The researchers have developed the tool to help find these features and will now use the study to analyse tissue samples collected from patients with prostate cancer during its clinical trial, and then further build models to classify prostate tumours based on different cell features.
The researchers said: “We’ve known for many years that specific patterns of non-cancerous cells, and the surrounding scaffolding that supports tumours, can drive more aggressive prostate cancer behaviour. However, we haven’t had the computational tools to find these “bad biology” tumour patterns.
“Recent advances in artificial intelligence mean there is now the potential to identify them. We’re very excited that our PCR award means we can apply powerful computational approaches to digital images of tumours, with the goal of enabling better treatment decisions for individual patients – maximising cure rates and minimising side effects.”
Following the study, the hope is for the tool to be implemented into clinics to support more personalised treatment for those diagnosed with prostate cancer. In the longer term, the aim is for the software to support different stages of prostate cancer to gain a better understanding of the biology that underpins aggressive disease and hormone therapy resistance.
Anna and Erik are working with other researchers from the Francis Crick Institute, the Institute of Cancer Research, Royal Marsden Hospitals NHS Trust and University College London. The team will also hire machine learning, statistics, and clinical trials experts into the study.
To find out more on the study, please click here.