Dissertations / Theses on the topic 'Classification des gliomes'

Les gliomes, tumeurs cérébrales primaires du système nerveux central, sont souvent de pronostic défavorable, d'autant plus que l'absence de critères indiscutables pour les identifier rend leur diagnostic et leur prise en charge particulièrement difficiles. L’analyse conjointe, d’une cohorte française de 64 patients porteurs de gliomes et d’une cohorte internationale de 671 patients issus du TCGA, a permis de mettre en évidence deux groupes pronostiques constitués par un panel d’expression différentielle de 26 gènes (p = 0,007). Cette stratification en deux groupes pronostiques a été confirmée quels que soient le grade et le groupe moléculaire de la tumeur (p < 0,0001). Nous avons établi une nouvelle stratégie diagnostique à partir de la classification moléculaire des gliomes en intégrant deux biomarqueurs pronostiques CHI3L1 et NTRK2. L’analyse multivariée confirme que ces biomarqueurs sont indépendants du statut IDH et du grade tumoral. Si nous avons mis en évidence par l’analyse protéique de CHI3L1 une concordance avec les transcrits, les résultats divergent pour TrkB. Ainsi, une expression élevée de TrkB et son corécepteur p75NTR serait liée à l’agressivité tumorale indépendamment du statut IDH. Enfin, TrkB et p75NTR sont présents aussi bien dans les exosomes issus du plasma de témoins sains et de patients atteints de gliomes mais leur expression augmente en fonction de l’agressivité de la tumeur
Gliomas, primary brain tumours of the central nervous system, are often of poor prognosis.The absence of clear criteria to identify them makes their diagnosis and management particularly difficult. The combined analysis of a cohort of 64 glioma patients and an international cohort of 671 patients from the TCGA revealed two prognostic groups of a differential expression panel of 26 genes (p = 0.007). This stratification into two prognostic groups was confirmed independently of the grade and molecular group of the tumor (p <0.0001). We have established a new diagnostic strategy based on the molecular classification of gliomas by integrating two prognostic biomarkers CHI3L1 and NTRK2. Multivariate analysis confirms that these biomarkers are independent of IDH status and tumor grade.While we have demonstrated by the protein analysis of CHI3L1 concordance with the transcripts, the results are different for TrkB. Therefore, a high expression of TrkB and its p75NTR co-receptor would be associated with tumor aggressiveness regardless of IDH status. Lastly, TrkB and p75NTR are present in exosomes from plasma of healthy controls and glioma patients, but their expression increases with the aggressiveness of tumor

L’incidence des gliomes est estimée à 6.6 pour 100 000 habitants. Les survies varient selon le sous-type de gliomes, avec des taux de survie à 5 ans d’environ 48% pour les astrocytomes diffus selon la classification de l’Organisation Mondiale de la Santé (OMS), 28% pour les astrocytomes anaplasiques, 80% pour les oligodendrogliomes, 52% pour les oligodendrogliomes anaplasiques et 5% pour les glioblastomes, tumeurs cérébrales malignes les plus fréquentes.Une meilleure compréhension des mécanismes et de la biologie de ces tumeurs et de nouvelles pistes thérapeutiques sont essentielles afin d’identifier de nouvelles thérapies pouvant améliorer le pronostic des patients. La classification OMS 2016 des tumeurs du système nerveux central a, pour la première fois, intégré les données de biologie moléculaires aux données histopathologiques, afin d’améliorer la distinction des différents sous-groupes de tumeurs et d’orienter au mieux les choix thérapeutiques pour chaque sous-groupe.Nous nous sommes intéressés dans ce travail à l’apport de l’approche en protéomique par imagerie par matrix-assisted laser desorption/ionization spectrométrie de masse MALDI (MALDI-MSI) couplée à l’analyse en microprotéomique dans les gliomes dans le cadre de l’étude clinique GLIOMIC (NCT02473484) qui a pour but de réaliser une classification moléculaire des gliomes en intégrant les données cliniques et celles obtenues par ces nouvelles approches.La faisabilité de la technique a d’abord été validée sur une série de gliomes anaplasiques. Dans cette première analyse, nous avons pu démontrer que, bien que l’approche protéomique confirmait également l’hétérogénéité tumorale, les analyses histologiques et protéomiques divergent et apportent des informations complémentaires. L’imagerie moléculaire protéomique a mis en évidence trois différents groupes d’expression de protéines : un groupe de protéines associé au cancer, un groupe de protéines impliquées dans l’inflammation et un groupe de protéines impliquées dans la différentiation des cellules nerveuses et la croissance des neurites.Nous nous sommes ensuite intéressés aux glioblastomes. Les premiers résultats ont également confirmés l’existence des 3 régions d’intérêt définies sur le plan moléculaires, apportant de nouvelles informations par rapport aux données histopathologiques. Ces résultats doivent être confirmés dans une cohorte plus large de patients.En conclusion, l’intégration de ces biomarqueurs protéomiques, aux données cliniques, histopathologiques et de biologie moléculaire, pourrait permettre d’améliorer les connaissances sur les gliomes, leur classification et l’identification de nouvelles cibles thérapeutiques potentielles
The annual incidence of gliomas is estimated at 6.6 per 100,000. Suvival varies profoundly by type of glioma, with 5-year survival rates of 48% for World Health Organization (WHO) grade II diffuse astrocytoma, 28% for WHO grade III anaplastic astrocytomas, 80% for WHO grade II oligodendroglioma, 52% for WHO grade III anaplastic oligodendroglioma and 5% for WHO grade IV glioblastoma, the most frequent primary malignant brain tumor. A better understanding of the molecular pathogenesis and the biology of these tumors is required to design better therapies which can ultimately improve the prognosis of patients. The WHO 2016 classification of central nervous system tumors has for the first time integrated molecular data with the histopathological data, in order to improve the classification of the different subgroups of central nervous system tumors and to allow to derive more specific therapeutic strategies for each of the different subgroups.In the present work, we aimed at evaluating the value of a proteomic approach using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry coupled with microproteomic analysis in gliomas through the GLIOMIC clinical study (NCT02473484), we aimed at obtaining a molecular classification of glioblastomas by integrating clinical data to the ones obtained by such technologies. The feasibility of this approach was first demonstrated in a cohort of anaplastic gliomas. In this first analysis, we showed that although proteomic analysis confirmed the heterogeneity of brain tumors already observed with the histological analysis, the two approaches may lead to different and complementary information. Three different groups of proteins of interest were identified: one involved in neoplasia, one related to glioma with inflammation, and one involved neurogenesis. Then, analyses of glioblastomas confirmed the three proteomic patterns of interest already observed in the anaplastic gliomas, which represents new information as compared to histopathological analysis alone. These results have to be confirmed in a larger cohort of patients.We conclude that MALDI mass spectrometry coupled with microproteomic analysis may provide new diagnostic information and may aid in the identification of new biomarkers. The integration of these proteomic biomarkers into the clinical data, histopathological data and data from molecular biology may improve the knowledge on gliomas, their classification and development of new targeted therapies

Les gliomes sont des tumeurs agressives de mauvais pronostic, très angiogéniques et infiltrantes ce qui rend leur exérèse particulièrement difficile. Vu les limites des techniques actuelles d’imagerie, nous avons proposé la spectro-imagerie Infrarouge à Transformée de Fourier (IRTF), d’une résolution spatiale de 6 µm, pour apporter une information moléculaire à l’examen histologique actuel des gliomes. Nos travaux ont été fondés sur la recherche de paramètres moléculaires des vaisseaux sanguins, notamment sur la base des contenus de leur membrane basale. Celle-ci subit des altérations dûes au stress angiogénique tumoral. Nous avons mis en évidence des altérations de la structure secondaire des protéines (tels les collagènes) des vaisseaux sanguins au cours de la croissance de la tumeur. Nous avons aussi évalué les modifications des chaines d’acides gras des phospholipides membranaires, qui révélent un degré d’insaturation plus important pour les vaisseaux tumoraux. Ensuite, sur un modèle de gliome murin, nous avons établi une méthode efficace de classification des capillaires sanguins sur la base d’absorptions de leurs contenus glucidiques et lipidiques, permettant de discriminer totalement les capillaires sains et tumoraux. La combinaison de ces paramètres a été mise à profit pour assurer une histopathologie moléculaire des gliomes humains. Nos résultats ont démontré qu’il est possible de différencier entre la vasculature saine et tumorale sur ces gliomes humains, ce qui permet une bonne délimitation des zones tissulaires correspondantes. Cette technique pourrait devenir un outil analytique fiable, rapide d’une durée compatible avec la chirurgie et donc très utile pour les neurochirurgiens
Malignant gliomas are very aggressive tumors with poor prognosis, highly angiogenic and invasive into the surrounding brain parenchyma, making their resection very difficult. Regarding the limits of current imaging techniques, we have proposed Fourier Transform Infrared (FTIR) spectro-imaging, with a spatial resolution of 6 µm, to provide molecular information for the histological examination of gliomas. Our work was based on the research of molecular parameters of blood vessels, notably on the basis of the contents of their basement membrane, which undergoes changes due to tumor angiogenic stress. We have identified alterations of the secondary structure of proteins (such as collagen) in blood vessels during tumor growth. We have also assessed the changes in fatty acyl chains of membrane phospholipids, which revealed a higher unsaturation level in tumor vessels. Then, on a murine glioma model, we have established an efficient method of blood vessels classification based on their carbohydrates and fats contents, allowing the differentiation between healthy and tumor blood vessels. The combination of these parameters was used to provide a molecular histopathology for the study of human gliomas. Our results have demonstrated the feasibility of differentiating between healthy and tumor vasculature in these human gliomas, which help delimitating areas of corresponding tissue. This technique could become a reliable and fast analytical tool, with duration compatible with the surgery and thus very useful for neurosurgeons

L'intelligence artificielle (IA) est très utilisée pour le diagnostic et le traitement de données médicales, donnant lieu à la médecine personnalisée assistée par l'IA. Ce manuscrit se concentre sur la proposition et l'analyse de méthodes d'IA, notamment l'apprentissage profond et la radiomique, pour le diagnostic du cancer. Tout d'abord, une approche efficace de segmentation automatique est essentielle pour mettre en place une méthode de diagnostic par IA, car c'est un préalable à une analyse par radiomiques. Nous avons proposé une nouvelle approche pour la segmentation automatique des lésions dans les images échographiques, basée sur des données multicentrique et multipathologique présentant différents types de cancers. En introduisant la convolution de groupe, nous avons proposé un réseau U-net léger en mémoire sans sacrifier les performances de segmentation. Deuxièmement, nous nous sommes intéressés au traitement de données d'imagerie par résonance magnétique (IRM) pour prédire de manière non invasive le sous-type de gliome, défini par le grade de la tumeur, la mutation de l'isocitrate déshydrogénase (IDH) et la codélétion 1p/19q. Nous proposons une approche par radiomiques. La performance de prédiction s'est améliorée de manière significative en optimisant différents paramètres de notre modèle. Les caractéristiques des éléments radiomiques qui distinguent le mieux les sous-types de gliome ont également été analysées. Ce travail a non seulement fourni un pipeline qui fonctionne bien pour prédire le sous-type de gliome, mais il a également contribué au développement et à l'interprétabilité du modèle radiomique. Troisièmement, nous nous intéressons à la problématique de reproductibilité des approches basées sur les radiomiques. Nous avons donc étudié l'impact de différentes méthodes de prétraitement d'images et de méthodes d'harmonisation (y compris la normalisation de l'intensité et l'harmonisation ComBat) sur la reproductibilité des caractéristiques radiomiques en IRM. Nous avons montré que la méthode ComBat est essentielle pour éliminer la variation non biologique causée par les différents paramètres d'acquisition d'image (à savoir, les effets du scanner) et améliorer la reproductibilité des caractéristiques dans les études radiomiques. Nous avons illustré l'importance de la normalisation de l'intensité, car elle permet d'obtenir des images IRM plus comparables et des résultats plus robustes. Enfin, nous avons cherché à améliorer la méthode ComBat en modifiant l'hypothèse classique, à savoir que les effets du scanner sont différents pour différentes classes (comme les tumeurs et les tissus normaux). Bien que le modèle proposé donne des résultats encore décevants, sûrement en raison du manque de contraintes appropriées pour aider à identifier les paramètres, il a néanmoins ouvert la voie à des perspectives intéressantes
Artificial intelligence (AI) has been widely used in the research field of AI-assisted diagnosis, treatment, and personalized medicine. This manuscript focuses on the application of artificial intelligence methods including deep learning and radiomics in cancer diagnosis. First, effective image segmentation is essential for cancer diagnosis and further radiomics-based analysis. We proposed a new approach for automatic lesion segmentation in ultrasound images, based on a multicentric and multipathology dataset displaying different types of cancers. By introducing the group convolution, we proposed a lightweight U-net network without sacrificing the segmentation performance. Second, we processed the clinical Magnetic Resonance Imaging (MRI) images to noninvasively predict the glioma subtype as defined by the tumor grade, isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status. We proposed a radiomics-based approach. The prediction performance improved significantly by tuning different settings in the radiomics pipeline. The characteristics of the radiomic features that best distinguish the glioma subtypes were also analyzed. This work not only provided a radiomics pipeline that works well for predicting the glioma subtype, but it also contributed to the model development and interpretability. Third, we tackled the challenge of reproducibility in radiomics methods. We investigated the impact of different image preprocessing methods and harmonization methods (including intensity normalization and ComBat harmonization) on the radiomic feature reproducibility in MRI radiomics. The conclusion showed that ComBat method is essential to remove the nonbiological variation caused by different image acquisition settings (namely, scanner effects) and improve the feature reproducibility in radiomics studies. Meanwhile, intensity normalization is also recommended because it leads to more comparable MRI images and more robust harmonization results. Finally, we investigated improving the ComBat harmonization method by changing its assumption to a very common case that scanner effects are different for different classes (like tumors and normal tissues). Although the proposed model yielded disappointing results, surely due to the lack of enough proper constraints to help identify the parameters, it still paved the way for the development of new harmonization methods

La métabolomique est un outil récent, aujourd'hui en plein essor, qui se définit comme étant l'étude de l'ensemble des petites molécules ; les métabolites, produites par un organisme sous différentes conditions. Son application à la problématique du cancer consiste en l'étude des perturbations métaboliques liées au processus oncologique. La métabolomique mêle diverses techniques d'analyses telles que la spectroscopie de masse et la spectroscopie de résonance magnétique nucléaire (RMN), couplées à des méthodes statistiques évoluées afin d'extraire les informations métaboliques pertinentes permettant de caractériser les systèmes biologiques. La spectrométrie RMN haute résolution en rotation à l'angle magique (HRMAS) est la technique que nous avons choisie pour l'étude du métabolome des tumeurs car elle regroupe un nombre important d'avantages (simplicité de préparation des échantillons, la reproductibilité intra et inter laboratoire et le cout relativement modeste de fonctionnement). L'étude principale réalisée dans le cadre de cette thèse a porté sur les tumeurs cérébrales. Une centaine de tumeurs ont ainsi été analysé et leur métabolome caractérisé. L'analyse effectuée s'est focalisé sur la problématique du « grading de malignité » des tumeurs cérébrales, principalement sur les gliomes. Ainsi une forte corrélation a été trouvé entre les profiles métabolique des gliomes (glioblastome, oligodendrogliome) et l'évolution clinique des patients. L'approche métabolomique pour l'étude des tumeurs, d'un point de vue diagnostic et pronostic, semble aujourd'hui prometteuse. De plus l'étude des profiles métaboliques, devrait, à terme, permettre une meilleure compréhension des perturbations métaboliques lié à la pathologie, et potentiellement, conduire à la mise en place de traitements individualisés parfaitement adaptés à chaque patient. Néanmoins, une étape de validation de ces premières observations est aujourd'hui indispensable. C'est pourquoi ces travaux ont accompagné l'installation du premier spectromètre RMN HRMAS dans le milieu clinique en novembre 2007 dans le cadre du projet CARMeN. L'objectif général de ce projet est, maintenant, d'étendre l'expérience acquise durant cette thèse à tous les domaines de la cancérologie où il existe, soit une dissociation entre le diagnostic histopathologique de la tumeur et le devenir du patient, soit une discordance à la réponse thérapeutique pour un sous‐type de tumeur.

La communication intercellulaire par les jonctions gap (CIJG) a été proposée comme l’un des éléments impliqués dans la cancérogenèse très rapidement après sa mise en évidence, dans les années 1960. Ainsi l’induction de l’expression de connexines, motif structural de base de la CIJG, a été décrite comme étant capable de « normaliser » le phénotype de cellules cancéreuses. Notre étude de la connexine 43 (Cx43), par tissue micro array, dans des tumeurs gliales humaines (59 échantillons) a montré une délocalisation et une perte de l’expression de la protéine. La situation s’avère complexe par l’hétérogénéité intratumorale; en effet, certaines cellules du tissu tumoral montrent un signal avec une localisation aberrante dans le cytoplasme ou dans le noyau. Certains travaux ayant suggéré que Cx43 pourrait « normaliser » le phénotype tumoral par une action indépendante de la CIJG, Cx43 ou des formes tronquées de la protéine ont été exprimées par des vecteurs rétroviraux dans des lignées de tumeurs gliales humaines. Les résultats obtenus ont suggéré que l’expression de la protéine ne permettait pas de réduire le potentiel prolifératif des cellules tumorales lorsque celles-ci sont maintenues en monocouche. En revanche, la capacité des cellules à proliférer sans ancrage est réduite par l’expression de Cx43 mais aussi par des formes tronquées de la protéine ne permettant pas la CIJG. De plus, les cellules exprimant Cx43, entière ou tronquée, apparaissent douées d’une plus grande motilité. En conclusion, Cx43 semble jouer un rôle complexe dans la progression des tumeurs gliales humaines, celle-ci apparaissant avec des localisations aberrantes dont l’effet demeure inconnu. L’expression de la Cx43 ne constituerait pas nécessairement un facteur de bon pronostic, car si les cellules montrent une diminution de leur prolifération dans un environnement défavorable, elles semblent, en revanche, plus aptes à migrer, ce qui permettrait l’invasion du tissu environnant
The possible involvement of Gap-Junctional Intercellular Communication (GJIC) in carcinogenesis has been hypothesized in the 1960s. Later, the expression of connexins, the molecular basis of GJIC, has been shown to “normalize” the phenotype of various tumor cells. Our study, using the tissue micro array approach, was focused on connexin 43 (Cx43) expression in human gliomas (59 tumor samples). We showed that the expression of Cx43 protein was altered and, in several cases, especially in grade-IV gliomas, Cx43 was lost. Nonetheless, due to tumor heterogeneity, a complex pattern of expression was revealed: Cx43 exhibited aberrant staining, that means a translocation into the cytoplasm possibly in the nucleus. Several works suggested that Cx43 could « normalize » tumor cells by a GJIC-independent mechanism. We investigated the role played by Cx43 and different truncated forms of the protein, unable to restore GJIC, in human glioma cell lines. Our data showed that Cx43 expression did not induce any change on cell proliferation when cell lines were maintained in monolayer cultures. On the contrary, the cells trandusced by Cx43 constructs (full-length or truncated) grew less in soft agar assay. In parallel, it appeared that all the Cx43 constructs increased motility. To conclude, Cx43 seems to play a complex role in human glioma progression. Its expression and localization are altered, but the underlying mechanisms remain unknown. Even if Cx43 seems to be altered in gliomas, a maintained expression of the protein could not be correlated with a good prognosis since their motility is increased by Cx43 expression

Les gliomes sont les tumeurs primitives les plus fréquentes du système nerveux central. Leur classification repose sur celle de l'OMS, mais celle-ci manque de reproductibilité. Afin d'améliorer la caractérisation des gliomes, nous avons étudié ces tumeurs d'un point de vue histologique et moléculaire. Nous avons montré que les gliomes sont des tumeurs hétérogènes constituées d'un mélange de précurseurs gliaux immatures et de leur descendance. Les cellules participant à la formation de ces tumeurs pourraient suivre un lignage cellulaire quasi-superposable à celui décrit dans le développement. Par ailleurs, les glioblastomes et les astrocytomes pilocytiques présentent chacun un profil moléculaire caractéristique, utile au diagnostic. Les glioblastomes expriment des protéines impliquées dans l'invasion et l'angiogenèse, deux processus responsables de l'agressivité de ces tumeurs. L'ensemble de ces travaux a permis de préciser l'histogenèse des gliomes et leur cartographie moléculaire
Gliomas are the most frequently occuring primary neoplasms in the central nervous system. The WHO classification remains the standard to classify these tumors, but it suffered from lack of reproducibility. In order to better characterize gliomas, we have studied them in a histological and a molecular point of vue. First, we have shown that gliomas contain a mixture of glial progenitor cells and their progeny. The cells involved in the glioma formation could belong to a glial lineage similar to that observed during development. On the other hand, glioblastomas and pilocytic astrocytomas show differential gene expression patterns, useful for diagnosis. Glioblastomas express a subset of genes involved in invasion and angiogenesis, two processes which are a hallmark of malignancy in these tumours. This work provides cues to glioma histogenesis and to the molecular cartography of these tumors

Les tumeurs sont très hétérogènes à la fois au niveau moléculaire et au niveau de la diversité cellulaire composant leur microenvironnement. La classification des gliomes repose actuellement sur des critères histologiques qui sont enclins à de fortes subjectivités inter- et intra-observateurs. Le but de ce projet est de réaliser une classification moléculaire des gliomes de haut grade en se basant sur des données protéiques permettant de localiser des biomarqueurs potentiels directement sur le tissu. Des sous-régions ayant des profils moléculaires différents ont été mises en évidence et les molécules les composants ont été identifiées. Les résultats démontrent que les annotations histologiques ne concordent pas avec la classification moléculaire. Cette hétérogénéité est également retrouvée dans le microenvironnement des tumeurs où l’on retrouve des cellules immunitaires telles que les macrophages. Les macrophages sont détournés de leur fonction par la tumeur pour lui permettre de se développer. Une stratégie thérapeutique pour contrer sa croissance est de réorienter le phénotype des macrophages vers un phénotype antitumoral. L’inhibition de la proprotéine convertase 1/3 s’est révélée être une stratégie prometteuse pour la réactivation des macrophages via les récepteurs TLR. Les facteurs sécrétés par ces macrophages ont un effet sur la viabilité et l’invasion de différentes cellules cancéreuses en fonction des ligands des récepteurs TLR utilisés. La première partie nous a permis d’identifier des sous-groupes de gliomes qui en fonction de leur profil moléculaire pourront recevoir des traitements personnalisés basés, par exemple, sur l’inhibition de proprotéines convertases
Tumors are highly heterogeneous both histologicaly and molecularly. In fact, several non-neoplasic cell types are present in the microenvironment. Glioma classification is based on histological criteria that are prone to inter- and intra-observers subjectivities. Within tumors of same grade, subgroups can be differentiated. The aim of this project is to realize a molecular classification of high grade glioma based on proteomics data allowing the localization of potential biomarkers directly on the tissue. Subregions having different molecular profiles have been highlighted and the molecules comprising them have been identified in a localized way. Results prove that histological annotations do not necessarily correspond to molecular classification. This heterogeneity is also found in the tumor microenvironment where we can find immune cells such as macrophages. Macrophages are changed from their primary function by the tumor to allow it to grow. A therapeutic strategy to counter the tumor growth has been developed in order to switch macrophages phenotype toward an antitumor one. The inhibition of PC1/3 enzyme has proven to be a promising therapy to reactivate macrophages via TLR receptors. Secreted factors by these PC1/3 inhibited macrophages have an effect on cancer cells viability and invasion according to TLR ligand used. The first part will allow us to identify subgroups of glioma which, depending on their molecular profiles, could, in a long-term view, receive personalized treatments based on the inhibition of proproteins convertases combined to TLR ligands

Anaplastic or Grade III glioma form a diverse group of tumours with a range of prognoses that have been historically managed with surgery followed by surveillance or adjuvant radiation therapy. The onset of molecular testing, specifically the recognition of the IDH1/2 mutations, has been able to identify a subgroup of patients with a more favourable prognosis. With this knowledge there is the need to optimise management, not only consolidate the improved prognosis of these patients, but also to minimise the late morbidity of treatment protocols. The initial chapters of this thesis outline aspects of molecular testing in relation to integrated diagnosis under the WHO 2016 Classification, with the recognition of the more favourable tumours containing IDH mutation (Chapter 2); and an approach to modify radiation therapy based on the presence of IDH mutation and radiological features including PET imaging to improve target volume delineation and minimise late morbidity (Chapter 3). The next two chapters demonstrate the response of these IDH mutated anaplastic glioma to radiation therapy and chemotherapy demonstrating the excellent reduction in radiological volume (Chapter 4), and also the unusual early pattern of failure post treatment based of a subgroup of IDH mutated tumours compared to IDH wild type tumours (Chapter 5). The final two chapters describe the outcome of treatment in regards to favourable six-year progression free survival which should translate to a high ten-year overall survival (Chapter 6). The improved survival is also demonstrated in Chapter 7 to be associated with a high level of functioning at three to five years post treatment with minimal negative impact from therapy.

The identification of eloquent areas is of utmost importance in the surgery of tumors located near speech-eloquent brain areas, since the classical concept of a constant localization was proven to be untrue and the spatial localization of these areas may show large interindividual differences. Some neurosurgical centers apply intraoperative electrophysiological methods that, however, necessitate the performance of surgery in the awake patient. This might be a severe burden both for the patient and the operating team in a procedure that lasts several hours; in addition, electrical stimulation may generate epileptic seizures. Alternatively, methods of functional brain imaging (e.g., PET, fMRI, MEG) may be applied, which allow individual localization of speech-eloquent areas. Matching of these image data with a conventional 3D-CT or MRI now allows the exact transfer of this information into the surgical field by neuronavigation. Whereas standards concerning electrophysiological stimulation techniques that could prevent a permanent postoperative worsening of language are available, until now it remains unclear whether the resection of regions shown to be active in functional brain imaging will cause a permanent postoperative deficit.
Die Identifikation sprachaktiver Areale ist von höchster Bedeutung bei der Operation von Tumoren in der Nähe des vermuteten Sprachzentrums, da das klassische Konzept einer konstanten Lokalisation des Sprachzentrums sich als unrichtig erwiesen hat und die räumliche Ausdehnung dieser Areale eine hohe interindividuelle Varianz aufweisen kann. Einige neurochirurgische Zentren benutzen deshalb intraoperativ elektrophysiologische Methoden, die jedoch eine Operation am wachen Patienten voraussetzen. Dies kann sowohl für den Patienten als auch das Operations-Team eine schwere Belastung bei diesem mehrstündigen Eingriff darstellen, zusätzlich können epileptische Anfälle durch die elektrische Stimulation generiert werden. Alternativ können Modalitäten des «functional brain imaging» (PET, fMRT, MEG usw.) eingesetzt werden, die die individuelle Lokalisation sprachaktiver Areale gestatten. Die Bildfusion dieser Daten mit einem konventionellen 3D-CT oder MRT erlaubt den exakten Transfer dieser Daten in den OP-Situs mittels Neuronavigation. Während Standards bei elektrophysiologischen Stimulationstechniken existieren, die eine permanente postoperative Verschlechterung der Sprachfunktion weitgehend verhindern, bleibt die Relevanz sprachaktiver Areale bei den neuesten bildgebenden Techniken bezüglich einer Operations-bedingten Verschlechterung der Sprachfunktion bisher noch unklar.
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Albright’s hereditary osteodystrophy (AHO) is a rare inherited disease characterized by skeletal abnormalities, short stature, and, in some cases, resistance to parathyroid hormone, resulting in pseudohypoparathyroidism (PHP). Heterozygous inactivating mutations of the GNAS1 gene are responsible for reduced activity of the alpha subunit of the Gs protein (GSα), a protein that mediates hormone signal transduction across cell membranes. Gsα is also known to have oncogenic potentials, leading to the development of human pituitary tumors and Leydig cell tumors. Here, we report the 1st case, a 3.5-year-old girl, with classic AHO phenotype and PHP type 1A associated with a cerebellar pilocytic astrocytoma. Coincidence or genetic relationships of both diseases are discussed according to molecular findings and current literature.
Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.

Patients and methods: Malignant supratentorial glioma (anaplastic astrocytoma, oligoastrocytoma, oligodendroglioma and glioblastoma incl. gliosarcoma), age 16-70y, KPS 50-100. Postoperative randomization to chemotherapy with either BCNU (B) (80 mg/m2 x 3 every 6 weeks) alone or additional VM 26 (V) (50 mg/m2 x 3 every 6 weeks) starting concomitant with radiotherapy. Central histopathological review was required. Primary endpoints were survival time (ST) and progression free survival (PFS) . In addition confirmative analysis of prognostic factors and their interaction with therapy was performed. Results: Eligible: 501 of 522 randomized pts: 82% WHO grade IV gliomas, 18% grade III gliomas. 57% male, mean KPS 74, mean age 50.9 years. The high incidence of lung toxicity – with a cumulative risk of 19% during the first year - was alarming. Survival was not significantly different ( median 50.3 (B) versus 52.4 (V) (weeks), but an increase in long term survivors was observed (18 months: 29% B, 34% V, 5 years 5% B, 12% V) and PFS showed a significant difference with a median of 31.4 (B) versus 34.3 (V) weeks. Qualitative interaction between KPS and therapy (p < 0.01) was demonstrated: pts with a KPS ≥ 70 benefited from additional VM26, those with reduced KPS < 70 did better with BCNU-monotherapy. Conclusion: Adding VM26 to BCNU is effective in the chemotherapy of malignant gliomas. Because of the demonstrated interaction with therapy performance status, not tumor grade is the crucial factor to determine application and aggressiveness of chemotherapy. With risk adapted therapy a significant proportion of patients even with glioblastoma survive for years in good general condition. BCNU should be replaced by an equipotent alkylans to avoid the unacceptable high rate of lung toxicity.

La classification OMS des tumeurs cérébrales de l'enfant distingue les tumeurs gliales des tumeurs glioneuronales, les gliomes circonscrits des infiltrants. Elle représente le meilleur indicateur pronostic mais se heurte pourtant à des limites de reproductibilité. Pour mieux préciser le diagnostic, mieux définir des sous-groupes de pronostic différent, et mieux orienter le thérapeutique, nous avons recherché les profils moléculaires de 108 tumeurs cérébrales circonscrites de l'enfant : astrocytome pilocytique (PA), tumeurs neuroépithéliales dysembryoplasiques (DNT), xanthoastrocytomes pléïomorphes (PXA) et gangliogliomes (GG). Aucune différence n'est retrouvée entre les gliomes corticaux de grade II (GC) et les DNT concernant IDH1 et 2, TP53 et la délétion1p19q. Les DNT non spécifiques et les GC partagent le même profil incluant CD34 et la mutation V600E de BRAF dans 50% des cas. Le PXA exprime la mutation V600E de BRAF dans plus de 50 % des cas et se rapproche du groupe des tumeurs glioneuronales. Concernant le PA, nous confirmons le caractère péjoratif de la topographie hypothalamo-chiasmatique, de l'histologie pilomyxoide, de l'âge inférieur à 36 mois et de l'exérèse partielle. A l'opposé des tumeurs infiltrantes qui appartiendraient au groupe " histones dépendantes", les tumeurs circonscrites pourraient être regroupées sous le terme "MAPKinases dépendantes". On y distinguerait alors les tumeurs avec fusion KIAA1543-BRAF de celles avec mutation V600E de BRAF. Ce travail a permis de mieux caractériser les tumeurs gliales et glioneuronales de l'enfant, reposant sur le transfert en routine de marqueurs moléculaires simples
The OMS classification for pediatric brain tumors includes glial tumors and mixed glial and glioneuronal tumors, diffuse and no diffuse glioma. All strategic decision making are based on this current classification but it drives to some limits of diagnosis reproductibility.The goal of our study was to define molecular profils for low grade no diffuse pediatric brain tumors including pilocytic astrocytoma (PA), dysembryoplasic neuroepithelial tumor (DNT), pleiomorphic xanthoastrocytoma (PXA) and benign gangliogliome (GG), to improve the quality of diagnosis, define different subgroups with different prognosis and then to improve treatment strategy decision making.No molecular difference was found between cortical grade II glioma (GC) and DNT regarding IDH1 and 2 TP53 alterations and 1p19q deletion. Similarly 50 % of no specific form of DNT share the same molecular profil with GC with CD34 expression and V600E mutation of BRAF. PXA demonstrated BRAFV600E mutation in 60 % of cases. PXA could then be very close glioneuronal tumors. Finally in PA we confirmed the negative impact of hypothalochiasmatic location, pilomyxoid diagnosis and age lower than 36 months and partial resection. We could work on the elaboration of a new classification and define the group named “Histone dependant” for tumors with histone aberrations and the group named “MAPKinases dependant” for tumors with either KIAA 1543-BRAF fusion or V600E BRAF mutation.In conclusion, this work has led to improve the molecular profil characteristics of glioneuronal tumors of childhood with different easy diagnostic markers that can be used in routine practice, and could potentially replace DNA sequencing

Changes in gene expression programs play a central role in cancer. Chromosomal aberrations such as deletions, duplications and translocations of DNA segments can lead to highly significant positive correlations of gene expression levels of neighboring genes. This should be utilized to improve the analysis of tumor expression profiles. Here, we develop a novel model class of autoregressive higher-order Hidden Markov Models (HMMs) that carefully exploit local data-dependent chromosomal dependencies to improve the identification of differentially expressed genes in tumor. Autoregressive higher-order HMMs overcome generally existing limitations of standard first-order HMMs in the modeling of dependencies between genes in close chromosomal proximity by the simultaneous usage of higher-order state-transitions and autoregressive emissions as novel model features. We apply autoregressive higher-order HMMs to the analysis of breast cancer and glioma gene expression data and perform in-depth model evaluation studies. We find that autoregressive higher-order HMMs clearly improve the identification of overexpressed genes with underlying gene copy number duplications in breast cancer in comparison to mixture models, standard first- and higher-order HMMs, and other related methods. The performance benefit is attributed to the simultaneous usage of higher-order state-transitions in combination with autoregressive emissions. This benefit could not be reached by using each of these two features independently. We also find that autoregressive higher-order HMMs are better able to identify differentially expressed genes in tumors independent of the underlying gene copy number status in comparison to the majority of related methods. This is further supported by the identification of well-known and of previously unreported hotspots of differential expression in glioblastomas demonstrating the efficacy of autoregressive higher-order HMMs for the analysis of individual tumor expression profiles. Moreover, we reveal interesting novel details of systematic alterations of gene expression levels in known cancer signaling pathways distinguishing oligodendrogliomas, astrocytomas and glioblastomas.

Medical imagery is increasingly evolving towards higher resolution and throughput. The increasing volume of data and the usage of multiple and often novel imaging modalities necessitates the use of mathematical and computational techniques for quicker, more accurate and more robust analysis of medical imagery. The fields of computer vision and machine learning provide a rich set of techniques that are useful in medical image analysis, in tasks ranging from segmentation to classification and population analysis, notably by integrating the qualitative knowledge of experts in anatomy and the pathologies of various disorders and making it applicable to the analysis of medical imagery going forward. The object of the proposed research is exactly to explore various computer vision and machine learning methods with a view to the improved analysis of multiple modalities of brain and cardiac imagery, towards enabling the clinical goals of studying schizophrenia, brain tumors (meningiomas and gliomas in particular) and cardiovascular disorders. In the first project, a framework is proposed for the segmentation of tubular, branched anatomical structures. The framework uses the tubular surface model which yields computational advantages and further incorporates a novel automatic branch detection algorithm. It is successfully applied to the segmentation of neural fiber bundles and blood vessels. In the second project, a novel population analysis framework is built using the shape model proposed as part of the first project. This framework is applied to the analysis of neural fiber bundles towards the detection and understanding of schizophrenia. In the third and final project, the use of mass spectrometry imaging for the analysis of brain tumors is motivated on two fronts, towards the offline classification analysis of the data, as well as the end application of intraoperative detection of tumor boundaries. SVMs are applied for the classification of gliomas into one of four subtypes towards application in building appropriate treatment plans, and multiple statistical measures are studied with a view to feature extraction (or biomarker detection). The problem of intraoperative tumor boundary detection is formulated as a detection of local minima of the spatial map of tumor cell concentration which in turn is modeled as a function of the mass spectra, via regression techniques.

Gliomagenesis is driven by a complex network of genetic alterations and while the glioma genome has been a focus of investigation for many years; critical gaps in our knowledge of this disease remain. The identification of novel molecular biomarkers remains a focus of the greater cancer community as a method to improve the consistency and accuracy of pathological diagnosis. In addition, novel molecular biomarkers are drastically needed for the identification of targets that may ultimately result in novel therapeutics aimed at improving glioma treatment. Through the identification of new biomarkers, laboratories will focus future studies on the molecular mechanisms that underlie glioma development. Here, we report a series of genomic analyses identifying novel molecular biomarkers in multiple histopathological subtypes of glioma and refine the classification of malignant gliomas. We have completed a large scale analysis of the WHO grade II-III astrocytoma exome and report frequent mutations in the chromatin modifier, alpha thalassemia mental retardation x-linked (ATRX), isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2), and mutations in tumor protein 53 (TP53) as the most frequent genetic mutations in low grade astrocytomas. Furthermore, by analyzing the status of recurrently mutated genes in 363 brain tumors, we establish that highly recurrent gene mutational signatures are an effective tool in stratifying homogeneous patient populations into distinct groups with varying outcomes, thereby capable of predicting prognosis. Next, we have established mutations in the promoter of telomerase reverse transcriptase (TERT) as a frequent genetic event in gliomas and in tissues with low rates of self renewal. We identify TERT promoter mutations as the most frequently mutated gene in primary glioblastoma. Additionally, we show that TERT promoter mutations in combination with IDH1 and IDH2 mutations are able to delineate distinct clinical tumor cohorts and are capable of predicting median overall survival more effectively than standard histopathological diagnosis alone. Taken together, these data advance our understanding of the genetic alterations that underlie the transformation of glial cells into neoplasms and we provide novel genetic biomarkers and multi – gene mutational signatures that can be utilized to refine the classification of malignant gliomas and provide opportunity for improved diagnosis.

Dissertation

Hedgehog-signalling in malignant gliomas The Hedgehog signalling pathway is important for the development of the central nervous system. On the other hand, aberrant induction is observed in different tumors. Immunofluorescence and real-time qRT-PCR confirmed that in some gliomas, specifically in Glioblastoma multiforme (GBM), Gli1, a transcription factor activated by signalling, is present. In general, the hedgehog pathway is initiated by binding of extracellular ligands to the transmembrane receptor Patched and leads finally to the activation of the transcription factors Gli1, Gli2, Gli3 and Gli4. Whereas Gli1 acts as an activator, Gli2 appears to be an activator but retains some repressor activities and Gli3 and Gli4 are believed to act only as inhibitors. Therefore, the determination of hedgehog activity at the level of transcription requires additional experiments measuring gene activation. For that reason, cells isolated from 13 tumors of patients with glioblastoma (WHO Grade IV) and cells from two different glioma cell lines were transfected with reporter genes. These reporter genes carried the luciferase gene from Gaussia princeps under the control of two promoters (pT109 and pT81) conjugated to Gli binding sites. The activity of the reporter genes was compared to a control plasmid with mutant Gli-binding sites. In addition reporter gene activity was analysed in the absence and presence of the hedgehog signalling inhibitor cyclopamine and the effect of cyclopamine on cellular metabolism was studied. The analysis revealed that the two cell lines and cells from 6 glioblastomas exhibited enhanced reporter gene activity compared to the activity mutant control. This points towards an enhanced expression of Gli1. In three cultures a repression was detected suggesting that Gli3 may be active in these cells. Four cultures did neither show activation nor repression. This could provide evidence that Gli1 and Gli3 effects cancel each other out or that there is no effect at all. Enhanced luciferase activity in cells from the line T98G and in cells from four primary cultures was not influenced by the hedgehog inhibitor cyclopamine, whereas one cell line significantly responded to its presence with a decreased activity. Interestingly, ATP level was suppressed by cyclopamine in cells from the line T98G and also in cells from one primary culture that responded to the inhibitor. This may point towards an effect of cyclopamine independent of smo. Since cyclopamine is a potential new substance for the treatment of tumors, the observed effect of this inhibitor even in cells without an indication of hedgehog signalling activity should be investigated in further experiments in more detail.
Der Hedgehog (Hh) -Signalweg spielt während der Embryonalentwicklung eine wichtige Rolle, so auch bei der Entstehung des zentralen Nervensystems (Varjosalo & Taipale 2008). Andererseits führt seine unregulierte Aktivität zur Ausbildung verschiedenster Tumore (Bailey et al. 2009; Fiaschi et al. 2009; Shaw et al. 2009; Velcheti & Govindan 2007). Vorausgegangene Studien wiesen durch Immunfluoreszenz und real-time qRT-PCR nach, dass auch in Gliomen, speziell in Glioblastoma multiforme, dem agressivsten Hirntumor des Menschen, Effektoren des Signalweges (Gli1) überexprimiert werden (Wang et al. 2010). Die Aktivierung des Signalweges geschieht über Bindung des Hh-Liganden an den Rezeptor Ptch und endet mit der Aktiverung der Transkriptionsfaktoren der Gli Familie (Kinzler & Vogelstein 1990; Stone et al. 1996). Die aktuell bekannten Vertreter dieser Familie sind der Aktivator der Transkription Gli1, Gli2, der als Aktivator und Repressor agieren kann sowie Gli3 und Gli4, die die Transkription inhibieren (Marine et al. 1997; Ruppert et al. 1988). Ziel dieser Arbeit war es, herauszufinden, inwieweit die Transkriptionsfaktoren der Gli-Familie in Zellen von Glioblastoma multiforme aktiv sind. Dafür wurden Zellen aus Tumormaterial isoliert und daraus Primärkulturen hergestellt. In diese 13 Primärkulturen, wie auch in zwei Gliom-Zelllinien, wurden mittels transienter Transfektion Reporterplasmide eingebracht. Diese enthielten ein Gen der Gaussia-Luciferase, das unter der Kontrolle zweier verschiedener Promotoren (pT109 und pT81) mit Bindungsmotiven für die Transkriptionsfaktoren der Gli-Familie stand. Weiterhin wurde der Einfluss des Inhibitors des Hh-Signalweges Cyclopamin auf die Gli-Aktivität und die Metabolische Aktivität der Zellen untersucht. Die Beobachtungen ergaben, dass die zwei Zelllinien und sechs der primären Kulturen eine erhöhte Luciferaseaktivität und damit gesteigerte Aktivität von Gli1 zeigten. Weiterhin wiesen vier Kulturen eine verminderte Luciferaseaktivität auf. Dies ließ darauf schließen, dass in diesen Zellen Gli3 aktiv war. In den restlichen vier Kulturen zeigte sich keine Veränderung der Luciferaseaktiviät, was für einen Aufhebungseffekt von Gli1 und Gli3 oder gar keinen Effekt spricht. Weiterhin konnte gezeigt werden, dass die Luciferaseaktivität und damit die Aktivität von Gli1 in Zellen der Zelllinie T98G und von vier Primärkulturen nicht durch Cyclopamin beeinflusst wird. Lediglich eine Probe der Primärkulturen reagierte mit einer Abnahme der Luciferaseaktivität. Außerdem konnte Cyclopamin die ATP-Produktion sowohl in Zellen von T98G als auch in Zellen der Zelllinie, deren Gli-Aktivität durch Cyclopamin vermindert wurde, senken. Dies sprach für eine Smo unabhängige Wirkung des Cyclopamins. Da Cyclopamin ein potenzielles Pharmakon für die Antitumortherapie ist, bedarf dieser Umstand näherer Untersuchungen.

碩士
元培醫事科技大學
醫學影像暨放射技術系碩士班
106
Glioma is the most common malignant brain tumor. According to its degree of malignancy, the World Health Organization divided it into four levels, and there are differences in tumor invasion trends between different levels, suggesting different prognosis and treatment options. The histopathology of tumor standard examination generally gave sampling errors. Therefore, magnetic resonance imaging (MRI) has been widely used in brain tumor evaluation in recent years, providing non-invasive and high-resolution brain imaging, assisting clinical identification and classification, and as a therapeutic evaluation and long-term evaluation. The MRI images of patients with gliomas confirmed by pathological section were collected in this retrospective study of Taipei Veterans General Hospital since April 2010 for eight years. These images were obtained using the GE 1.5 T system. Patients were aged 30 to 64 years old and there are 70 cases in total. According to the tumor levels, the patient's apparent diffusion coefficient map (ADC map) and the pre-operative magnetic resonance spectrum (MRS) were combined with gender, age, height, weight, body mass index and body surface area for statistical analysis. Alpha reliability, one way-ANOVA, receiver operating characteristic curve (ROC) and Pearson’s correlation analysis on differential staging showed that the diagnostic benefit of MRS was better than ADC map, and the differential diagnoses were highly or moderately correlated with most of the MRS metabolites and ADC. An ADC map (p < 0.05) with 120% tumor area preoperatively selected was more appropriate determined by multivariate analysis. In addition, the ADC map has excellent tracking benefit in the paired sample t-test. By the way, the ADCs of preoperative/postoperative lesions (p ≦ 0.001, r = 0.23) and preoperative disease/health ratio to postoperative disease/health ratio (p ≦ 0.001, r = 0.45) showed low and medium correlation, respectively. Finally, the ROC test is used to calculate the thresholds and analyze the diagnostic efficacy. It is found that the MRS metabolites ratio are more suitable for disease diagnoses, while the MRS single metabolite concentrations are more suitable for identifying the tumor stage. Overall, MRS has better sensitivity, while ADC has better specificity. These two techniques complement with each other, which can effectively improve the diagnostic value and implement precise treatment goals.

Gliomas are the most common and lethal malignant tumors of central nervous system. In 2016, World Health Organization (WHO) classification included IDH mutations and 1p/19q codeletion as a diagnostic criteria to define gliomas. However new biomarkers of diagnosis, prognosis and response to therapy are needed. In this context, PIK3CA mutations have been described as constitutive mutations seeming to be a good therapeutic target. Our objective was to clarify the clinical importance of PIK3CA mutations according to the 2016 WHO classification, as well as the impact of several biomarkers on diagnosis, prognosis and response to therapy in 437 glioma samples. According to the multivariate analysis performed, gliomas molecular subgroups have higher prognostic value than histological subgroups (P<0.001). PTEN deletions were considered prognostic factors of poor outcomes in astrocytomas IDH wildtype, while in GBM IDH wildtype were associated with better prognosis. On opposite, EGFR amplification and TERT mutations had no impact in the overall survival of patients. We verified that EGFR amplification had a predictive value of response to radiotherapy (P=0.007). PIK3CA mutations were most common in IDH mutant + 1p/19q codeletion (oligodendrogliomas) (10%). H1047R and E542K were the most frequent mutations identified in the remaining gliomas molecular subgroups. Importantly, we found 3 unreported pathogenic variants in exon 20 of PIK3CA (c.3112T>C, c.2988T>C, c.3040C>T) and one polymorphic variant (c.3210A>G). For the first time, it was identified the rs45455192 polymorphism (16% - 24%) in the different gliomas molecular subgroups, although this polymorphism did not showed prognostic value. The recurrences analysis demonstrated that PIK3CA mutations constitute early events maintained during tumor progression. Overall, this study showed molecular classification is a more accurate method to predict clinical outcome and despite PIK3CA mutations being present at low frequency in gliomas, they seem to be important for tumor progression.

Glioma, the tumor of glial cells, is one of the common types of primary central nervous system (CNS) neoplasms. Astrocytoma is the most common of all gliomas and originates from astrocytic glial cells. Astrocytoma tumors belong to two main categories: benign tumors, comprising of grade I Pilocytic astrocytoma and malignant tumors which diffusely infiltrate throughout the brain parenchyma. Diffusely infiltrating astrocytomas are graded into diffuse astrocytoma (DA; grade II), anaplastic astrocytoma (AA; grade III) and glioblastoma (GBM; grade IV) in the order of increasing malignancy. Patients with grade II astrocytoma have a median survival time of 6 to 8 years after surgical intervention. While the more aggressive grade III (AA) and grade IV (GBM) are together called malignant astrocytomas, the treatment protocols and length of survival are distinctly different between these grades. The median survival time for grade III patients is 2 to 3 years whereas patients with grade IV have a median survival of 12-15 months. GBMs have been further divided into primary GBM and secondary GBM on the basis of clinical and histopathological criteria. Primary GBM presents in an acute de novo manner with no evidence of an antecedent lower grade tumor and it accounts for >90% of all GBMs. In contrast, secondary GBM results from the progressive malignant transformation of a grade II or grade III astrocytoma. The current WHO grading system of astrocytomas is based on the histopathological characteristics of the underlying tumor tissue. Diagnoses by pathologists are dependent on specific histologic features: increased mitosis, nuclear atypia, microvascular proliferation and/or necrosis, which associate with biologically aggressive behaviour (WHO 2007). Though grading based on histology is largely reproducible and well accepted, subjectivity involved and substantial disagreement between pathologists has remained a major concern. Because of inherent sampling problems (mainly due to tumor location in the brain) and inadequate sample size available for histological evaluation, there exists a very high possibility of error in grading. Recent studies have attempted to characterize the molecular basis for the histological and prognostic differences between grade III and grade IV astrocytoma. While reports have shown the grade specific profile of gene expression, there is no molecular signature that can accurately classify grade III and grade IV astrocytoma samples. In the current work, we have identified molecular signatures for the accurate classification of grade III and grade IV astrocytoma patients by using transcriptome and miRNome data. The receptor tyrosine kinase pathway is known to be overexpressed in 88% of glioblastoma patients. The expression and activation of the receptors is reported to be deregulated by events like amplification and activating mutations. The aberrant expression of RTKs could also be due to the deregulation of miRNAs, which, in the untransformed astrocytes regulate and fine-tune the levels of the RTKs. In the current study, we have identified that tumor suppressor miRNA miR-219-5p regulates RTK pathway by targeting EGFR and PDGFRα. Part I. Transcriptome approach: Identification of a 16-gene signature for classification of malignant astrocytomas In order to obtain a more robust molecular classifier to accurately classify grade III and grade IV astrocytoma samples, we used transcriptome data from microarray study previously performed in our laboratory. The differential regulation of 175 genes identified from microarray was validated in a cohort of grade III and grade IV patients by real-time qRT-PCR. In order to identify the classification signature that can classify grade III and grade IV astrocytoma samples, we used the expression data of 175 genes for performing Prediction Analysis of Microarrays (PAM) in the training set of grade III and grade IV astrocytoma samples. PAM analysis identified the most discriminatory 16-gene expression signature for the classification of grade III and grade IV astrocytoma. The Principal Component Analysis (PCA) of 16-genes astrocytoma patient samples revealed that the expression of 16-genes could classify grade III and grade IV astrocytoma samples into two separate clusters. In the training set, the 16-gene signature was able to classify grade III and grade IV patients with an accuracy rate of 87.9% as tested by additional analysis of Cross-Validated probability by PAM. The 16-gene signature obtained in the training set was validated in the test set with diagnostic accuracy of 89%. We further validated the 16-gene signature in three independent cohorts of patient samples from publicly available databases: GSE1993, GSE4422 and TCGA datasets and the classification signature got validated with accuracy rates of 88%, 92% and 99% respectively. To address the discordance in grading between 16-gene signature and histopathology, we looked at the clinical features (age and survival) and molecular markers (CDKN2A loss, EGFR amplification and p53 mutation) that differ substantially between grade III and grade IV in discordant grade III and grade IV samples. The grading done by 16-gene signature correlated with known clinical and molecular markers that distinguish grade III and grade IV proving the utility of the 16-gene signature in the molecular classification of grade III and grade IV. In order to identify the pathways that 16 genes of the classification signature could regulate, we performed protein-protein interaction network and subsequently pathway analysis. The pathways with highest significance were ECM (extracellular matrix) and focal adhesion pathways, which are known to be involved in the epithelial to mesenchymal transition (EMT), correlating well with the aggressive infiltration of grade IV tumors. In addition to accurately classifying the grade III and grade IV samples, the 16-gene signature also demonstrated that genes involved in epithelial-mesenchymal transition play key role in distinguishing grade III and grade IV astrocytoma samples. Part II. miRNome approach microRNAs (miRNAs) have emerged as one of the important regulators of the interaction network that controls various cellular processes. miRNAs are short non-coding RNAs (mature RNA being 21-22nt long) that regulate the target mRNA by binding mostly in the 3’ UTR bringing about either translational repression or degradation of the target. miRNAs are shown to play key roles in cell survival, proliferation, apoptosis, migration, invasion and various other characteristic features that get altered in human cancers. miRNAs are characterized to have oncogenic or tumor suppressor role and the aberrant expression of miRNAs is reported in multiple human cancer types. Part A. Genome-wide expression profiling identifies deregulated miRNAs in malignant astrocytoma With an aim to identify the role of miRNAs in the development of in malignant astrocytoma, we performed a large-scale, genome-wide microRNA (miRNA) (n=756) expression profiling of 26 grade IV astrocytoma, 13 grade III astrocytoma and 7 normal brain samples. Using Significance Analysis of Microarrays (SAM), we identified several differentially regulated miRNAs between control normal brain and malignant astrocytoma, grade III and grade IV astrocytoma, grade III astrocytoma and grade IV secondary GBM, progressive pathway and de novo pathway of GBM development and also between primary and secondary GBM. Importantly, we identified a most discriminatory 23-miRNA expression signature, by using PAM, which precisely distinguished grade III from grade IV astrocytoma samples with an accuracy of 90%. We re-evaluated the grading of discordant samples by histopathology and identified that one of the discordant grade III samples had areas of necrosis and it was reclassified as grade IV GBM. Similarly, out of two discordant grade IV samples, one sample had oligo component and it was reclassified as grade III mixed oligoastrocytoma. Thus, after the revised grading, the prediction accuracy increased from 90% to 95%. The differential expression pattern of nine miRNAs was further validated by real-time RT-PCR in an independent set of malignant astrocytomas (n=72) and normal samples (n=7). Inhibition of two glioblastoma-upregulatedmiRNAs (miR-21 and miR-23a) and exogenous overexpression of two glioblastoma-downregulatedmiRNAs (miR-218 and miR-219-5p) resulted in reduced soft agar colony formation but showed varying effects on cell proliferation and chemosensitivity. Thus, we have identified the grade specific expression of miRNAs in malignant astrocytoma and identified a miRNA expression signature to classify grade III astrocytoma from grade IV glioblastoma. In addition, we have demonstrated the functional relevance of miRNA modulation and thus showed the miRNA involvement and their importance in astrocytoma development. Part B. miR-219-5p inhibits the receptor tyrosine kinase pathway by targeting mitogenic receptor kinases in glioblastoma The receptor tyrosine kinase (RTK) pathway, being one of the important growth promoting pathways, is known to be deregulated in 88% of the patients with glioblastoma. In order to understand the role of miRNAs in regulating the RTK pathway, we undertook a screening procedure to identify the potential miRNAs that could target different members of the RTK pathway. From the screening study involving bioinformatical prediction of miRNAs and subsequent experimental validation by modulation of miRNA levels in glioma cell lines, we identified miR-219-5p as a candidate miRNA. The overexpression of miR-219-5p reduced the protein levels of both EGFR and PDGFRα. We confirmed the binding of miR-219-5p to the 3’ UTRs by using reporter plasmids. We also confirmed the specificity of miR-219-5p binding sites in the 3’ UTR of EGFR by site directed mutagenesis of binding sites which abrogated the miRNA-UTR interaction. The expression of miR-219-5p was significantly downregulated in grade III as well as in grade IV astrocytoma samples in the miRNA microarray experiment and we further validated the downregulation in an independent cohort of grade III and grade IV astrocytoma patients by real-time qRT-PCR. The ectopic overexpression of miR-219-5p in glioma cell lines inhibited cell proliferation, colony formation, anchorage independent growth and the migration of glioma cells. In addition, overexpression of miR-219-5p decreased MAPK and PI3K pathways, in concordance with its ability to target EGFR and PDGFRα. Additionally, for the further characterization of miR-219-5p – EGFR interaction and its effect on MAPK and PI3K pathways, we used U87 glioma cells that stably overexpress wild-type EGFR and constitutively active ΔEGFR (both lacking 3’-UTR and thus being insensitive to miR-219-5p overexpression) along with U87 parental cells. In these cell lines with the overexpression of EGFR lacking 3’-UTR, miR-219-5p was unable to inhibit - MAPK and PI3K pathways and also glioma cell migration suggesting that these effects were indeed because of its ability to target EGFR. Further, in the glioblastoma patient cohort (TCGA dataset), we found significant negative correlation between EGFR protein levels, both total EGFR and phospho EGFR and miR-219-5p levels in the glioblastoma tissue samples suggesting a role of miR-219-5p in increasing the protein levels of EGFR in glioblastoma. In summary, we have identified and characterized miR-219-5p as the RTK regulating tumor suppressor miRNA in glioblastoma.

Glioma, the tumor of glial cells, is one of the common types of primary central nervous system (CNS) neoplasms. Astrocytoma is the most common of all gliomas and originates from astrocytic glial cells. Astrocytoma tumors belong to two main categories: benign tumors, comprising of grade I Pilocytic astrocytoma and malignant tumors which diffusely infiltrate throughout the brain parenchyma. Diffusely infiltrating astrocytomas are graded into diffuse astrocytoma (DA; grade II), anaplastic astrocytoma (AA; grade III) and glioblastoma (GBM; grade IV) in the order of increasing malignancy. Patients with grade II astrocytoma have a median survival time of 6 to 8 years after surgical intervention. While the more aggressive grade III (AA) and grade IV (GBM) are together called malignant astrocytomas, the treatment protocols and length of survival are distinctly different between these grades. The median survival time for grade III patients is 2 to 3 years whereas patients with grade IV have a median survival of 12-15 months. GBMs have been further divided into primary GBM and secondary GBM on the basis of clinical and histopathological criteria. Primary GBM presents in an acute de novo manner with no evidence of an antecedent lower grade tumor and it accounts for >90% of all GBMs. In contrast, secondary GBM results from the progressive malignant transformation of a grade II or grade III astrocytoma. The current WHO grading system of astrocytomas is based on the histopathological characteristics of the underlying tumor tissue. Diagnoses by pathologists are dependent on specific histologic features: increased mitosis, nuclear atypia, microvascular proliferation and/or necrosis, which associate with biologically aggressive behaviour (WHO 2007). Though grading based on histology is largely reproducible and well accepted, subjectivity involved and substantial disagreement between pathologists has remained a major concern. Because of inherent sampling problems (mainly due to tumor location in the brain) and inadequate sample size available for histological evaluation, there exists a very high possibility of error in grading. Recent studies have attempted to characterize the molecular basis for the histological and prognostic differences between grade III and grade IV astrocytoma. While reports have shown the grade specific profile of gene expression, there is no molecular signature that can accurately classify grade III and grade IV astrocytoma samples. In the current work, we have identified molecular signatures for the accurate classification of grade III and grade IV astrocytoma patients by using transcriptome and miRNome data. The receptor tyrosine kinase pathway is known to be overexpressed in 88% of glioblastoma patients. The expression and activation of the receptors is reported to be deregulated by events like amplification and activating mutations. The aberrant expression of RTKs could also be due to the deregulation of miRNAs, which, in the untransformed astrocytes regulate and fine-tune the levels of the RTKs. In the current study, we have identified that tumor suppressor miRNA miR-219-5p regulates RTK pathway by targeting EGFR and PDGFRα. Part I. Transcriptome approach: Identification of a 16-gene signature for classification of malignant astrocytomas In order to obtain a more robust molecular classifier to accurately classify grade III and grade IV astrocytoma samples, we used transcriptome data from microarray study previously performed in our laboratory. The differential regulation of 175 genes identified from microarray was validated in a cohort of grade III and grade IV patients by real-time qRT-PCR. In order to identify the classification signature that can classify grade III and grade IV astrocytoma samples, we used the expression data of 175 genes for performing Prediction Analysis of Microarrays (PAM) in the training set of grade III and grade IV astrocytoma samples. PAM analysis identified the most discriminatory 16-gene expression signature for the classification of grade III and grade IV astrocytoma. The Principal Component Analysis (PCA) of 16-genes astrocytoma patient samples revealed that the expression of 16-genes could classify grade III and grade IV astrocytoma samples into two separate clusters. In the training set, the 16-gene signature was able to classify grade III and grade IV patients with an accuracy rate of 87.9% as tested by additional analysis of Cross-Validated probability by PAM. The 16-gene signature obtained in the training set was validated in the test set with diagnostic accuracy of 89%. We further validated the 16-gene signature in three independent cohorts of patient samples from publicly available databases: GSE1993, GSE4422 and TCGA datasets and the classification signature got validated with accuracy rates of 88%, 92% and 99% respectively. To address the discordance in grading between 16-gene signature and histopathology, we looked at the clinical features (age and survival) and molecular markers (CDKN2A loss, EGFR amplification and p53 mutation) that differ substantially between grade III and grade IV in discordant grade III and grade IV samples. The grading done by 16-gene signature correlated with known clinical and molecular markers that distinguish grade III and grade IV proving the utility of the 16-gene signature in the molecular classification of grade III and grade IV. In order to identify the pathways that 16 genes of the classification signature could regulate, we performed protein-protein interaction network and subsequently pathway analysis. The pathways with highest significance were ECM (extracellular matrix) and focal adhesion pathways, which are known to be involved in the epithelial to mesenchymal transition (EMT), correlating well with the aggressive infiltration of grade IV tumors. In addition to accurately classifying the grade III and grade IV samples, the 16-gene signature also demonstrated that genes involved in epithelial-mesenchymal transition play key role in distinguishing grade III and grade IV astrocytoma samples. Part II. miRNome approach microRNAs (miRNAs) have emerged as one of the important regulators of the interaction network that controls various cellular processes. miRNAs are short non-coding RNAs (mature RNA being 21-22nt long) that regulate the target mRNA by binding mostly in the 3’ UTR bringing about either translational repression or degradation of the target. miRNAs are shown to play key roles in cell survival, proliferation, apoptosis, migration, invasion and various other characteristic features that get altered in human cancers. miRNAs are characterized to have oncogenic or tumor suppressor role and the aberrant expression of miRNAs is reported in multiple human cancer types. Part A. Genome-wide expression profiling identifies deregulated miRNAs in malignant astrocytoma With an aim to identify the role of miRNAs in the development of in malignant astrocytoma, we performed a large-scale, genome-wide microRNA (miRNA) (n=756) expression profiling of 26 grade IV astrocytoma, 13 grade III astrocytoma and 7 normal brain samples. Using Significance Analysis of Microarrays (SAM), we identified several differentially regulated miRNAs between control normal brain and malignant astrocytoma, grade III and grade IV astrocytoma, grade III astrocytoma and grade IV secondary GBM, progressive pathway and de novo pathway of GBM development and also between primary and secondary GBM. Importantly, we identified a most discriminatory 23-miRNA expression signature, by using PAM, which precisely distinguished grade III from grade IV astrocytoma samples with an accuracy of 90%. We re-evaluated the grading of discordant samples by histopathology and identified that one of the discordant grade III samples had areas of necrosis and it was reclassified as grade IV GBM. Similarly, out of two discordant grade IV samples, one sample had oligo component and it was reclassified as grade III mixed oligoastrocytoma. Thus, after the revised grading, the prediction accuracy increased from 90% to 95%. The differential expression pattern of nine miRNAs was further validated by real-time RT-PCR in an independent set of malignant astrocytomas (n=72) and normal samples (n=7). Inhibition of two glioblastoma-upregulatedmiRNAs (miR-21 and miR-23a) and exogenous overexpression of two glioblastoma-downregulatedmiRNAs (miR-218 and miR-219-5p) resulted in reduced soft agar colony formation but showed varying effects on cell proliferation and chemosensitivity. Thus, we have identified the grade specific expression of miRNAs in malignant astrocytoma and identified a miRNA expression signature to classify grade III astrocytoma from grade IV glioblastoma. In addition, we have demonstrated the functional relevance of miRNA modulation and thus showed the miRNA involvement and their importance in astrocytoma development. Part B. miR-219-5p inhibits the receptor tyrosine kinase pathway by targeting mitogenic receptor kinases in glioblastoma The receptor tyrosine kinase (RTK) pathway, being one of the important growth promoting pathways, is known to be deregulated in 88% of the patients with glioblastoma. In order to understand the role of miRNAs in regulating the RTK pathway, we undertook a screening procedure to identify the potential miRNAs that could target different members of the RTK pathway. From the screening study involving bioinformatical prediction of miRNAs and subsequent experimental validation by modulation of miRNA levels in glioma cell lines, we identified miR-219-5p as a candidate miRNA. The overexpression of miR-219-5p reduced the protein levels of both EGFR and PDGFRα. We confirmed the binding of miR-219-5p to the 3’ UTRs by using reporter plasmids. We also confirmed the specificity of miR-219-5p binding sites in the 3’ UTR of EGFR by site directed mutagenesis of binding sites which abrogated the miRNA-UTR interaction. The expression of miR-219-5p was significantly downregulated in grade III as well as in grade IV astrocytoma samples in the miRNA microarray experiment and we further validated the downregulation in an independent cohort of grade III and grade IV astrocytoma patients by real-time qRT-PCR. The ectopic overexpression of miR-219-5p in glioma cell lines inhibited cell proliferation, colony formation, anchorage independent growth and the migration of glioma cells. In addition, overexpression of miR-219-5p decreased MAPK and PI3K pathways, in concordance with its ability to target EGFR and PDGFRα. Additionally, for the further characterization of miR-219-5p – EGFR interaction and its effect on MAPK and PI3K pathways, we used U87 glioma cells that stably overexpress wild-type EGFR and constitutively active ΔEGFR (both lacking 3’-UTR and thus being insensitive to miR-219-5p overexpression) along with U87 parental cells. In these cell lines with the overexpression of EGFR lacking 3’-UTR, miR-219-5p was unable to inhibit - MAPK and PI3K pathways and also glioma cell migration suggesting that these effects were indeed because of its ability to target EGFR. Further, in the glioblastoma patient cohort (TCGA dataset), we found significant negative correlation between EGFR protein levels, both total EGFR and phospho EGFR and miR-219-5p levels in the glioblastoma tissue samples suggesting a role of miR-219-5p in increasing the protein levels of EGFR in glioblastoma. In summary, we have identified and characterized miR-219-5p as the RTK regulating tumor suppressor miRNA in glioblastoma.

Da hochgradige Gliome nur eine geringe Tendenz zur Metastasierung aufweisen, beschränkte sich das klinische Wissen über diesen seltenen Krankheitsverlauf bisher im Wesentlichen auf die Erkenntnisse aus Einzelfallberichten und kleineren Fallserien. Eine detaillierte Analyse der beschriebenen Fälle war bisher nicht verfügbar. Die vorliegende Arbeit stellt eine systematische Auswertung der wissenschaftlichen Literatur über Patienten mit metastasierten Glioblastomen oder Gliosarkomen dar. Unser Ziel war es, sämtliche Publikationen zu berücksichtigen, welche bis April 2013 veröffentlicht worden sind. Mit Hilfe einer systematischen Literaturrecherche in den beiden Datenbanken PubMed und Web of Science konnten 215 Arbeiten identifiziert werden, welche insgesamt 357 Fallberichte enthielten. Die Prognose nach Diagnose einer Metastasierung ist infaust. In der untersuchten Patientenkohorte betrug die mediane Überlebenszeit lediglich 3.0 ± 0.4 Monate. Eine univariate Datenanalyse ergab, dass Geschlecht, Alter, der histologische Subtyp und das Zeitintervall zwischen der Diagnose des Primärtumors und der Metastasen die Überlebenszeit nicht beeinflussten. Im Gegensatz dazu war eine Metastasierung, die ausschließlich außerhalb des zentralen Nervensystems (ZNS) auftrat, mit längeren Überlebenszeiten verbunden. In den letzten Jahrzehnten wurden offenbar keine entscheidenden therapeutischen Fortschritte erzielt. Fälle, die in Publikationen bis zum Jahr 2000 Erwähnung fanden, wiesen keine schlechteren Überlebenszeiten auf als die nach der Jahrtausendwende publizierten Fälle. Aktuell gibt es keinen Datensatz, der geeignet wäre, die vielfältigen Therapieansätze systematisch auf ihre Wirksamkeit hin zu überprüfen. Wir sehen hier die Notwendigkeit, ein zentrales Register zu etablieren.:1. Bibliographische Beschreibung 2 2. Abkürzungsverzeichnis 3 3. Tabellenverzeichnis 4 4. Abbildungsverzeichnis 4 5. Einführung 5 5.1.1. Klassifikation und Epidemiologie 5 5.1.2. Ätiologie 5 5.1.3. Diagnose 5 5.1.4. Molekularpathologie 7 5.1.5. Therapie 7 5.2. Metastasierung 9 5.2.1. Wege der Metastasierung eines Glioblastoms 9 5.2.2. Therapie im Fall einer Metastasierung 12 5.3. Zielsetzung 13 6. Publikationen in Originalsprache 15 6.1 An individual patient data meta-analysis on characteristics, treatments and outcomes of the glioblastoma/ gliosarcoma patients with central nervous system metastases reported in literature until 2013 15 6.2 An individual patient data meta-analysis on characteristics, treatments and outcomes of glioblastoma/ gliosarcoma patients with metastases outside of the central nervous system 23 7. Zusammenfassung der Arbeit 38 8. Anhang I 8.1. Übersicht über klinische Charakteristika I 8.2. Übersicht über die Prozedur der Literaturrecherche V 8.3. Literaturverzeichnis der Publikationspromotion VI 8.4. Verzeichnis der Patientenkohorte XI 8.5. Literaturverzeichnis der individuellen Patientendaten-Metaanalyse XXIII 8.6. Danksagung XXXIII 8.7. Lebenslauf XXXIV 8.8. Publikationen XXXVI 8.8.1 Erstautorenschaften XXXVI 8.8.2 Coautorenschaften XXXVI 8.8.3 Kongressbeiträge XXXVI 8.9. Erklärung über die eigenständige Abfassung der Arbeit XXXVII

Das Glioblastom ist der häufigste hirneigene Tumor des Erwachsenen und mit einer 5-Jahres-Überlebensrate von weniger als 5 % eine der aggressivsten Hirntumorerkrankungen (Batash et al., 2017). Verbunden mit einer schlechten Prognose und geringen Remissionsraten ergibt sich die Notwendigkeit, bestehende Therapieoptionen zu optimieren und zu erweitern. Im Rahmen dieser Arbeit wurde das vor einigen Jahren entwickelte und aktuell in klinischen Studien angewandte Konzept der Therapie von Malignomen mit elektrischen Wechselfeldern, den sog. Tumor Treating Fields (TTFields), aufgegriffen. Basis der anti-tumoralen Wirkung der im Rahmen von Glioblastom-Studien applizierten TTFields bildet eine Tumor-spezifische Frequenz von 200 kHz sowie geringe Intensitäten, die einen nebenwirkungsarmen anti-mitotischen Effekt erzielen (Kirson et al., 2004; Kirson et al., 2007; Clark et al., 2017; Porat et al., 2017). Dieser resultiert sowohl aus alternierenden elektrischen Feldern, die während der Metaphase über eine Irritation des Dipolmoments von Tubulin-Untereinheiten die Assemblierung des Spindelapparates inhibieren, als auch aus inhomogenen elektrischen Feldern, die während der Telophase die Trennung der Tochterzellen behindern. Mit dieser Behandlungsoption konnten schon einige gute Ergebnisse für die Behandlung von Glioblastomen in klinischen Studien erreicht werden (Stupp et al., 2017). Eine weitere anti-mitotische Therapieoption stellt die Inhibierung der Aurora B Kinase mittels AZD1152 dar. Die Aurora B Kinase ist Teil des Chromosomal Passenger Complex (CPC), der bei Inhibierung der Kinase seine Kontrollfunktionen während der Mitose und Zytokinese nicht wahrnehmen kann. Diese fehlende Kontrolle führt zu Polyploidie, die einen Zelltod verursachen kann (Wiedemuth et al., 2016). Aufgrund dieses ähnlichen biologischen Hintergrundes wurde zu Beginn dieser Arbeit die Hypothese aufgestellt, dass eine kombinierte Therapie mittels TTFields und AZD1152 einen additiven zytotoxischen Effekt im Vergleich zur Monotherapie mit TTFields erzielen kann. Es konnte zunächst für die etablierte Zelllinie U87-MG ein signifikanter additiver Effekt in der Kombinationstherapie der TTFields mit AZD1152 im Vergleich zur alleinigen Therapie mittels TTFields nachgewiesen werden. Die mediane Tumorzellzahl konnte hierbei in der Kombinationstherapie um 60 % reduziert werden. Dieser additive Effekt konnte ebenfalls an zwei Primärkulturen reproduziert werden. Hierbei konnte die relative mediane Tumorzellzahl der Primärkultur HT18584 ebenfalls um 60 % in der Kombinationstherapie gesenkt werden. Diese tetraploide Zellreihe zeigte außerdem einen außergewöhnlich großen zytotoxischen Effekt bei der Behandlung mit AZD1152. Signifikant zeigte ebenso die Primärkultur HT12347 einen medianen Verlust von 56 % der Tumorzellen nach einer kombinierten Behandlung. Qualitativ und zellmorphologisch konnte mittels konfokaler Laser-Scanning- sowie Lichtmikroskopie die Akkumulation von mitotischen Defekten detektiert werden, die auch in den Monotherapien aber vor allem in der Kombinationstherapie zu finden waren. Die in der quantitativen Analyse gezeigte additive Zytotoxizität der Kombinationstherapie konnte hier nochmals visualisiert und bestätigt werden. Für eine klinische Phase I-Studie zur Überprüfung der Effektivität sollten zunächst weitere zellkulturtechnische Daten erfasst werden, um die Universalität der kombinierten Behandlung zu überprüfen. Weiterhin wäre die Entwicklung einer selektiven/lokalen Therapie mittels AZD1152 wünschenswert, um die Nebenwirkungen des Medikamentes abzumildern. Es sollte außerdem das im Rahmen dieser Arbeit detektierte sensitivere Ansprechen der tetraploiden Zelllinie HT18584 genauer untersucht werden, um eine potentiell prognostisch günstige Verbindung zwischen der Behandlung mit AZD1152 und tetraploiden Zellen herstellen zu können.:1 EINLEITUNG 1 1.1 Glioblastoma multiforme – Definition, Inzidenz und Ätiologie 1 1.1.1 Symptomatik und Diagnostik des Glioblastoms 2 1.2 Molekulare Klassifizierung 3 1.2.1 Primäre und sekundäre Glioblastome und einige allgemeine Marker 3 1.2.2 Der MGMT-Status 5 1.3 Der eukaryotische Zellzyklus und sequentielle Kontrollpunkte 6 1.3.1 Der Chromosomal Passenger Complex (CPC) 8 1.3.2 Die Familie der Aurorakinasen 9 1.4 Therapie maligner Gliome 10 1.4.1 Standardtherapie eines Glioblastoms 10 1.4.2 Tumor Treating Fields (TTFields) – Biologischer Effekt und Studienlage 11 1.4.3 Aurora Kinase-Inhibitoren 14 1.5 Zielstellung der Arbeit 15 2 METHODEN UND MATERIALIEN 17 2.1 Methoden 17 2.1.1 Zellkultivierung allgemein 17 2.1.2 Passagieren adhärenter Zellen 17 2.1.3 Kultivierung von primärem Patientenmaterial 18 2.1.4 Kryokonservierung und Rekultivierung eukaryotischer Zelllinien 18 2.1.5 Bestimmung der Lebendzellzahl mittels Neubauer-Zählkammer 19 2.1.6 Durchflusszytometrische Analyse 19 2.1.7 Bestimmung der Lebendzellzahl mittels Propidiumiodid (PI) 20 2.1.8 Durchflusszytometrische Immunphänotypisierung von Glioblastomzellen 20 2.1.9 In vitro-Applikation der Tumor Treating Fields (TTFields) 21 2.1.10 Titration der effektiven Aurora B Kinase-Inhibitorkonzentrationen mittels PI 22 2.1.11 Titration inhibitorischer Temozolomidkonzen-trationen mittels AlamarBlue-Assay 23 2.1.12 Konfokale Laser-Scanning-Mikroskopie 23 2.2. Materialien 25 2.2.1 Geräte 25 2.2.2 Chemikalien und Reagenzien 25 2.2.3 Lösungen 26 2.2.4 Medien 27 2.2.5 Kommerzielle Kits 28 2.2.6 Antikörper 28 2.2.7 Software 28 2.2.8 Statistik 29 2.2.9 Zelllinien 29 3 ERGEBNISSE 30 3.1 Wahl des Designs der Kontrollgruppen 30 3.2 Typisierung der verwendeten Primärkulturen 32 3.2.1 Befunde der Pathologie des Universitätsklinikums Dresden 33 3.2.2 Immunphänotypisierung der Primärkultur HT18584 34 3.2.3 Immunphänotypisierung der Primärkultur HT12347 35 3.3 Titrationen mit AZD1152 36 3.3.1 Titration mit AZD1152 für die Primärkultur HT18584 36 3.3.2 Titration mit AZD1152 für die Primärkultur HT12347 37 3.4 Kombinationstherapie mittels AZD1152 und TTFields 38 3.4.1 Quantitativer Effekt der Kombinationstherapie an U87-MG 39 3.4.2 Quantitativer Effekt der Kombinationstherapie an HT18584 40 3.4.3 Quantitativer Effekt der Kombinationstherapie an HT12347 41 3.4.4 Qualitativer Effekt der Kombinationstherapien 42 3.4.4.1 Die Kombinationstherapie mit U87-MG 43 3.4.4.2 Die Kombinationstherapie mit HT18584 44 3.4.5 Zytotoxischer Effekt der Kombinationstherapie an HT12347 45 3.5 Titrationen mit Temozolomid 47 3.5.1 Therapie mit Temozolomid an U87-MG 48 3.5.2 Therapie mit Temozolomid an Primärkulturen 48 4 DISKUSSION 52 4.1 Vorversuche 52 4.1.1 Wachstumsanalyse der Kontrollgruppen 52 4.1.2 Charakterisierung der Primärkulturen 53 4.2 Die neuen Behandlungsoptionen 54 4.2.1 Applikation der TTFields 54 4.2.2 Die Behandlung mit AZD1152 55 4.2.3 Die Kombinationstherapie 57 4.3. Die Behandlung mit Temozolomid (TMZ) 59 5 ZUSAMMENFASSUNG 62 LITERATURVERZEICHNIS 64 TABELLENVERZEICHNIS 73 ABBILDUNGSVERZEICHNIS 74 ABKÜRZUNGSVERZEICHNIS 75 ANHANG 77 Anhang 1: Einverständniserklärung der Patienten 77 Anhang 2: Erlaubnis zur Nutzung der Patientendaten der Pathologie 78 Anhang 3: Erklärungen zur Eröffnung des Promotionsverfahrens 79 Anhang 4: Erklärung über die Einhaltung gesetzlicher Vorgaben 81