Pre-clinical study of cancer often involves imaging different aspects of a tumor, ranging from visualizing sub-cellular detail to imaging of the tumor anatomy. Multimodal imaging seeks to combine imaging techniques with complementary strengths and use them to provide a more complete picture of the disease. In this dissertation work, the development of various optical, nuclear and magnetic resonance imaging (MRI) techniques applicable to the study of cancer xenografts in murine window chamber models was carried out. Two types of window chamber models were used in this work: the dorsal skinfold WC (DSFWC) model and the mammary WC (MWC) model. The MWC was specifically used to study breast cancer xenografts. In this work, optical pH imaging with a pH-sensitive fluorescent agent was used to evaluate methods to achieve tumor-specific pH modulation. Temporary tumor acidification was performed by administration of an agent that consists of glucose and meta-iodobenzylguanidine. On the other hand, re-normalization of pHₑ in acidic tumor tissue was achieved by administration of buffer solutions, such as sodium bicarbonate. A broadband reflectance spectral imaging system was developed to perform in vivo imaging of oxygen saturation in the MWC murine model. The imaging system was used to study tissue oxygenation changes in animals that receive chemotherapy. Preliminary results were obtained to evaluate the utility of the MWC murine model in imaging the spatiotemporal changes in oxygen saturation (SaO₂) as an early biomarker of response to neo-adjuvant chemotherapy. To study metabolic activity, nuclear imaging of radiolabeled fluorodeoxyglucose (18F-FDG) was carried out using a beta-imager, as well as a pre-clinical PET system. The 2D nuclear imaging capability of the beta-imager was cross-validated with the 3D PET imaging system. Anatomical and functional MRI was performed on the MWC murine model. Anatomical MRI was used to study tumor growth rates, which aid in the identification of animals that responded to chemotherapy. In addition, diffusion-weighted (DW) MRI, dynamic-contrast-enhancement (DCE) MRI, and perfusion MRI were performed to study various functional aspects of the tumor xenografts. Lastly, work was done to incorporate patient derived xenograft (PDX) tumors into the MWC murine model. As opposed to xenografts grown from cultured cancer cells, PDX tumors better recapitulate characteristics of human tumors. This new cancer model is aimed at improving the translational power of pre-clinical studies employing window chamber models.

Die Behandlung von Krebserkrankungen wurde in den letzten Jahren von zwei großen Trends beeinflusst. Statt zytotoxischer Therapien, wurden zielgerichtete monoklonale Antikörper entwickelt. Zudem verstärkten sich die Bemühungen in der Entwicklung prädiktiver Biomarker, die die Stratifizierung von Patienten vor der Behandlung ermöglichen. Obwohl hunderte von zielgerichteten Krebsmedikamenten entwickelt wurden, erreichten nur wenige davon eine Zulassung. Grund hierfür ist die noch hohe Ausfallrate bei der „Übersetzung“ von vielversprechenden präklinischen Daten, die mit Krebs-Zelllinien und Xenograft-Modellen von Krebs-Zelllinien erlangt wurden, in positive klinische Phase II- und Phase III-Daten. Das Ziel der Forschung ist es, neue zielgerichtete Therapien und gleichzeitig prädiktive Marker, mit Hilfe von verbesserten präklinischen Tumormodellen zu entwickeln. Ein Panel von 133 Xenograftmodellen aller vier UICC-Stadien wurde etabliert. Zur Überprüfung dieses Modells wurde die Wirksamkeit von Cetuximab, Bevacizumab und Oxaliplatin getestet. Für dieses Experiment benutzten wir 67 Xenograft-Modelle, die aus chemonaiven CRC-Patienten entwickelt wurden. Die Behandlung mit einer Cetuximab-Monotherapie ergab eine objektive Ansprechrate von 27%. Dank dieser hohen Ansprechrate, konnten wir das verfügbare Tumorgewebe zur Vorhersage der Reaktion auf die Anti-EGFR-Antikörper in den Xenograft-Modellen verwenden. Wir untersuchten die Genauigkeit von Mutations-Markern (KRAS, BRAF und PIK3CA) kombiniert mit RNA-Expressionsdaten von Amphiregulin und Epiregulin. Weiterhin wurden neue prädiktive Marker-Kombinationen, basierend auf einer mRNA- und microRNA- Expressionsanalyse, ermittelt. Aufgrund der erfolgreichen Nachbildung der klinischen Situation in unserem Panel von Xenograft-Modellen, zeigt dieser Modellansatz vielversprechendes Potenzial für eine zukünftige Anwendung in der Erprobung neuartiger Krebsmedikamente und der Entwicklung von prädiktiven Biomarkern. / Over the last ten years two major trends have influenced drug development. Instead of cytotoxic therapies a variety of targeted monoclonal antibodies have been developed. In parallel, higher attention has been paid to the identification and validation of predictive markers, which allow the stratification of patients prior to the treatment. Hundreds of targeted cancer drugs have been developed, but only a few have been approved. Despite these two trends, there is still a high rate of failure in translating promising preclinical data obtained with cancer cell lines and xenograft models derived from cancer cell lines into positive clinical phase II and phase III data. The goal of the scientific community is to develop novel targeted therapies and predictive biomarkers using better preclinical tumour models. To bridge the gap between preclinical and clinical development a panel of 133 patients-derived CRC xenografts of all four UICC stages was established. An efficacy of cetuximab, bevacizumab and oxaliplatin was tested in the subset of 67 models. In the treatment experiment with cetuximab monotherapy an objective response rate of 27% was obtained. This high response rate allowed the use of the tumour tissues for evaluating molecular markers for predicting response to the anti-EGFR antibody in the xenograft models. The accuracy of three mutation markers including KRAS, BRAF and PIK3CA was investigated in combination with RNA expression levels of two EGFR ligands – amphiregulin and epiregulin. Novel predictive markers panels based on gene expression profiling of mRNA and microRNA were also tested and compared with the established biomarkers. Successful reconstruction of the clinical situation in the panel of xenograft models proves their potential for future use in testing of novel anti-cancer drugs. Moreover, their broad molecular characterization allows the simultaneous development of predictive biomarkers along with the testing of novel cancer drugs.

La progression tumorale est un processus multi-étapes dépendant notamment des interactions entre les cellules cancéreuses et le stroma environnant. Le développement du cancer du sein implique une communication étroite entre les cellules épithéliales mammaires, les cellules inflammatoires, les myofibroblastes et les cellules endothéliales. Ainsi, le microenvironnement tumoral apparaît comme une cible de choix dans le traitement anti-tumoral. L’utilisation de modèles précliniques est une étape clé dans le développement et la validation de nouvelles thérapies. Néanmoins, peu d’études sont disponibles sur le rôle du stroma péri-tumoral dans ces modèles.Dans le but d’étudier le stroma péri-tumoral des modèles précliniques de cancers du sein, nous avons combiné une analyse par cytométrie en flux à une analyse par immunohistochimie afin d’identifier, puis de quantifier, les différentes populations stromales hématopoïétiques (lymphocytes, monocytes/macrophages, polynucléaires) et non hématopoïétiques (myofibroblastes, cellules endothéliales). Vingt et un modèles de xénogreffe de tumeurs humaines de cancers du sein ainsi que 2 modèles transgéniques (MMTV-PyMT et MMTV-ErbB2), ainsi que leurs allogreffes respectives, furent utilisés lors de ce travail.Les analyses des tumeurs humaines et murines ont montré un infiltrat stromal très hétérogène d’une tumeur à l’autre, avec pour composante majoritaire les macrophages. Un infiltrat important en polynucléaires a également été détecté dans les modèles de PDX, caractéristique d’une inflammation locale importante dans ces modèles. L’analyse phénotypique de macrophages a montré une expression variable de marqueurs M1 et M2 dans les modèles de PDX. Les macrophages issus de tumeurs murines transgéniques, spontanées ou allogreffées, présentaient quant à eux un profil majoritairement M1. L’étude transcriptomique de macrophages triés, a permis à la fois de valider les résultats obtenus au niveau protéique mais a également mis en évidence des différences majeures dans l’expression de nombreux gènes, impliqués dans des voies de signalisation variées telles que la croissance tumorale, l’invasion et la métastase.Cette étude nous a permis de mettre en évidence le rôle de la tumeur sur son microenvironnement. En effet, celle-ci est à la fois capable d’attirer un panel de cellules stromales qui lui et propre et ensuite de l’activer de façon spécifique. / Tumor development is a multi-step process influencing by interactions between tumor cells and surrounding stroma. Breast cancer development involves a high level of communication between mammary epithelial cells, inflammatory cells, myofibroblasts and endothelial cells. So, the tumoral microenvironment appears as a prime target for anti-tumoral treatment. The use of preclinical models is a critical step in development and validation processes of new therapies. Nevertheless, the role of stroma in these models is poorly understood.In order to evaluate stromal cell populations in breast cancer preclinical models, we combined flow cytometry analysis and immunohistochemistry to identify, and then quantify, various stromal populations as hematopoietic cells (lymphocytes, monocytes/macrophages, polymorphonuclear leukocytes) and non-hematopoietic cells (myofibroblasts, endothelial cells). Twenty-one breast cancer patient-derived xenografts as well as 2 transgenic mouse models (MMTV-PyMT and MMTV-ErbB2), and their respective allografts, were studied.Analysis of human and murine tumors showed a strong heterogeneity between tumors regarding infiltrating stroma-cells, with a high proportion of macrophages. A significant amount of polymorphonuclear leukocytes was also detected in PDXs, indicating a local inflammation in these models. The phenotypic analysis of macrophages showed a variable expression of M1 and M2 markers in PDXs. Macrophages infiltrating transgenic mouse tumors, spontaneous or allografted, were mainly M1. Transcriptomic analyses of sorted macrophages, allowed us to validate previous results but also highlighted major differences in the expression of numerous genes implicated in various pathways as tumor growth, invasion and metastasis.Finally, this study highlighted the impact of tumor cells on their surrounding stroma. Indeed, we demonstrate that cancer cells are able to attract a specific panel of stromal cells and activate them in a specific way.