Elucidating and Targeting Clonal Lineages Influencing Resistance to Therapy in Distinct Mutational Subtypes of High-Grade Ovarian Serous Carcinoma
Abstract
Over the last decade, it has become increasingly clear that tumors are very complex and made up of lots of different kinds of cells, including cancer cells and healthy cells. Importantly, not all the cancer cells are the same, even within a single tumor, and it is this diversity among the cancer cells that often causes therapy to be unsuccessful. When the tumor is treated, the majority of the cancer cells are successfully destroyed, the tumor shrinks, and the therapy appears to be successful. But, in reality, there may be a small number of other types of cancer cells present in the tumor that are able to survive the treatment and then regrow, often more vigorously than they did before, causing a relapse. Resistance to treatment is the main reason someone’s cancer may return and become incurable. We need to understand why and how a particular cancer becomes resistant to specific drugs and how we can stop this from happening. Ovarian tumors are characterized by particularly high levels of cancer cell diversity because they often have mutations in genes which normally prevent errors occurring in our DNA. This leads to an accumulation in errors or mutations in the DNA, the pattern of which can be used to categorize a patient’s tumor. Work from the Brenton lab has shown that these patterns or signatures can predict whether a patient will have poor prognosis and whether they will benefit from therapy or not. However, we do not understand why these predictions work at the cellular level, which is critical if we want to improve therapy and identify alternative drugs for treatment of tumors that do not respond to standard therapy. A major challenge to being able to investigating this is that it can be very hard for researchers to determine how each type of cancer cell is behaving within a complex mixture. The Hannon lab have developed a new approach to tackle this problem that allows us to unambiguously identify each type of cancer cell before and after treatment within tumors in a dish or grown in mice. Each cell type is given a unique genetic barcode that we can use to identify it. These barcodes are used alongside cutting-edge technologies that allow us to measure the patterns of genes which are turned on and off within each cell and dictate the cell’s identity and behavior. This enables us to follow each type of cancer cell simultaneously over the course of treatment, determine whether it was killed by or survived treatment, measure the characteristics of the cells, and determine how those characteristics change when it is treated with drug. Recent improvements to this barcoding approach now allow us to additionally purify a single type of cancer cell of interest from a complex mixture by using its unique barcode to activate a fluorescent gene in only that cell type. We will use these barcoding technologies in clinically relevant ovarian cancer models established by the Brenton lab. Specifically, the Brenton lab have isolated cells directly from ovarian cancer patients at Addenbrookes hospital and then grow them as 3D tumors in a dish, called organoids. When these organoids are treated with chemotherapy, they respond in the same way as the original tumor in the patient, making them ideal models to study chemotherapy response in the lab. We have organoids derived from patients with different subtypes of ovarian cancer, meaning that we can determine whether our results are applicable to all patients or a specific subset. In these models, we will determine which types of tumor cells are killed by or survive chemotherapy, what determines this behavior, and how the cells are altered by treatment. Having identified cell types that survive treatment, we will purify these and test them against a large panel of drugs to identify drugs that preferentially kill these resistant cells. Those drugs are then good candidates to be used in combination with standard chemotherapy, as the chemotherapy will kill the majority o
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 04, 2024
- Source ID
- HT94252310276
Entities
People
- James D Brenton
Organizations
- United States Army
- University of Cambridge