Fact file

  • Group Leader at Barts Cancer Institute
  • Consultant Urological and Robotic Surgeon at UCLH and Barts
  • Has studied and trained in Cambridge, Edinburgh, Glasgow, and Stockholm
  • Goal to utilise data science to improve the lives of patients with prostate cancer

Describe your work in a nutshell.

One theme is the analysis of genetic and patient data to better understand and treat prostate cancer. My lab work focuses on a gene-shuffling process that affects thousands of genes, and alters the way cancers grow or respond to treatment, while my clinical research explores patterns within prostate cancer patients’ data that may lead to better treatments.

What aspect of your research is exciting you right now?

A project using machine learning to identify genetic changes in patients’ blood that predict how well they respond to treatment. It’s exciting because it may change how we monitor prostate cancer patients, moving from invasive needle biopsies to blood tests.

A recent highlight?

Using a Swedish database of over 100,000 prostate cancer patients, we previously found that, in contrast to older prostate cancer patients, younger patients fared better with surgery than radiotherapy. We were concerned that this finding was an artefact of older patients having more comorbidities, rather than being older per se.

Digging further into the database, I discovered that comorbidities don’t affect prostate cancer survival after treatment with surgery or radiotherapy. This suggested that our previous findings were likely to be real, and is important in my clinical practice, where I recommend surgery to younger men. It illustrates the power of big data.

Your work in three words…

Challenging; exciting; rewarding.

What book would you recommend?

Did He Save Lives?: A Surgeon's Story by David Sellu. An extraordinary book about how a miscarriage of justice led to the imprisonment of a respected surgeon for manslaughter.

 

Man using medical equipment
Prabhakar using a liquid biopsy system used to to look for cancer cells in a blood sample.