Through a series of major breakthrough studies, scientists at UBC and the BC Cancer Agency have transformed our understanding of breast cancer and set the stage for the development of new treatments.
It began with a landmark discovery in 2009.
By decoding—for the first time in history—the three billion letters in the DNA sequence of a patient’s metastatic lobular breast cancer and following its evolution over nine years, Dr. Samuel Aparicio, Dr. Marco Marra and Dr. Sohrab Shah were able to show how this complex cancer mutates and spreads.
Aparicio is a Professor in the Department of Pathology and Laboratory Medicine at UBC and heads the BC Cancer Agency’s Department of Molecular Oncology; Marra directs the Michael Smith Genome Sciences Centre and the Department of Medical Genetics at UBC; and Shah is an Associate Professor in the Department of Pathology and Laboratory Medicine at UBC, a Scientist at the BC Cancer Agency, and Canada Research Chair in Computational Cancer Genomics.
The research team they led found that of the 32 mutations in the metastatic tumour, only five could have been present in all the cells of the original tumour, thereby identifying them as the suspected cause of the disease getting started in the first place.
The internationally significant findings were published in the prestigious journal Nature.
“This is a watershed event in our ability to understand the causes of breast cancer and to develop personalized medicines for our patients,” declared Aparicio at the time.
In 2012, international research led by Aparicio at the BC Cancer Agency and Dr. Carlos Caldas at the Cancer Research UK Cambridge Institute was able to classify breast cancer into ten subtypes. They then grouped these subtypes by common genetic features, which correlate with survival, to suggest how treatments could be tailored to treat women with better defined types of breast cancer.
This discovery followed on the heels of Aparicio, Shah and Marra leading the decoding of the most deadly triple-negative breast cancer. This research similarly discovered new genes that had never before been linked to the disease and showed that breast cancer is an umbrella term for what is really a number of unique diseases.
Aparicio and Shah have since led further research to understand and predict how these complex cancers evolve over time.
The two researchers used Shah’s statistical modelling software, PyClone, to analyze the billions of pieces of genetic data gathered from the tumour samples. Their findings, published in Nature in 2014, provided a map for how certain breast cancers evolve to become drug resistant over time.
“By pinpointing which individual cancer cells are the ‘resilient’ ones that are most likely to have an impact on patient survival,” says Shah, “We are paving the way for drug development and treatment practices that will stop these cellular superbugs from taking over.”
“Because of this research we have a way to identify the cancer ‘super-cells’ and stay one step ahead of disease progression by tailoring effective treatments to individual patients,” adds Aparicio.
It’s a radical shift in the way we understand cancer—one that is of vital importance to both the global cancer research community and to future drug studies.