The Precision Medicine for Breast Cancer Research (B-PRECISE) program’s purpose is to conduct research on breast cancer with a multidisciplinary team that is integrated with clinical practice.
Dr. Aparicio and his team work with unyielding determination on genomics of high-risk breast cancer patients (Triple Negative Breast Cancer and relapsed ER+) in order to improve the outcome of patients affected by this disease
The goals of the program are:
- To understand and define the nature of breast cancer, at the molecular level, by studying populations of BC women affected by this disease.
- Identify new approaches to treat breast cancer.
- Determine why breast cancers resist treatment and spread to other organs.
- Develop new methods to unravel the genetic code of breast cancer.
To date B-PRECISE has had several major breakthroughs that have improved our understanding of breast cancer:
- Sequencing for the first time the entire genome of a patient and her breast cancer (Shah et al, Nature 2009)
- Identifying 10 subtypes of breast cancer (METABRIC) (Curtis et al, Nature 2012, Dvinge et al, Nature 2013, Pereira et al, Nat.Commun 2016)
- Examining the mutations observed in Triple Negative Breast Cancer, the most aggressive form of breast cancer (Shah et al., Nature 2012)
- Investigating the role of microRNA, small regulatory molecules that direct how the genome is translated into proteins, in breast cancer biology (Dvinge et al, Nature 2013).
- Dr. Aparicio and his team are participating in an international consortium developing virtual reality technology to map out breast cancer tumours so they can take a “walk” in them (Cancer Research UK Grand Challenge funding). The program has built optical platforms which allow them to measure hundreds to thousands of blueprint messages within a tumour simultaneously.
- Another highly promising area is the program’s work in clinical applications such as analyzing how tumour cells change over time and space from a small sample obtained from breast fine needle aspirates.
Dr. Aparicio and his team are at the leading edge of a revolutionary approach called ‘single cell genomics’ and are developing a cancer cell dynamics observatory. A central problem in cancer control is the capacity of tumour cell populations to evolve over time, contributing to cancer cells spreading to other locations, treatment resistance, evasion of the cancer patient's immunity, and differences found within the tumour tissue itself due to single cells evolving and changing over time in different manners from each other. This research area facilitates "precision oncology" in which genomes of patients and their tumours will inform the choice of the therapy that is most likely to benefit the patient. It is directed at understanding how to rationally combine treatments and how to avoid expensive and toxic treatment failures. This may also enable early detection of breast cancers before they cause abnormalities on mammograms.
The ability to investigate and track single cells is critical to understand why some cancers eventually stop responding to treatment. Each cell can be analyzed, and this enables researchers to understand which groups of cells evade treatment and invade other organs. This work is improving our understanding on how breast cancers evolve over time (Eirew et al, Nature 2015). Many new techniques have been developed for single cell sequencing, both in the lab and using computational methods (Zahn et al, Nature Methods 2017). Developing computational methods and data science are of paramount importance in moving forward with this area of research.
Model systems and methods developed in B-PRECISE have resulted in advancements in other cancer types, such as determining how ovarian cancer cells migrate in the abdomen (a collaboration with BC Cancer Foundation funded OVCARE, Zhang et al, 2018 Cell), how lymphoma blood cancers transform and progress, and to improve our understanding of leukemia and glioblastoma, an aggressive brain cancer.
Further work is planned to investigate genetic changes that are observed in the pre-cancer stage (breast, ovary, pancreas, colon), and for identifying therapies targeted at gene alterations observed in Triple Negative Breast Cancer as well as other cancers.