La motilité cellulaire est fondamentale dans de nombreux processus physiologiques, qu’ils soient normaux ou pathologiques. Cependant, bien que ces derniers impliquent la plupart du temps de nombreuses cellules se mouvant en même temps, les effets des interactions entre cellules sur leur dynamique, à la fois individuelle et collective, restent assez mal connu. Dans cette thèse, j’ai utilisé Dictyostelium discoideum à l’état végétatif pour étudier cette régulation collective de la motilité. Je me suis principalement appuyé sur une analyse minutieuse de nombreuses trajectoires cellulaires dans des situations variées pour (i) caractériser un facteur sécrété qui régule négativement la motilité cellulaire (nature chimique, voie de signalisation, dynamique de sécrétion et de réponse) et (ii) analyser et modéliser quantitativement la dynamique d’étalement de colonie cellulaires de forme, dimension et densité contrôlées. Je décris enfin un phénomène d’agrégation dynamique observé lorsque les cellules sont placées à haute densité dans un milieu nutritif / Cell motility is fundamental in many physiological, either normal or pathological, phenomena. Yet, although these most often involve several cells moving at the same time, how the interactions between cells affect both individual and collective dynamics remains a poorly understood question. In this thesis, I used vegetative Dictyostelium discoideum cells as a model to study this collective regulation of the motility. I relied mainly on the thorough analysis of numerous cell trajectories in various situations to (i) characterise a secreted factor used to down-regulate the cells’ motility (biochemical nature, response pathway, secretion and response dynamics) and (ii) quantitatively analyse and model the dynamics of spreading cell colonies of controlled initial shape, size and density. Last, I describe a dynamic aggregation phenomenon that occurs when the cells are seeded at high density in a nutrient-rich medium

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.

Die Leber ist das am häufigsten von Metastasen betroffene Organ und kann daher als Modellorgan für metastatische Invasion dienen. Aus diesem Grund war es das Ziel dieser Dissertation Genexpressionsprofile zu verstehen und metastasierungs- sowie invasionsassoziierte Gene zu identifizieren. Differentielle Genexpression wurde in drei Systemen überprüft: Einem syngenen Mausmodell, einem Xenograftmodell sowie in fünf Gewebeproben von Patienten. Genexpressionprofile des syngenen Mausmodells und der Patientenproben zeigten, dass man die Invasionsfront als Ganzes betrachten, um möglichst viele über-lappende Gene zu finden. Globale Genexpressionstudien, die auf den Wirtsteil der Invasionsfront zeigten bemerkenswerte Überrepräsentation z. B. der „GO-terms“ „extrazelluläre Matrix“, Zellkommunikation“, „Antwort auf biotischen Stimulus“, Strukturmolekülaktivität“ und „Zellwachstum“. Marker der Aktivierung hepatischer Sternzellen überrepräsentiert in der invasionsfront, was die Durchführbarkeit einer Analyse differentieller Genexpression im genomweiten Rahmen anzeigt. Globale Genexpressionsstudien, auf den Tumorzellen in der in vitro Situation, in vivo und in der Invasionsfront zeigten insgesamt einen Anstieg zellulärer Spezialisierung von der in vitro zur Invasionsfront. Sezernierte proangiogenetische Chemokine zeigten eine Hochregulation in der Invasionsfront. Das beta catenin Gen war in der Invasionsfront 9.6 fach erhöht im Vergleich zur in vitro Situation. Die Überprüfung der transkriptionellen Aktivierung von beta catenin über die Prüfung der Promotoraktivität zeigte einen 18.4 fachen Anstieg in den Tumorzellen der Invasionsfront. Weiterhin war die Promotoraktivität (an Hand der Aktivität der mRNA des Alkalischen Phosphatase Reportergens) im Tumorinneren 3.5 fach höher als in der Zellkultur, was für einen transkriptionellen Mechanismus der beta catenin Regulation zusätzlich zu den posttranslationalen Mechanismen spricht. / Liver is most frequently populated by metastases and may therefore serve as a model organ for metastatic invasion. So the aim of this thesis is to understand the gene expression profiles and identify metastasis and invasion related genes. Differential gene expression was examined in three systems: A syngeneic mouse model, a xenograft model and five clinical specimens. Gene expression profiles of a syngenic mouse model and human clinical specimen revealed that the invasion front should be considered as a whole to find more overlapping potential target genes. Global gene expression studies on the host part of the invasion front, revealed a pronounced overrepresentation of GO-terms (e.g. “extracellular matrix”, “cell communication”, “response to biotic stimulus”, “structural molecule activity” and “cell growth”). Hepatic stellate cell activation markers were over-represented in the invasion front demonstrating the feasibility of a differential gene expression approach on a genome wide scale. Global gene expression studies of the tumor cells in vitro, in vivo and tumor part of the invasion front revealed an overall increase of cellular specialization from in vitro to the invasion front. Secreted angiogenic cytokines were found to be up regulated in the invasion front. Beta catenin gene of “cell adhesion” GO term was elevated 9.6 fold in invasion front compared to in vitro. Evaluation of transcriptional up-regulation of beta catenin by promoter activity showed an 18.4 fold increase in the tumor cells of the invasion front as compared to those from the faraway tumor. Promoter activity assessed by soluble human placental alkaline phosphatase reporter gene mRNA was 3.5 fold higher in the inner parts of the tumor than in vitro cells indicating a transcriptional mechanism of beta catenin regulation in addition to the posttranslational regulatory mechanisms.