Integrating Tumor Genetics and Microenvironment as Predictors of Response and Resistance to Immunotherapy in Ovarian Cancer
Abstract
Rationale: The immune system plays an important role in recognizing cancers. Specialized immune cells called T cells have an ability to recognize cancer cells as foreign and to eliminate them. Cancer cells have evolved multiple strategies to escape the killing by the immune system. One of such strategies involves expression of special proteins known as immune checkpoints on the surface of T cells. Two examples of checkpoint proteins are known as CTLA-4 and PD-1. Immune checkpoints prevent T cells from functioning appropriately, and thus prevent them from recognizing and killing cancer cells. A new class of drugs known as immune checkpoint inhibitors, which target the immune checkpoints, has been demonstrated to reactivate T cells, allowing them to kill cancer cells. These drugs have resulted in significant tumor shrinkage in even cures in some patients. Unfortunately, in ovarian cancer, only a small fraction of patients responds to such treatments. It is thus necessary to identify the mechanisms that allow ovarian tumors to resist immunotherapy and to develop novel approaches that can target such mechanisms. We have recently conducted a clinical trial (NRG-GY003) in 100 patients with ovarian cancer testing PD-1 inhibitor nivolumab or a combination of nivolumab with CTLA-4 inhibitor ipilimumab. While tumor shrinkage was observed in only 12% of patients treated with nivolumab, the efficacy of therapy was significantly better in the combination group, with 33% of patients experiencing tumor shrinkage. While these results potentially represent a major advancement for future treatment of ovarian cancer, they nevertheless highlight that the majority of ovarian cancer patients still do not benefit from such treatments. Furthermore, we still do not know: (1) how to identify the patients that are more likely to benefit from such therapies and (2) the reasons why some patients benefit from treatments or others do not. The goal of our proposed project is to use the patient samples collected on the NRG-GY003 trial to help us answer these questions. To accomplish this goal, we have put together a team of experts in ovarian cancer genetics, immunology, medical oncology, and bioinformatics. First, by analyzing the DNA from the patients’ tumor samples, we will determine whether specific mutations and types of mutations can help us identify the patients that are more likely to respond to immunotherapy. Second, we will determine whether mutations in cancer cells lead to activation of specific mechanisms that can stimulate or resist the immune system. Third, by using specialized microscopic analyses of the tumors, we will determine what types of immune cells are present in the tumors, how they interact with each other and with tumor cells, and whether such interactions can help us predict whether the patients will or will not respond to immunotherapy. In parallel, by analyzing T cells in tumors and blood, we will study how T cells change as a result of immunotherapy and whether these changes can help us predict which patients can or cannot respond. Relevance: The proposed work is directly relevant to the OCRP mission. Improved understanding of the determinants of response and resistance to immunotherapy in ovarian cancer is critical for the development of more effective therapies in this disease. Our study is uniquely positioned to answer these questions. This work will offer novel insights into the biology of ovarian cancer that will enable us to identify: (1) which genetic subtypes of ovarian cancer respond better or worse to immunotherapy; (2) how specific genetic subtypes of ovarian cancer interact with the immune system; and (3) which mechanisms in ovarian cancer are associated with resistance to immunotherapy. Applicability of Research: We believe that findings from the study will be beneficial for all patients with ovarian cancer, including the patients who do not currently benefit from immunotherapy. F
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Dec 05, 2021
- Source ID
- W81XWH2110561
Entities
People
- Daniel J Powell
Organizations
- United States Army
- University of Pennsylvania