Liquid Biopsy Detection of Structural Variant Breakpoints to Monitor Ovarian Cancer Clonal Evolution: A Pilot Study
Abstract
Most ovarian cancers are diagnosed at an advanced stage. Although these tumors usually respond to chemotherapy, true cure is rare in these cases and resistance to treatment will usually develop and eventually lead to death. Tumors such as ovarian cancer are not uniform but are instead comprised of a mixture of genetically related tumor cells, often with differing sensitivity to chemotherapy or other treatments. From this baseline tumor heterogeneity, treatment can lead to the selection and growth of a resistant subset of tumor cells. A method for using blood samples to identify resistant patterns of tumor evolution would be a significant advance in allowing physicians to personalize ovarian cancer treatments for all women with this deadly disease. It has long been known that ovarian cancers shed portions of their DNA into the bloodstream of affected women and that sensitive methods can be used to detect this tumor DNA from blood samples. The research proposed in this study will develop a novel method for individually detecting rare populations of tumor cells from the bloodstream of women with ovarian cancer in order to longitudinally detect tumor evolution in real time. This approach will rely on a key observation that the genomes of ovarian cancer are frequently rearranged, meaning each tumor has numerous breakpoints from two or more distant locations that are brought together. Since these breakpoints both identify tumor cell sub-populations and by definition do not occur in normal cells, the key insight of this proposal is that breakpoint detection from blood samples is an innovative and powerful approach to detecting ovarian cancer tumor evolution from blood samples. The proposed pilot study has the potential to result in a completely new paradigm for monitoring ovarian cancer response to treatment. Rather than waiting for treatment completion to assess response, a woman and her doctor could observe her tumor’s evolution in real time and personalize treatment decisions based on this information. The early detection of emerging tumor resistance could lead to earlier changes in treatment and improvement in survival outcomes. Importantly, this novel approach to monitoring tumor evolution is a broadly applicable technology that could be used across tumor types.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Dec 28, 2022
- Source ID
- W81XWH2210316
Entities
People
- Robert Hillman
Organizations
- The University of Texas MD Anderson Cancer Center
- United States Army