New PhD researchers will crunch big data to help fight against prostate cancer

Today, with support from the Movember Foundation, we’re proud to announce over £450,000 in funding for four new PhD students, who specialise in using computing power to deal with the huge amounts of data that researchers are creating and will help us take prostate cancer research into a new era.

This is the first time we’ve made a targeted effort to recruit PhDs into a specific area of research. But we recognised that there was a need for greater expertise in the increasingly important area of bioinformatics, so we changed from our usual, broader approach.

Using big data to better understand prostate cancer

While big data is a buzzword more usually associated with Google or the Large Hadron Collider, it could also reveal ways for us to treat and diagnose prostate cancer more accurately.

As technology develops, we continue to get a deeper and deeper understanding of the disease. Each step down the rabbit hole raises further questions and challenges, but also presents new opportunities to develop new treatments.

When the human genome was first decoded in 2000, it gave us the 3 billion letter-long recipe for what makes up a person. There was great hope that this would lead the way to solving a wide range of health problems, and it has given us some great insights. However, like any recipe, it all depends on how it’s followed.

We’ve since learned that there is a huge array of molecules and processes that work to control the activity of our genes, making the picture much more complex.

Scientists needed on laptops as well as in labs

All of this extra complexity means that we need scientists on their laptops, as well as in the lab. While coding might seem a big step from finding cures, our four new PhD students will be helping us to identify aggressive cancer, match the right treatment to the right man, and understand how cancer cells develop, delivering our strategy of better diagnosis, better treatment and better prevention.

To find out more about each of these projects, read our summaries in the links below:

• Gather information on molecules that influence the activity of genes
• Build a database of genetic data from biopsy and blood samples
• Predict how gene activity is affected by prostate cancer treatments
• Develop computer models to understand why multiple prostate cancers appear together