Project 467255

Among all gynecological malignancies high-grade serous carcinoma (HGSC) is the deadliest and most common. It is nicknamed the silent killer because it is detected at later stages and has a poor survival rate. HGSC is a highly mutated and genetically unstable cancer, which reduces the effectiveness of many standard treatments. HGSC consists of epithelial cell, stromal cell and ascitic compartments. Recent research on HGSC suggests that pre-treatment immune infiltration into specific compartments can predict survival outcomes. Natural killer (NK) cells are one such subset, and may be manipulated with monoclonal antibodies, cytokines, or adoptive cell therapy which make them excellent targets for immunotherapy, but the specific features that enable their anticancer activity are incompletely understood. We recently determined that NK cells predict beneficial outcomes for patients with HGSC. More specifically, the CD16high and CD16neg low predict improved and worse survival for patients with HGSC respectively, but the specific characteristics of each subset and how they define the tumor microenvironment remain outstanding questions. Here we aim to understand the spatial-temporal relationship between tumor and NK cells and to determine how common mutations in HGSC impact infiltration of NK cells. We will conduct this using a syngeneic ID8 mouse model, along with matched analyses within a biomimetic engineered HGSC platform developed in our laboratory. This will facilitate mechanistic in-vivo and in-vitro analysis of tumor-immune cell interactions. From this we hope to better understand the impact of NK cell tumor cell interactions and common HGSC mutations to better understand how to leverage immune subsets against tumor cells in a novel immunotherapy for this disease.