Susan Farrington
Colorectal Cancer Genetics

Research in a Nutshell
The overall aim is to target appropriate clinical screening to those people most at risk of developing colorectal cancer, as this has proven efficacy. This can only be done, by better understanding of the risk factors associated with the disease, both at the genetic/heritable level and environmental factors influencing disease and indeed the ways they can interact and modify disease risk. Identification of the pathways involved in tumour initiation and progression using model systems, will help us further our ability to stratify screening by risk.

People |
|
Susan Farrington | Principal Investigator and Reader |
Anna-Maria Ochocka | Research Fellow |
Vidya Rajasekaran | Research Fellow |
Victoria Svinti | Bioinformatician |
Maria Timofeeva | Statistician (shared role: Farrington and Dunlop) |
Marion Walker | Laboratory Manager |
Stuart Reid | Research Technician |
Ruby Osborn | PhD student |
Peter Vaughan-Shaw | Clinical Research PhD student |
Paz Friele | (shared role: Farhat Din/Susan Farrington/Malcolm Dunlop/Mark Arends/ Kevin Myant) |
Collaborations
- Professor Malcolm Dunlop, University of Edinburgh
- Professor Harry Campbell, University of Edinburgh
- Dr Farhat Din, University of Edinburgh
- Professor Colin Semple, University of Edinburgh
- Dr Evropi Theodoratou, University of Edinburgh
- Professor Mark Arends, University of Edinburgh
- Professor Martin Taylor, University of Edinburgh
- Professor Ian Jackson, University of Edinuburgh
- Dr Carmel Moran, University of Edinburgh
- Professor Albert Tenesa, University of Edinburgh
- Dr Lina Zgaga, University College Dublin
- Professor Ian Tomlinson, University of Oxford
- Professor Richard Houlston, ICR
- Professor Maurizio Genuardi via InSiGHT variant Interpretation Committee
Partners and Funders
- CRUK/Programme/5yrs/£3.3M
- MRC/Project/3yrs/£1.1M
- Melville Trust/Project/1yr/£8.1K
Scientific Themes
Colorectal cancer, genetics, environmental, mechanisms of risk, risk stratification, models of risk alleles
Technology Expertise
Genomics approaches (GWAS, eQTL analysis)