Cancer is genetic disorder of numerous tissue types and cells. Throughout our lives, the cells that make up our body are subject to numerous insults that allow these cells to slowly acquire genetic mutations that promote uncontrollable growth and longevity. In essence, cancer is a disease of the self. It starts in any one of our cells and the survival advantages it acquires propagate and over time lead to disease. Since the completion of the human genome project in 2003 the international scientific community has focused on improving our understanding of how molecular and structural changes to our DNA implicates cancer progression. From this effort, we now know which genetic events can drive growth in a majority of common cancer types, and we are able to identify “at-risk” populations. Technological advances have also provided us the ability to sequence whole patient genomes. It is this data that holds the key to curing cancer. What we lack however, is the ability to analyse their genetic code properly, and with enough expertise, to predict outcomes or provide more appropriate treatments. Imagine, if this technology was developed then patients would receive personalised treatments routinely. Treatments would be specifically aimed at giving patients the best opportunity for remission, or even cure. The key to advancing personalised medicine is to improve the computational technology and programmes available for sample analysis. Indeed, there are many already available yet they are flawed!
The purpose of my PhD is to further our efforts to improve personalised medicine within cancer, and specifically within leukaemia and lymphoma (i.e. blood cancer). With the help of the Principal’s Go Abroad Fund I visited the laboratory of a prominent geneticist in Amsterdam, the Netherlands, whose research specialises in lymphoma genetics and who in recent years has spearheaded a number of research projects aimed at developing new and improved computational programmes for clinical oncology. During my visit, I spent 5 days working closely with a number of different bioinformaticians – some also completing their own PhDs! I saw first-hand their approach to use complex programming languages to analyse genetic code, and ultimately link a patient’s DNA to treatment response. These tools when fully developed could be implemented in further research projects, or even the clinic – the ultimate goal!
As you can probably imagine it was very intense! Before I went, I only had a basic understanding of very few computational languages! The 5 day hard graft was tiring. Being able to work with these people, and observe their approach to tackling this very large problem has, since my return to Edinburgh, allowed me to progress so much further with my own project that I really can’t complain. After my visit, I spent the weekend exploring the inner city and canals of Amsterdam (typical tourist!), eating amazing food, and having an excellent time with really interesting people – even if I did lose my passport in the process!
University of Edinburgh Go Abroad 
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