Single-cell RNA-sequencing makes possible to study the gene expression at the level of individual cells. However, one of the main challenges of the single-cell RNA-sequencing analysis today, is the identification and annotation of cell types. The current method consists in manually checking the expression of genes using top differentially expressed genes and comparing them with related cell-type markers available in scientific publications. It is therefore time-consuming and labour intensive. Nevertheless, in the last two years,numerous automatic cell-type identification and annotation tools which use different strategies have been created. But, the lack of specific comparisons of those tools in the literature and especially for immuno-oncologic and oncologic purposes makes difficult for laboratories and companies to know objectively what are the best tools for annotating cell types. In this project, a review of the current tools and an evaluation of R tools were carried out.The annotation performance, the computation time and the ease of use were assessed. After this preliminary results, the best selected R tools seem to be ClustifyR (fast and rather precise) and SingleR (precise) for the correlation-based tools, and SingleCellNet (precise and rather fast) and scPred (precise but a lot of cell types remains unassigned) for the supervised classificationtools. Finally, for the marker-based tools, MAESTRO and SCINA are rather robust if they are provided with high quality markers.

Lors du développement, la coordination d’évènements moléculaires et cellulaires mène à la production du cortex qui orchestre les fonctions sensori-motrices et cognitives. Son développement s’effectue par étapes : les cellules gliales radiaires (RGs) – les cellules souches neurales (NSCs) du cerveau en développement – et les cellules progénitrices de la zone ventriculaire (VZ) et de la zone sous ventriculaire (SVZ) génèrent séquentiellement des vagues distinctes de nouveaux neurones qui formeront les différentes couches corticales. Autour de la naissance, les RGs changent de devenir et produisent des cellules gliales. Cependant, une fraction persiste tout au long de la vie dans la SVZ qui borde le ventricule, perdant au passage leur morphologie radiale. Ces NSCs produisent ensuite les différents sous types d’interneurones du bulbe olfactif ainsi que des cellules gliales en fonction de leur origine spatiale dans la SVZ. Ces observations soulèvent d’importantes questions non résolues sur 1) le codage transcriptionnel régulant la régionalisation de la SVZ, 2) le potentiel des NSCs postnatales dans la réparation cérébrale, et 3) le lignage et les spécificités transcriptionnelles entre les NSCs et leur descendants. Mon travail de doctorat repose sur une étude transcriptionnelle des domaines de la SVZ postnatale. Celle-ci soulignait le fort degré d’hétérogénéité des NSCs et progéniteurs et identifiait des régulateurs transcriptionnels clés soutenant la régionalisation. J’ai développé des approches bio-informatiques pour explorer ces données et connecter l’expression de facteurs de transcription (TFs) avec la genèse régionale de lignages neuraux distincts. J’ai ensuite développé un modèle d’ablation ciblée pour étudier le potentiel régénératif des progéniteurs postnataux dans divers contextes. Finalement, j’ai participé au développement d’une procédure pour explorer et comparer des progéniteurs pré et postnataux à l’échelle de la cellule unique. Objectif 1 : Des expériences de transcriptomique et de cartographie ont été réalisées pour étudier la relation entre l’expression régionale de TFs par les NSCs et l’acquisition de leur devenir. Nos résultats suggèrent un engagement précoce des NSCs à produire des types cellulaires définis selon leur localisation spatiale dans la SVZ et identifient HOPX comme un marqueur d’une sous population biaisé à générer des astrocytes. Objectif 2 : J’ai mis au point un modèle de lésion corticale qui permet l’ablation ciblée de neurones de couches corticales définies pour étudier la capacité régénérative et la spécification appropriée des progéniteurs postnataux. Une analyse quantitative des régions adjacentes, incluant la région dorsale de la SVZ, a révélé une réponse transitoire de progéniteurs définis. Objectif 3 : Nous avons développé la lignée de souris transgénique Neurog2CreERT2Ai14, qui permet le marquage de cohortes de progéniteurs glutamatergiques et de leurs descendants. Nous avons montré qu’une large fraction de ces progéniteurs persiste dans le cerveau postnatal après la fermeture de neurogénèse corticale. Ils ne s’accumulent pas pendant le développement embryonnaire mais sont produits par des RGs qui persistent après la naissance dans la SVZ et qui continuent de générer des neurones corticaux, bien que l’efficacité soit faible. Le séquençage d’ARN sur cellule unique a révélé une dérégulation transcriptionnelle qui corrèle avec le déclin progressif observé in vivo de la neurogénèse corticale. Ensemble, ces résultats soulignent le potentiel des études transcriptomiques à résoudre mais aussi à soulever des questions fondamentales comme les changements trancriptionnels intervenant dans une population de progéniteurs au cours du temps et participant aux changements de leur destinée. Cette connaissance sera la clé du développement d’approches novatrices pour recruter et promouvoir la génération de types cellulaires spécifiques, incluant les sous-types neuronaux dans un contexte pathologique. / During development, a remarkable coordination of molecular and cellular events leads to the generation of the cortex, which orchestrates most sensorimotor and cognitive functions. Cortex development occurs in a stepwise manner: radial glia cells (RGs) - the neural stem cells (NSCs) of the developing brain - and progenitor cells from the ventricular zone (VZ) and the subventricular zone (SVZ) sequentially give rise to distinct waves of nascent neurons that form cortical layers in an inside-out manner. Around birth, RGs switch fate to produce glial cells. A fraction of neurogenic RGs that lose their radial morphology however persists throughout postnatal life in the subventricular zone that lines the lateral ventricles. These NSCs give rise to different subtypes of olfactory bulb interneurons and glial cells, according to their spatial origin and location within the postnatal SVZ. These observations raise important unresolved questions on 1) the transcriptional coding of postnatal SVZ regionalization, 2) the potential of postnatal NSCs for cellular regeneration and forebrain repair, and 3) the lineage relationship and transcriptional specificities of postnatal NSCs and of their progenies. My PhD work built upon a previously published comparative transcriptional study of defined microdomains of the postnatal SVZ. This study highlighted a high degree of transcriptional heterogeneity within NSCs and progenitors and revealed transcriptional regulators as major hallmarks sustaining postnatal SVZ regionalization. I developed bioinformatics approaches to explore these datasets further and relate expression of defined transcription factors (TFs) to the regional generation of distinct neural lineages. I then developed a model of targeted ablation that can be used to investigate the regenerative potential of postnatal progenitors in various contexts. Finally, I participated to the development of a pipeline for exploring and comparing select populations of pre- and postnatal progenitors at the single cell level. Objective 1: Transcriptomic as well as fate mapping were used to investigate the relationship between regional expression of TFs by NSCs and their acquisition of distinct neural lineage fates. Our results supported an early priming of NSCs to produce defined cell types depending of their spatial location in the SVZ and identified HOPX as a marker of a subpopulation biased to generate astrocytes. Objective 2: I established a cortical lesion model, which allowed the targeted ablation of neurons of defined cortical layers to investigate the regenerative capacity and appropriate specification of postnatal cortical progenitors. Quantitative assessment of surrounding brain regions, including the dorsal SVZ, revealed a transient response of defined progenitor populations. Objective 3: We developed a transgenic mouse line, i.e. Neurog2CreERT2Ai14, which allowed the conditional labeling of birth-dated cohorts of glutamatergic progenitors and their progeny. We used fate-mapping approaches to show that a large fraction of Glu progenitors persist in the postnatal forebrain after closure of the cortical neurogenesis period. Postnatal Glu progenitors do not accumulate during embryonal development but are produced by embryonal RGs that persist after birth in the dorsal SVZ and continue to give rise to cortical neurons, although with low efficiency. Single-cell RNA sequencing revealed a dysregulation of transcriptional programs, which correlates with the gradual decline in cortical neurogenesis observed in vivo. Altogether, these data highlight the potential of transcriptomic studies to unravel but also to approach fundamental questions such as transcriptional changes occurring in a population of progenitors over time and participating to changes in their fate potential. This knowledge will be key in developing innovative approaches to recruit and promote the generation of selected cell types, including neuronal subtypes in pathologies.

The mortality rate is high for cancer patients and treatments are only efficient in a fraction of patients. To be able to cure more patients, new treatments need to be invented. Immunotherapy activates the immune system to fight against cancer and one treatment targets immune checkpoints. If more targets are found, more patients can be treated successfully. In this project, interactions between immune and cancer cells that drive tumour growth were investigated in an attempt to find new potential targets. This was achieved by creating a machine learning model that finds genes expressed in cells involved in tumour-driving interactions. Single-cell RNA sequencing and spatial transcriptomic data from breast cancer patients were utilised as well as single-cell RNA sequencing data from healthy patients. The tumour rate was based on the cumulative expression of G2/M genes. The G2/M related genes were excluded from the analysis since these were assumed to be cell cycle genes. The machine learning model was based on a supervised variational autoencoder architecture. By using this kind of architecture, it was possible to compress the input into a low dimensional space of genes, called a latent space, which was able to explain the tumour rate. Optuna hyperparameter optimizer framework was utilised to find the best combination of hyperparameters for the model. The model had a R2 score of 0.93, which indicated that the latent space was able to explain the growth rate 93% accurately. The latent space consisted of 20 variables. To find out which genes that were in this latent space, the correlation between each latent variable and each gene was calculated. The genes that were positively correlated or negatively correlated were assumed to be in the latent space and therefore involved in explaining tumour growth. Furthermore, the correlation between each latent variable and the growth rate was calculated. The up- and downregulated genes in each latent variable were kept and used for finding out the pathways for the different latent variables. Five of these latent variables were involved in immune responses and therefore these were further investigated. The genes in these five latent variables were mapped to cell types. One of these latent variables had upregulated immune response for positively correlated growth, indicating that immune cells were involved in promoting cancer progression. Another latent variable had downregulated immune response for negatively correlated growth. This indicated that if these genes would be upregulated instead, the tumour would be thriving. The genes found in these latent variables were analysed further. CD80, CSF1, CSF1R, IL26, IL7, IL34 and the protein NF-kappa-B were interesting finds and are known immune-modulators. These could possibly be used as markers for pro-tumour immunity. Furthermore, CSF1, CSF1R, IL26, IL34 and the protein NF-kappa-B could potentially be targeted in immunotherapy.

Le carcinome séreux de haut grade (CSHG) est le sous-type de cancer de l'ovaire le plus agressif et mortel. Alors qu'une meilleure survie globale des patientes soit associée à une infiltration lymphocytaire, l'immunothérapie par blocage des points de contrôle immunitaires a obtenu des résultats limités, témoignant ainsi l'importance de comprendre le fonctionnement du système immunitaire au sein de ces tumeurs malignes. L’immunologie des tumeurs intègre des cellules immunitaires innées et adaptatives et utilise des médiateurs inflammatoires pour ajuster finement l'ampleur et la durée de la réponse immunitaire. Ainsi, cette thèse a pour objectif de définir l'hétérogénéité des cellules immunitaires intratumorales et périphériques chez les patientes atteintes d'un cancer de l'ovaire mais aussi à explorer les mécanismes de la réponse immunitaire. En combinant des techniques de biologie computationnelle et de séquençage de l'ARN à cellule unique nous avons pu identifier les différents composants du système immunitaire des patientes atteintes d'un cancer de l'ovaire mais aussi valider nos résultats dans une plus large cohorte associant d'autres types de cancer. Dans un premier temps, nous avons étudié l'un des médiateurs de l'inflammation, la voie de signalisation extracellulaire de l'adénosine. Nous avons évalué l'impact de cette voie de signalisation sur la survie des patientes atteintes de CSHG et identifié les cellules du microenvironnement tumoral participant au fonctionnement de cette voie. Ensuite, nous avons concentré notre étude sur la dynamique des lymphocytes T et identifié leurs états cellulaires associés, déduit leur relation développementale et étudié les changements transcriptionnels déclenchés par les interactions entre les cellules dans le microenvironnement immunitaire tumoral. Nous avons démontré que les cellules de type Tfh produisent le médiateur 7α,25 dihydroxycholestérol (7α,25-HC) décrit comme régulant le positionnement des cellules immunitaires dans les organes lymphoïdes secondaires. Ainsi, notre étude suggère que les cellules de type Tfh utilise ce mécanisme pour recruter des lymphocytes T CD8 pré-effecteurs/prédysfonctionnels et des cellules dendritiques plasmacytoïdes dans les tumeurs. Finalement, nos résultats indiquent que les cellules de type Tfh exprimant l'interleukine-21 aident à promouvoir l'immunité antitumorale contre les tumeurs ovariennes en coordonnant l'action des lymphocytes et des cellules dendritiques plasmacytoïdes sensibles au 7α,25-HC. En conclusion, nos travaux de recherche ont permis d’identifier des vulnérabilités dans le microenvironnement immunitaire tumoral pouvant être ciblées dans la thérapie contre le CSHG. / High-grade serous ovarian carcinoma (HGSOC) is the most aggressive and lethal subtype of ovarian cancer. Although better overall survival is associated with lymphocytic infiltration, immunotherapy by immune checkpoint blockades achieved modest results, reinforcing the importance of understanding immunity in this malignancy. Cancer immunity integrates innate and adaptive immune cells and makes use of inflammatory mediators to finely tune the magnitude and duration of the immune response. This thesis aims to reveal the heterogeneity of intratumoral and peripheral immune cells in ovarian cancer patients and explore the mechanisms of the immune response. For this purpose, we have used the high-resolution technology of single-cell RNAsequencing and computational biology to immune profile HGSOC patients. Firstly, we explored one of the mediators of inflammation, the immunosuppressive extracellular adenosine (eADO). The ectonucleotidases CD73 and CD39 regulate the eADO signaling pathway, and their expression is prognostic in several cancer types. Since their role in HGSOC was yet largely unexplored, we hypothesized that a transcriptomic meta-analysis of eADO signaling pathway would provide the clinical impact of the pathway in this malignancy. We analyzed the transcriptome of approximately 1200 HGSOC patients to evaluate the effect of CD39 and CD73 on clinical outcomes. While high expression of both ectonucleotidases was associated with worse overall survival in HGSOC, only CD39 was associated with chemoresistance, supporting the evaluation of eADO-targeting agents in HGSOC. Subsequently, we investigated T cell dynamics. Because T cell clones expanded in both tumor and peripheral tissue associated with response to ICB, we hypothesized that the tumor immune microenvironment (TIME) modulates their function and, therefore, analysis of cell-cell interaction would identify the cells participating in this process. Thus, we identified T cell states, inferred their developmental relationship, and studied transcriptional changes triggered by cellcell interactions in the TIME. We demonstrated that exhausted CD8 T cells highly expressed the chemokines CCL4 and XCL1, previously described in the priming of CD8 T cells in secondary lymphoid organs (SLOs). Finally, we proposed that the lipid mediator 7α,25 dihydroxycholesterol (7α,25-HC), only described in SLOs, may also modulate cell-cell interactions in the tumor immune microenvironment. Collectively, our studies propose strategies to modulate TIME in HGSOC targeting the adenosine pathway and oxysterols metabolites.