Detecting and Preventing Progression of High-Risk Precancerous Breast Lesions
Abstract
Breast cancer remains a devastating disease, with over 200,000 new cases and 40,000 deaths per year in the United States alone. Despite that the number of breast cancer-related deaths has declined in recent years, the overall incidence is increasing. Although detection methods have improved to the point where breast lesions can be detected at the earliest stages, clinicians are currently unable to predict which lesions will progress to carcinoma. Moreover, aggressive treatment at early stages does not lead to improvements in long-term survival rates, suggesting that early-stage breast cancer is overdiagnosed and overtreated. This is likely because the mechanisms directing cancer development remain unclear and cannot be predicted based on genetics alone. In the absence of such knowledge, overtreatment will continue to burden healthcare systems and expose patients to unnecessary and unjustified risks. Women at high risk for developing breast cancer may be eligible for preventative therapy; however, existing treatments only prevent some breast cancers and the net benefit is limited by serious side effects. Identifying novel targeted therapies will reduce breast cancer incidence, but a major barrier to this is a limited understanding of the mechanisms underlying early stages of breast cancer development. In addition to the growth of too many cells, breast cancers are characterized by loss of normal tissue structure. An emerging concept is that this altered tissue structure creates a permissive state for the development of breast cancers. To begin to understand the early stages of breast cancer, we recently characterized panels of precancerous breast lesions from patient biopsies to understand how tissues change from a normal architecture to a cancerous one. We recently identified a novel marker called Par6, which can distinguish less and more aggressive breast lesions. Moreover, Par6 is detected at the earliest stages, well before breast cancer is present, indicating that it might be useful to predict breast cancer. Initiating events in breast cancer occur when an individual cell acquires mutations that alter its function in an otherwise normal tissue. Our overall hypothesis is that the surrounding normal tissue acts as a natural barrier to prevent individual mutant cells from growing and initiating breast cancer. We propose that if mutant cells lose normal structure and organization early on, they can escape control by surrounding normal cells. It is our view that these cells are “born-to-be-bad” and are responsible for aggressive lesions that lead to cancer. To test our hypothesis, we will first examine archived breast biopsy samples, in which we now have information whether patients developed breast cancer or not. We will ask whether Par6 expression in these biopsy samples correlates with breast cancer development or overall patient survival. If successful, this would indicate that Par6 could be further developed as a biomarker to predict breast cancer development in patients undergoing biopsy screening. Next, we will examine properties of breast tissue from low-grade and high-grade lesions to determine if there are features that are associated with more aggressive lesions. The grade is used by pathologists as a measure of how aggressive a lesion is. This will provide important information on additional markers that can be used to identify lesions that are most likely to progress to breast cancer and could help identify novel drug targets to prevent breast cancer. Finally, we will grow “organoid” cultures, miniature fragments of breast tissue that maintain the tissue structure and organization. We will use a special microscope to make videos to visualize normal cells and their interaction with cells that we induce cancer-causing mutations in. Using the organoids, we will examine how cells from women at a high risk for breast cancer are more susceptible to form cancer than tissue from women at lo
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Oct 29, 2018
- Source ID
- W81XWH1810079
Entities
People
- Luke Mccaffrey
Organizations
- McGill University
- United States Army