pour réduire la subjectivité associée à la quantification par inspection visuelle, et pour augmenter la surface et la vitesse de l’analyse. Par conséquent, un plus grand nombre de populations de cellules immunitaires ont été visualisées, quantifiées et cartographiées, et leurs relations spatiales ont été déterminées. Dans la deuxième partie de l’étude, nous avons déterminé la cinétique et la dynamique spatiale des cellules de Kupffer (KCs) et des macrophages dérivés de monocytes (MoMFs) en réponse à une atteinte hépatique aiguë au CCl4, afin de mieux comprendre leurs rôles fonctionnels, et la répartition du travail entre eux. Nous avons constaté que les KC et les MoMFs présentent des différences au niveau de la distribution tissulaire, la morphologie, et la cinétique. En plus, seulement les KCs ont proliféré pour repeupler la population de macrophages résidents pendant la réparation tissulaire. Finalement, nous avons montré que le degré de colocalization de KCs et des MoMFs avec les cellules stellaires est différent. En plus, cette colocalisation varie avec la progression de la réponse immunitaire. Dans l’ensemble, nous avons montré que les KCs et les MoMFs ont des profils spatiaux et temporels différents en réponse à une atteinte hépatique aiguë. Dans l’ensemble, les observations faites dans cette étude suggèrent que le comportement spatial et temporel d’une sous-population donnée de cellules immunitaires est distinct et sous-tend sa capacité à remplir ses fonctions spécifiques pendant la réponse immunitaire. / The immune response is spatially and temporally regulated. Immune cells are part of a larger community of interconnected immune and non-immune cell populations that coordinate their actions mostly through cell-cell intercellular signaling. In the liver, the distribution pattern, and the composition of the immune compartment evolve during an immune response to injury influencing disease pathology, progression, and response to treatment. Hence, information on the location and interacting partners of immune cells in the hepatic tissue is critical for the proper understanding of their functions in health and disease. However, the spatial organization of hepatic resident and infiltrating immune cells in response to acute injury, and the functional consequences of their specific topographical distribution, remain poorly defined. Hepatic macrophages are key effector cells during homeostasis and in response to injury and are involved in the pathogenesis of several liver diseases. The heterogeneity and plasticity of the macrophage compartment in the liver have only recently started to be appreciated with the emergence of RNA sequencing, flow cytometry, and mass cytometry. Detailed transcriptomic and phenotypic profiling have deeply expanded our understanding of macrophage biology. However, these technologies involve tissue disruption with loss of spatial information and tissue context. Therefore, the spatial and temporal profiling of liver macrophages in tissue samples during the steady state, and in response to injury, provide novel information on how the macrophages relate to neighboring cells and their behavior during immune responses. In the first part of this study, we designed a strategy for the spatial phenotyping of hepatic immune cells in tissue samples. This strategy combined serial and sequential labeling, and digital tissue alignment to overcome current limitations in the number of markers that can be simultaneously visualized. In addition, we generated protocols for automated quantification of cells of interest in whole tissue sections which removed the subjectivity associated with quantification by visual inspection and greatly increased the area and the speed of the analysis. As a result, a larger number of immune cell populations were visualized, quantified, and mapped, and their spatial relations were determined in an unbiased manner. In the second part of this study, we monitored the kinetics, and spatial dynamics of resident Kupffer cells (KCs) and infiltrating monocyte-derived macrophages (MoMFs) in response to acute liver injury with CCl4, to gain insight into their functional roles, and the distribution of labor between them. KCs and MoMFs exhibited different tissue distribution patterns and cell morphology, different kinetics, and occupied neighboring but unique microanatomical tissue locations. KCs and MoMFs displayed a different capacity to replenish the macrophage pool upon acute injury, and were differentially related to hepatic stellate cells. Different kinetics and spatial profiles revealed that KCs and MoMFs have distinct spatial signatures and suggest that they perform distinct functions during the wound-healing response to acute liver injury. In summary, we optimized techniques and put together a strategy for the spatial profiling of hepatic immune cells. Then, we used this methodology to profile resident and infiltrating macrophage subpopulations to gain insight into their biology and distinct contribution to healing in response to acute liver injury. Overall, the observations made in this study suggest that the spatial and temporal behavior of a given subpopulation of immune cells underlie its ability to perform its specific functions during the immune response.

Despite the possible common histopathological features at diagnosis, cancer cells present within breast carcinomas are highly heterogeneous in their molecular signatures. This heterogeneity is responsible for disparate clinical behaviors, treatment responses and long-term outcomes in breast cancer patients. Although the few histopathological markers can partially describe the diversity of cells found in tumor tissue sections, the full molecular characterization of individual cancer cells is currently impossible in routine clinical practice. In this respect, Fourier transform infrared (FTIR) microspectroscopic imaging of histological sections allows obtaining, for each pixel of tissue images, hundreds of independent potential markers, which makes this technique a particularly powerful tool to distinguish cell types and subtypes. As a complement to the conventional clinicopathological evaluation, this spectroscopic approach has the potential to directly reveal molecular descriptors that should allow identifying different clonal lineages found within a single tumor and therefore provide knowledge relevant to diagnosis, prognosis and treatment personalization. Yet, interpretation of infrared (IR) spectra acquired on tissue sections requires a well-established calibration, which is currently missing. Conventionally, mammary epithelial cells are studied in vitro as adherent two-dimensional (2D) monolayers, which lead to the alteration of cell-microenvironmental interplay and consequently to the loss of tissue structure and function. A number of key in vivo-like interactions may be re-established with the use of three-dimensional (3D) laminin-rich extracellular matrix (lrECM)-based culture systems. The aim of this thesis is to investigate by FTIR imaging the influence of the in vitro growth environment (2D culture versus 3D lrECM culture and 3D monoculture versus 3D co-culture with fibroblasts) on a series of thirteen well-characterized human breast cancer cell lines and to determine culture conditions generating spectral phenotypes that are closer to the ones observed in malignant breast tissues. The reference cell lines cultured in a physiologically relevant basement membrane model and having undergone formalin fixation, paraffin embedding (FFPE), a routine treatment used to preserve clinical tissue specimens, could contribute to the construction of a spectral database. The latter could be ultimately employed as a valuable tool to interpret IR spectra of cells present in tumor tissue sections, particularly through the recognition of unique spectral markers.To achieve the goal, we developed and optimized, in a first step, the preparation of samples derived from traditional 2D and 3D lrECM cell cultures in order to preserve their morphological and molecular relevance for FTIR microspectroscopic analysis. We then highlighted the importance of the influence of the growth environment on the cellular phenotype by comparing spectra of 2D- and 3D-cultured breast cancer cell lines between them. A particular focus was placed to establish a correlation between FTIR spectral data and publicly available microarray-based gene expression patterns of the whole series of breast cancer cell lines grown in 2D and 3D lrECM cultures. Our results revealed that, although based on completely different principles, gene expression profiling and FTIR spectroscopy are similarly sensitive to both the cell line identity and the phenotypes induced by cell culture conditions. We also identified by FTIR imaging changes in the chemical content occurring in the microenvironment surrounding cell spheroids grown in 3D lrECM culture model. Finally, we illustrated the impact of the in vivo-like microenvironment on the IR spectra of breast cancer cell lines grown in 3D lrECM co-culture with fibroblasts and compared them with spectra of cell lines grown in 3D lrECM monoculture. Unsupervised statistical data analyses reported that cells grown in 3D co-cultures produce spectral phenotypes similar to the ones observed in FFPE tumor tissue sections from breast carcinoma patients. Altogether, our results suggest that FFPE samples prepared from 3D lrECM cultures of breast cancer cell lines and studied by FTIR microspectroscopic imaging provide reliable information that could be integrated in the setting up of a recognition model aiming to identify and interpret specific spectral signatures of cells present in breast tumor tissue sections. / Le cancer du sein est une maladie très hétérogène, tant au niveau clinique que biologique. Cette hétérogénéité rend impossible la caractérisation moléculaire complète des cellules cancéreuses individuelles dans la pratique clinique courante. Dans ce contexte, l’imagerie infrarouge à transformée de Fourier (FTIR) des coupes tissulaires permet d'obtenir pour chaque pixel d'une image de tissu des centaines de marqueurs potentiels indépendants, ce qui pourrait faire de cette technique un outil particulièrement puissant pour identifier des différents types et sous-types cellulaires. L'interprétation des spectres infrarouges (IR) enregistrés à partir des coupes histologiques nécessite cependant une calibration qui fait actuellement défaut. Cette calibration pourrait être obtenue à partir de lignées cellulaires tumorales bien caractérisées. Traditionnellement, les cellules épithéliales mammaires sont étudiées in vitro sous forme de monocouches adhérentes bidimensionnelles (2D), ce qui conduit à l'altération de la communication entre les cellules et leur environnement et, par conséquent, à la perte de l’architecture et de la fonction du tissu épithélial. Un certain nombre d'interactions physiologiques clés peuvent être rétablies en utilisant des systèmes de culture tridimensionnelle (3D) dans une matrice extracellulaire riche en laminine (lrECM). L'objectif de cette thèse consiste à étudier par imagerie FTIR l'influence du microenvironnement (via une comparaison entre les cultures 2D et 3D lrECM ou les cultures 3D lrECM en présence ou en l’absence de fibroblastes) sur une série de treize lignées de cellules tumorales mammaires humaines bien caractérisées et à déterminer les conditions de culture générant des phénotypes spectraux qui se rapprochent le plus de ceux observés dans les tissus tumoraux. Au cours de ce travail, nous avons mis au point la culture des lignées cellulaires dans un modèle 3D lrECM ainsi qu’une méthodologie de préparation des échantillons offrant la possibilité de les comparer de manière pertinente avec les cellules cancéreuses présentes dans les coupes histologiques. De même, nous avons étudié par imagerie FTIR les effets du microenvironnement sur les lignées de cellules tumorales et inversement. Pour les lignées investiguées, le passage d’une culture 2D à une culture 3D lrECM s’accompagne, en effet, de modifications du spectre IR étroitement corrélées aux modifications du transcriptome. Les marqueurs spectraux indiquent également que l’environnement 3D génère un phénotype cellulaire proche de celui trouvé dans les coupes histologiques. De manière intéressante, cette proximité est d’autant plus renforcée en présence de fibroblastes dans le milieu de culture. / Doctorat en Sciences agronomiques et ingénierie biologique / info:eu-repo/semantics/nonPublished

Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma. It is a molecular and prognostic heterogeneous disease. Three main genetic subtypes are called germinal center-like DLBCL (GC-like DLBCL), non-germinal center-like DLBCL (nonGC-like DLBCL) and primary mediastinal B-cell lymphoma (PMBL). These subtypes can be reliably distinguished only with usage of gene expression profiling (GEP). The GEP method can be applied only when fresh frozen tissue is available. The method is technically difficult and expensive. Thus, it is not used routinely. Since the DLBCL subtypes differ in prognosis, it is extremely important to be able to distinguish them. The presented thesis is focused on distinguishing of PMBL diagnosis in the group of DLBCL. Easily stored formalin-fixed, paraffin-embedded tissue (FFPE) and gene expression analysis using real-time quantitative polymerase chain reaction (RTqPCR) are used. In the first step, PMBL and DLBCL cases were distinguished with an internationally accepted clinical-pathological method. The agreement between clinical-pathological diagnosis and GEP is only 76%. In the presented text a genetic algorithm for PMBL/DLBCL distinguishing is suggested. It uses three carefully chosen genes and their expression is measured with RTqPCR. Both, the...

Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma. It is a molecular and prognostic heterogeneous disease. Three main genetic subtypes are called germinal center-like DLBCL (GC-like DLBCL), non-germinal center-like DLBCL (nonGC-like DLBCL) and primary mediastinal B-cell lymphoma (PMBL). These subtypes can be reliably distinguished only with usage of gene expression profiling (GEP). The GEP method can be applied only when fresh frozen tissue is available. The method is technically difficult and expensive. Thus, it is not used routinely. Since the DLBCL subtypes differ in prognosis, it is extremely important to be able to distinguish them. The presented thesis is focused on distinguishing of PMBL diagnosis in the group of DLBCL. Easily stored formalin-fixed, paraffin-embedded tissue (FFPE) and gene expression analysis using real-time quantitative polymerase chain reaction (RTqPCR) are used. In the first step, PMBL and DLBCL cases were distinguished with an internationally accepted clinical-pathological method. The agreement between clinical-pathological diagnosis and GEP is only 76%. In the presented text a genetic algorithm for PMBL/DLBCL distinguishing is suggested. It uses three carefully chosen genes and their expression is measured with RTqPCR. Both, the...