A Precision Medicine Biomarker-Driven Approach to MECP2-Related Ovarian Cancer
Abstract
This grant proposal will develop new therapies for women with ovarian cancer and thus relieve some of the enormous suffering this disease causes. For this reason, the research will be relevant to a large number of people. In the United States as a whole, there will be about 21,750 new cases of ovarian cancer and 13,940 deaths in 2020. Therefore, approximately 64% of all ovarian cancer diagnoses lead to death, an unacceptably high death rate. Among the 2 million women alive today who have served in our armed forces, there will be roughly 30,000 cases of ovarian cancer. Further, there will be many more cases in the families of those who have served. The proposed research aims to develop novel therapies that will significantly reduce the tremendous burden of this disease and therefore is highly relevant for active-duty Service members, Veterans, military beneficiaries, and the American public as a whole. We have previously scanned all human genes for new oncogenes that might be active in certain cancer types including ovarian cancer. The goal of this work was to identify new oncogenes that would be targets for drugs to treat those cancers whose growth depends on the newly discovered oncogenes. Oncogenes are genes that encode functions that cancers depend upon for their ability to grow and spread. In cancers, these genes are either turned on at too high a level or have undergone changes in their sequence (mutations) that keep them stuck in the “on” position. In our screen, we sought genes that are essential for cancer growth and spread when turned on at too high a level. We found one gene whose function as an oncogene was not previously appreciated. This gene, called MECP2, appears to be present in extra copies and expressed at too high a level in at least 38% of ovarian cancers, suggesting these cancers are driven by MECP2. Further, there may be many more ovarian cancers that do not have extra copies of MECP2, but express MECP2 at too high a level for other reasons. This application will explore the extraordinary possibilities that cancers that are driven by MECP2 may be treated with drugs that are not currently in use for ovarian cancer. A unique aspect of this grant proposal is the fact that MECP2 is a previously unappreciated therapeutic target in ovarian cancer. This means that successful completion of this grant will provide completely new therapies for ovarian cancers that are driven by MECP2, and these therapies may substantially improve outcomes for these patients. Another key aspect of this grant proposal that positions it for success is that in addition to expertise with MECP2, our team includes two laboratories with deep experience and understanding of the best kind of ovarian cancer models to work with in the lab, called patient-derived xenografts (PDXs). These models are created by placing tumor cells that have come directly from a patient into a highly immunosuppressed mice in the anatomical location in the mouse corresponding to where they came from in the human patient. These tumors then grow in mice and are transferred from one generation of mice to the next. In the mouse, they recapitulate the important genetic changes that were present in the original human cancer sample, and form tumors with the same microscopic architecture as the original human cancer. They are by far and away the best representations of human ovarian cancers available to work with in the laboratory. Together, we have access to a very large library of these models consisting of over 115 separate individual human ovarian cancers. Some of these models were derived from surgical specimens from surgeries soon after initial diagnosis with ovarian cancer, so these models represent early-stage ovarian cancer. Other models were derived from patients who have had ovarian cancers that have relapsed after multiple therapies and therefore these represent late-stage ovarian cancer. Using these extensive and rich resources allows us to identif
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Dec 05, 2021
- Source ID
- W81XWH2110353
Entities
People
- Daniel Silver
Organizations
- Thomas Jefferson University
- United States Army