FROM BULK TO SINGLE-CELL RNA-SEQUENCING DATA: THE TUMOR HETEROGENEITY EVOLUTION IN MULTICELLULAR ECOSYSTEMS OF OVARIAN CANCER

Epithelial ovarian cancer (EOC) is a significant global health concern, ranking as the second most common cause of death among gynecological cancers. It predominantly affects women around the age of 63 and accounts for 90% of all primary ovarian cancers. The disease's high incidence results in approximately 313,959 new cases worldwide each year, with 207,252 deaths annually. This alarming mortality rate places EOC as the most lethal gynecological malignancy and the seventh most frequent cause of cancer-related death among women worldwide. EOC is a highly heterogeneous disease, encompassing various histological subtypes, grades, and molecular characteristics, which significantly influence treatment outcomes. High-grade serous ovarian carcinoma (HGSOC) is one of the most aggressive forms of EOC. Despite extensive research, the standard treatment for EOC still relies on a combination of optimal surgery and platinum-based chemotherapy. Primary debulking surgery (PDS) aims to remove as much tumor tissue as possible, followed by intravenous chemotherapy with paclitaxel and platinum-based drugs, often accompanied by maintenance therapy. An alternative approach for patients who can't undergo complete resection during PDS is neoadjuvant chemotherapy (NACT) followed by interval debulking surgery (IDS). However, a major challenge in HGSOC treatment is the development of platinum resistance, affecting nearly 70% of advanced-stage patients within two years of treatment. The tumor microenvironment (TME) plays a pivotal role in ovarian cancer progression, comprising a complex network of various cell types, including cancer-associated fibroblasts (CAFs), fibroblasts, myofibroblasts, adipocytes, endothelial cells, and immune cells, embedded within a unique extracellular matrix (ECM). CAFs, in particular, are a significant component of the TME, significantly influencing tumor behavior by inducing ECM remodeling, leading to increased matrix stiffness, promoting cancer cell adhesion, migration, invasiveness, and angiogenesis. My PhD research focused on unraveling the complexities of tumor heterogeneity within the TME, particularly in HGSOC. I began by analyzing pre-chemotherapy bulk datasets, employing cell type deconvolution techniques to understand how different individuals respond to therapy based on their tumor composition. Subsequently, I explored temporal heterogeneity by studying pre- and post-chemotherapy samples, observing how platinum chemotherapy impacted the TME and ECM over time. Transitioning to single-cell data analysis, I examined spatial heterogeneity across different tumor locations within the abdominal cavity. Additionally, I conducted assessments at two distinct time points within the same patient, gaining insights into how the TME evolves in response to therapy. Preliminary findings highlighted significant heterogeneity within chemotherapy-naive samples, likely influenced by chemotherapy's impact on the immune system and tumor cell selection, resulting in the emergence of distinct tumor subtypes and a reduction in tumor heterogeneity. Moreover, the presence of a substantial number of stromal cells after NACT was expected, aligning with bulk sample analysis. Further research is needed to characterize these differences accurately. In conclusion, this research provides valuable insights into tumor heterogeneity in HGSOC and its implications for treatment strategies. While preliminary, it underscores the importance of understanding how the TME evolves in response to therapy and its potential impact on treatment outcomes. Further research and validation are necessary to build upon these initial observations and potentially enhance treatment strategies for HGSOC.