Breast cancer mortality is at its lowest level in 30 years. This success has largely been fueled by advances in early detection and treatment. In contrast, the approach to cancer prevention has not progressed at nearly the same rate, as illustrated by the steady rates of breast cancer incidence over the same period. To address this unmet need, BCRF is leading the charge by awarding $5 million in grants, underwritten by Blizzard Entertainment, to launch the Precision Prevention Initiative—applying the tools of artificial intelligence (AI) and mathematics to develop personalized risk prediction models, and new tools and technologies to develop new targeted interventions—taking a personalized approach to prevention.
“Our vision is to create a world where doctors can customize a prevention plan based on an individual patient’s biology, history and lifestyle to stop cancer before it starts,” said Dr. Dorraya El-Ashry, BCRF Chief Scientific Officer.
The field of cancer prevention will evolve quickly as emerging technologies continue to be incorporated into all areas of precision medicine research. BCRF has long been at the vanguard of breast cancer research, playing a role in every major advance in clinical care. We now aim to take the lead in precision prevention.
By providing the initial and necessary funding for cutting-edge research through three multi-year and four pilot studies, BCRF’s precision prevention initiative aims to propel advances in individual risk assessment, surveillance and risk management to reduce the incidence of breast cancer as quickly as possible. The overarching goal is to translate the gains made in precision medicine for the treatment of breast cancer to the field of prevention.
“There is an enormous opportunity for multidisciplinary research in breast cancer prevention,” said Dr. Judy Garber, BCRF Co-Scientific Director. “Just as emerging technologies are transforming precision medicine, this new initiative seeks to capitalize on these new techniques and discoveries to reduce the incidence of breast cancer with all possible speed.”
This first group of projects will focus specifically on prevention of aggressive breast cancers —those most likely to be lethal, thereby having the most impact in the shortest time. Collectively, they will improve our understanding of the underlying biology of aggressive breast cancers, such as triple negative and BRCA-driven breast cancers, and will help identify individuals who are at increased risk for aggressive breast cancer.
Three-year projects include:
Harnessing AI to develop risk models: In a multidisciplinary project, researchers will harness artificial intelligence (AI) to improve the risk prediction capacity of screening mammography from existing patient data. The AI model will combine traditional risk-factor analysis, like family history and lifestyle, with complex data from digital mammography in an effort to enhance current risk prediction models.
Measuring risk for triple-negative breast cancer (TNBC): Experts aim to develop a new risk model to identify women at risk for TNBC, an aggressive form of breast cancer, using methods such as imaging-coupled artificial intelligence and machine learning to identify features of normal breast tissue that are associated with TNBC. The project can lay the groundwork that will enable a woman and her physician to develop a specific plan to prevent TNBC.
Predicting triple-negative breast cancer: We know little about the early events that lead to the development of TNBC. This team will work to identify factors in the breast tissue that promote the evolution of a precancerous lesion to a malignant cancer—understanding the very root causes of TNBC to, ultimately, prevent it.
One-year pilot projects include:
Targeted therapies: Researchers have linked a specific protein to breast cancer progression and metastasis. Targeting this protein not only prevents tumor growth and metastasis in laboratory models, but also as a possible means to prevent breast cancer altogether. Findings will help to determine whether drugs that target this protein can be an effective way to prevent breast cancer.
Mapping BRCA1/BRCA2 mutations: Researchers will use a technique called single-cell sequencing to molecularly characterize the different cells in the breast of BRCA1/BRCA2 mutation carriers. The goal of this project is to identify a novel way to both predict breast cancer risk and prevent BRCA-driven breast cancers by understanding which cells in the breast are most likely to become cancerous.
Replicating the protective effect of breastfeeding: Breastfeeding can reduce the risk of developing breast cancer. This BCRF-funded project will explore the possibility that the molecular mechanism underlying the protective effect of breast feeding can be replicated. The goal of this study is to develop a lactation-replacement therapy as a strategy of precision prevention.
Therapies to eradicate precancerous cells: Anti-estrogens are effective for the prevention of breast cancer in high-risk women, but many women either can’t or choose not to use anti-estrogen drugs. This research team is developing an alternative to anti-estrogen therapy by targeting a well-known survival protein found in premalignant cells. They will test whether targeting this protein can prevent the progression of a precancerous lesion to a malignant cancer.
Primary investigators are available for comments.
Contact Sadia Zapp: firstname.lastname@example.org