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Pancreatic ductal adenocarcinoma: From biomarkers discovery to personalized treatmentPuleo, Francesco 14 June 2018 (has links)
En 2016, environ 53 070 patients ont reçu un diagnostic d'adénocarcinome canalaire pancréatique (PDA) aux États-Unis et la plupart d'entre eux mourront de leur maladie dans les 5 ans. Le registre belge du cancer rapporte une incidence estimée à 1200 nouveaux cas par an. La survie globale à 5 ans pour toutes stades confondus a marginalement augmenté au cours des 50 dernières années, passant de 2 à 6%, malgré l'imagerie, les soins périopératoires et l'amélioration des techniques chirurgicales.La chirurgie reste la seule chance de guérison, cependant, seulement 10-15% des patients nouvellement diagnostiqués sont jugés éligibles pour une chirurgie. Même s'il existe peu d'autres modalités de traitement efficaces qui puissent considérablement prolonger la survie globale, la plupart des patients finiront par mourir de métastases au foie, au poumon et / ou au péritoine, les sites de propagation les plus courants. Les patients, les cliniciens et les chercheurs restent frustrés par le manqué d’outils thérapeutiques et des nouvelles stratégies sont nécessaires pour comprendre et mieux prendre en charge cette maladie.Le terme «cancer» engendre un sentiment de peur et colère, en particulier quand on est confronté au diagnostic dévastateur de cancer du pancréas. En plus, une réaction commune est de personnifier le cancer comme une entité maléfique qui doit être combattue pour sauver la vie du patient. Les armes pour cette bataille comprennent le scalpel d'un chirurgien, la chimiothérapie, la radiothérapie, les thérapies ciblées, les immunothérapies, les approches holistiques et la foi religieuse. Mais nous avons trop souvent oublié ou sous-estimé la contribution de la recherche translationnelle pour la médecine de précision, pour mieux adapter les thérapies et éviter les toxicités inutiles.Dans un sens biologique, qu'est-ce qu'un cancer du pancréas ou un cancer? Le cancer est une maladie génétique, soumise à un phénomène évolutif avec ses propres règles, contraintes et caractéristiques prévisibles qui mènent finalement à un phénotype unique.La stratégie "one size fits all" dans la PDA a souvent échoué dans les essais de nouveaux médicaments dans une population non sélectionnée.Cette thèse est une contribution modeste et authentique à une approche plus personnalisée du PDA, de l'acquisition tissulaire, à l'analyse de biomarqueurs tissulaires, à une analyse moléculaire plus profonde afin de mieux comprendre cette maladie mortelle et de proposer l'intégration de biomarqueurs dans le developpement d’etudes cliniques guides par les analyses moléculaires. / Doctorat en Sciences / info:eu-repo/semantics/nonPublished
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An integrative strategy for targeted evaluation of biomarker expression in non-small cell lung cancerMattsson, Johanna January 2016 (has links)
Despite improvements in therapy, the prognosis for non-small cell lung cancer (NSCLC) patients remains poor, and cure is only possible in localized tumors after surgical resection. A new generation of targeted cancer drugs has led to the expectation that lung cancer therapy can be significantly improved, but these drugs are today only an option in a small subset of NSCLC patients, and their effect is temporary. Therefore, the aim of this thesis was to characterize NSCLC in order to find new treatment targets and to evaluate biomarkers that further optimize therapy selection. In Paper I, the expression of the potential treatment targets claudin 6 and claudin 18.2 were evaluated based on immunohistochemical- and gene expression analysis. High ectopic protein and gene expression were demonstrated for both claudins in small subgroups of NSCLC. Clinical trials using humanized monoclonal antibodies against both proteins are ongoing in other cancer forms and may be extended to NSCLC. In Paper II, the prognostic impact of the inflammatory mediator cyclooxygenase 2 (COX-2) was evaluated. No prognostic significance was found in a meta-analysis incorporating gene expression data of 1337 NSCLC patients. Likewise, COX-2 protein expression in tumor cells was not associated with survival in two independent NSCLC cohorts. However, in one of the analyzed cohorts, higher COX-2 expression in the tumor stroma was associated with longer survival and may therefore be a subject for further investigation. In Paper III, tumor and stromal COX-2 protein expression was examined in patients treated with the COX-2 inhibitor celecoxib in order to evaluate if COX-2 expression is a predictive biomarker for benefit of celecoxib therapy. Celecoxib did not prolong overall survival neither in the whole cohort nor in patients stratified according to COX-2 expression in tumor or stromal cells. Noteworthy, a tendency towards longer survival was again demonstrated in patients with high COX-2 stromal expression. In Paper IV, the diagnostic methods for identification of ALK rearrangements were assessed in a large representative Swedish NSCLC population. Fluorescence in situ hybridization (FISH), as the diagnostic standard, was compared to two immunohistochemical assays. ALK gene expression levels were incorporated to supplement the molecular data. The frequency of ALK rearrangements was lower than previously reported. The different methods to detect the ALK fusion demonstrated overlapping results. However, the overlap was poor, so the methods cannot be regarded as interchangeable and should thereby be interpreted with caution when used in clinical diagnostics. In summary, this thesis applied an integrative translational approach to characterize potential new treatment targets and to evaluate the detection of existing predictive biomarkers in NSCLC.
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Meta-análise integrativa secretoma-proteoma para identificação de potenciais biomarcadores de adenocarcinoma ductal pancreáticoOliveira, Grasieli de January 2020 (has links)
Orientador: Robson Francisco Carvalho / Resumo: Adenocarcinoma ductal do pâncreas (PDAC) é extremamente agressivo, possui prognóstico desfavorável e não existem biomarcadores satisfatório para a doença ou identificação de indivíduos com alto risco de morbidade e mortalidade. A complexidade celular e molecular do câncer de pâncreas leva a inconsistências nas validações clínicas de muitas proteínas que foram avaliadas como biomarcadores prognósticos da doença. O secretoma tumoral desempenha um papel crucial na proliferação e metástase de células PDAC, bem como na resistência a tratamentos terapêuticos, que juntos contribuem para um pior resultado clínico. Assim, a enorme quantidade de dados proteômicos do câncer de pâncreas que foram gerados a partir de diferentes tipos de amostras e técnicas de espectrometria de massa pode ser integrada para a seleção de proteínas secretadas compartilhadas relevantes para o diagnóstico e prognóstico da doença. O objetivo do presente estudo foi realizar uma meta-análise combinando dados do proteoma do câncer de pâncreas e secretome publicamente para identificar novos potenciais biomarcadores de doenças. Realizamos uma meta-análise integrando dados de espectrometria de massa obtidos de duas revisões sistemáticas da literatura sobre câncer de pâncreas, que selecionaram independentemente 20 estudos do secretoma e 35 do proteoma. Em seguida, realizamos análises de predição de proteínas secretadas usando sete ferramentas ou bancos de dados “in silico”, que identificaram 39 proteínas compartilhada... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Pancreatic ductal adenocarcinoma (PDAC) is extremely aggressive, has an unfavorable prognosis and there are no satisfactory biomarkers for the disease or identification of individuals at high risk of morbidity and mortality. The cellular and molecular complexity of pancreatic cancer leads to inconsistences in clinical validations of many proteins that have been evaluated as prognostic biomarkers of the disease. Tumor secretome plays a crucial role in PDAC cell proliferation and metastasis, as well as in resistance to therapeutic treatments, which together contribute to a worse clinical outcome. Thus, the massive amount of proteomic data from pancreatic cancer that have been generated from different studies can be integrated into the selection of shared secreted proteins relevant to the prognosis of the disease. The aim of the present study was to perform a metaanalysis combining pancreatic cancer proteome and secretome publicly data to identify new potential disease biomarkers. We performed a meta-analysis integrating mass spectrometry data obtained from two systematic reviews of the pancreatic cancer literature, which independently selected 20 studies of the secretome and 35 of the proteome. Next, we performed prediction analyses of secreted proteins using seven “in silico” tools or databases, which identified 39 proteins shared between the secretome and the proteome data. Notably, the expression of 31 genes of these proteins was upregulated in pancreatic adenocarcinoma samp... (Complete abstract click electronic access below) / Doutor
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Diagnostic and prognostic value of current phenotyping methods and novel molecular markers in idiopathic pulmonary fibrosisNicol, Lisa Margaret January 2018 (has links)
Background Idiopathic pulmonary fibrosis (IPF) is a devastating form of chronic lung injury of unknown aetiology characterised by progressive lung scarring. A diagnosis of definite IPF requires High Resolution Computed Tomography (HRCT) appearances indicative of usual interstitial pneumonia (UIP), or in patients with 'possible UIP' CT appearances, histological confirmation of UIP. However the proportion of such patients that undergo SLB varies, perhaps due to a perception of risk of biopsy and additive diagnostic value of biopsy in individual patients. We hypothesised that an underlying UIP pathological pattern may result in increased risk of death and aimed to explore this by comparing the risk of SLB in suspected idiopathic interstitial pneumonia, stratified according to HRCT appearance. Additionally we sought to determine the positive-predictive value of biopsy to diagnose IPF in patients with 'possible UIP HRCT' in our population. In patients with possible UIP who are not biopsied, the clinical value of bronchoalveolar lavage (BAL) is uncertain. We aimed to prospectively study the diagnostic and prognostic value of BAL differential cell count (DCC) in suspected IPF and determine the feasibility of repeat BAL and the relationship between DCC and disease progression in two successive BALs. We hypothesised that BAL DCC between definite and possible IPF was different and that baseline DCC and change in BAL DCC predicted disease progression. Alveolar macrophages (AMs) are an integral part of the lung's reparative mechanism following injury, however in IPF they contribute to pathogenesis by releasing pro-fibrotic mediators promoting fibroblast proliferation and collagen deposition. Expansion of novel subpopulations of pulmonary monocyte-like cells (PMLCs) has been reported in inflammatory lung disease. We hypothesised that a distinct AM polarisation phenotype would be associated with disease progression. We aimed to perform detailed phenotyping of AM and PMLCs in BAL in IPF patients. Several prognostic scoring systems and biomarkers have been described to predict disease progression in IPF but most were derived from clinical trial patients or tertiary referral centres and none have been validated in separate cohorts. We aimed to identify a predictive tool for disease progression utilising physiological, HRCT and serum biomarkers in a unique population of incident treatment naïve IPF patients. Methods Between 01/01/07 and 31/12/13, 611 consecutive incident patients with suspected idiopathic interstitial pneumonia (IIP) presented to the Edinburgh lung fibrosis clinic. Of these patients 222 underwent video-assisted thoracoscopic lung biopsy and histological pattern was determined according to ATS/ERS criteria. Post-operative mortality and complication rates were examined. Fewer than 2% received IPF-directed therapy and less than 1% of the cohort were lost to follow-up. Disease progression was defined as death or ≥10% decline in VC within 12 months of BAL. Cells were obtained by BAL and a panel of monoclonal antibodies; CD14, CD16, CD206, CD71, CD163, CD3, CD4, CD8 and HLA-DR were used to quantify and selectively characterise AMs, resident PMLCs, inducible PMLCs, neutrophils and CD4+/CD8+ T-cells using flow cytometry. Classical, intermediate and non-classical monocyte subsets were also quantified in peripheral blood. Potential biomarkers (n=16) were pre-selected from either previously published studies of IPF biomarkers or our hypothesis-driven profiling. Linear logistic regression was used on each predictor separately to assess its importance in terms of p-value of the associated weight, and the top two variables were used to learn a decision tree. Results Based on the 2011 ATS/ERS criteria, 87 patients were categorised as 'definite UIP', of whom 3 underwent SLB for clinical indications. IPF was confirmed in all 3 patients based on 2013 ATS/ERS/JRS/ALAT diagnostic criteria. 222 patients were diagnosed with 'possible UIP'; 55 underwent SLB, IPF was subsequently diagnosed in 37 patients, 4 were diagnosed with 'probable IPF' and 14 were considered 'not IPF'. In this group, 30 patients were aged 65 years or over and 25/30 (83%) had UIP on biopsy. 306 patients had HRCTs deemed 'inconsistent with UIP', SLB was performed in 168 patients. Post6 operative 30-day mortality was 2.2% overall, and 7.3% in the 'possible UIP' HRCT group. Patients with 'definite IPF' based on HRCT and SLB appearances had significantly better outcomes than patients with 'definite UIP' on HRCT alone (P=0.008, HR 0.44 (95% CI 0.240 to 0.812)). BAL DCC was not different between definite and possible UIP groups, but there were significant differences with the inconsistent with UIP group. In the 12 months following BAL, 33.3% (n=7/21) of patients in the definite UIP group and 29.5% (n=18/61) in the possible UIP group had progressed. There were no significant differences in BAL DCC between progressor and non-progressor groups. Mortality in patients with suspected IPF and a BAL DCC consistent with IPF was no different to those with a DCC inconsistent with IPF (P=0.425, HR 1.590 (95% CI 0.502 to 4.967)). There was no difference in disease progression in either group (P=0.885, HR 1.081 (95% CI 0.376 to 3.106)). There was no statistically significant difference in BAL DCC at 0 and 12 months in either group. There was no significant change in DCC between 0 and 12 month BALs between progressors and non-progressors. Repeat BAL was well tolerated in almost all patients. There was 1 death within 1 month of a first BAL and 1 death within 1 month of a second BAL; both were considered 'probably procedure-related'. AM CD163 and CD71 (transferrin receptor) expression were significantly different between groups (P < 0.0001), with significant increases in the IPF group vs non fibrotic ILD (P < 0.0001) and controls (P < 0.0001 and P < 0.001 respectively). CD71 expression was also significantly increased in the IPF progressor vs non-progressor group (P < 0.0001) and patients with high CD71 expression had significantly poorer survival than the CD71low group (P=0.040, median survival 40.5 and 75.6 months respectively). CD206 (mannose receptor) expression was also significantly higher in the IPF progressor vs non-progressor group (P=0.034). There were no differences in baseline BAL neutrophil, eosinophil or lymphocyte percentages between IPF progressor or non-progressor groups. The percentage of rPMLCs was significantly increased in BAL fluid cells of IPF patients compared to those with non-fibrotic ILD (P < 0.0001) and healthy controls (P < 0.05). Baseline rPMLC percentage was significantly higher in IPF progressors vs IPF non-progressors (P=0.011). Baseline BAL iPMLC:rPMLC ratio was also significantly different between IPF progressor and non-progressor groups (P=0.011). Disease progression was confidently predicted by a combination of clinical and serological variables. In our cohort we identified a predictive tool based on two key parameters, one a measure of lung function and one a single serum biomarker. Both parameters were entered into a decision tree, and when applied to our cohort yielded a sensitivity of 86.4%, specificity of 92.3%, positive predictive value of 90.5% and negative predictive value of 88.9%. We also applied previously reported predictive tools such as the GAP Index, du Bois score and CPI Index to the Edinburgh IPF cohort. Conclusions SLB can be of value in the diagnosis of ILD, however perhaps due to the perceived risks associated with the procedure, only a small percentage of patients undergo SLB despite recommendations that patients have histological confirmation of the diagnosis. Advanced age is a strong predictor for IPF, and in our cohort 83% of patients aged over 65 years with 'possible UIP' HRCT appearances, had UIP on biopsy. BAL and repeat BAL in IPF is feasible and safe (< 1.5% mortality). Of those that underwent repeat BAL, disease progression was not associated with a change in DCC. However, 22% of lavaged patients died or were deemed too frail to undergo a second procedure at 12 months. These data emphasise the importance of BAL in identifying a novel human AM polarisation phenotype in IPF. Our data suggests there is a distinct relationship between AM subtypes, cell-surface expression markers, PMLC subpopulations and disease progression in IPF. This may be utilised to investigate new targets for future therapeutic strategies. / Disease progression in IPF can be predicted by a combination of clinical variables and serum biomarker profiling. We have identified a unique prediction model, when applied to our locally referred, incident, treatment naïve cohort can confidently predict disease progression in IPF. IPF is a heterogeneous disease and there is a definite clinical need to identify 'personalised' prognostic biomarkers which may in turn lead to novel targets and the advent of personalised medicines.
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Prognostic Biomarkers and Target Proteins for Treatment of High-grade GliomasSooman, Linda January 2014 (has links)
The survival for high-grade glioma patients is poor and the treatment may cause severe side effects. A common obstacle in the treatment is chemoresistance. To improve the quality of life and prolong survival for these patients prognostic biomarkers and new approaches for chemotherapy are needed. To this end, a strategy to evade chemoresistance was evaluated by combining chemotherapeutic drugs with agents inhibiting resistance mechanisms identified by a bioinformatic analysis (paper I). The prognostic value of 13 different proteins was analyzed in this thesis (papers II-IV). Two of them, p38 mitogen-activated protein kinase (MAPK) and protein tyrosine phosphatase non-receptor type 6 (PTPN6, also known as SHP1) were analyzed for their potential as targets in combination chemotherapy (in paper III and IV, respectively). We found that: PTPN6 expression and methylation status may be important for survival of anaplastic glioma patients, p38 MAPK phosphorylation may be a potential negative prognostic biomarker for high-grade glioma patients and FGF2 expression may be a potential negative prognostic biomarker for proneural glioma patients. PTPN6 may be a useful target for combination chemotherapy with cisplatin, melphalan or bortezomib in high-grade gliomas. The following drug combinations; camptothecin combined with an EGFR or RAC1 inhibitor, imatinib combined with a Notch or RAC1 inhibitor, temozolomide combined with an EGFR or FAK inhibitor and vandetanib combined with a p38 MAPK inhibitor may be useful combination chemotherapy for high-grade gliomas.
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Identification de biomarqueurs prédictifs de la survie et de l'effet du traitement dans un contexte de données de grande dimension / Identification of biomarkers predicting the outcome and the treatment effect in presence of high-dimensional dataTernes, Nils 05 October 2016 (has links)
Avec la révolution récente de la génomique et la médecine stratifiée, le développement de signatures moléculaires devient de plus en plus important pour prédire le pronostic (biomarqueurs pronostiques) ou l’effet d’un traitement (biomarqueurs prédictifs) de chaque patient. Cependant, la grande quantité d’information disponible rend la découverte de faux positifs de plus en plus fréquente dans la recherche biomédicale. La présence de données de grande dimension (nombre de biomarqueurs ≫ taille d’échantillon) soulève de nombreux défis statistiques tels que la non-identifiabilité des modèles, l’instabilité des biomarqueurs sélectionnés ou encore la multiplicité des tests.L’objectif de cette thèse a été de proposer et d’évaluer des méthodes statistiques pour l’identification de ces biomarqueurs et l’élaboration d’une prédiction individuelle des probabilités de survie pour des nouveaux patients à partir d’un modèle de régression de Cox. Pour l’identification de biomarqueurs en présence de données de grande dimension, la régression pénalisée lasso est très largement utilisée. Dans le cas de biomarqueurs pronostiques, une extension empirique de cette pénalisation a été proposée permettant d’être plus restrictif sur le choix du paramètre λ dans le but de sélectionner moins de faux positifs. Pour les biomarqueurs prédictifs, l’intérêt s’est porté sur les interactions entre le traitement et les biomarqueurs dans le contexte d’un essai clinique randomisé. Douze approches permettant de les identifier ont été évaluées telles que le lasso (standard, adaptatif, groupé ou encore ridge+lasso), le boosting, la réduction de dimension des effets propres et un modèle implémentant les effets pronostiques par bras. Enfin, à partir d’un modèle de prédiction pénalisé, différentes stratégies ont été évaluées pour obtenir une prédiction individuelle pour un nouveau patient accompagnée d’un intervalle de confiance, tout en évitant un éventuel surapprentissage du modèle. La performance des approches ont été évaluées au travers d’études de simulation proposant des scénarios nuls et alternatifs. Ces méthodes ont également été illustrées sur différents jeux de données, contenant des données d’expression de gènes dans le cancer du sein. / With the recent revolution in genomics and in stratified medicine, the development of molecular signatures is becoming more and more important for predicting the prognosis (prognostic biomarkers) and the treatment effect (predictive biomarkers) of each patient. However, the large quantity of information has rendered false positives more and more frequent in biomedical research. The high-dimensional space (i.e. number of biomarkers ≫ sample size) leads to several statistical challenges such as the identifiability of the models, the instability of the selected coefficients or the multiple testing issue.The aim of this thesis was to propose and evaluate statistical methods for the identification of these biomarkers and the individual predicted survival probability for new patients, in the context of the Cox regression model. For variable selection in a high-dimensional setting, the lasso penalty is commonly used. In the prognostic setting, an empirical extension of the lasso penalty has been proposed to be more stringent on the estimation of the tuning parameter λ in order to select less false positives. In the predictive setting, focus has been given to the biomarker-by-treatment interactions in the setting of a randomized clinical trial. Twelve approaches have been proposed for selecting these interactions such as lasso (standard, adaptive, grouped or ridge+lasso), boosting, dimension reduction of the main effects and a model incorporating arm-specific biomarker effects. Finally, several strategies were studied to obtain an individual survival prediction with a corresponding confidence interval for a future patient from a penalized regression model, while limiting the potential overfit.The performance of the approaches was evaluated through simulation studies combining null and alternative scenarios. The methods were also illustrated in several data sets containing gene expression data in breast cancer.
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Altérations de composition des ribosomes dans les cancers du sein : analyses de cohortes humaines et modèles cellulaires / Alterations of ribosomes composition in breast cancers : analyses of human cohorts and cellular modelsNguyen Van Long, Flora 26 June 2019 (has links)
Les ribosomes sont responsables de la traduction des ARNm en protéines. Des modifications de la composition des ribosomes altèrent son activité de traduction et favorisent la tumorigenèse. L’identification des altérations de composition des ribosomes dans les cancers du sein pourrait être un nouveau mécanisme de tumorigenèse mammaire et ouvrir de nouvelles perspectives thérapeutiques. En effet, les cancers du sein restent la première cause de mortalité liés aux cancers chez la femme et leur hétérogénéité induit un problème thérapeutique important. Dans ce contexte, les altérations de composition des ribosomes dans les cancers du sein ont été abordées dans des cohortes humaines et dans des modèles cellulaires de l’EMT (Transition Epithélio-Mésenchymateuse), un processus impliqué dans la tumorigenèse mammaire. Ces travaux ont permis d’identifier : i) deux facteurs impliqués dans la biogenèse des ribosomes, FBL (fibrillarine) et NCL (nucléoline) dont les variations d’expression sont associées à un mauvais pronostic chez les patientes ; et ii) des variations de composition du ribosome et de son activité traductionnelle dans l’EMT. L’ensemble de ces résultats soutient l’existence d’altérations de composition des ribosomes dans les cancers du sein / Ribosomes are responsible of translating mRNAs to proteins. Alterations of ribosome composition modify its translation activity and favour tumourigenesis. Identification of ribosomes composition alterations in breast cancers might correspond to a new mechanism responsible of mammary tumourigenesis and might open up novel therapeutic approaches. Indeed breast cancers represent the first cause of women mortality due to cancers and their heterogeneity induces an important therapeutic problem.In this context, alterations of ribosomes composition were determined in human cohorts and in EMT (Epithelial to Mesenchymal Transition) cellular models, the EMT being a process involved in mammary tumourigenesis. This studies identify : (i) two factors involved in ribosome biogenesis, FBL (fibrillarin) and NCL (nucleolin) whose expression variations are associated with poor prognosis in patients and (ii) variations of ribosome composition and its translational activity in EMT. Altogether, this data support the presence of ribosomes composition alterations in breast cancers
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Implication du métabolisme de la sérotonine dans les cancers du sein triple négatifs et perspectives cliniques / Implication of Serotonin Metabolism in Triple Negative Breast Cancers and Clinical PerspectivesMarques Pinheiro, Alice 20 September 2019 (has links)
Les cancers triple négatif (TN) représente la forme la plus agressive des cancers du sein, avec un pourcentage de décès importants. Il existe une grande hétérogénéité au sein de cette maladie en termes de présentation clinique initiale, de caractéristiques biologiques, de sensibilité au traitement et d’évolution. Aucun progrès en survie n’a été réalisé depuis l’avènement des protocoles de chimiothérapie standards. En effet, malgré une bonne réponse initiale au traitement, 65% des patientes résistent aux thérapies actuelles et récidivent ce qui leur confère un pronostic particulièrement sombre. Il y a donc urgence à identifier de nouveaux protocoles de traitement et de nouvelles molécules efficaces pour ces patientes.Une stratégie de plus en plus intéressante actuellement est celle du repositionnement de composés médicaux qui n’étaient initialement pas destinés au traitement d’une maladie donnée. Cette approche a pour avantage de profiter de l’effort de recherche et développement initial extrêmement couteux et de profiter des études pharmacologiques déjà disponibles. J’ai ainsi effectué au cours de ma thèse un criblage de composés chimiques à haut débit sur 12 lignées de cancers du sein TN afin de prendre en compte leur hétérogénéité. A l’issue de ce crible, plusieurs composés se sont avérés intéressants de par leur potentiel anti-cancéreux. Plus particulièrement, des molécules psychoactives impliquées dans le métabolisme de la sérotonine (ie antidépresseurs, et notamment les inhibiteurs de recapture de la sérotonine-SSRI) sont apparues comme des « hits » forts.Suite à ces résultats, mon travail de thèse s’est orienté plus particulièrement vers la compréhension de l’activité de ces molécules et du métabolisme de la sérotonine dans nos modèles TN afin de comprendre pourquoi ces composés pouvaient présenter un intérêt dans le traitement de ces cancers. Différents aspects biologiques ont ainsi été investigués pour ces antidépresseurs. J’ai ainsi étudié le rôle exercé par la sérotonine sur mes modèles cellulaires. D’autre part, j’ai entrepris une cartographie des acteurs du métabolisme de la sérotonine afin de caractériser mes modèles. J’ai ainsi découvert deux récepteurs à la sérotonine majoritairement présents, HTR1D et HTR1B, qui ont fait l’objet de recherches approfondies. J’ai ainsi pu démontrer l’intérêt de ces deux récepteurs comme cibles thérapeutiques potentielles dans les cancers triple négatifs. Grace à une étude rétrospective j’ai pu mettre en évidence une corrélation statistiquement significative entre le niveau d’expression de chacun de ces deux récepteurs et la survie des patientes TN. Nous observons ainsi une nette discrimination entre les deux groupes de cancers exprimant peu ou fortement ces gènes. J’ai ainsi pu mettre en évidence que ces deux récepteurs représentent des biomarqueurs pronostics forts des patientes TN. L’étude immunohistochimique, a permis de confirmer la présence de ces récepteurs dans les tumeurs TN. Par ailleurs, j’ai pu identifier un micro ARN régulant l’expression de l’un des récepteurs dans les lignées TN. De façon cohérente, j’ai pu observer un effet pronostic significatif du niveau d’expression de ce micro ARN sur la survie des patientes TN. L’efficacité des composés de type SSRI et d’un antagoniste de nos deux récepteurs a pu être vérifiée sur des cultures ex vivo issues de PDX notamment résistantes aux chimiothérapies. L’évaluation préclinique de ces composés a pu être testée sur un premier modèle murin TN de type PDX mais n’a cependant pas permis de démontrer d’efficacité antitumorale in vivo. En effet, la complexité du métabolisme de la sérotonine, tout comme l’hétérogénéité biologique des TN requièrent des études plus approfondies afin de pouvoir faire la preuve de concept du ciblage thérapeutique de ces récepteurs et de la modulation du métabolisme de la sérotonine dans ces cancers. Ce travail fait l’objet d’un manuscrit en préparation pour publication dans le cadre de cette thèse. / Triple negative breast cancer (TNBC) is the most aggressive form of breast cancers. It accounts for 15-20% of breast cancers. No progress in survival has been achieved since the advent of standard chemotherapy protocols. TNBC is an important clinical challenge. They have the worst outcome among breast cancer subgroups. Given their poor prognosis, their assumed hetetogeneity, and absence of any alternative specific targeted therapy, chemotherapy remains the only TNBC treatment. Despite an often good initial response to treatment, more than a half of patients do not achieve a pathological complete response, with a frequent and fast tumor relapse. Several therapeutic approaches have been identified preclinically, but none of these molecules have been shown to be effective on all of these patients. There is a urge for the identification of new treatments.An interesting strategy is the repurposing of medical compounds that were initially not intended for the treatment of a given disease. This strategy takes advantage of the extremely expensive initial research and development effort. This process is potentially efficient and cost-effective as previous clinical trials have been performed and pharmacokinetics/pharmacodynamics and toxicity have been already explored. In order to develop new treatment schemes we addressed the following question: Is there available drugs with strong activity in TNBC? To do so, we performed a high-throughput drug screening on 12 TNBC cell lines to reflect the dramatic heterogeneity of the disease. From this drug discovery program, several interesting compounds were identified with significant anti-tumor potential against TNBC. More particularly, psychoactive compounds regulating serotonin metabolism (ie antidepressant drugs and notably serotonin selective reuptake inhibitors-SSRIs) were found to be highly effective “hits”.My thesis work turned to the comprehension of serotonin implication in TNBC physiopathology to understand if modulating its metabolism could be of therapeutic interest for TNBC management. Different biological aspects were investigated concerning serotonin effects on TNBC cellular models (serotonin adjunction in vitro or endogenous synthesis inhibition). In addition, I established a comprehensive map of the serotonergic landscape in TNBC (biosynthetic capacity, transporters, receptors) that led to the identification of therapeutic targets that would be of interest in the treatment of cancer: HTR1D and HTR1B. Indeed, by blocking these promising targets (with chemical inhibitors or siRNA knockdown) we observed a strong reduction in cell viability in our large panel of TNBC cell lines. Remarkably, we found that their expression levels were associated to poor prognosis in breast cancer, and notably in TNBC subtype with huge dichotomy observed in the outcome, allowing future stratification of TNBC patient management and selection for further targeted therapies. These results pinpoint HTR1D and HTR1B as strong prognosis biomarkers in TNBC. Immunohistochemistry staining was also conducted to confirm the presence of these targets at the protein level in tumor samples. Moreover, I could identify a microRNA regulating one of these receptors: has-miR-599. Consistently, expression levels of this microRNA demonstrated a prognostic impact on TNBC survival. While ex vivo data of one SSRI and the dual antagonist of HTR1D/HTR1D receptors shown encouraging efficacy, their preclinical evaluation assessed in a TN PDX model could not allow to demonstrate any significant effect on tumor growth in vivo. As a matter of fact, serotonin metabolism is a complex system and TNBC heterogeneity does not permit to conclude on the therapeutic proof of concept of the serotonergic modulation in TNBC with this first attempt. A scientific manuscript of this work is being prepared for publication.
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Identification of Therapeutic Targets for Oral Squamous Cell CarcinomaAvinash, Pradhan Shalmali January 2013 (has links) (PDF)
Oral squamous cell carcinoma (OSCC) is the most common head and neck cancer, with a
worldwide incidence of 275,000 new cases annually (Warnakulasuriya, 2009). Globally, the head and neck carcinoma represents a major cause of morbidity and mortality and is the sixth most commonly occurring cancer (Warnakulasuriya, 2009). A majority (>90%) of the head and neck cancers are squamous in origin and thus are linguistically referred to as head and neck squamous cell carcinoma (HNSCC) (Warnakulasuriya, 2009). HNSCC includes cancers of the oral cavity, larynx and pharynx; oral cancer being the most common (Warnakulasuriya, 2009).
Although, HNSCC is the sixth most common cancer globally (Warnakulasuriya, 2009), the
Indian scenario is graver. According to GLOBOCAN 2008 (http://globocan.iarc.fr), the
worldwide age standardized incidence rate (ASR) for HNSCC (and thus OSCC) is 5.3 and 2.5 per 100,000 males and females respectively (Ferlay et al., 2010). In India, the ASR is 9.8 and 5.2 per 100,000 males and females respectively, clearly demonstrating a remarkably high incidence rate of OSCC (Ferlay et al., 2010; http://globocan.iarc.fr). OSCC is a peculiar cancer which is largely preventable and rarely presents as a familial disorder. The most common etiological factors associated with OSCC include tobacco and alcohol consumption (Johnson, 2001). Additionally, high risk human papillomaviruses (HPV strains 16 and 18) as well as genetic predispositions have been implicated.
The treatment of OSCC mainly relies on surgical resection of the tumor. The site, size, depth of infiltration and proximity to the bone of the tumor determine whether a combination of surgery with radiation therapy or chemotherapy would be advised (Scully and Bagan, 2009). The concomitant chemo-radiation therapy is the most commonly used strategy in locally advanced cancer. Taxanes (e.g., paclitaxel and docetaxel) and platinum-based induction chemotherapy (e.g., cisplatin) are the options in the treatment of locally advanced cancer. Epidermal growth factor receptor (EGFR) targeted with cetuximab in combination with radiotherapy has been successfully tested in a large randomized trial and thus is currently a new option (Scully and Bagan, 2009). The success of cetuximab has paved the path for the development and implementation of molecules targeting various signaling pathways.
Despite extensive research on oral squamous cell carcinoma (OSCC), the five-year survival rate has not changed in several decades with the exception of the targeted treatment strategies involving cetuximab as discussed above. The current chemotherapeutic approaches lack selectivity and are flagitious. Thus, effective treatment of OSCC requires the identification of molecular targets to design appropriate therapeutic strategies. To this end, the present study took three distinct approaches in order to validate the use of existing targets and to reveal novel prognostic biomarkers and therapeutic targets.
1) Targeting the PI3K-AKT-MTOR pathway in OSCC and identification of determinants of its sensitivity.
2) Gene expression analysis of ectopically overexpressed TSC2 to identify new therapeutic targets and prognostic biomarkers as well as to elucidate the genes regulated by it.
3) Expression profiling of CYP1B1 in order to validate the use of CYP1B1 based prodrug therapy in OSCC.
Investigations pertaining to the changes in gene and protein expression profiles in malignant as well as pre-malignant lesions have documented the deregulation of the PI3K-AKT-MTOR (phosphoinositide 3-kinase-AKT-mechanistic target of rapamycin) and EGFR (epidermal growth factor receptor) pathways in OSCC which are being widely targeted in many therapeutic strategies (Molinolo et al., 2007; Chakraborty et al., 2008; Matta and Ralhan, 2009; Molinolo et al., 2009; Stransky et al., 2011). The PI3K-AKT-MTOR pathway is a central hub for controlling cellular proliferation and growth in response to various intracellular as well as extracellular stimuli. Crucial signaling cascades including WNT, RAS, HIF-1α and AMPK cross-talk with the PI3K-AKT-MTOR pathway at a variety of molecular junctions. Thus, making this pathway sensitive to perceiving various growth modulatory conditions, ranging from the presence of growth factors to hypoxia and nutrient deprivation (Sengupta et al., 2010; Yang and Guan, 2007).
The aberrant expression of the PI3K-AKT-MTOR pathway in OSCC advocated the targeting of this coveted pathway (Chakraborty et al., 2008). In various cancers, the monotherapeutic treatments with inhibitors like LY294002 (PI3K inhibitor) and rapamycin (MTOR inhibitor) demonstrated reduced efficacies. Such reduced efficacies were attributed to the drug toxicity and non-specific action of LY294002 (Davies et al., 2000; Sun et al., 2005; Ikezoe et al., 2007; Wang et al., 2008; Liu et al., 2009), or the ablation of a feedback inhibition loop leading to the reactivation of the PI3K-AKT-MTOR pathway by rapamycin (O'Reilly et al., 2006; Carracedo et al., 2008). Thus, rapamycin or its analogues demonstrated mediocre efficacy due to cytostatic effects in clinical trials, primarily due to the paradoxical activation of major survival kinases namely MAPK and AKT (O'Reilly et al., 2006; Carracedo et al., 2008).
The present study aimed at increasing the efficacy of these drugs by incorporating a combinatorial approach. The MTT assay demonstrated that prolonged monotherapeutic treatments with rapamycin led to a modest growth inhibition in three OSCC (KB, SCC131 and SCC084) and HeLa cell lines. Western blot analysis of the phosphorylation status of AKT and RPS6KB1 revealed that monotherapeutic treatments with rapamycin for 96 hr led to the reactivation of the PI3K-AKT-MTOR pathway. Thus, the modest growth inhibitory effect of rapamycin was attributed to the reactivation of the PI3K-AKT-MTOR pathway. A combinatorial treatment approach was hence believed to circumvent this problem in order to increase the efficacy of targeting the PI3K-AKT-MTOR pathway. The PI3K inhibitor LY294002 was used combinatorially with rapamycin. This prolonged dual combinatorial treatment regime was distinctly more efficacious than either of the drugs alone and led to a reduction in cellular viability accompanied by increased sub-G1 population, indicating marked cell death that was characterized as caspase-3 dependent apoptosis. The differential sensitivity of the cell lines towards this combinatorial treatment revealed a novel determinant of the sensitivity, the transactivation of EGFR. The cell lines (SCC131 and SCC084) that were capable of transactivating EGFR were relatively resistant to the dual targeting of PI3K and MTOR in comparison to cell lines that did not transactivate EGFR (HeLa and KB). Further, targeting PI3K, MTOR and EGFR simultaneously was more efficacious in the presence of EGFR transactivation than dually targeting PI3K and MTOR. The results conclusively proved that the combinatorial therapeutic approach dually targeting PI3K and MTOR is a promising treatment strategy as compared to a monotherapeutic treatment and a major factor determining the sensitivity towards this treatment is the status of autophosphorylation of EGFR (Tyr1173) which governs the potential for EGFR transactivation by the combinatorial treatment. Thus, this study demonstrated that the status of EGFR autophosphorylation (Tyr1173) can be used as a biomarker to predict the sensitivity towards the combinatorial targeting of PI3K and MTOR in OSCC.
The PI3K-AKT-MTOR pathway is negatively regulated by TSC2 (tuberous sclerosis complex 2; tuberin) (Tee et al., 2002). The importance of the TSC2 gene in the regulation of cell growth and proliferation is irrefutable. TSC2 facilitates the crosstalk between a variety of cellular signals, making it a crucial hub where many cellular networks integrate like AKT, MAPK and AMPK (Clements et al., 2007; Rosner et al., 2007; Rosner et al., 2008). It is a tumor suppressor gene and is downregulated in many cancers including OSCC (Chakraborty et al., 2008). In order to identify the genes regulated by TSC2 in OSCC, we stably overexpressed TSC2 in KB cells and the changes in the gene expression profiles caused by this ectopic overexpression were observed using a whole genome expression microarray. The results showed differential regulation of 268 genes (107 genes were upregulated and 161 genes were downregulated, p<0.05, fold change ≥ 1.5). A majority of these genes were functionally associated with transcription, cell growth and proliferation, apoptosis, cell cycle and neurogenesis. Functional annotation and network analysis was performed by using the DAVID v6.7 and IPA version 8.7 softwares. The microarray data revealed a novel aspect in the crosstalk between WNT signaling and TSC2, namely the transcriptional regulation of WNT signaling by TSC2. Further, in the context of therapeutic applications, the microarray analysis revealed multiple genes that were functionally categorized to be involved in response to radiation, UV and drugs (e.g., SERPINB13 and IL1B). Future studies on the regulation of such genes that are involved in responses to drugs and radiation may give insights into the role of TSC2 in resistance or sensitivity towards chemotherapy and radiation therapy.
Moreover, EREG, a member of the epidermal growth factor family, was found to be the most downregulated gene in the microarray analysis. Previous reports have documented elevated levels of EREG in tuberous sclerosis lesions and its association with poor clinical prognosis in OSCC patients (Li et al., 2008; Shigeishi et al., 2008), making its regulatory aspects intriguing. Additionally, published data on the transcriptional functions of TSC2 instigated us to analyze the role of TSC2 in the regulation of EREG. TSC2 has been shown to modulate the transcription mediated by members of the steroid receptor superfamily of genes (Henry et al., 1998) and was shown to bind specifically to ERα and inhibit estrogen induced proliferation (Finlay et al., 2004). Also, TSC2 has been shown to possess C-terminal transcriptional activation domains (Tsuchiya et al., 1996). We have therefore attempted to investigate the transcription related functional aspects of TSC2 by exploiting the observed transcriptional repression of EREG.
The physiological roles of TSC1 and TSC2 that are independent of the PI3K-AKT-MTOR pathway have been termed as ‘non-canonical’ (Neuman and Henske, 2011). The repression of EREG by TSC2 was observed to be insensitive to rapamycin, suggesting that it was independent of MTORC1 and thus a non-canonical function of TSC2. To determine whether the repression in EREG was at the level of the promoter, we performed a dual luciferase reporter assay. The results showed that the EREG promoter was repressed by stable as well as transient overexpression of TSC2.
In order to elucidate the mechanism of transcriptional regulation by TSC2, we performed the ChIP analysis to observe the in vivo binding of TSC2 to the EREG promoter. In the ChIP analysis with the anti-TSC2 antibody, we observed that TSC2 did not bind to the EREG promoter between the regions -857 bp to -302 bp or -325 bp to +165 bp. Further, in silico analysis revealed an interesting trend among the transcription factors that were differentially regulated by TSC2 and had putative binding sites on the EREG promoter. A majority of these transcription factors (17/21) were downregulated by the overexpression of TSC2. This observation suggested that the repression of EREG could be an indirect effect due to repression of transcription factors caused by overexpression of TSC2. On the whole, this study revealed novel functions of TSC2 in OSCC with implications in determining novel biomarkers and therapeutic targets.
As discussed previously, OSCC has a very flagitious treatment regime. A prodrug approach is thought to aid in targeting chemotherapy (Rooseboom et al., 2004). CYP1B1, a member of the cytochrome P450 family, has been implicated in chemical carcinogenesis (Bandiera et al., 2005; Sliwinski et al., 2010). There exists a general accordance that this protein is overexpressed in a variety of cancers (e.g., colon, lung, renal, bladder, prostate, breast, endometrial and esophageal cancers), making it an ideal candidate for a prodrug therapy (McFadyen et al., 1999; Murray et al., 2001; McFadyen et al., 2004; Sissung et al., 2006; Wen and Walle, 2007; Sliwinski et al., 2010). The activation of the prodrug facilitated by CYP1B1 would enable the targeting of chemotherapy to tumor tissues in which CYP1B1 is specifically overexpressed as a result reducing the non-specific side effects that the current chemotherapy elicits (Rooseboom et al., 2004). This study was aimed at validating the use of CYP1B1 as a target for the prodrug therapy in OSCC. The expression profile of CYP1B1 was analysed in a panel of 51 OSCC tumors, their corresponding normal tissues, an epithelial dysplasia lesion and its matched normal tissue by qRT-PCR, Western blotting and Immunohistochemistry. Counterintuitively, CYP1B1 was found to be downregulated in 77.78% (28/36) tumor tissues in comparison to their corresponding normal tissues as well as in the epithelial dysplasia lesion compared to its matched normal tissue at the transcriptional level, and in 92.86% (26/28) of tumor tissues at the protein level. This clearly demonstrated the downregulation of CYP1B1 at the transcriptional and translational levels in tumor tissues in comparison to their corresponding normal tissues. These observations indicate that caution should be observed as this therapy may not be applicable universally to all cancers. Since CYP1B1 has been shown to be involved in the activation of pro-carcinogens (Murray et al., 2001; Bandiera et al., 2005; Sissung et al., 2006), its inhibition could facilitate the development of a prophylactic therapy for oral cancer.
Overall, this study has identified the transactivation of EGFR as a determinant of sensitivity towards combinatorial targeting of PI3K and MTOR in OSCC and has demonstrated that the autophosphorylation of EGFR (Tyr1173) can be used as a marker to judge the sensitivity towards this treatment. In the clinical perspective, the identification of such markers would aid in predicting the efficacy of targeted therapies. Such investigations would enable the strategic treatment of OSCC patients, thus decreasing the time lost in trial and errors for determining the appropriate treatment. Additionally, this study elucidated a novel role of TSC2 in the transcriptional repression of EREG, a prognostic biomarker for OSCC. Further, the study revealed potential prognostic biomarkers as well as therapeutic targets that are regulated by TSC2 by using a whole genome expression microarray. Moreover, the counterintuitive downregulation of CYP1B1 in OSCC tumors suggested the possibility of a prophylactic therapy for oral cancer but also advised a precautionary note for the application of prodrug treatments based on CYP1B1 overexpression in OSCC.
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