The Role of the Tumor Microenvironment in Cancer Stem Cell Regulation and the Development of Chemoresistance in Ovarian Cancer

Abstract

Tumors are a complex mixture of cancer cells, non-cancer cells, extracellular matrix, and other stimuli. To maximize clinical translation of in vitro models, it is critical to recapitulate the high degree of complexity found in vivo. This work presents three novel in vitro high grade serous ovarian cancer (HGSOC) models that recapitulate key features of the HGSOC tumor microenvironment (TME). HGSOC is characterized by high rates of chemoresistance development and recurrence due to the presence of cancer stem cells (CSCs) which are inherently chemoresistant and have the capacity to repopulate the entire tumor. The non-cancer cells in the TME, such as mesenchymal stem cells (MSCs), endothelial cells (ECs), and immune cells help to maintain CSCs and influence the classification of HGSOC molecular subtypes, which have variable clinical prognoses. However, it is unclear exactly how CSCs and the other TME cells collectively promote chemoresistance and poor outcomes. To better understand this phenomenon, practical in vitro model systems that more closely represent in vivo microenvironments are needed. We hypothesize that development of more physiologically relevant in vitro models will contribute novel insights into TME-mediated CSC regulation and development of chemoresistance in HGSOC. In aim 1 we developed a 3D in vitro serial passaging model to study chemoresistance development in the context of CSCs. This model demonstrated increased proliferation, CSC marker experssion, tumorigenicity, chemoresistance, and a malignant gene signature in patient-derived spheroids over the course of long-term passaging. Treatment responses were reflective of patient-specific chemoresistance development in vivo. Finally, we used this model to show that Metformin treatment can hinder CSC driven development of chemoresistance. This model facilitates research of patient-specific chemoresistance development and could serve as a pre-clinical screening tool. In aim 2 we developed a tumoroid culture system that enabled culture of patient-derived tumor cells with controlled ratios of MSCs, ECs, and immune cells to study how non-cancer cells in the TME drive CSC maintenance and chemoresistance. We found composition-specific changes in CSC marker expression, increased tumorigenic potential, and increased chemoresistance in tumoroids with evidence of epithelial-to-mesenchymal transition (EMT), altered CSC phenotypes, a malignant matrisome signature, and a mesenchymal subtype molecular signature. Together, this indicates that the non-cancer cells in the TME contribute to the development of advanced, chemoresistant disease. In aim 3, we generated tumoroids with 23 different cell compositions to evaluate how TME cell composition affects response to therapy. Drug assays revealed that different composition tumoroids respond differently to therapy and that the number of monocytes included in the culture was associated with the greatest resistance to therapy. Random forest models were able to predict drug response with moderate success and showed that nuanced differences in cell composition can influence drug response. We found that the strongest predictor of response to therapy was the total quantity of non-cancer cells. Overall, this model demonstrates the potential of using the TME composition to predict patient drug response and direct clinical management. In conclusion, we demonstrate the utility of complex and realistic, yet practical in vitro models to study the influence of the TME and CSCs on chemoresistance and outcomes. Overall, the models presented in this work can be used to better understand the role of CSCs and the TME in chemoresistance and clinical outcomes. This could ultimately lead to the development of novel therapies, enhanced clinical management, and improved clinical outcomes.