L’autophagie est un processus catabolique par lequel certaines protéines cytosoliquessont dirigées vers le compartiment lysosomial, afin d’y être dégradées. Ce processus débutepar la séquestration de constituants cytoplasmiques par une structure multimembranaireappelée phagophore. La fermeture du phagophore donne naissance à une vésicule à doublemembrane nommée autophagosome, qui fusionne avec les lysosomes, ce qui conduit à ladégradation du contenu de sa lumière. Ainsi, la modulation de l’autophagie permet unremodelage dynamique du protéome cellulaire. Bien que des données récentes ont permis dedémontrer la dégradation autophagique de protéines impliquées dans la migration cellulaire,telles que des intégrines, ou encore les protéines RhoA et Src, l'impact fonctionnel del'autophagie sur la migration cellulaire demeure sujet à controverse. Alors que l'autophagie estdécrite comme un processus pro-migratoire et pro-invasif dans certaines études, d'autrestravaux indiquent que l'inactivation des protéines pro-autophagiques stimule l'invasion descellules cancéreuses. De plus, l'effet fonctionnel des RCPG chimiotactiques sur l’activitéautophagique reste totalement inexploré. Sur la base de ces données, les objectifs de mon travail de thèse ont été i) d’évaluer les effets des RCPG chimiotactiques, le CXCR4 et l’UT,sur le processus autophagique et ii) d’étudier l’impact de cette modulation sur la migrationcellulaire. Pour ce faire, nous avons utilisé des cellules HEK-293, transfectées à l’aide deconstruits permettant l’expression des RCPG CXCR4 et UT, ainsi que la lignée deglioblastome humain U87, exprimant ces deux récepteurs de manière endogène.Nous avons dans un premier temps évalué l’activité autophagique à l’aide de laprotéine de fusion EGFP-LC3, marqueur des autophagosomes. Nous avons ainsi démontréque l’activation du CXCR4 et de l’UT provoque une diminution significative de la biogénèsedes autophagosomes. Une étape essentielle de cette biogenèse est le recrutement des protéinesAtg16L1 et Atg5 à la membrane plasmique, conduisant à la formation d'endosomes Atg16L1-Atg5-positifs, appelés « endosomes pré-autophagiques ». Cette population d’endosomesconstitue une source importante de phospholipides nécessaire à l’expansion du phagophore etla formation d’un autophagosome mature. Afin d’évaluer l’impact des RCPG chimiotactiquessur le recrutement de la protéine Atg16L1 à la membrane plasmique, nous avons bloqué leprocessus d’endocytose par l’utilisation d’un inhibiteur de la dynamine, le Dynasore. Cettemolécule provoque une accumulation marquée de la protéine Atg16L1 dans les endosomespré-autophagiques en formation, retenus à la membrane plasmique. / Autophagy is a catabolic process by which certain cytosolic proteins are directed to thelysosomal compartment to be degraded. This process begins with the sequestration ofcytoplasmic components, by a multimembrane structure called the phagophore. The closure ofthe phagophore gives rise to a double membrane vesicle called autophagosome, which thenmerges with lysosomes in order to degrade its luminal content. Autophagy modulation allowsa dynamic remodeling of the cellular proteome. Although recent evidence has demonstratedautophagic degradation of key proteins involved in cell migration, such as integrins, RhoAand the Src kinase, the functional impact of autophagy on cell migration remainscontroversial. While autophagy is described as a pro-migratory and pro-invasive process insome studies, others indicate that the inactivation of pro-autophagic proteins stimulates thecancer cell invasion. In addition, the functional effect of chemotactic GPCR on autophagicactivity remains unexplored. On the basis of these data, the objectives of my thesis were i) toevaluate the effects of the chemotactic GPCRs for SDF-1 (CXCR4) and for the vasoactivepeptide urotensin II (UT), on the autophagic process and ii) to study the impact of thismodulation on cell migration. In order to do this, we used HEK-293 cells, transfected with constructs allowing the expression of CXCR4 and UT, as well as the human glioblastomaline, U87, which endogenously expresses these two receptors. Previous studies have demonstrated a direct interaction of Atg5 with membranes,suggesting that recruitment of Atg16L1 to the plasma membrane may depend on Atg5. This prompted us to evaluate the formation of Atg16L1-positive pre-autophagic endosomes,following depletion of Atg5 levels. Several interfering RNAs, targeting the transcriptencoding Atg5, have been tested and, as expected, these interfering RNAs completely blockedthe recruitment of Atg16L1 to forming pre-autophagic endosomes. We then tested the effectsof chemotactic GPCRs on the subcellular localization of the Atg5 protein. By confocalmicroscopy, we found that a significant fraction of Atg5 localized to the plasma membraneunder basal conditions. The activation of CXCR4 or UT is accompanied by a marked decreaseof the Atg5 pool localized at the plasma membrane. Furthermore, we have demonstrated thatthe anti-autophagic effects of chemotactic GPCRs are completely abrogated byoverexpression of a recombinant Atg5 protein, suggesting that chemotactic GPCRs exert theiranti-autophagic effects by reducing the membrane pool of Atg5, necessary for the productionof pre-autophagic endosomes, and the expansion of the phagophore.

To prevent further brain tumour growth, malignant tissue should be removed as completely as possible in neurosurgical operations. Therefore, differentiation between tumour and brain tissue as well as detecting functional areas is very important. Hyperspectral imaging (HSI) can be used to get spatial information about brain tissue types and characteristics in a quasi-continuous reflection spectrum. In this paper, workflow and some aspects of an adapted hardware system for intraoperative hyperspectral data acquisition in neurosurgery are discussed. By comparing an intraoperative with a laboratory setup, the influences of the surgical microscope are made visible through the differences in illumination and a pixel- and wavelength-specific signal-to-noise ratio (SNR) calculation. Due to the significant differences in shape and wavelength-dependent intensity of light sources, it can be shown which kind of illumination is most suitable for the setups. Spectra between 550 and 1,000 nm are characterized of at least 40 dB SNR in laboratory and 25 dB in intraoperative setup in an area of the image relevant for evaluation. A first validation of the intraoperative hyperspectral imaging hardware setup shows that all system parts and intraoperatively recorded data can be evaluated. Exemplarily, a classification map was generated that allows visualization of measured properties of raw data. The results reveal that it is possible and beneficial to use HSI for wavelength-related intraoperative data acquisition in neurosurgery. There are still technical facts to optimize for raw data detection prior to adapting image processing algorithms to specify tissue quality and function.:Abstract Introduction Materials and methods (Clinical workflow and setup for hyperspectral imaging process, Characteristics of the lighting, Characteristics of the hyperspectral imaging camera, Spectral data acquisition and raw data pre-processing in neurosurgery, Spectral data evaluation) Results (Spectral characteristics of the lighting, SNR of the HSI camera, Data acquisition and raw data preprocessing during neurosurgical operation, Spectral data evaluation) Discussion Conclusions

Histopathology refers to inspecting and analysing tissue samples under a microscope to identify and examine signs of diseases. The manual investigation procedure of histology slides by pathologists is time-consuming and susceptible to misconceptions. Deep learning models have demonstrated outstanding performance in digital histopathology, providing doctors and clinicians with immediate and reliable decision-making assistance in their workflow. In this study, deep learning models, including vision transformers (ViT) and convolutional neural networks (CNN), were employed to compare their performance in patch-level classification task on feature annotations of glioblastoma multiforme in H\&E histology whole slide images (WSI). The dataset utilised in this study was obtained from the Ivy Glioblastoma Atlas Project (IvyGAP). The pre-processing steps included stain normalisation of the images, and patches of size 256x256 pixels were extracted from the WSIs. In addition, the per-subject split method was implemented to prevent data leakage between the training, validation and test sets. Three models were employed to perform the classification task on the IvyGAP data image, two scratch-trained models, a ViT and a CNN (variant of VGG16), and a pre-trained ViT. The models were assessed using various metrics such as accuracy, f1-score, confusion matrices, Matthews correlation coefficient (MCC), area under the curve (AUC) and receiver operating characteristic (ROC) curves. In addition, experiments were conducted to calibrate the models to reflect the ground truth of the task using the temperature scale technique, and their uncertainty was estimated through the Monte Carlo dropout approach. Lastly, the models were statistically compared using the Wilcoxon signed-rank test. Among the evaluated models, the scratch-trained ViT exhibited the best test accuracy of 67%, with an MCC of 0.45. The scratch-trained CNN obtained a test accuracy of 49% and an MCC of 0.15. However, the pre-trained ViT only achieved a test accuracy of 28% and an MCC of 0.034. The reliability diagrams and metrics indicated that the scratch-trained ViT demonstrated better calibration. After applying temperature scaling, only the scratch-trained CNN showed improved calibration. Therefore, the calibrated CNN was used for subsequent experiments. The scratch-trained ViT and calibrated CNN illustrated different uncertainty levels. The scratch-trained ViT had moderate uncertainty, while the calibrated CNN exhibited modest to high uncertainty across classes. The pre-trained ViT had an overall high uncertainty. Finally, the results of the statistical tests reported that the scratch-trained ViT model performed better among the three models at a significant level of approximately 0.0167 after applying the Bonferroni correction.  In conclusion, the scratch-trained ViT model achieved the highest test accuracy and better class discrimination. In contrast, the scratch-trained CNN and pre-trained ViT performed poorly and were comparable to random classifiers. The scratch-trained ViT demonstrated better calibration, while the calibrated CNN showed varying levels of uncertainty. The statistical tests demonstrated no statistical difference among the models.

Glioblastoma is the fastest-growing, and the most common malignant brain tumour in adults. It is normally treated with surgery and radio- or chemotherapy, but the approximate life expectancy is of 15 months with a high probability of cancer recurring. Therefore, there is a need for decreasing its severity. Bulk and single-cell RNA sequencing allow the identification of cellular states in tumours affected by cell-intrinsic and extrinsic factors. Four different cellular states have been identified in glioblastoma: neural progenitor-like, oligodendrocyte progenitor-like, astrocyte-like, and mesenchymal-like. As glioblastoma is an immunosuppressive tumour, it can alter the immune system and increase the tumour's immune escaping by segregating immunosuppressive factors or interacting with the brain microenvironment.Two datasets were used in this study to explore if the localization of the tumour in the brain microenvironment and the tendency of glioblastomas to activate microglial cells are due to particular ligand-receptor interactions. Data quality control was applied to both datasets and SingleCellSignalR and CellphoneDB packages were used to predict the possible interactions. A total of seven experiments were designed for this study. The first dataset, GBmap, allowed us to do a comparison between tumour cells and microglia, tumour cells and other cell types in the brain, and the four cellular states of glioblastoma with microglia and macrophages. Next, healthy microglia from GBmap was used to compare with the tumour bulk data from the second dataset, HGCC. The bootstrap technique was performed to compare bulk data vs single-cell data, and a comparison between tumour cells and microglia or other cell types was analysed.Results showed specific and shared interactions between cell types or cellular states, revealing the different localization of the tumour cells depends on the expressed ligand-receptor pairs. Also, a total of four patterns of interactions were found in the 50 samples to have a different tendency to activate microglial cells, which are promising results to further explore drugs to interfere with or how these interactions are related to patient survival. Furthermore, even if glioblastoma is a heterogenous disease, more interactions were predicted with microglial/macrophage cells without a uniform pattern between patients, and therefore, this study is a starting point upon which further in vitro studies would be needed to study the predicted interactions as potential targets to stop the progression of this type of cancer.

Mémoire de maîtrise présenté en vue de l'obtention de la maîtrise en psychologie (M. Sc) / Introduction. Il est bien établi que les survivants tumeurs cérébrales pédiatriques (STCP) éprouvent des difficultés sociales, et la reconnaissance d’émotions faciales a été étudiée comme un mécanisme sous-jacent. Cependant, l'influence possible de la pandémie sur les capacités de reconnaissance des affects chez les STCP reste inexplorée. La présente étude visait à comparer la reconnaissance des émotions faciales (avec accès au visage complet versus seulement la région des yeux) entre les STCP et des jeunes à développement typique ainsi qu’à examiner son association avec l'adaptation sociale. Méthode. Des STCP (n=23) au moins un an après le traitement et des contrôles (n=24) entre 8 et 16 ans ont complété le sous-test de reconnaissance des affects du NEPSY-II (visage complet) et la version enfant du Reading the Mind in the Eyes Test (RMET, seulement le haut du visage). Résultats. Les groupes ne différaient pas sur leurs habiletés de reconnaissance d’émotions et ceux-ci n’étaient pas associés à leur adaptation sociale. Comparé aux normes pré-pandémie, notre échantillon avait plus de difficultés dans leur capacité de reconnaissance d’émotions avec visage complet ainsi qu’une meilleure performance avec seulement le haut du visage disponible (p < .05). Les participants ont aussi obtenu de meilleurs résultats au RMET qu’au NEPSY-II (p< .05). Conclusion. En somme, la pandémie semble avoir joué un rôle sur les capacités de reconnaissance des émotions faciales, tant chez les STCP que chez les contrôles, soulignant la nécessité d'études futures sur les effets à long terme de la pandémie sur les compétences sociales des jeunes. / Introduction. It is well-established that pediatric brain tumour survivors (PBTS) experience social difficulties, and facial emotion recognition has been studied as an underlying mechanism. However, the possible influence of the pandemic on affect recognition abilities in PBTS remains unexplored. The present study aimed to compare facial affect recognition (with full versus partial facial features) between PBTS and healthy controls (HC) and to examine its association with social adjustment. Method. PBTS (N=23, ages 8-16) at least one-year post-treatment and HC (N=24, ages 8-16) completed the NEPSY-II Affect Recognition subtest (full face) and the child version of the Reading the Mind in the Eyes Test (RMET, upper face only). Results. The groups did not differ in their ability to recognize emotions, and these were not associated with social adjustment. Compared with pre-pandemic norms, our sample had a lower performance in their emotion recognition ability with full face and a better performance with only upper face (p < .05). Participants also performed better on the RMET than on the NEPSY-II (p< .05). Conclusion. In sum, the pandemic appears to have played a role in facial emotion recognition abilities in both PBTS and controls, highlighting the need for future studies on the pandemic long-term effects on young people's social skills.