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Research Objectives


Professor Stephen Elledge and his international team of researchers are stepping up to the plate, and are looking to answer this question once and for all. By carefully mapping cancer drivers in our cells – molecules that are known to cause cancer – they hope to shed light on which drivers cause cancer in different tissues throughout the body.

In a collaboration that involves researchers from multiple disciplines – including geneticists, cell biologists and bioinformaticians – this Grand Challenge project aims to generate a comprehensive map of cancer drivers and their specificity to different tissues. This has the potential to improve our basic understanding of cancer, and provide information that will impact therapeutic choices for patients.

Our international team is made up of researchers from:


The University of Manchester, UK

Utrecht University, Utrecht, Netherlands
New York University School of Medicine, USA
Baylor College of Medicine, Houston, USA
Institute of Cancer Sciences, University of Glasgow, UK
Brigham and Women's Hospital, Boston, USA

Memorial Sloan Kettering Cancer Center, USA

Harvard University, Harvard Medical School, Boston, USA

Dana Farber Cancer Institute, Boston, USA

We are going to look at our cells’ DNA to identify which genes control whether cells divide or not. By looking at the DNA in different locations in the body, this screen will allow the team to look at whether certain genes are only active in specific tissues. This will provide vital information on known cancer drivers, as well as allowing the team to identify new potential drivers of cancer. Alongside this, the researchers will be assessing how well different cancer drugs work in different types of cancer, and if this can be linked to the activity of cancer drivers.


If successful, this map of ‘tissue specificity’ will give us a complete overview of which cancer drivers play a role in the different tissues throughout the body. This understanding could transform the way doctors treat cancer, as they will be able to select which drugs are more likely to work based on exactly how and where the cancer originated.


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