Highlights
- Novel method for stratifying patients based on the accumulation of genetic alterations determined by the behaviour of the androgen receptor
- Can be applied in conjunction with histological Gleason grade to create a risk stratifier with exceptional performance
- Can identify alternative-evotype prostate cancers, better informing treatment decisions for these patients
The Opportunity
Tumour evolution is a dynamic process involving the accumulation of genetic alterations. The evolutionary processes that give rise to these genetic alterations are complex and not well understood, however, in some malignancies these have been related to prognosis and treatment susceptibility.
There are no current methods routinely used in the clinic for prostate cancer risk stratification based on the evolution of genetic alternations, and this cancer is currently treated as one type of disease. The Gleason score, based on histological analysis of biopsies, is currently used for prognosis but is susceptible to interobserver variability.
Evotest provides a method based on DNA/RNA sequencing that can be applied in conjunction with histological Gleason grade to create a risk stratifier with exceptional performance that allows patient prognosis to be determined with higher accuracy.
The method stratifies prostate cancer patients into one of two prognostic groups: Canonical-evotype and Alternative-evotype. These evotypes are based on the evolutionary accumulation of genetic alterations caused by the androgen receptor. Evotest is a genomic marker panel with a machine learning classifier that outputs a 2D risk score, informing on: 1) the most likely evotype and 2) the degree of disease progression relative to the evotype.
The Evotest method has been developed using 159 prostatectomy samples and validated on 900 samples.
Evotest will be targeted at improving intermediate risk grading, informing on treatment decisions, assigning more men to active surveillance, reducing overtreatment, increasing quality of life, and reducing cost to health services.
Developed by world-leading academics with funding from CRUK: Dan Woodcock (University of Oxford), David Wedge (University of Manchester), and Colin Cooper (University of East Anglia).