The thesis provides a comprehensive overview of key issues affecting practice, policy and patients, in current efforts for colorectal cancer (CRC) disease control. The global burden of CRC is expected to increase by 60% to more than 2.2 million new cases and 1.1 million deaths by 2030. CRC incidence and mortality rates vary up to 10-fold worldwide, which is thought to reflect variation in lifestyles, especially diet. Better primary prevention, and more effective early detection, in screening and surveillance, are needed to reduce the number of patients with CRC in future1. The risk factors for CRC development include genetic, behavioural, environmental and socio-economic factors. Changes to surveillance, which offer non-invasive testing and provide primary prevention interventions represent promising opportunities to improve outcomes and personalise care in those at risk of CRC. By systematic review of the literature, I highlight the gaps in comparative effectiveness analyses of post-polypectomy surveillance. Using micro-simulation methods I assess the role of non-invasive, faecal immunochemical testing in surveillance programmes, to optimise post-polypectomy surveillance programmes, and in an accompanying sub-study, I explore the value of adding an adjunct diet and lifestyle intervention. The acceptability of such revisions is exposed to patient preference evaluation by discrete choice experiment methods. These preferences are accompanied by evidence generated from the prospective evaluation of the health literacy, numeracy, sedentary behaviour levels, body mass index (BMI) and information provision about cancer risk factors, to highlight the potential opportunities for personalisation and optimisation of surveillance. Additional analysis examines the optimisation of a screening programme facing colonoscopy constraints, highlighting the attendant potential to reduce costs and save lives within current capacity.

Connor O’Hara July 29, 2019 Inhibition of Cancer Stem Cells by Glycosaminoglycan Mimetics In the United States cancer is the second leading cause of death, with colorectal cancer (CRC) being the third deadliest cancer and expected to cause over 51,000 fatalities in 2019 alone.1 The current standard of care for CRC depends largely on the staging, location, and presence of metastasis.2 As the tumor grows and invades nearby lymph tissue and blood vessels, CRC has the opportunity to invade not only nearby tissue but also metastasize into the liver and lung (most commonly).3 The 5-year survival rate for metastasized CRC is <15%, and standard of care chemotherapy regimens utilizing combination treatments only marginally improve survival.3-5 Additionally, patients who have gone into remission from late-stage CRC have a high risk of recurrence despite advances in treatment.6-7 The Cancer Stem-like Cell (CSC) paradigm has grown over the last 20 years to become a unifying hypothesis to support the growth and relapse of tumors previously regressed from chemotherapy (Figure 1).8 The paradigm emphasizes the heterogeneity of a tumor and its microenvironment, proposing that a small subset of cells in the tumor are the source of tumorigenesis with features akin to normal stem cells.9 The CSCs normally in a quiescent state survive this chemotherapy and “seed” tumor redevelopment.10 First observed in acute myeloid lymphoma models, CSCs have since been identified in various other cancers (to include CRC) by their cell surface antigens and unique properties characterizing them from normal cancer cells.11-12 These include tumor initiation, limitless self-renewal capacity to generate clonal daughter cells, as well as phenotypically diverse, mature, and highly differentiated progeny.13-14 Previously our lab has identified a novel molecule called G2.2 (Figure 2) from a unique library of sulfated compounds showing selective and potent inhibition of colorectal CSCs in-vitro.15 G2.2 is a mimetic of glycosaminoglycans (GAGs) and belongs to a class of molecules called non-saccharide GAG mimetics (NSGMs). Using a novel dual-screening platform, comparisons were made on the potency of G2.2 in bulk monolayer cells, primary 3D tumor spheroids of the same cell line, and subsequent generations of tumor spheroids. This work has shown in-vitro the fold-enhancement of CSCs when culturing as 3D tumor spheroids. Spheroid culture serves as a more accurate model for the physiological conditions of a tumor, as well as the functional importance of upregulating CSCs. Evaluation of G2.2 and other NSGMs was performed in only a few cell lines, developing a need to better understand the ability of G2.2 to inhibit spheroids from a more diverse panel of cancer cells to better understand G2.2’s mechanism. The last few decades have seen the advancement in fundamental biological and biochemical knowledge of tumor cell biology and genetics.16 CRC, in particular, has served as a useful preclinical model in recapitulating patient tumor heterogeneity in-vitro.17 Recent work has characterized the molecular phenotypes of CRC cell lines in a multi-omics analysis, stratifying them into 4 clinically robust and relevant consensus molecular subtypes (CMS).18-19 Our work was directed to screen a panel of cells from each of the molecular subtypes and characterize the action of G2.2 and 2nd generation lipid-modified analogs, synthesized to improve the pharmacokinetic properties of the parent compound. Four NSGMs, namely G2.2, G2C, G5C, and G8C (Figure 2) were studied for their ability to inhibit the growth of primary spheroids across a phenotypically diverse panel. Compound HT-29 IC50 (μM) Panel Average IC50 (μM) G2.2 28 ± 1 185 ± 55 G2C 5 ± 2 16 ± 15 G5C 8 ± 2 63 ± 19 G8C 0.7 ± 0.2 6 ± 3 Primary spheroid inhibition assays were performed comparing the potency of new NSGMs to G2.2. Fifteen cell lines were evaluated in a panel of colorectal adenocarcinoma cell lines with several cell lines representing each CMS. Primary spheroid inhibition assays revealed 3 distinct response with regard to G2.2’s ability to inhibit spheroid growth. Cells from CMS 3 and 4, which display poor clinical prognosis, metabolic dysregulation, and enhanced activation of CSC pathways, showed the most sensitivity to G2.2 (mean IC50 = 89 ± 55 μM). Mesenchymal CMS 4 cell lines were over 3-fold more sensitive to treatment with G2.2 when compared to CMS 1 cell lines. Resistant cell lines were composed entirely of CMS 1 and 2 (mean IC50 = 267 ± 105 μM). In contrast, all lipid-modified analogs showed greater potency than the parent NSGM in almost every CRC cell line. Of the three analogs, G8C showed the greatest potency with a mean IC50 of less than 15 μM. Of the CRC spheroids studied, HT-29 (CMS 3) was most sensitive to G8C (IC50 = 0.73 μM). To evaluate the selectivity of NSGMs for CSC spheroid inhibition, MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium) cytotoxicity assays were performed on monolayer cell culture, and the fold-selectivity of NSGM for spheroids was analyzed. Data shows that NSGMs preferentially target CSC-rich spheroids compared with monolayer cellular growth, with G2.2 having over 7-fold selectivity for spheroid conditions. This fold selectivity was enhanced in CMS 3/4, supporting the idea that G2.2 targets a mesenchymal and stem-like phenotype. To further validate this selectivity, limiting dilution assays were performed across the panel to determine the tumor-initiating capacity of each cell line. Cell lines which showed a sensitive response to G2.2 were over 2-fold more likely to develop into spheroids, validating the previous hypothesis. Further characterization was performed analyzing the changes G2.2 induced on CSC markers, as well as the basal expression of a unique pair of cancer cells. Western blots showed a reduction in self-renewal marker across all CMS after treatment with G2.2, and that cell lines sensitive to G2.2-treatment overexpress mesenchymal and stem-like markers. G2.2-resistant cell lines show an epithelial phenotype, lacking this expression. The positive results observed in these studies enhance the understanding of G2.2 and analogs, and further evaluation with additional cell lines of various tissues would improve the knowledge thus far gained. However, all experiments described take valuable time to perform and analyze. Thus, there became a need to develop a high-throughput screening (HTS) platform for our assays that standardized analysis and enhanced productivity. Initial development of the method for this assay are underway, and recent evidence from these evaluations of breast cancer spheroids suggests that G2.2 and analogs may be tissue-specific compounds for the treatment of cancer. Future work entails refining the application of this method for evaluation of the NCI-60 (National Cancer Institute) tumor cell panel. Overall, these results make several suggestions concerning the NSGMs evaluated against the panel. First, G2.2 selectively targets CSCs with limited toxicity to monolayer cells of the same cell line. Further, G2.2 has the greatest potency with CMS 3/4, whose mesenchymal phenotypes are associated with poor clinical prognosis and enrichment of CSCs. Supporting evidence include that sensitive cell lines are highly tumorigenic and show enhanced expression of mesenchymal/CSC markers compared to resistant cell lines. Lipid-modification of G2.2 enhances in-vitro potency against spheroid growth, with nM potency reached in the most sensitive cell lines. Evidence in the development of a HTS platform also suggests these NSGMs show tissue specificity to cancers of the intestine. Further work characterizing the mechanism of NSGMs in a broader multi-tissue panel will enhance our understanding of the compounds as a potential therapy to dramatically improve patient survival through specific targeting of tumorigenesis. References 1. Colorectal Cancer Facts & Figures 2017-2019. American Cancer Society 2017. 2. Compton, C. C.; Byrd, D. R.; Garcia-Aguilar, J.; Kurtzman, S. H.; Olawaiye, A.; Washington, M. K. Colon and rectum. In AJCC Cancer Staging Atlas, 2nd ed.; Ed. Springer Science: New York, 2012; pp 185–201. 3. Van Cutsem, E.; Cervantes, A.; Adam, R.; Sobrero, A.; Van Krieken, J. H.; Aderka, D.; Aranda Aguilar, E.; Bardelli, A.; Benson, A.; Bodoky, G.; et al. ESMO consensus guidelines for the management of patients with metastatic colorectal cancer. Ann. Oncol. 2016, 27, 1386–422. 4. Siegel, R. L.; Miller, K. D.; Fedewa, S. A.; Ahnen, D. J.; Meester, R. G. S.; Barzi, A.; Jemal, A. Colorectal cancer statistics, 2017. CA Cancer J. Clin. 2017, 67, 177–193. 5. Moriarity, A.; O'Sullivan, J.; Kennedy, J.; Mehigan, B.; McCormick, P. Current targeted therapies in the treatment of advanced colorectal cancer: a review. Ther. Adv. Med. Oncol. 2016, 8, 276–293. 6. Seidel, J.; Farber, E.; Baumbach, R.; Cordruwisch, W.; Bohmler, U.; Feyerabend, B.; Faiss, S. Complication and local recurrence rate after endoscopic resection of large high-risk colorectal adenomas of >/=3 cm in size. Int. J. Colorectal Dis. 2016, 31, 603–611. 7. Pugh, S. A.; Shinkins, B.; Fuller, A.; Mellor, J.; Mant, D.; Primrose, J. N. Site and stage of colorectal cancer influence the likelihood and distribution of disease recurrence and postrecurrence survival: data from the FACS randomized controlled trial. Ann. Surg. 2016, 263, 1143–1147. 8. Batlle, E.; Clevers, H. Cancer stem cells revisited. Nat. Med. 2017, 23, 1124–1134. 9. Hanahan, D.; Weinberg, R. A. Hallmarks of cancer: the next generation. Cell 2011, 144, 646–674. 10. Tirino, V.; Desiderio, V.; Paino, F.; De Rosa, A.; Papaccio, F.; La Noce, M.; Laino, L.; De Francesco, F.; Papaccio, G. Cancer stem cells in solid tumors: an overview and new approaches for their isolation and characterization. FASEB J. 2013, 27, 13–24. 11. Bonnet, D.; Dick, J. E. Human acute myeloid leukemia is organized as a hierarchy that originates from a primitive hematopoietic cell. Nat. Med. 1997, 3, 730–737. 12. Desai, A.; Yan, Y.; Gerson, S. L. Concise reviews: cancer stem cell targeted therapies: toward clinical success. Stem Cells Transl. Med. 2019, 8, 75–81. 13. Munro, M. J.; Wickremesekera, S. K.; Peng, L.; Tan, S. T.; Itinteang, T. Cancer stem cells in colorectal cancer: a review. J. Clin. Pathol. 2018, 71, 110–116. 14. Zhou, Y.; Xia, L.; Wang, H.; Oyang, L.; Su, M.; Liu, Q.; Lin, J.; Tan, S.; Tian, Y.; Liao, Q.; Cao, D. Cancer stem cells in progression of colorectal cancer. Oncotarget 2018, 9, 33403–33415. 15. Patel, N. J.; Karuturi, R.; Al-Horani, R. A.; Baranwal, S.; Patel, J.; Desai, U. R.; Patel, B. B. Synthetic, non-saccharide, glycosaminoglycan mimetics selectively target colon cancer stem cells. ACS Chem. Biol. 2014, 9, 1826–1833. 16. Punt, C. J.; Koopman, M.; Vermeulen, L. From tumour heterogeneity to advances in precision treatment of colorectal cancer. Nat. Rev. Clin. Oncol. 2017, 14, 235–246. 17. Mouradov, D.; Sloggett, C.; Jorissen, R. N.; Love, C. G.; Li, S.; Burgess, A. W.; Arango, D.; Strausberg, R. L.; Buchanan, D.; Wormald, S.; et al. Colorectal cancer cell lines are representative models of the main molecular subtypes of primary cancer. Cancer Res. 2014, 74, 3238–3247. 18. Guinney, J.; Dienstmann, R.; Wang, X.; de Reynies, A.; Schlicker, A.; Soneson, C.; Marisa, L.; Roepman, P.; Nyamundanda, G.; Angelino, P.; et al. The consensus molecular subtypes of colorectal cancer. Nat. Med. 2015, 21, 1350–1356. 19. Berg, K. C. G.; Eide, P. W.; Eilertsen, I. A.; Johannessen, B.; Bruun, J.; Danielsen, S. A.; Bjornslett, M.; Meza-Zepeda, L. A.; Eknaes, M.; Lind, G. E.; et al. Multi-omics of 34 colorectal cancer cell lines - a resource for biomedical studies. Mol. Cancer 2017, 16, 116–132.

Au cours de la dernière décennie, la pathologie numérique a été améliorée grâce aux avancées des algorithmes d'analyse d'images et de la puissance de calcul. Néanmoins, le diagnostic par un expert à partir d'images histopathologiques reste le gold standard pour un nombre considérable de maladies notamment le cancer. Ce type d'images préserve la structure des tissus aussi proches que possible de leur état vivant. Ainsi, cela permet de quantifier les objets biologiques et de décrire leur organisation spatiale afin de fournir une description plus précise des tissus malades. L'analyse automatique des images histopathologiques peut avoir trois objectifs: le diagnostic assisté par ordinateur, l'évaluation de la sévérité des maladies et enfin l'étude et l'interprétation des mécanismes sous-jacents des maladies et leurs impacts sur les objets biologiques. L'objectif principal de cette thèse est en premier lieu de comprendre et relever les défis associés à l'analyse automatisée des images histologiques. Ensuite, ces travaux visent à décrire les populations d'objets biologiques présents dans les images et leurs relations et interactions à l'aide des statistiques spatiales et également à évaluer la significativité de leurs différences en fonction de la maladie par des tests statistiques. Après une étape de séparation des populations d'objets biologiques basée sur la couleur des marqueurs, une extraction automatique de leurs emplacements est effectuée en fonction de leur type, qui peut être ponctuel ou surfacique. Les statistiques spatiales, basées sur la distance pour les données ponctuelles, sont étudiées et une fonction originale afin de mesurer les interactions entre deux types de données est proposée. Puisqu'il a été montré dans la littérature que la texture d'un tissu est altérée par la présence d'une maladie, les méthodes fondées sur les motifs binaires locaux sont discutées et une approche basée sur une modification de la résolution de l'image afin d'améliorer leur description est introduite. Enfin, les statistiques descriptives et déductives sont appliquées afin d'interpréter les caractéristiques extraites et d'étudier leur pouvoir discriminant dans le cadre de l'étude des modèles animaux de cancer colorectal. Ce travail préconise la mesure des associations entre différents types d'objets biologiques pour mieux comprendre et comparer les mécanismes sous-jacents des maladies et leurs impacts sur la structure des tissus. En outre, nos expériences confirment que l'information de texture joue un rôle important dans la différenciation des deux modèles d'implantation d'une même maladie. / During the last decade, digital pathology has been improved thanks to the advance of image analysis algorithms and calculus power. However, the diagnosis from histopathology images by an expert remains the gold standard in a considerable number of diseases especially cancer. This type of images preserves the tissue structures as close as possible to their living state. Thus, it allows to quantify the biological objects and to describe their spatial organization in order to provide a more specific characterization of diseased tissues. The automated analysis of histopathological images can have three objectives: computer-aided diagnosis, disease grading, and the study and interpretation of the underlying disease mechanisms and their impact on biological objects. The main goal of this dissertation is first to understand and address the challenges associated with the automated analysis of histology images. Then it aims at describing the populations of biological objects present in histology images and their relationships using spatial statistics and also at assessing the significance of their differences according to the disease through statistical tests. After a color-based separation of the biological object populations, an automated extraction of their locations is performed according to their types, which can be point or areal data. Distance-based spatial statistics for point data are reviewed and an original function to measure the interactions between point and areal data is proposed. Since it has been shown that the tissue texture is altered by the presence of a disease, local binary patterns methods are discussed and an approach based on a modification of the image resolution to enhance their description is introduced. Finally, descriptive and inferential statistics are applied in order to interpret the extracted features and to study their discriminative power in the application context of animal models of colorectal cancer. This work advocates the measure of associations between different types of biological objects to better understand and compare the underlying mechanisms of diseases and their impact on the tissue structure. Besides, our experiments confirm that the texture information plays an important part in the differentiation of two implemented models of the same disease.

Une dérégulation de la voie de signalisation Ras/Raf/MEK/ERK1/2 est observée dans plus de 30% des cancers et des mutations activatrices de RAS sont observées dans 30% à 50% des adénomes colorectaux. À la suite d’une analyse extensive de biopsies de tumeurs colorectales humaines par micromatrices tissulaires (TMA), nous avons observé que 44% des tissus cancéreux exprimaient MEK1/2 phosphorylés, contre 10% des tissus normaux. L'analyse des TMA a également révélé que 79% des tumeurs arboraient un marquage nucléaire de MEK1/2 phosphorylés, contre 4 % pour les tissus normaux. Bien que la voie MEK/ERK1/2 soit fréquemment activée dans les cancers, le rôle précis des isoformes de MEK1 et de MEK2 n'a jamais été clairement établie. De même, l'impact de cette localisation nucléaire aberrante de phospho-MEK1/2, dans l'initiation et la progression des cancers colorectaux, est inconnu. Lors d'un premier projet, nous avons démontré, que l’expression de MEK1 ou MEK2 activé est suffisante pour transformer in vitro des cellules intestinales épithéliales de rat (IEC-6). L'expression des mutants actifs de MEK1 ou MEK2 est suffisante pour induire une dérégulation de la prolifération cellulaire et engendrer la formation d'adénocarcinomes invasifs dans un modèle de greffe orthotopique du côlon chez la souris. Nous avons également démontré que l'inhibition de MEK2 par shRNA supprime complètement la prolifération des lignées humaines de cancer du côlon, alors que la suppression de MEK1 a peu d'effet sur la capacité de prolifération. Le deuxième projet, nous a permis d'observer que l'expression d'un mutant nucléaire de MEK1 dans les cellules IEC-6 transforme drastiquement les cellules. Une augmentation de prolifération, une résistance à l'anoikose, un dérèglement du cycle cellulaire, de l'instabilité chromosomique (CIN), de la tétra/aneuploïdie sont observés. La caractérisation des mécanismes responsables de cette localisation aberrante de MEK1/2 phosphorylés, a permis d'identifier la protéine Sef, un régulateur de la localisation cytoplasmique de MEK/ERK1/2. Nous avons démontré que l'expression d'une forme oncogénique de Ras (H-RasV12) inhibe l'expression de Sef, engendrant alors une accumulation nucléaire de MEK1/2 activés. Plus encore, la réexpression de Sef restaure la localisation cytoplasmique de MEK1/2 et renverse les propriétés tumorigéniques ainsi que l'aneuploïdie induite par Ras activé. Un troisième projet, visant la caractérisation des mécanismes associés à la CIN et à l'aneuploïde engendrés par l'activation aberrante de la voie de Ras-ERK1/2, a permis d'observer que l'hyperactivation de ERK1/2 induit des anomalies mitotiques menant à la binucléation. Une localisation erronée et une surexpression de la kinase Aurora A, de même que des protéines de passage du complexe chromosomique (CPC), Aurora B, Survivine et INCENP, sont observées. L'inhibition partielle de l'activation de ERK1/2 par de faible dose de PD184352, un inhibiteur de MEK1/2, est suffisante pour renverser la surexpression de ces régulateurs mitotiques, de même que corriger les anomalies de la mitose et réduire la tétra/aneuploïdie engendrée par Ras oncogénique. Ainsi, nous avons démontré, pour la première fois, que la voie des MAP kinases ERK1/2 est impliquée dans la CIN, la tétraploïdie et l'aneuploïdie. Nos résultats suggèrent que la perte de Sef est un événement oncogénique précoce, qui contribue à la localisation nucléaire aberrante de MEK1/2 qui est observée dans les tumeurs colorectales. Cette localisation anormale de MEK1/2 est associée à l'initiation de la transformation, la progression tumorale et la CIN, via l'activité soutenue de ERK1/2. Ces informations sont capitales et démontrent l’importance de la voie de signalisation Ras/Raf/MEK/ERK1/2 dans le processus de tumorigénèse colorectale. / The Ras-dependent Raf/MEK/ERK1/2 signaling pathway is frequently hyperactivated in human cancer as a result of receptor tyrosine kinase overexpression or gain-of-function mutations in RAS or RAF genes. More specificaly, activating mutation in RAS genes are found in ~ 30-50% of colorectal adenomas and phosphorylation of ERK1/2 is frequently observed in human colorectal cancer cells and tumor specimens. In a large TMA analysis, we found that MEK1/MEK2 are aberrantly activated in 44% of human colorectal cancers. In addition, our analysis revealed that 79% of colorectal cancers exhibit aberrant phospho-MEK1/2 staining in the nucleus, as compared to 4% of normal tissue. How dysregulation and mislocalization of MEK1/2 contribute to tumor initiation and progression is not well understood. In order to determine the exact contribution of MEK1 and MEK2 to the pathogenesis of colorectal cancer, wild type and constitutively active forms of MEK1 and MEK2 were ectopically expressed by retroviral gene transfer in the normal intestinal epithelial cell line IEC-6. We found that the expression of activated MEK1 or MEK2 is sufficient to morphologically transform intestinal epithelial cells, dysregulate cell proliferation and induce the formation of high-grade adenocarcinomas after orthotopic transplantation in mice. A large proportion of these intestinal tumors metastasize to the liver and lung. Importantly, we show that silencing of MEK2 expression completely suppresses the proliferation of human colon carcinoma cell lines, whereas inactivation of MEK1 has a much weaker effect. In a second project, we have investigated the impact of the nuclear mislocalization of phosphorylated MEK1/2 observed in colorectal tumors. We show that oncogenic activation of Ras is sufficient to induce the nuclear accumulation of phosphorylated MEK1/2 and ERK1/2 in intestinal epithelial cells. To evaluate the biological impact of the mislocalization of MEK1/2, we have forced the localization of MEK1 in the nucleus of epithelial cells. We found that sustained nuclear MEK1 signaling leads to hyperactivation of ERK1/2 and to enhanced cell proliferation. Nuclear localization of MEK1 also leads to tetraploidization, chromosomal instability (CIN) and tumorigenesis. Importantly, we show that oncogenic Ras downregulates the spatial regulator Sef, concomitant to nuclear accumulation of activated MEK1/2. Moreover, re-expression of Sef is sufficient to restore the normal localization of MEK1/2 and to revert the cell cycle defects and tumorigenesis induced by oncogenic Ras. Another project was initiated to characterize the tetraploidy and CIN observed upon hyperactivation of the Ras-ERK1/2 pathway. Aneuploidy and CIN are observed in the majority of colorectal cancers and are associated with a poorer prognosis. We show that hyperactivation of ERK1/2 by oncogenic Ras or sustained nuclear MEK-ERK1/2 signaling induces mitotic defects that lead to tetraploidy, aneuploidy and CIN. We also found that dysregulation of Ras-ERK1/2 signaling alters the expression and localization of Aurora A and the Chromosomal passenger complex proteins. In conclusion, we show for the first time that the MEK/ERK1/2 signaling pathway is implicated in aneuploidy and CIN. Our results suggest that sustained nuclear ERK1/2 signaling may contribute to the initiation and progression of colorectal cancer by rapidly inducing aneuploidy and CIN. We suggest that loss of Sef is an early oncogenic event that contributes to genetic instability and tumor progression by sustaining nuclear ERK1/2 signaling. These observations are significant and highlight the importance of the Ras-ERK1/2 signaling pathway in colorectal tumorigenesis.

Les cellules du système immunitaire sont capables de reconnaître et d'éliminer les cellules cancéreuses prévenant ainsi l'apparition de cancers. Parmi celles-ci, l'activité antitumorale est principalement attribuée aux lymphocytes T CD4 helper de type 1 (Thl). Les lymphocytes CD4 sont activés lors de la reconnaissance d'un antigène (Ag) de tumeur présenté par le complexe majeur d'histocompatibilité de classe II (CMH-II). Ils possèdent des propriétés cytotoxiques propres et activent les autres cellules immunitaires. Dans un premier temps, nous nous somme intéressés au mécanisme de présentation sur le CMH-II de la télomérase (hTERT). La protéine hTERT est capable d'interagir avec les HSPGs facilitant ainsi son internalisation par les DC. Elle emprunte ensuite les voies endolysosomale et cytosolique pour générer des peptides nommés UCP présentés dans le contexte HLA-DR. Cette découverte soutient son utilisation en immunothérapie associée aux chimiothérapies. Nous avons ensuite identifié quatre peptides dérivés de hTERT restreints HLA-DP4 puis comparé leur immunogénicité avec les UCP. Cette analyse a mis en évidence la supériorité des UCP en termes d'immunoprévalence et d'immunodominance. Enfin, nous avons étudié l'impact de l'acquisition d'une résistance à l'oxaliplatine sur le profil antigénique de lignées tumorales de cancers colorectaux (CCR). L'évaluation des réponses immunitaires de patients atteints de CCR nous a permis d'identifier des peptides immunogènes dérivés d'Ag surexprimés après une exposition à l'oxaliplatine. En conclusion, ces travaux pourront participer à l'amélioration des stratégies d'immunothérapie et d'immunomonitoring ciblant les lymphocytes CD4 Thl. / Immune cells are able to recognize and eliminate cancer cells to prevent from cancer development. Among them, antitumoral activity is mainly attributed to CD4 T helper 1 (Thl) cells. CD4 Thl cells are activated upon recognition of tumor antigen presented on the Major Histocompatibility Complex class II (MHC-II) molecules. These cells possess their own cytotoxic capacities and activate other immune cells. Firstly, we were interested in the mechanism of presentation of the catalytic subunit of telomerase (hTERT) which is an attractive tumor antigen target for immunotherapies. hTERT protein can interact with cell surface HSPGs facilitating its internalization by DC. Then, hTERT uses thé endo-lysosomal and cytosolic proteolysis pathways to generale immunogenic peptides named UCP (Universal Cancer Peptide) presented in HLA-DR context. This discovery is an additional argument in favor of using hTERT as a target for cancer immunotherapies. Then, we identified four novel hTERT-derived peptides presented by HLA-DP4 and compared their immunogenicity with UCP. This analysis highlighted the superiority of UCP in term of immunoprevalence and immunodominance. This stresses the importance of considering MHC-II locus for immunotherapy strategies stimulating CD4 T cells. Finally, we studied the impact of oxaliplatin treatment and/or oxaliplatin résistance acquisition on CRC antigenome. Evaluation of immune responses in CRC patients permitted the identification of immunogenic peptides derived from antigens upregulated after oxaliplatin exposition. In conclusion, this work could participate in the improvement of cancer immunotherapies and immunomonitoring targeting CD4 Thl cells.

Le cancer colorectal (CCR) est la troisième maladie maligne la plus fréquente et la deuxième cause de décès par cancer. La famille des récepteurs tyrosine kinases transmembranaires ErbB a été identifiée comme l'un des principaux moteurs du développement et de la progression du CCR et l'un de ses membres les plus connus, le récepteur du facteur de croissance épidermique (EGFR / ERBB1 / Her1), considéré comme l'une des cibles les plus importantes en traitement CRC. Deux autres membres de la famille ErbB, les récepteurs Her2 et Her3, apparaissent également comme de nouvelles cibles importantes pour le CRC en raison de la mutation somatique, de l’amplification génique ou de la résistance aux traitements anti-EGFR. La protéine transmembranaire, Fas (TNFRSF6 / CD95), est un membre de la superfamille des récepteurs du facteur de nécrose tumorale (TNFRSF). Il peut transmettre des signaux multiples qui mènent à des destins de cellules complètement différents. Selon les contextes cellulaires, Fas initie la mort cellulaire par apoptose, essentielle pour arrêter les réponses immunitaires chroniques et prévenir l'auto-immunité et le cancer, ou pour stimuler la survie, la prolifération et la motilité des cellules, ce qui favorise l'auto-immunité, la croissance cancéreuse et les métastases. Avec des preuves de plus en plus nombreuses de la signalisation pro-survie médiée par Fas, les activités de promotion du cancer chez les patients atteints de cancer sont maintenant reconnues comme étant significatives et cliniquement pertinentes. Bien que cette polyvalence de signalisation ait été particulièrement bien démontrée dans le cancer du côlon, les mécanismes moléculaires qui sous-tendent les voies de survie sont encore largement inconnus. Dans ce contexte, l'objectif principal de mon doctorat Le projet visait à étudier l’importance du crosstalks entre les membres de la famille Fas et ErbB et, plus particulièrement, à déterminer si la signalisation Fas pouvait influencer la signalisation de l’EGFR favorisant le cancer.Plus précisément, je décris comment l’état de phosphorylation de la tyrosine Fas influence fortement la signalisation de la voie EGFR dans les cellules colorectales. Mes données démontrent que Fas dans son état prosurvival, phosphorylé à Y291 (pY291-Fas), interagit en effet avec EGFR et que cette interaction intensifie significativement la signalisation de l'EGFR dans les cellules cancéreuses colorectales anti-EGFR via la voie Yes-1 / STAT3. Le pY291-Fas s'accumule dans le noyau lors du traitement par EGF et favorise la localisation nucléaire du phospho-EGFR et du phospho-STAT3, l'expression de la cycline D1, l'activation des voies Akt et MAPK médiées par STAT3 et enfin la prolifération et la migration cellulaires. De plus, je découvre également le rôle potentiel que Her3 pourrait jouer avec Fas dans la libération des cellules cancéreuses colorectales de l'inhibition anti-EGFR.Tous ensemble mon doctorat des études permet de mieux comprendre le rôle des voies de survie de Fas dans la signalisation ErBb dans le CRC. Fait important, en démontrant un lien entre l'émergence d'une résistance aux traitements anti-ErbB et le signal de Fas pro-survie, mon travail justifie le développement d'une thérapie ciblée Fas / phospho-Fas comme nouvelle option thérapeutique pour surmonter les anti-EGFR, chez les patients présentant une résistance anti-EGFR secondaire. / Colorectal cancer (CRC) is the third most common malignant disease and the second most frequent cause of cancer-related death. The ErbB family of transmembrane receptor tyrosine kinases has been identified as a major driver of the development and progression of CRC and one its best-known member, the epidermal growth factor receptor (EGFR /ERBB1/Her1), considered one of the most important targets in CRC treatment. Two others members of the ErbB family, the receptors Her2 and Her3, also emerge as important new targets for CRC due to the somatic mutation, gene amplification or resistance to the anti-EGFR therapies. The transmembrane protein, Fas (TNFRSF6/CD95), is a member of the tumor necrosis factor receptor superfamily (TNFRSF). It can transmit multiple signals that lead to completely different cell fates. Depending on cellular contexts, Fas either initiates cell death by apoptosis, which is essential for shutting down chronic immune responses and preventing autoimmunity and cancer, or stimulates cell survival, proliferation, and motility, which can promote autoimmunity, cancer growth, and metastasis. With increasing evidence of Fas-mediated pro-survival signaling, the cancer-promoting activities of Fas are now recognized as significant and clinically relevant. While this signaling versatility has been particularly well demonstrated in colon cancer, the molecular mechanisms underlying the survivals pathways are still largely unknown. In this context, the main aim of my Ph.D. project was to study the importance of the crosstalks between Fas and the ErbB family members and more specifically to determine whether the Fas signaling could influence the cancer-promoting signaling of EGFR.More precisely, I describe how the Fas tyrosine phosphorylation status strongly influences the signaling of the EGFR pathway in colorectal cells. My data demonstrate that Fas in its prosurvival state, phosphorylated at Y291 (pY291-Fas), indeed interacts with EGFR and that this interaction significantly intensifies EGFR signaling in anti-EGFR-resistant colorectal cancer cells via the Yes-1/STAT3-mediated pathway. The pY291-Fas accumulates in the nucleus upon EGF treatment and promotes the nuclear localization of phospho-EGFR and phospho-STAT3, the expression of cyclin D1, the activation of STAT3-mediated Akt and MAPK pathways, and finally the cell proliferation and migration. Additionally, I also uncover the potential role that Her3, may play along with Fas, in the colorectal cancer cell escape from anti-EGFR inhibition. All together my Ph.D. studies provide a better understanding of the role of the Fas survival pathways in the ErBb signaling in CRC. Importantly, by demonstrating a connection between the emergence of resistance to anti-ErbB therapies and the Fas pro-survival signal, my work provides a rationale for the development of Fas/phospho-Fas targeted therapy as a new therapeutic option for overcoming anti-EGFR, in patients with secondary anti-EGFR resistance.

Au cours de la dernière décennie, la pathologie numérique a été améliorée grâce aux avancées des algorithmes d'analyse d'images et de la puissance de calcul. Néanmoins, le diagnostic par un expert à partir d'images histopathologiques reste le gold standard pour un nombre considérable de maladies notamment le cancer. Ce type d'images préserve la structure des tissus aussi proches que possible de leur état vivant. Ainsi, cela permet de quantifier les objets biologiques et de décrire leur organisation spatiale afin de fournir une description plus précise des tissus malades. L'analyse automatique des images histopathologiques peut avoir trois objectifs: le diagnostic assisté par ordinateur, l'évaluation de la sévérité des maladies et enfin l'étude et l'interprétation des mécanismes sous-jacents des maladies et leurs impacts sur les objets biologiques. L'objectif principal de cette thèse est en premier lieu de comprendre et relever les défis associés à l'analyse automatisée des images histologiques. Ensuite, ces travaux visent à décrire les populations d'objets biologiques présents dans les images et leurs relations et interactions à l'aide des statistiques spatiales et également à évaluer la significativité de leurs différences en fonction de la maladie par des tests statistiques. Après une étape de séparation des populations d'objets biologiques basée sur la couleur des marqueurs, une extraction automatique de leurs emplacements est effectuée en fonction de leur type, qui peut être ponctuel ou surfacique. Les statistiques spatiales, basées sur la distance pour les données ponctuelles, sont étudiées et une fonction originale afin de mesurer les interactions entre deux types de données est proposée. Puisqu'il a été montré dans la littérature que la texture d'un tissu est altérée par la présence d'une maladie, les méthodes fondées sur les motifs binaires locaux sont discutées et une approche basée sur une modification de la résolution de l'image afin d'améliorer leur description est introduite. Enfin, les statistiques descriptives et déductives sont appliquées afin d'interpréter les caractéristiques extraites et d'étudier leur pouvoir discriminant dans le cadre de l'étude des modèles animaux de cancer colorectal. Ce travail préconise la mesure des associations entre différents types d'objets biologiques pour mieux comprendre et comparer les mécanismes sous-jacents des maladies et leurs impacts sur la structure des tissus. En outre, nos expériences confirment que l'information de texture joue un rôle important dans la différenciation des deux modèles d'implantation d'une même maladie. / During the last decade, digital pathology has been improved thanks to the advance of image analysis algorithms and calculus power. However, the diagnosis from histopathology images by an expert remains the gold standard in a considerable number of diseases especially cancer. This type of images preserves the tissue structures as close as possible to their living state. Thus, it allows to quantify the biological objects and to describe their spatial organization in order to provide a more specific characterization of diseased tissues. The automated analysis of histopathological images can have three objectives: computer-aided diagnosis, disease grading, and the study and interpretation of the underlying disease mechanisms and their impact on biological objects. The main goal of this dissertation is first to understand and address the challenges associated with the automated analysis of histology images. Then it aims at describing the populations of biological objects present in histology images and their relationships using spatial statistics and also at assessing the significance of their differences according to the disease through statistical tests. After a color-based separation of the biological object populations, an automated extraction of their locations is performed according to their types, which can be point or areal data. Distance-based spatial statistics for point data are reviewed and an original function to measure the interactions between point and areal data is proposed. Since it has been shown that the tissue texture is altered by the presence of a disease, local binary patterns methods are discussed and an approach based on a modification of the image resolution to enhance their description is introduced. Finally, descriptive and inferential statistics are applied in order to interpret the extracted features and to study their discriminative power in the application context of animal models of colorectal cancer. This work advocates the measure of associations between different types of biological objects to better understand and compare the underlying mechanisms of diseases and their impact on the tissue structure. Besides, our experiments confirm that the texture information plays an important part in the differentiation of two implemented models of the same disease.

Indiana University-Purdue University Indianapolis (IUPUI) / Colon rectal cancer (CRC) is one of the most common cancers worldwide. It is characterized by the successive accumulation of mutations in genes controlling epithelial cell growth and differentiation leading to genomic in-stability. This results in the activation of proto-oncogene(K-ras), loss of tumor suppressor gene activity and ab-normality in DNA repair genes. Targeted therapy is a new generation of cancer treatment in which drugs attack targets which are specific for the cancer cell and are critical for its survival or for its malignant behavior. Survival of metastatic CRC patients has approximately doubled due to the development of new combinations of stan-dard chemotherapy, and the innovative targeted therapies, such as monoclonal antibodies against epidermal growth factor receptor (EGFR) or monoclonal antibodies against vascular endothelial growth factor (VEGFR).The study is to exhibit the need for right drug-right target and provides a proof of principle for potent efficacy of molecular targeted therapy for CRC. We have performed the weighted gene co-expression network analysis for three different patient cohort treated with different targeted therapy drugs. The results demonstrates the variation across different treatment regime in context of transcription factor networks. New significant tran-scription factors have been identified as potential biomarker for CRC cancer including EP300, STAT6, ATF3, ELK1, HNF4A, JUN, TAF1, IRF1, TP53, ELF1 and YY1. The results provides guidance for future omic study on CRC and additional validation work for potent biomarker for CRC.

Ziel der vorliegenden Arbeit ist die retrospektive Beurteilung der Sicherheit und Effektivität der Leberteilresektion bei der Behandlung von Lebermetastasen des kolorektalen Karzinoms sowie der Re-Resektion bei Patienten mit Rezidivlebermetastasen. Weiterhin soll das operative Vorgehen bei synchronen Lebermetastasen hinsichtlich simultaner Resektionsverfahren und zweizeitigen Vorgehens untersucht werden. Insgesamt wurden die Ergebnisse von 660 Patienten ausgewertet, die zwischen 1988 und 2004 mit 685 Leberteilresektionen behandelt wurden. Unter diesen waren 75 Patienten, die eine Re-Resektion erhielten sowie 202 Patienten, bei denen die Lebermetastasen synchron auftraten. Neben der Analyse der postoperativen Letalität und postoperativen Komplikationen sollen prognostische Faktoren für das Langzeitüberleben und das Auftreten von Tumorrezidiven nach Leberteilresektion identifiziert werden. Da sich die Studienpopulation aus einem Zeitraum von über 15 Jahren rekrutiert, sollen außerdem verschiedene Zeitabschnitte vergleichend analysiert werden. Die Leberteilresektion ist derzeit die einzige potentiell kurative Therapie bei kolorektalen Lebermetastasen. Als prognostisch günstige Parameter in der multivariaten Analyse zeigten sich die Radikalität des Eingriffes, die Anzahl der Metastasen, vorhandene ligamentäre Lymph-knotenmetastasen sowie das Jahr der Resektion. Auch bei Rezidiven kolorektaler Lebermetastasen ist das chirurgische Vorgehen derzeit die einzige kurative Intervention. Re-Resektionen weisen ein vergleichbares operatives Risiko und vergleichbare Langzeitüberlebensraten auf wie Erstresektionen. Als einziger prognostischer Parameter für das Langzeitüberleben erwies sich in der multivariaten Analyse die Radikalität des Eingriffes. Bei synchronen Lebermetastasen sind die wichtigsten Kriterien, um eine simultane Resektion durchzuführen, die Berücksichtigung des Alters sowie des Resektionsausmaßes. Simultane Resektionen sind bei synchronen kolorektalen Lebermetastasen dann so sicher und effizient durchführbar wie Resektionen im zweizeitigen Vorgehen.

Colorectal cancer (CRC) is a health challenge worldwide and early detection of the disease is crucial to improve patient prognosis. It is common for the first contact with care to occur in primary care centers where general practitioners often face the challenge of distinguishing CRC from other diseases with similar symptoms. In this master thesis, patient records from primary care were used to create, optimize, and evaluate a machine learning model that classifies patients with CRC for early detection of the disease. The data used in the project included parts of electronic health records (EHRs) from both public (SLSO) and privately run (Capio and Praktikertjänst) primary care centers in the Stockholm region. The available dataset was cleaned and pre- processed, and then tested on four separate models. After selecting and optimizing the most promising model, LightGBM, a detailed evaluation of the model was performed. To simulate realistic clinical conditions, data from the three months prior to diagnosis were excluded from two of the datasets. The results were then compared with a baseline machine learning model that utilized ICD codes extracted from EHRs in primary care for early detection of CRC.The results showed that the final developed model had a generally good performance with an AUROC score of a maximum of 85.8%, which indicates very good ability to distinguish between the classes. The performance dropped when using the datasets with 3 months of data removed, but the ROC curves still showed a better ability than random classification to distinguish between the classes with a AUROC score of maximum 60,8%. The results also showed that the model developed in this master thesis outperforms the baseline model, which was based on ICD codes, from a performance perspective. For future development and before a possible clinical implementation, a larger data set should be used for training and testing. / Tjock- och ändtarmscancer, kolorektal cancer (KRC) är en hälsoutmaning över hela världen och tidig upptäckt av sjukdomen är avgörande för att förbättra patientens prognos. Det är vanligt att den första kontakten med vården inträffar på vårdcentraler där allmänläkare ofta står inför utmaningen att skilja KRC från andra sjukdomar med liknande symtom. I denna masteruppsats kommer patientjournaler från primärvården att användas för att skapa, optimera och utvärdera en maskininlärningsmodell som klassificerar patienter med KRC för tidig upptäckt av sjukdomen.De data som använts i projektet omfattade delar av elektroniska patientjournaler (EHR) från både offentliga (SLSO) och privatägda (Capio och Praktikertjänst) primärvårdscentraler i Stockholmsregionen. Den tillgängliga datamängden städades och förbehandlades, och testades sedan på fyra separata modeller. Efter att ha valt ut och optimerat den mest lovande modellen, LightGBM, utfördes en detaljerad utvärdering av modellen. För att simulera realistiska kliniska tillstånd utvärderades modellen på två datamängder där data från tre månader före diagnos uteslöts. Resultaten jämfördes sedan med en baslinjemodell som använde ICD-koder som hämtats från journalsystem inom primärvården för tidig upptäckt av CRC.Resultaten visade att den slutliga utvecklade modellen hade en generellt bra prestanda med en AUROC-poäng på högst 85,8%, vilket indikerar mycket god förmåga att skilja mellan klasserna. Prestandan sjönk vid användning av datasatserna med 3 månaders data borttagen, men ROC-kurvorna visade fortfarande en bättre förmåga än slumpmässig klassificering att skilja mellan klasserna med en AUROC-poäng på högst 60,8%. Resultaten visade också att den modell som utvecklats i denna masteruppsats överträffar baslinjemodellen, som baserades på ICD-koder, ur ett prestationsperspektiv. För framtida utveckling och före en eventuell klinisk implementation bör en större datamängd användas för träning och testning av modellen.