Around $6.5 million of funding has been awarded to help Cambridge doctors predict the best treatment for high-risk breast cancer patients.
The four-year project is being led by Professor Jean Abraham, Director of the Precision Breast Cancer Institute (PBCI) at the Cancer Research UK Cambridge Centre, which will be moving into the new Cambridge Cancer Research Hospital.
It will build on the PBCI’s pioneering research to improve and personalise treatment for breast cancer patients, and the vision for our new specialist cancer research hospital.
Currently only a fraction of the data collected from patients in the clinic is used to determine a patient's treatment options. This is because the data is stored in different formats and locations, making it difficult to compare and analyse.
The new funding from the US Department of Defence, Department of the Navy, Office of Naval Research will be used by researchers at the University of Cambridge to bring together many different types of patient data in one place, to create an 'integrated data platform'.
This will mean researchers can compare and examine the data, and develop tools to predict the best treatment option for each patient.
"The Precision Breast Cancer Institute will move into the new Cambridge Cancer Research Hospital when it opens, further enabling us to apply the latest technologies and innovations to our research expertise and transform the way we manage breast cancer patients."Professor Jean Abraham, Director of the Precision Breast Cancer Institute (PBCI)
Using AI and technology to personalise treatments
Samples that have already been collected from over 6,000 breast cancer patients who have taken part in research studies and clinical trials, and agreed for their data to be used in research, will be combined to increase our understanding of how different subtypes of breast cancer respond to different treatment options.
Alongside each biopsy sample, a variety of genomic, imaging, molecular and clinical data has also been recorded, but all the different types of information are currently stored separately, making useful analysis difficult.
Initially these massive diverse data sets will be merged, using cutting edge technology to create a multi-modal breast cancer resource called Synergia-Breast Cancer.
The data will then be analysed collectively, using machine learning and artificial intelligence to identify the key factors that determine why some cancers respond to treatment, and others do not, and why some cancers recur and spread while others do not.
Using the results of this analysis, the team will develop tools for use in the clinic that can predict which treatment option is best for each patient, how they will respond to treatment and detect the earliest signs of relapse.
Patient advocates have played an essential role in developing the project proposal and will be part of the research team throughout the project to ensure that the integrated data platform and prediction tools meet the needs of breast cancer patients and address any concerns.
Professor Jean Abraham said: “This project will help us answer key questions about the molecular profile, the genetics, the radiology and the pathology that we see in one person’s breast cancer that means we have to treat them differently from the person sitting next to them in the clinic.
“The Precision Breast Cancer Institute will move into the new Cambridge Cancer Research Hospital when it opens, further enabling us to apply the latest technologies and innovations to our research expertise and transform the way we manage breast cancer patients.”
Prof Greg Hannon, Director of the CRUK Cambridge Institute (CRUK CI) is the partnering investigator for the project.
Researchers in the Hannon lab (opens in a new tab) at the CRUK CI will undertake detailed analysis of individual cells in the biopsy samples to increase our understanding of the development of breast cancers, their response to treatment and their potential for spreading or becoming metastatic.
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Office of Naval Research.