High Definition Profiling of Ovarian Cancer Ascites

HGSOC is a major cause of cancer-related mortality, due to the late-stage diagnosis and failure of surgery and chemotherapy (CHT) to eradicate the disease with no significant improvement in overall survival. In recent years, new therapeutic regimens are being tested to improve the care of HGSOC patients. These approaches include the use of poly-ADP-ribose polymerase inhibitors (PARPi) targeting Homology Directed Repair deficiency, anti-angiogenic drugs, such as anti-VEGF monoclonal antibodies, and immune checkpoint inhibitors, that target immune modulation induced by tumor and tumor-associated cells and inflammatory signals. Unfortunately, the outcome of such therapies has been to date either erratic or dismal. This points to the acute need to identify new biomarkers predictive of treatment response, effectively geared to the clinical setting. The primary objective of the project is to generate a comprehensive map of ascites cell components, detailing both their intrinsic features and the landscape of cellular interactions mediated by soluble factors in ascitic fluid. This will allow to define tumoral archetypes, reflecting HGSOC's endophenotypes, associated with prognosis in patients, possibly guiding future refined therapeutical paradigms for ovarian cancer patients and endowing researchers with a well-characterized multilayered dataset for future reference in the context of molecular dissection and target discovery paradigms. Indeed, the combination of origin- and archetype-based stratification of HGSOC patients, will allow to better identify patients for which existing therapeutical regimens could be beneficial, such as the use of checkpoint inhibitors and anti-angiogenic drugs, that have been so far erratic in ameliorating patient's survival.